Prepared for—

Economic Analysis Office

National Institute of Standards and 

Technology

100 Bureau Drive

Gaithersburg, MD 20899

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.GCR.16-006

Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing 

Additive Manufacturing

August 2016

Prepared by—

Troy J. Scott

Travis J. Beaulieu

Ginger D. Rothrock

Alan C. O’Connor

RTI International

3040 E. Cornwallis Road

Research Triangle Park, NC 27709

NIST GCR 16-006
Acknowledgements

Many contributed to the preparation of this report, and we wish to acknowledge in particular the 

private companies, industry associations, research institutes, universities, and government 

agencies whose experts contributed data and insights underlying the analysis herein.

In addition to this study’s lead authors, significant contributors included Luca Alessandro 

Remotti of the Joint Institute for Innovation Policy (formerly of Intrasoft S.A.) and Ola 

Harrysson, Richard Wysk, Paul Cohen, and Russell King with NC State University’s Department 

of Industrial and Systems Engineering.

We would also like to acknowledge the advice and subject matter expertise contributed by NIST 

economic and scientific staff. Specifically, we are especially grateful for the contributions of

 Gary Anderson of NIST’s Economic Analysis Office,

 Timothy Burns of NIST’s Applied and Computational Mathematics Division,

 Stephen Campbell of NIST’s Economic Analysis Office,

 Heather Evan of NIST’s Program Coordination Office,

 Simon Frechette of NIST’s Systems Integration Division,

 Albert Jones of NIST’s Systems Integration Division,

 James Liddle of NIST’s Center for Nanoscale Science and Technology,

 Eric Lin of NIST’s Materials Science and Engineering Division,

 Richard Ricker of NIST’s Materials Measurement Science Division,

 Christopher Soles of NIST’s Materials Science and Engineering Division,

 Albert Wavering of NIST’s Intelligent Systems Division, and

 Paul Zielinski of NIST’s Technology Partnerships Office.

Disclaimer

This publication was produced as part of contract GS10F0097L with the National Institute of 

Standards and Technology. The contents of this publication do not necessarily reflect the views 

or policies of the National Institute of Standards and Technology or the US Government.

About RTI

RTI International is one of the world’s leading research institutes, dedicated to improving the 

human condition by turning knowledge into practice. Our staff of more than 4,150 provides 

research and technical services to governments and businesses in more than 75 countries in the 

areas of health and pharmaceuticals, education and training, surveys and statistics, advanced 

technology, international development, economic and social policy, energy and the environment, 

and laboratory testing and chemical analysis. For more information, visit www.rti.org.

RTI International is a registered trademark and a trade name of Research Triangle Institute.
NIST GCR 16-006

Economic Analysis of Technology 

Infrastructure Needs for Advanced 

Manufacturing: Additive Manufacturing

Prepared for

U.S. Department of Commerce

Economic Analysis Office

Office of the Director

National Institute of Standards and Technology

Gaithersburg, MD 20899

By

Troy J. Scott

Travis J. Beaulieu

Ginger D. Rothrock

Alan C. O’Connor

RTI International

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.GCR.16-006

August 2016

U.S. Department of Commerce 

Penny Pritzker, Secretary

National Institute of Standards and Technology 

Willie May, Under Secretary of Commerce for Standards and Technology and Director 
iii

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Contents

Section Page

Executive Summary ES-1

1 Introduction1-1

1.1 Definition of Technology Infrastructure.......................1-3

1.1.1 Infratechnologies...........................................1-3

1.1.2 Technology Platforms .....................................1-4

1.1.3 Proprietary Technologies.................................1-4

1.2 Study Scope ...........................................................1-5

1.3 Role of NIST............................................................1-8

1.4 What Distinguishes This Report ...............................1-11

2 Analytical Approach2-1

2.1 Data Collection........................................................2-1

2.1.1 Interviews ....................................................2-2

2.1.2 Stakeholder Groups .......................................2-3

2.2 Economic Models .....................................................2-3

2.2.1 Firm-Level Data.............................................2-4

2.2.2 Impact Applicability .......................................2-5

2.2.3 Industry-Level Impacts ..................................2-6

2.2.4 Apportioning Total Impacts over Industry 

Needs ..........................................................2-6

2.3 Conservative Nature of Approach...............................2-7

3 Overview of Additive Manufacturing3-1

3.1 Materials and Processes............................................3-2

3.1.1 Plastics.........................................................3-3

3.1.2 Metals ..........................................................3-4
iv

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

3.1.3 Metallic Additive Manufacturing Systems...........3-5

3.2 Applications and Industries .......................................3-6

3.3.1 Modeling and Prototyping ...............................3-7

3.3.2 Tooling.........................................................3-8

3.3.3 Aerospace.....................................................3-8

3.3.4 Armaments .................................................3-11

3.3.5 Automotive .................................................3-12

3.3.6 Dental........................................................3-12

3.3.7 Biomedical..................................................3-12

3.3.8 Consumer Goods .........................................3-13

3.4 Stakeholders.........................................................3-13

3.4.1 Standards Organizations...............................3-14

3.4.2 Industry Associations ...................................3-14

3.4.3 Federal Investment......................................3-15

4 Quantitative Results and Economic Impact 

Analysis4-1

4.1 Importance Ratings of Infrastructure Technology 

Needs ....................................................................4-1

4.2 Impacts of Meeting Infrastructure Technology 

Needs ....................................................................4-3

4.3 Impacts Apportioned over Technology Needs ..............4-6

5 Qualitative Results: Stakeholder Views5-1

5.1 Materials and Process Standards and Reference 

Databases ..............................................................5-1

5.2Design Optimization for AM.......................................5-5

5.3 Modeling and Simulation...........................................5-6

5.4 Real-Time Metrology ................................................5-7

5.5 Surface Finishing of Metal Additive Parts and 

Related Testing .......................................................

5-7

5.6 Mechanical Testing Procedures ..................................5-8

6 Conclusion6-1

ReferencesR-1
v

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Appendixes

A: Interview Guide for Additive Systems Developers ........A-1

B: Interview Guide for Additive End Users.......................B-1

C: Importance Scores...................................................C-1

Figures

Number Page

ES-1. Total Annual Impact, Apportioned by Technology Need 

(Millions of 2013 US$) ...................................................ES-5

3-1. Metal-AM Part Design Complexities....................................3-7

4-1. Importance of Technology Needs ......................................4-2

4-2. Cost Reductions for Additive Manufacturing by Industry .......4-4

4-3. Total Annual Impact, Apportioned by Technology Need 

(Millions of 2013 US$) .....................................................4-7
vi

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Tables

Number Page

ES-1. General Industry-Level Needs for Additive Manufacturing...ES-3

1-1. Definitions of Key Concepts ..............................................1-6

1-2. General Industry-Level Needs for Additive Manufacturing.....1-7

1-3. Barriers to Developing and Adopting New Technology 

That Brings about Market Failure.......................................1-9

3-1. Techniques/Methods Used in Additive Manufacturing ...........3-3

3-2. Selected Alloys Used in Additive Manufacturing...................3-5

4-1. General Industry-Level Needs for Additive Manufacturing.....4-2

4-2. Economic Impact Summary Table .....................................4-4

4-3. Process Improvements.....................................................4-5
ES

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Executive Summary

Through extensive engagement with industry stakeholders, RTI 

International identified pressing needs in additive 

manufacturing applications for technology infrastructure most 

closely aligned with the National Institute for Standards and 

Technology’s (NIST’s) unique mission and capabilities. These 

needs are in the areas of standards, metrology, design 

allowables, modeling and simulation, surface finishing, and 

testing procedures.

We estimate the potential impact of meeting these needs to be 

$4.1 billion per year, which is defined as costs that U.S. 

manufacturers could avoid if these needs were met. There are 

three important impacts that would accrue. First, lowering

application–specific costs of capital, labor, energy, and 

materials for U.S. manufacturers would lead to lower prices for 

consumers of 3D-printed goods, which in turn would lead to the 

expansion of these market segments. Second, meeting 

technology infrastructure needs would lead to improvements in 

the performance characteristics of parts produced additively, 

which would increase demand and expand these market 

segments still further. Third, the emergence of altogether new 

products and markets would almost certainly also be 

accelerated.

We view our $4.1 billion impact estimate as conservative, 

because it does not take into account the second-order effect of 

the growth AM would experience as a direct result of cost 

reductions being shared with consumers in the form of lower 

prices, moving AM outward along its demand curve. Our 

quantitative impact estimate also does not take into account 

that the demand for additively manufactured parts will increase

as their performance characteristics improve and end users

become better able to verify and certify those performance 

characteristics.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

ES-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

ES.1 SCOPE OF THE ANALYSIS

This report identifies gaps in technology infrastructure inhibiting 

the development and adoption of AM technologies by U.S. 

manufacturers and quantifies the prospective economic benefits 

of addressing these gaps. The report also outlines specific 

actions that NIST can take to accelerate the development and 

adoption of critical technology infrastructure.

The research supporting this report was informed by primary 

data collection that consisted of unstructured and structured 

interviews with experts in the AM value chain, combined with 

secondary collection of industry information and data points. 

The findings of this report—the potential economic benefits and 

roles for NIST—are thus rooted in the perspectives of industry 

experts.

This report focuses on enhancements to six types of technology 

infrastructure, identified through stakeholder interviews as 

industries’ most pressing needs (Table ES-1). Technology 

infrastructure is the broad base technologies and technical 

knowledge with varying degrees of public-good content

supporting the R&D and production efforts of firms, universities, 

and laboratories, as well as the development and adoption of 

improved and entirely new products, processes, and services.

Technology infrastructure includes infratechnologies and 

technology platforms. Infratechnologies are a varied set of 

“technical tools” that include measurement and test methods, 

artifacts such as standard reference materials that allow these 

methods to be used efficiently, scientific and engineering 

databases, process models, and the technical basis for physical 

and functional interfaces between components of systems 

technologies. Technology platforms are precompetitive proofs 

of concept that demonstrate the potential commercial viability 

of a new or improved product, process, or service.
Executive Summary

ES-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table ES-1. General Industry-Level Needs for Additive Manufacturing

Industry Needs Examples of Potential Impacts

Standards—standards, best practices, and 

reference data for materials and AM processes

• Improve confidence via reproducibility across 

manufacturing methods

• Provide greater assurance in raw materials

Metrology—real-time, in situ metrology, enabled 

by integrated sensors for real-time feedback 

during a build

• Identify in-build defects in time to correct and 

continue the build or scrap before using 

additional material

Design Allowables—design optimization tools 

and protocols for complex builds

• Improve “design to manufacture” guidance for 

designing and printing complex parts, including 

mesh, lightweight, and sacrificial support 

structures

• Reduce scrap rates and turnaround times and 

improve reliability and reproducibility of parts

Modeling and Simulation—high-fidelity process 

modeling and simulation for different materials and 

designs

• Improve yields, shorter and fewer R&D cycles

• Predict anomalies at various stages of a build

• Understand material-specific processes leading 

to new applications

Surface Finishing—cost-effective approaches to 

improve surface finishing of metal AM parts and 

standards for measuring surface finish and 

tolerances

• Eliminate or greatly reduce the degree of 

postprocessing required to make productionquality parts

Testing Procedures—innovative mechanical 

testing procedures

• Improve efficiency and cost savings from 

nondestructive and other test methods

• Improve confidence in AM processes and 

materials to speed up adoption and validation of 

high-value printed parts in various applications

ES.2 ANALYSIS APPROACH

The methodology includes the collection and analysis of 

qualitative and quantitative data from primary and secondary 

sources. To ensure that a variety of perspectives are accounted 

for, RTI interviewed a cross-section of nearly 60 interviews with

technology experts representing end using firms, technology 

developers and universities. We also had informal conversations 

with individuals at conferences and industry events, which 

contributed to the findings in this report.

We approached interviewees with a set of infrastructure 

technology needs, which, through our first phase of interviews, 

we found to be of the utmost importance to members of the 

manufacturing value chain:

 Materials and process standards and reference data

 Real-time metrology
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

ES-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

 Design optimization tools

 Modeling and simulation

 Surface finishing

 Mechanical testing procedures

Quantitative information from interviews about the prospective 

impact of meeting these needs formed the basis of our 

economic models that estimate the economic benefits that 

enhanced technology infrastructure would have on the U.S. 

manufacturing sector. Other key parameters in our models 

were derived from publicly available data on the manufacturing 

sector.

ES.3 ANALYSIS OF TECHNOLOGY 

INFRASTRUCTURE NEEDS

Our discussions highlighted significant complementarities 

among the six industry needs (Table ES-1). For instance, highfidelity predictive models would be a valuable tool for 

optimizing designs for 3D-printed parts and for qualifying parts 

for demanding applications with less need for destructive 

testing; building useful models requires large, high-quality 

scientific and engineering databases linking materials, 

processes, process conditions, and surface finish with the 

performance characteristics of the finished part.

Figure ES-1 apportions the estimated $4.1 billion annual impact 

over the six areas of unmet need. Enhanced standards, best 

practices, and reference data are associated with annual cost 

reductions for U.S. manufacturers of nearly $800 million. The 

cost impact of meeting each of the other five industry needs is 

between $600 and $700 million.

Stakeholders’ perceptions and opinions on each of the six needs 

are highlighted below.
Executive Summary

ES-5

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Figure ES-1. Total Annual Impact, Apportioned by Technology Need (Millions of 2013 US$)

ES.3.1 Materials and Process Standards and Reference Data

Our interview sample was unanimous in their assessment that 

the most important infratechnology needs at this time are 

materials standards, process standards, and reference 

databases. Standards serve the industry by ensuring quality 

and consistency for the input materials and during a build.

A key inhibitor to AM is convincing customers and certifying 

bodies that an additively produced part has the necessary 

quality to meet the application. One large manufacturing 

company shared that it spends $500,000 over a 6-month time 

frame to obtain mechanical properties just for a single part, 

made from a single material, using a specific additive 

manufacturing process with specific parameters.

A senior engineer at a leading aerospace company explained 

that AM needs “objective evidence of compliance to design 

intent. When you pull a part out of the machine, how do you 

know it meets its design intent?” According to another 

respondent in the same industry, “[you need] empirical 

evidence of success to build customer confidence.” This is the 

ultimate goal for AM: achieving a level of confidence that a part 

is almost certainly free of deformations and functionally sound, 

while adhering to design standards and guidelines. Combining 

specialized scientific and engineering expertise with 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

ES-6

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

impartiality, NIST is especially well positioned to overcome this 

barrier—an uncertainty-based market failure—by acting as an 

honest broker among parties at different tiers of supply chains.

Property data for a set of common process–material pairs could 

accelerate the introduction of additively built parts into service 

in existing industries, as well as new industries, and open up 

additional opportunities for small suppliers and manufacturers.

But because of the process–material connection and the many 

different process–material pairs relevant across applications 

(the lack of a single or even a few process–material pairs 

relevant to wide cross sections of industry), this is a task 

probably beyond the resources, at least for the time being, 

even of national laboratories. A practical and very useful first 

step would be to standardize the testing protocols, standardize 

the database schema for what data to collect, make a database 

available to the public, and allow the AM community to upload 

property data (obtained using standard procedures) to the 

database.

ES.3.2 Real-Time Metrology

Additively manufactured parts have an advantage in that the 

inherent layer-by-layer production provides an opportunity to 

take a snapshot at each fractional stage of product build. 

However, the metrology tools and associated real-time 

feedback processes remain in infancy. Most interviewees saw a 

need and value for real-time metrology, but few offered 

solutions or even topics for further research. Academic, 

government, and consortia groups are heavily pursuing this 

field, investigating optical (geometric), infrared, and thermal 

methods.

As reported by the companies surveyed, qualification is 

primarily done postproduction, with process and materials 

alterations done primarily by a trial-and-error method. The 

implementation of real-time metrology has clear benefits in 

efficiency, throughput, and related cost, replacing subjective 

reasoning with quantitative decision making. Given the 

variability in materials and processes as described above, realtime metrology and feedback loops offer a means of control 

that could compensate for the inputs.

Much like metrology desires in other manufacturing processes, 

manufacturers seek metrology solutions that are rapid, 
Executive Summary

ES-7

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

quantitative, nondestructive, inexpensive, and high resolution 

and that have wide dynamic range. The range of features that 

interviewees could monitor varies from geometric distortion to 

porosity to mechanical and thermal stress.

ES.3.3 Design Optimization Tools

Designers—using computer-aided design (CAD) software to 

define part requirements to meet the desired function—must 

know the tolerances of the materials and processes that will be 

used to bring their designs to life: How closely can they expect 

the raw materials and the process conditions to conform to the 

ideal? How will any variance affect how the part performs or 

under what conditions it will fail?

Accelerating AM will require approaches for optimizing designs. 

One of the most significant benefits of AM is the ability to 

create 3D, complex, interlocking pieces in one process. In this 

manner, additively produced parts may have advantages in 

both economics and performance over their subtractively built 

counterparts, but guidance and data to support these novel 

designs (e.g., angles, sacrificial structures, meshes) are 

needed.

One firm noted that when building an AM part for the first time 

from a CAD file, they are able to do it correctly only two out of 

three times. On the second attempt, there is a 90% success 

rate. This comment suggests that improvements to AM design 

rules could reduce scrap rates and result in more productive 

machine time.

ES.3.4 Modeling and Simulation

Tools are needed to model and simulate materials properties 

and establish robust process-structure-property relationships. 

Most AM modeling efforts are focused on creating predictive 

capabilities to understand resulting part properties given 

material and process inputs. Time-temperature history 

determines material microstructure, which determines 

mechanical properties. Measurement and control of that time-

temperature history is therefore important.

For aerospace and energy applications, in particular, modeling 

and simulation tools are critical. To date, this field has been 

held back by the lack of quality inputs. The variability in raw 

materials and processes, the lack of consistent metrology data, 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

ES-8

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

and simply the low number of similar parts produced by AM all 

contribute to the gap.

ES.3.5 Surface Finishing

Surface finish is a nagging problem for prototype and service 

parts. Additively built parts naturally have a rougher finish, 

similar to cast surfaces, requiring some postprocessing 

machining. This surface roughness is a function of both input 

materials (e.g., metal grain size) and process parameters 

(sintering, melting, beam width) and is often correlated with 

the fabrication time.

Better measurement methods are needed to enable the types 

of improvements in build processes that can reduce the need 

for surface finishing following a build.

Also, because topology optimization of additively built parts 

often creates surfaces where machine tools cannot reach, 

innovative surface finishing techniques, including hybrid 

manufacturing, may be required.

ES.3.6 Mechanical Testing Procedures

Innovative mechanical testing procedures are needed, 

especially to enable nondestructive testing. Closely linked with 

the needs for high-quality scientific and engineering data and 

high-fidelity modeling and simulation based on established 

process-structure-property relationships, novel mechanical 

testing procedures are needed to qualify 3D-printed parts for 

critical applications in aerospace and medicine.

As reported by an interviewee, one challenge with AM 

technology relates to “objective evidence of compliance to 

design intent.” When a part is extracted from a machine, it 

needs to be evaluated to determine whether it meets the 

design intent. The surface geometry can be analyzed, but there 

is no nondestructive methodology for determining whether the 

metal chemistry meets design specifications. A firm can 

produce a part, but how does one inspect and validate it? There 

needs to be a methodology to tell an operator that part A 

matches the history of yield specimens. Presently, firms are 

using ultrasound, X-ray, and computerized tomography scans 

to determine some qualities of the final part, but more costeffective approaches are needed.
1

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

1 Introduction

Additive manufacturing (AM) describes a set of processes for 

joining materials to make objects, layer on layer, from three-

dimensional model data. AM technologies are now enabling

transformative innovation across a range of manufacturing 

applications and industries: from accelerating modeling and 

prototyping cycles to producing complex metal structures with 

unique capabilities and features, and from ultrasound 

equipment and medical implants to gas turbines and jet engine 

components.

The consensus among the more than 50 AM experts RTI 

interviewed for this study was that AM has even greater

potential to enable both sustaining and disruptive innovation 

but is held back by the inadequacy of technology infrastructure 

needed to support the further development and application of 

AM technologies. This report provides in-depth analysis of those 

infrastructure needs and the potential economic benefits of 

meeting them through public research and development (R&D) 

investment.

AM processes are an alternative to conventional manufacturing 

methods such as injection molding (for plastics) and, for 

metals: investment casting; shaping, as by forging or rolling, to 

produce wrought metal; welding; and machining (e.g., drilling, 

turning, milling, and grinding).

When AM enhances the productivity of these conventional 

manufacturing processes, as when AM is used to produce 

prototypes for fit and assembly, patterns for prototype tooling, 

patterns for metal castings, and tooling components, AM can be 

seen as enabling sustaining innovation. For example, AM is 

enabling Siemens, a large, highly diversified engineering 

company, to greatly reduce the cost and time needed to replace 

blades on customers’ gas turbines and to accelerate prototyping 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

1-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

of turbine blades from 16-20 weeks to 48 hours (“Heavy 

Metal,” 2015).

The potential of AM to spur disruptive innovation is most 

evident in applications where additively manufactured (or 3Dprinted) parts can achieve performance characteristics that 

conventionally produced parts cannot. In applications where

these performance characteristics are sufficiently valuable to

end users, companies that have built sustainable competitive 

advantage on perfecting the conventional manufacture of the 

parts may find their business models disrupted.

Illustrating the potential performance gains AM can deliver, GE 

Aviation has developed a single-piece fuel nozzle for the nextgeneration LEAP (for Leading Edge Aviation Propulsion)

commercial jet engines (developed by CFM International, a 50-

50 joint venture between France’s Safran and GE Aviation) that 

is 25% lighter and five times more durable than a 

conventionally made nozzle composed of 20 separate parts. To 

produce the fuel nozzles for the LEAP engines—as well as a 

sensor housing, known as T25, already in service in the GE90 

engines that power Boeing’s 777—GE has installed more than a 

dozen additive machines in its 300,000-square-foot factory in 

Auburn, Alabama, billed by GE as the world’s highest-volume 

additive manufacturing center (GE Aviation, 2015).

As AM technology shortens the duration of product design 

cycles, enables more seamless transition from prototyping to 

production, and increases the frequency with which new 

product designs supplant old ones in production, companies can 

be expected to perceive greater advantages in collocating R&D 

and production and locating production facilities close to their 

customers. For U.S. companies especially, these trends will 

tend to favor locating production facilities in the United States. 

Providing the measurement science and other technology 

infrastructure necessary for U.S. companies to fully realize the 

potential of AM may, therefore, be expected to improve the 

U.S. trade balance for advanced technology products over time.

Worldwide sales revenues for AM equipment and services 

increased from less than $100 million in 1993 to $1 billion in 

2006, exceeded $2 billion in 2012, and surpassed $4 billion in 

2014. But this robust growth is largely driven by the 

prototyping and tooling applications that are less dependent on 

the next generation of measurement science and technical 
Section 1 

— Introduction 1-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

infrastructure that are the focus of this report.

1 AM is still in its 

infancy for applications like the LEAP engine fuel nozzle, and its 

rate of maturation will depend on the parallel development of 

infrastructure analogous to that now supporting fully mature 

conventional manufacturing methods.

1.1 DEFINITION OF TECHNOLOGY 

INFRASTRUCTURE

Technology infrastructure is the broad base of public and quasi-

public technologies

2 and technical knowledge that support the 

R&D and production efforts of firms, universities, and 

laboratories, as well as the development and adoption of 

improved and entirely new products, processes, and services 

(e.g., higher quality, more effective, more efficient, more 

productive).

Technology infrastructure includes infratechnologies and 

technology platforms. The public sector supports the majority 

of technology infrastructure research because of its public-good 

content (Tassey, 2008). A third element of Tassey’s (2008) 

technology element model, proprietary technology, is closest to 

a pure private good, but even in this case, relatively high risk 

typically leads to underinvestment.

Table 1-1 contains abbreviated definitions of the key concepts 

for ease of reference and lists examples of each term to make 

the concepts more concrete.

1.1.1 Infratechnologies

Historically, NIST has focused resources on this aspect of 

technology infrastructure. Infratechnologies are a varied set of 

“technical tools” that include measurement and test methods, 

artifacts such as standard reference materials that allow these 

methods to be used efficiently, scientific and engineering 

databases, process models, and the technical basis for physical 

and functional interfaces between components of systems 

technologies. As written in Tassey (2008), “[c]ollectively they 

constitute a diverse technical infrastructure, various types of 

 1 To be sure, prototyping and tooling applications also depend on 

measurement science and standards. The perception of industry 

stakeholders was by and large that the infrastructure technology 

needs of these applications was already being adequately met.

2

Technologies with varying degrees of public good content.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

1-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

which are applied at each stage of economic activity” (p. 618-

619). New infratechnologies often replace less efficient forms of 

infratechnology that support current standards (Tassey, 2008).

Infratechnologies influence the development of technology 

platforms and proprietary technologies. They also support 

efficient R&D, production, and market transactions such as 

complying with customer requirements and regulations.

Infratechnologies provide the technical basis for standards that 

are set using consensus standard-setting processes that are 

usually led by industry organizations. Their benefits include full 

disclosure of information, reduced uncertainty regarding 

product attributes, and an overall improved level of trust that 

helps to reduce market transaction costs.

The provision of infratechnologies requires a combination of 

industry and government investment because infratechnologies 

have substantial public good content (Antonelli and Link, 2014). 

Some industries depend on hundreds of distinct 

infratechnologies and associated standards. Furthermore, a 

particular infratechnology may have spillover benefits for many 

industries.

1.1.2 Technology Platforms

Technology platforms are precompetitive proofs of concept that 

demonstrate the potential commercial viability of a new or 

improved product, process, or service. These fundamental 

technical concepts originate from basic science research and 

can even be enabled by measurement infratechnologies (Link & 

Scott, 2010).

A characteristic of a technology platform is that it will often be 

foundational to multiple products and processes, the scope of 

which is typically broader than the business model of any one 

firm. Therefore, no firm is able to fully appropriate the benefits 

of investing in the development of a technology platform, so 

achieving the socially optimal level of investment will generally 

require additional public investment.

1.1.3 Proprietary Technologies

Proprietary technologies are not included in the definition of 

technology infrastructure for this study. Proprietary 

technologies are commercialized products, processes, and 

services that may be derivatives of technology platforms and 
Section 1 

— Introduction 1-5

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

have been influenced by infratechnologies. Generally, firm 

investments in proprietary technology fall under the category of 

R&D spending. Proprietary technologies that are ubiquitous 

may have quasi–public good characteristics, although they are 

almost exclusively funded and developed by private-sector 

firms. Proprietary technologies are included within the scope of 

this study to the extent that the infratechnologies and 

technology platforms on which we focus enable their 

development and adoption.

1.2 STUDY SCOPE

This report identifies gaps in technology infrastructure inhibiting 

the development and adoption of AM technologies by U.S. 

manufacturers and quantifies the prospective economic benefits 

of addressing these gaps. The report also outlines specific 

actions that the National Institute of Standards and Technology 

(NIST) can take to accelerate the development and adoption of 

critical technology infrastructure.

The research supporting this report was informed by primary 

data collection that consisted of unstructured and structured 

interviews with experts in the AM value chain, combined with 

secondary collection of industry information and data points. 

The findings of this report—the potential economic benefits and 

roles for NIST—are thus rooted in the perspectives of industry 

experts.

To ensure that a variety of perspectives were accounted for, 

RTI spoke with a cross section of experts in various stakeholder 

groups. We interviewed individuals from industry associations 

and research centers (observers), manufacturers of AM 

systems (developers), and end users of AM systems in a range 

of manufacturing industries (end users).

This report focuses on enhancements to the following types of 

technology infrastructure, identified through stakeholder 

interviews as industries’ most pressing needs:
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

1-6

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table 1-1. Definitions of Key Concepts

Term Definition Examples

Technology 

infrastructure

The broad base of quasi-public 

technologies and technical

knowledge that support the R&D 

and production efforts of firms, 

universities, and laboratories, as 

well as the development and 

adoption of improved products, 

processes, and services.

• Infratechnologies

• Technology platforms

Infratechnologies A varied set of “technical tools” 

that include measurement and test 

methods, artifacts such as 

standard reference materials that 

allow these methods to be used 

efficiently, scientific and 

engineering databases, process 

models, and the technical basis for 

physical and functional interfaces 

between components of systems 

technologies such as factory 

automation and communications.

• Standard reference materials

• Process models

• Techniques for process and quality 

control

• Calibration services

• Traceability of measurements and test 

methods

• Benchmarks and testbeds for 

characterizing a new technology’s 

expected performance under realistic 

conditions

• Objective characterization of 

performance attributes of component 

technologies

Technology 

platforms

Precompetitive proofs of concept 

that demonstrate the potential 

commercial viability of a new or 

improved product, process, or 

service. A characteristic of a 

technology platform is that it will 

often be foundational to multiple 

products and processes, generally 

from multiple firms.

• Bell Labs’ transistor proof-of-concept 

using solid state physics principles 

(Tassey, 2008)

• Prototype networks such as ARPANET 

and NSFNET that led to the Internet

• Chip-scale atomic clocks

• The fusing together of metal particles 

by selective laser melting, direct 

metal laser sintering, or electron 

beam to form a part according to a

set of computer-aided design (CAD)

instructions

Proprietary 

technologies

Commercialized products, 

processes, and services that may 

be derivatives of technology 

platforms and have been 

influenced by infratechnologies. 

Proprietary technologies that are 

ubiquitous may have quasi–public 

good characteristics, although they 

are almost exclusively funded and 

developed by private-sector firms.

• The specific AM systems produced and 

marketed by, for example, ARCAM,

3D Systems, EOS, Optomec, MTT, 

Renishaw, Realizer, and POM DMD

• The Rolls Royce–patented Shaped 

Metal Deposition technology

• GE Aerospace’s LEAP engine fuel 

nozzles and T25 sensor housings
Section 1 — Introduction

1-7

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

1. materials and process standards and reference 

databases

2. design optimization tools

3. process modeling and simulation

4. real-time, in situ metrology

5. improved surface finishing of metal additive parts (i.e., 

improved build processes to reduce the need for 

postprocessing)

6. innovative mechanical testing procedures

These six needs are summarized with examples of potential 

impacts in Table 1-2 and discussed at length in Sections 5.1 

through 5.6, drawing on explanations and anecdotes from 

stakeholder interviews.

Table 1-2. General Industry-Level Needs for Additive Manufacturing

Industry Needs Examples of Potential Impacts

Standards—standards, best practices, and 

reference data for materials and AM processes

• Improve confidence via reproducibility across 

manufacturing methods

• Provide greater assurance in raw materials

Metrology—real-time, in situ metrology, enabled 

by integrated sensors for real-time feedback 

during a build

• Identify in-build defects in time to correct and 

continue the build or scrap before using 

additional material

Design Allowables—design optimization tools 

and protocols for complex builds

• Improve “design to manufacture” guidance for 

designing and printing complex parts, including 

mesh, lightweight, and sacrificial support 

structures

• Reduce scrap rates and turnaround times, and 

improve reliability and reproducibility of parts

Modeling and Simulation—high-fidelity process 

modeling and simulation for different materials and

designs

• Improve yields, shorter and fewer R&D cycles

• Predict anomalies at various stages of a build

• Understand material-specific processes leading 

to new applications

Surface Finishing—cost-effective approaches to 

improve surface finishing of metal AM parts and 

standards for measuring surface finish and 

tolerances

• Eliminate or greatly reduce the degree of 

postprocessing required to make productionquality parts

Testing Procedures—innovative mechanical 

testing procedures

• Improve efficiency and cost savings from 

nondestructive and other test methods

• Improve confidence in AM processes and 

materials to speed up adoption and validation of 

high-value printed parts in various applications
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

1-8

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

In many interviews, our discussions highlighted significant

complementarities among these six areas. For instance, highfidelity predictive models would be a valuable tool for 

optimizing designs for 3D-printed parts and for qualifying parts 

for demanding applications with less need for destructive 

testing; building useful models requires large, high quality 

scientific and engineering databases linking materials, 

processes, process conditions, and surface finish with the 

performance characteristics of the finished part.

This report focuses on unmet needs that NIST is especially well

positioned to address, highlights experts’ perspectives on these 

needs and the business imperative of meeting them, and 

provides quantitative estimates of the potential return on 

appropriately targeted public investment. This report does not 

attempt a comprehensive treatment of AM materials, 

processes, and applications. For a broader overview, see 

Caffrey and Wohlers (2015). This report also does not provide a 

comprehensive statement of everything that NIST can do, 

because it is guided by one sample of interviewees at a given 

point in time.

1.3 ROLE OF NIST

A motivating principle for this study is that private investments 

in the development and adoption of new technologies typically 

generate social value in excess of their private returns. As a 

result, some socially productive technology investments are not 

undertaken because private companies do not see the research 

as profitable.3 The extent of private underinvestment, and thus 

the potential return on public investment, is likely to be 

greatest for precompetitive technology platforms and 

infrastructure—technologies with applications ranging well 

beyond the scope of any one company’s business model, often 

helping to bridge the divide between fundamental science and 

commercial development of proprietary technologies.

The private returns to developers’ and end users’ investments 

in AM technologies, and thus the rate and extent of adoption of 

these technologies in advanced manufacturing applications, will 

depend on the parallel development and diffusion of technology 

 

3 The private rate of return is less than what is required (the private 

hurdle rate), even though the social rate of return exceeds that 

required by society (the social hurdle rate).
Section 1 — Introduction

1-9

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

infrastructure that is generally underprovided by the market. It 

is this market failure—the failure of the market to provide a 

socially optimal level of technology infrastructure—that 

provides an opportunity to improve the efficiency of economic 

outcomes through public investment.

As discussed in this report, many of the general reasons for 

private underinvestment in technology development and 

adoption listed in Table 1-3 are relevant for AM technology 

specifically.4

NIST’s mission includes the provision of critical measurement 

science, technical inputs to standards, and other technical 

infrastructure to enable the efficient development and adoption 

of new technology by industry. NIST’s Engineering Laboratory, 

in collaboration with the Material Measurement Laboratory,

Physical Measurement Laboratory, and other parts of NIST,

Table 1-3. Barriers to Developing and Adopting New Technology That Brings about Market 

Failure

Barrier

General 

R&D 

Market 

Failures

Market Failures 

with Regard to 

Technology 

Infrastructure

Inability to appropriate all social benefits, such as positive 

network externalities ● ●

Scope of commercial applications is broader than the market 

strategy of any one firm ● ●

Risk that R&D outcomes will be technically insufficient 

(technical risk) ●

Risk that R&D outcomes, although technically sufficient, will not 

be received well by the market, thereby providing an 

unacceptable return on investment (commercial or market risk)

●

Long and uncertain lag between R&D investments and returns ●

Asymmetric information between developers and adopters of 

new technology ● ●

Difficulties in bringing together component technologies from 

different industry segments ● ●

Industry structure, such as network externalities, presenting 

market-entry barriers to new technology ●

 

4 The taxonomy of barriers presented here draws insight from Link and 

Scott (2010) and Jaffe, Newell, and Stavins (2005).
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

1-10

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

launched on October 1, 2013, the Measurement Science for 

Additive Manufacturing Program with four focus areas: material 

characterization, real-time process control, process and product 

qualification, and systems integration.5

To improve the accuracy and efficiency of material 

characterization, NIST is developing standardized methods to 

characterize the properties of metal additive powder and 3Dprinted parts and, by applying these methods in extensive 

round robin tests, generating high-fidelity reference data.

To enable real-time process control, NIST is developing 

measurement systems and control algorithms using a smallscale metal laser sintering platform as a test bed. The process 

metrology, test methods, and traceable data developed here 

will support the validation of process models on factory floors 

everywhere, calibration of in-process sensors, and 

determination of optimal process conditions.

To reduce the need for extensive empirical testing to fully 

qualify AM processes and parts, NIST is developing 

measurement science to support equivalence-based and modelbased qualification. In cooperation with industry and university 

partners, NIST is developing high-fidelity multi-physics process 

models and generating trusted data necessary for validating 

models that will be able to predict the performance 

characteristics of a 3D-printed part by integrating pre-process, 

in-process, and postprocess measurements.

To improve the performance of AM systems, NIST is developing 

standards to support consistent data exchange among AM 

modeling and simulation tools and methods of validation and 

verification to support the integration and exchange of AM 

models and data. The ultimate aim is to develop a federated 

information systems architecture with common data structures 

and interfaces to streamline the integration of AM systems.

Additional NIST activities related to additive include research in 

the Materials Measurement Laboratory on AM material property 

measurement, material testing and modeling, and defect 

detection; work by the Center for Neutron Research related to 

neutron imaging and AM residual stress measurement; 

 

5 For details of the program and its four focus areas, see 

http://www.nist.gov/el/isd/sbm/msam.cfm. 
Section 1 

— Introduction 1-11

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

statistical analysis by the Information Technology Laboratory of 

AM round robin test results; work by the Physical Measurement 

Laboratory related to thermal emissivity measurement for AM 

processes and laser power measurement; and industry 

outreach and assistance through the Manufacturing Extension 

Partnership.

6

1.4 WHAT DISTINGUISHES THIS REPORT

AM has received widespread attention, in the popular press, in 

the scientific and engineering literature, and in an important 

gray literature comprising conference presentations and 

technical reports produced by industry stakeholders. A recent 

and particularly incisive example of the latter is the Consortium 

for Additive Manufacturing Materials’ Strategic Roadmap for the 

Next Generation of Additive Manufacturing Materials (CAMM, 

2015). Caffrey and Wohlers (2015) provide the latest 

installment in a fine series documenting AM technology state of 

the art and providing market analysis.

The unique contribution of this report is to identify AM 

technology needs most closely aligned with NIST’s mission and 

provide defensible estimates of the economic impact of meeting 

those needs. This report is intended to provide NIST and other 

stakeholders with relevant quantitative and qualitative 

information to consider when planning and prioritizing 

investments and research activities.

This report complements previous studies and roadmaps by 

engaging industry stakeholders and reporting their opinions and 

perspectives related to the importance to their manufacturing 

operations of infrastructure technology for AM. This report also 

builds on earlier studies by providing quantitative estimates of 

the potential impact of enhanced infrastructure based on 

stakeholder views. To facilitate stakeholder interviews, 

emphasis was placed on high-level areas of need, with specific 

infrastructure technology elements referenced only as 

illustrative examples. For a more exhaustive discussion of a 

larger set of infrastructure technology elements relevant to AM, 

a useful reference is the 2013 Measurement Science Roadmap 

for Metal-Based Additive Manufacturing(NIST, 2013). The focus 

 6 For more details see http://www.niu.edu/ceeT/MSAM/NIST_DED_ 

Workshop2016_Day1_Intro_Slides_Jurrens.pdf. 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

1-12

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

of this report on stakeholder views, related directly and 

transformed into quantitative impact estimates, also 

distinguishes it from recent economic studies of AM such as 

Thomas (2013) and Thomas and Gilbert (2014).

This report provides a working portrait of AM technology as it is 

applied in U.S. manufacturing industries today, focusing 

especially on the gaps that now exist in technology 

infrastructure—the currently unmet needs for measurement 

science, including metrology and test methods, traceable 

reference data, and other formal knowledge—that limit AM 

technology’s further development and adoption, and the ways 

in which meeting these needs could spur innovation and growth 

in US advanced manufacturing.

The remainder of this report is organized as follows:

 Section 2 outlines our approach to data collection and 

analysis.

 Section 3 provides an overview of AM technology and its 

application in advanced manufacturing industries.

 Section 4 presents quantitative results and economic 

impact analysis.

 Section 5 provides qualitative results, drawing heavily 

on stakeholder interviews and discussing each of the six 

identified needs.

 Section 6 concludes the report by summarizing our 

general findings.
2

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

2 Analytical Approach

This section discusses the details of our data collection process 

and the transformation of interview data to support models that 

estimate the economic impact that enhanced technology 

infrastructure would have on the U.S. manufacturing sector.

2.1 DATA COLLECTION

The analysis presented in this report was informed by nearly 60 

interviews with technology experts representing end-using

firms, technology developers, and universities. These interviews 

yielded a detailed summary of the most pressing technology 

infrastructure needs for AM, expected economic outputs and 

outcomes resulting from those technology needs being met, 

and quantitative impact data as well as anecdotes and 

qualitative information for context.

The sample of interviewees was identified by researching firms, 

industry associations, research efforts, and conferences with 

expertise in AM. RTI attended two conferences in 2014 and four 

in 2015 that were either dedicated to AM or had heavy 

representation from firms using AM. As well, individuals in 

industry and academia well connected in the AM space provided 

additional contacts as potential interviews.

In total, and through the means mentioned above, RTI 

contacted 118 individuals in a wide range of industries and 

research environments and succeeded in securing interviews 

with 55 of them. Of the 55 interviews conducted, 23 provided 

quantitative responses related to their respective organizations’ 

operating costs. The other 32 respondents did not provide 

quantitative responses for various reasons, most often because 

their involvement was more closely related to R&D or academic 

research; thus, their focus and expertise did not support 

venturing estimates of cost impacts.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

2-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Our data collection process began with selecting relevant 

sectors, then identifying contacts within those sectors with the 

appropriate level of expertise, conducting detailed interviews 

with those contacts, and determining their detailed North 

American Industry Classification System (NAICS) code with in 

the sector.

2.1.1 Interviews

Interviews were primarily conducted over the phone. For phone 

interviews, we provided the interview guide several days before 

the interview to help interviewees become better acquainted 

with our questions. The remaining interviews were conducted in 

person at industry events and conferences.

Interviews were preferable to other alternative data collection 

modes such as online surveys because of the highly complex, 

nuanced subject matter. Through interviews we were able

obtain high-quality and rich information where we could walk 

the interviewee through our questions, providing prompts and 

adjusting course throughout as needed.

We identified potential interview respondents by first identifying 

firms selling AM systems or components (developers) and firms 

using AM systems in their manufacturing activities (end users). 

We then searched for key personnel within those firms. To 

supplement this list, we also identified contacts by conducting 

Internet searches for specific job titles. Finally, we identified 

and secured high-value respondents by attending industry 

conferences and trade shows.

Respondents represented a broad set of industries that use and 

develop AM technologies. Respondents also varied in seniority, 

from middle management to executives. Following are some 

examples of the job titles of those with whom we spoke:

 senior engineering manager

 director, advanced manufacturing technology

 senior automation engineer

 process automation engineer/process modeling and 

optimization engineer

 CEO/president

 founder

 chief technology officer/chief technical advisor
Section 2 

— Analytical Approach 2-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

 global lead for manufacturing

Interview guides were used to structure the conversations and 

collect specific quantitative information. Two versions of the 

interview guide were used, one for developers (Appendix A) 

and one for end users (Appendix B). Some firms are hybrid 

developer-users, and in these cases, we focused on the end-

user perspective but asked about both. Interview questions 

asked about expectations for the economic impact of applicable 

AM manufacturing technologies in terms of the percentage 

changes in their firm’s capital and labor, energy, and materials 

costs.

2.1.2 Stakeholder Groups

AM developers (systems manufacturers and material providers) 

and end-users (manufacturers using AM systems and service 

bureaus) provided complementary insights through their responses to interview questions.

All respondents provided quantitative ratings of the importance 

of the identified infrastructure needs. Both groups also provided 

qualitative insights on their perceived barriers to AM technology 

development and adoption, key technical pain points, and how 

these could be addressed by meeting the identified needs.

End users provided additional quantitative responses on how 

meeting identified needs for AM technology infrastructure would 

change the costs of four factors of production—capital, labor, 

energy, and materials (KLEM).

2.2 ECONOMIC MODELS

Using the sales impact estimates provided by developers and 

the production cost impact estimates provided by end users 

associated with having identified needs met, we estimated the 

annual national impact for the United States using industry data 

and information about applicability.

Respondents were asked to provide a percentage impact 

estimate for each quantitative response, with ranges being 

acceptable. In cases where a respondent provided a range, we 

took the midpoint of the range. In cases where a respondent 

provided a single point estimate, the low and the high 

responses were assumed to be identical to the midpoint. The 

focus of the methods discussed below is on the midpoint impact 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

2-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

estimates, but the same approach was carried out with the low 

and the high responses to obtain ranges for impacts.

Quantitative responses were summarized at the micro or firm 

level and also scaled to reflect the applicable part of the 

industries represented by the interview respondents. For both 

approaches, we identified the industries represented by the 

respondents by querying a variety of sources including the 

following:

 Hoover’s database of company profiles.

 Census NAICS website search with information provided 

by the respondent about the division within their firm 

that they represent.

 Descriptions of activities from company websites and/or 

annual reports.

2.2.1 Firm-Level Data

Respondents provided percentage changes to KLEM costs (as 

well as other production variables such as production yield and 

scrap rate). Dollar impacts were derived by first estimating the 

firm-level domestic sales to which the impact estimates applied. 

We estimated firm-level costs using industry-level cost-to-sales 

ratios from secondary sources such as the Annual Survey of 

Manufactures (ASM) and the Bureau of Labor Statistics InputOutput (IO) data. Percentage changes in costs were then 

applied to these estimates.

Firm-level sales were pulled from annual reports, public filings, 

and the Hoover’s database of company profiles. For larger firms 

with multiple lines of business where it was clear that the 

impact estimates only applied to a certain division, we 

estimated division-level sales using information from annual 

reports.

To estimate costs-to-sales ratios, we used industry data from 

national accounts provided by the Bureau of Labor Statistics 

(BLS) for industry-level energy and materials cost estimates. 

Energy costs included the manufacturing industry’s purchases 

of oil and gas extraction (NAICS 211), coal (NAICS 2121), 

electricity (NAICS 2211), natural gas (NAICS 2212), and 

refined petroleum (NAICS 324). Materials costs included 

purchases from other manufacturing industries in the NAICS 

range 3210–3330, excluding 324 (refined petroleum and coal).
Section 2 

— Analytical Approach 2-5

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

The data provided by BLS give highly aggregated accounts for 

capital and labor. To better identify capital and labor costs 

associated with “shop floor” activities, we relied on the 2013 

ASM. Capital costs include capital expenditures on machinery 

and equipment (CEXMCH, RPMCH), computer and peripheral 

equipment (CEXMCHC, PCHCMPQ), and other machinery and 

equipment (CEXMCHO, RPMCH). Labor costs include production 

workers’ annual wages (PAYANPW) grossed up to include 

nonwage benefits such as health insurance (BENHEA), 

retirement (BENPEC, BENPEB), and other fringe benefits 

(BENOTH).

Firm-level KLEM cost estimates then equal the estimate of firm 

or division sales times the relevant industry’s cost-to-sales ratio 

based on the BLS (energy and materials) or ASM (labor and 

capital) data. For example, we estimate production capital is 

5.4% of sales in the iron and steel mills industry (NAICS 3311). 

A respondent at a firm with $500 million in sales within this 

industry who reported a 5% reduction in firm-wide capital costs 

would yield a $1.4 million ($500 * 0.054 * 0.05) capital impact 

estimate for advanced manufacturing technology adoption.

2.2.2 Impact Applicability

The values at the industry level, however, do not accurately 

reflect AM’s share of revenue generation. Because AM 

applications represent only a fraction of U.S. manufacturing 

activity, RTI analyzed the findings in the Wohlers Report 2015

(Caffrey and Wohlers, 2015) to offer more realistic impact 

estimates.

The Wohlers Report estimates that revenues generated from 

AM activities totaled roughly $4.1 billion worldwide. Because 

RTI is interested in only advanced manufacturing technologies 

in the United States for the purposes of this report, we 

estimated the U.S. market for AM to be $2.3 billion. This value 

was generated by multiplying the cumulative share of AM 

industrial machines installed in the United States between 1998 

and 2014 (approximately 40%, according to the Wohlers Report 

2015 [Caffrey and Wohlers, 2015]) by the 2014 worldwide 

market for AM. Thus, 40% of $5.8 billion results in a $2.3 

billion market share for the United States.

Additionally, only the “services” market, which is defined as 

revenues generated from “parts produced on AM systems by 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

2-6

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

service providers, system maintenance contracts, training, 

seminars, conferences, expositions, advertising, publications, 

contract research, and consulting services,” were used in our 

economic impact analysis (Section 5). Revenues generated 

from AM system sales, materials, aftermarket products, or 

software were excluded.

The Wohlers Report provides industry shares of additive in 

terms of machine sales, which were used as a proxy for the 

relative size of AM at each industry. These industry shares were 

applied to the domestic sales value of AM ($2.3 billion) to 

obtain the dollar value of AM in each industry. The dollar values 

were then applied to our microeconomic model to discount the 

results because AM is involved in such a small percentage of 

manufacturing production.

2.2.3 Industry-Level Impacts

Respondents were asked to provide a percentage estimate for 

each quantitative response, with ranges being acceptable. In 

cases where a respondent provided a range, we took the 

midpoint of the range. In cases where a respondent provided a 

single point estimate, the low and the high numbers were 

assumed to be identical to the midpoint.

The midpoint estimates were averaged and applied to the 

respondent’s industry at the six-digit level that most closely 

aligned with the division and role of the respondent. However, 

the results were rolled up to the four-digit level for presentation 

purposes only, and the underlying data were still derived at the 

six-digit level.

The number of responses varies by four-digit manufacturing 

NAICS. We received quantitative responses for 12 of the 

approximately 85 NAICS manufacturing sectors defined at the 

four-digit NAICS level. The majority of the 85 manufacturing 

industries are not using AM. Though they may benefit from the 

technology in the future, the industries targeted in this analysis 

were the industries that are most familiar with AM. This underresponse biases our estimates downward.

2.2.4 Apportioning Total Impacts over Industry Needs

We apportioned a share of the total cost impact to each of the 

six industry needs in Table 1-2 according to the average 

importance ratings associated with each need. We used only 
Section 2 

— Analytical Approach 2-7

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

the importance ratings provided by end users (see Section 4.1 

and Appendix C on importance ratings).

For example, if an interviewee awarded a total of 20 points 

across the six capabilities (i.e., if the sum of the six importance 

ratings was 20), and if modeling and simulation was rated a 5 

and real-time metrology was rated a 2, then these shares 

would be 25% and 10%, respectively. We then averaged these 

shares across individuals and applied them to the total cost 

impact.

2.3 CONSERVATIVE NATURE OF APPROACH

The quantitative economic impact estimates calculated in this 

study are considered to be conservative in that they do not 

capture all the benefits that would result from an improved 

technology infrastructure. As discussed below, the focus of our 

analysis is on reductions in manufacturers’ production costs

that would result from meeting the identified technology 

infrastructure needs. However, this focus does not encompass

all of the potential economic benefits associated with an 

enhanced technology infrastructure.

Lowering U.S. manufacturers’ production costs in AM-specific 

applications would lead to lower prices for consumers of 3D-

printed goods, which in turn would lead to the expansion of 

these market segments. Of even greater importance, albeit 

more difficult to quantify with any sort of accuracy, meeting 

these needs would lead to improvements in the performance 

characteristics of AM parts, which would shift demand outward 

and expand these market segments still further. The 

emergence of altogether new products and markets would 

almost certainly also be accelerated.

Quantifying the value of new (yet to be defined) products or 

product attributes is difficult, involves great uncertainty, and is 

beyond the scope of the study.

An improved technology infrastructure will also lead to reduced 

R&D costs. However, interviewees were not able to quantify 

R&D savings, saying that the benefits would be a mixture of 

improved/accelerated R&D and enhanced product quality. 

Hence, these categories of benefits are discussed only 

qualitatively and are not included in the quantitative economic 

impact estimates.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

2-8

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

In general, focusing on manufacturing cost savings implies the 

analysis captures primarily gains in producer surplus and does 

not capture gains in consumer surplus associated with 

improved product quality. In addition, the analysis does not 

capture increases in social welfare from increased output 

(sales), which result from lower cost and higher demand. Nor 

does the analysis capture long-term competitive benefits such 

as on-shoring (or re-shoring) of advanced manufacturing 

activity that would result from general improvements in 

productivity and specifically greater advantages in collocating 

R&D and production and locating production facilities close to 

the large U.S. customer base. Also not quantified is the 

potential effect of enhanced infrastructure to improve the 

reliability of additively manufactured parts, with its implications 

for product safety, product liability, and the chilling effect 

premature failures can have on the adoption of new technology.

For these reasons, the economic impacts presented are 

considered to be conservative, lower-bound estimates.
3

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

3

Overview of 

Additive 

Manufacturing

In the early 1980s, an engineer named Chuck Hull had an idea: 

to use UV light to cure successive layers of (liquid) photo-

curable polymer one on another to form 3D shapes. By the 

mid-1980s, Hull was marketing his rudimentary 3D printer to 

the US automotive industry as a means of producing prototypes 

without the need to send blueprints to a tool-and-die shop and 

wait months for the parts to come back (Kennedy, 2013).

Fittingly, rapid prototyping (RP) was the first name given to this 

emerging technology. As the technology became more widely 

used in myriad applications, 3D printing became the popular 

name, although solid freeform fabrication and other synonyms 

are sometimes still used. Perhaps to emphasize the difference 

between hobbyist-scale 3D printers and the industrial scale 

machines that melt advanced metal alloys with lasers, industry 

users have gravitated to the term additive manufacturing (AM).

Manufacturers across a range of industries are exploring an 

even wider range of applications for this versatile new 

technology as an alternative to conventional manufacturing 

methods: injection molding for plastics and, for metals: 

investment casting; shaping, as by forging or rolling, to 

produce wrought material; welding; and machining, typically 

using Computer Numerical Control (CNC) machines to guide 

machine tools such as drills, lathes, mills, and grinders.

Extant measurement science, materials property databases, 

standards, design methodologies, all have had decades to 

mature around these conventional manufacturing methods. 

Polymers and metal alloys have been optimized for these 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

processes. Even in this environment, manufacturers’ perceive 

worthwhile investments in AM technologies, particularly in 

prototyping and tooling applications, but only up to a point. 

Continued strong growth in AM, especially in metal and in the 

production of critical structural and functional parts, will depend 

on the development of analogous infrastructure for AM.

3.1 MATERIALS AND PROCESSES

The performance characteristics of 3D-printed parts depend on 

the properties of the raw materials—additive feedstocks—and 

the process by which the particles of material are fused 

together to form the part. These dependencies are sometimes 

described as process-structure-property relationships: 

Feedstock and process conditions determine the microscopic 

structure of the 3D-printed material, and that structure in turn 

determines its properties. Postbuild processing that influences 

material properties (such as heating or shot peening) also 

affects the properties of the finished part.

When performance characteristics of the 3D-printed parts are 

critical—as in the case of functional jet engine parts or 

implantable medical devices—AM systems users must be able 

to ascertain all the relevant properties of their feedstocks, 

control and monitor all of the relevant variables during the 

build, and have a fundamental understanding of how those 

material properties and process conditions correlate with the 

performance characteristics of the finished part.

Designers—using CAD software to define part requirements to 

meet the desired function—must know the tolerances of the 

materials and processes that will be used to bring their designs 

to life: How closely can they expect the raw materials and the 

process conditions to conform to the ideal? How will any 

variance affect how the part performs or under what conditions 

it will fail?

The two major categories of AM feedstocks are plastics and 

metals. Ceramic materials are also used, in combination with 

plastics or metals, in a limited number of applications. The 

ceramic material may be blended with sacrificial polymers that 

act as support structures during the build, often to produce 

porous ceramic molds for investment casting, or may be mixed 

with metal powder, the ceramic powder acting as an additive, 

to change the fluidity or melting behavior of the metal (CAMM, 
Section 3 — Overview of Additive Manufacturing

3-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

2015). Table 3-1 summarizes the most commonly used 

processes and materials.

3.1.1 Plastics

Plastic additive feedstocks account for more than 90% of all AM 

feedstock sales.7 As a rough indication of the relative scale of 

AM, Caffrey and Wohlers (2015, p. 54) cite an estimate by a 

representative of an international chemical company that for 

every kilogram of AM polymer sold, 100,000 kilograms of 

plastic material are sold for conventional manufacturing 

applications. In part because of the additional processing steps 

involved in producing plastic additive feedstocks, but also in no 

small part because of the relatively small market dominated by 

a small number of sellers, additive plastic feedstocks sell for 50 

to 100 times the price per kilogram of the same raw materials 

for conventional use.8

Fully characterizing property-structure-performance 

relationships for plastics is important in many applications, 

although plastics-focused industry stakeholders with whom RTI 

spoke expressed relatively less need for technology 

infrastructure to support their efforts. Part of the reason seems 

Table 3-1. Techniques/Methods Used in Additive Manufacturing

Production Process Material Market

Vat photopolymerization Photopolymers Prototyping

Powder bed fusion Polymers, metals Prototyping, direct part, tooling

Material jetting Polymers, waxes Prototyping, casting pattern

Binder jetting Polymers, metals, foundry, sand Prototyping, casting molds, direct part

Material extrusion Polymers Prototyping, non-structural direct part

Sheet lamination Paper, metals Prototyping, direct part

Directed energy deposition Metals Repair, direct part, tooling

Source: ASTM; compiled by the Industrial Economics & Knowledge Center, Industrial Technology Research Institute 

of Taiwan (2013).

 

7 Of $640 million in worldwide additive feedstock sales in 2014, metal 

accounted for $48.7 million (Caffrey and Wohlers, 2015). 8 Caffrey and Wohlers (2015, p. 54) report a range of $175 to $250 

per kilogram for thermoplastics and photopolymers for industrial AM 

systems, compared with $2 to $3 per kilogram for thermoplastics 

for injection molding.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

to be that knowledge of conventionally processed plastics is 

relatively easy to leverage into an adequate understanding of 

the same materials processed on AM systems; additive 

processing introduces only a limited range of additional 

uncertainty. Also part of the reason: 3D-printed plastic parts 

are less often used in the most demanding applications, 

requiring qualification and certification. When qualification of a 

plastic part is required, it is less likely to be prohibitively 

expensive for a company to satisfy the requirement by brute 

force—relying on extensive empirical testing. Finally, plastic AM 

has simply been around longer, and the relevant knowledge 

base has had longer to develop. Several technical barriers and 

unmet measurement science needs exist in polymer AM. NIST’s 

Material Measurement Laboratory is hosting a road mapping 

workshop on polymers in June 2016 to further define and 

address these issues.

3.1.2 Metals

Although metal additive feedstocks currently account for less 

than 10% of all AM feedstock sales, metal dominates 

manufacturing applications for which technology infrastructure 

needs are most pressing.

Various metal alloys are used in different applications. The 

consensus among the metal-focused industry stakeholders with 

whom RTI spoke was that formal knowledge would be fairly 

specific to an alloy, or a family of alloys, and that formal 

knowledge about a particular alloy would be relatively 

application-agnostic. Note that it is generally not possible to 

separate the materials (i.e., type of alloy) from the process 

(i.e., the AM system used to build the parts) because of the 

specialized nature of structure-processing-property 

relationships for each alloy and the fact that AM, unlike 

traditional subtractive manufacturing, is also materials 

processing.

In other words, formal knowledge (using this term as shorthand 

for the measurement science and various elements of 

technology infrastructure NIST can provide) about stainless 

steel would be of little use to manufacturers building with 

titanium or aluminum but would be equally useful to 

manufacturers in different industries building stainless steel 

parts for different applications (provided they are using the 

same process).
Section 3 — Overview of Additive Manufacturing

3-5

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

One aerospace engineer suggested that the greatest value 

would come from NIST pursuing three to five alloys in parallel, 

generating formal knowledge about the most commonly used 

titanium, aluminum, and stainless alloys, plus one super alloy, 

plus Cobalt-Chromium, or CoCr (Table 3-2). Because of the 

noted interdependence of process and material, a challenge in 

undertaking this type of study would be to select the process 

most appropriate for each alloy. Selection of material–process 

pairs for study may run into trade-offs across different 

industries and applications that may make it difficult to move 

forward. That is, if there is no single material–process pair (or 

even a small set of such pairings) that would be widely 

applicable across a range of industries, it may be difficult to 

justify moving forward with a scope of inquiry likely to benefit 

(at least in the short run) only a relatively narrow industry 

segment.

3.1.3 Metallic Additive Manufacturing Systems

Metal AM systems include powder bed, powder feed, and wire 

feed. Feedstocks are melted and fused by laser, electron beam, 

or plasma arc. Frazier (2014) provides an excellent overview.

In powder feed–directed energy deposition systems, metal 

powder is fed through a nozzle, or deposition head, onto the 

build surface and fused with a laser. The work piece may 

remain stationary while the deposition head moves, or the 

deposition head may remain stationary while the work piece 

moves. The build area can be large, upwards of 1 cubic meter, 

and the systems can be used to refurbish worn parts or repair 

damaged ones. Siemens uses SLM Solutions’ powder feed 

systems to replace blades on customers’ gas turbines (“Heavy 

Table 3-2. Selected Alloys Used in Additive Manufacturing

Titanium Aluminum Tool Steels Super Alloys

Stainless 

Steel Refractory

Ti-6Al-4V Al-Si-Mg H13 IN625 316 & 316L MoRe

ELI Ti 6061 Cermets IN718 420 Ta-W

CP Ti Satellite 347 CoCr

γ-TiAl PH 17-4 Alumina

Source: Frazier (2014).
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-6

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Metal,” 2015). Powder feed systems are also used to repair the 

burner tips of gas turbine burners.

Wire feed–directed energy deposition systems are unusual 

among metal AM systems in using feedstock in the form of wire 

rather than powder. Wire feed offers build areas comparable to 

powder feed, using electron beam, laser beam, or plasma arc to 

melt a bead of material onto the work piece. Advantages of 

wire feed systems include high deposition rate and large build 

volumes, but for most applications require more extensive 

surface finishing (Frazier, 2014).

Powder bed fusion systems afford manufacturers the greatest 

capabilities to maintain dimensional control and to produce high 

resolution features and internal passages, albeit in a smaller 

build area; think of a cube roughly 30 cm on a side (Frazier, 

2014). Think of a surface onto which a thin layer of powder is 

raked, and then selectively melted with a laser or electron 

beam.9 The work piece is lowered slightly—by the height of a 

layer of powder, a fresh layer of powder is raked across, and 

the process repeats. The LEAP engine fuel nozzles and T25 

sensor housings are built with powder bed fusion systems.

3.2 APPLICATIONS AND INDUSTRIES

The first AM systems, emerging in the 1980s, were used for 

modeling and prototyping, applications that cut across all 

manufacturing industries. The formal knowledge base 

supporting these applications has had decades to mature.10

Soon after, and similarly cross-cutting, came 3D-printed 

silicone rubber tooling, or molds, for prototype, pre-production, 

and production urethane parts. More recently, investment 

casting patterns, molds and cores for sand casting, tooling, and 

tooling inserts have been 3D printed (Caffrey and Wohlers, 

2015).

 

9 Selective laser melting is more common; used by six of eight 

systems manufacturers. EOS (Germany) uses direct metal laser 

sintering. ARCAM (Sweden) uses electron beam. Until recently, all 

eight powder bed fusion systems manufacturers were located 

outside the United States (Frazier, 2014). 3D Systems, 

headquartered in Rock Hill, South Carolina, recently added a 

powder bed fusion system to its product line. 10 The first systems from the 1980s actually consist of multiple (and 

very different) technologies, each with its own knowledge base.
Section 3 — Overview of Additive Manufacturing

3-7

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Application of metal AM for functional end-use parts ranges 

from custom biomedical implants (Harrysson et al., 2008) to 

complex aerospace parts (Petrovic et al., 2011). One 

interviewee in the biomedical space believes that in 5 to 10 

years, 20 to 30% of bone implants and surgical guides will be 

patient-specific and produced using AM. The defining advantage 

of metal AM is its enabling of design complexity as shown in 

Figure 3-1, ranging from complex biomedical implants to 

engineered lattice structures and filters. For these applications, 

AM is still an emerging technology, and the formal knowledge 

base supporting these applications is not fully formed.

This section discusses applications of AM with emphasis on their 

relative needs for measurement science, traceable reference 

data, high-fidelity modeling and simulation capabilities, and 

other infrastructure technology NIST can provide.

3.3.1 Modeling and Prototyping

Common to all manufacturing industries is the need to 

communicate design intent—to facilitate the translation of twodimensional blueprints (now mostly 3D CAD models, not 

drawings) into functional commercial products—using 3D 

models and prototypes.

Prototyping parts—from car door handles to gas turbine 

blades—can take weeks or months using conventional 

manufacturing methods, and the tooling created for the 

prototypes is expensive, amortized over only a small number of 

Figure 3-1. Metal-AM Part Design Complexities

Source: North Carolina State University.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-8

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

pieces. AM eliminates the need for tooling and reduces the 

turnaround time to days if not hours.

These applications of AM are exciting and offer real value to 

manufacturers. The formal knowledge base supporting these 

applications is relatively mature, and the potential return on 

public investment to further develop that knowledge base is 

relatively small.

3.3.2 Tooling

Tooling, such as molds and cores, dies, fixtures, and jigs, also 

cuts across all manufacturing industries. The role of AM is 

detailed by Caffrey and Wohlers (2015).11 Illustrative examples 

include the use of AM parts as investment casting patterns, 

eliminating the need for costly, time-intensive wax pattern 

tooling; 3D-printed molds and cores for sand casting prototype 

engine, transmission, and brake components; and 3D-printed 

tooling and tooling inserts with conformal cooling channels that 

wick heat more efficiently and so improve the quality of the 

molded part.

Like prototyping, although tooling applications of AM are 

exciting and offer real value to manufacturers, the formal 

knowledge base supporting these applications is relatively 

mature, and the potential return on public investment to further 

develop that knowledge base is therefore relatively small.

3.3.3 Aerospace

3D printed parts are now in service on commercial aircraft. 

These include many polymer parts and some metal structural 

parts—not flight-critical wing struts but such parts as overhead 

luggage brackets—and the T25 sensor housing now flying in 

some of the GE90 engines that power Boeing’s 777. In October 

2015, CFM International, a 50-50 joint venture between 

France’s Safran and GE Aviation, delivered the first LEAP 1B 

engines to Boeing; the engines will power the new 737 MAX 

airplane.12 Each LEAP engine contains 19 of GE’s 3D-printed 

fuel nozzles.

 

11 Additional discussion of metal casting processes can be accessed at 

wohlersassociates.com/castmetal2015.pdf. A history of AM tooling 

options can be accessed at wohlersassociates.com/tooling2015.pdf. 12 http://www.cfmaeroengines.com/press/cfm-delivers-first-leap-1bengines-to-boeing/823.
Section 3 

— Overview of Additive Manufacturing 3-9

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Eliminating 1 kilogram from a commercial jet would have saved 

an estimated $3000 annually in 2011, when the price of jet fuel 

was around $3 per gallon (West, 2011). Jet fuel has recently 

been around $1, so at today’s prices, 1 kilogram saved is worth 

roughly $1000. Each of the 58 3D-printed fuel nozzles on the 

737 MAX (29 in each of two engines) is 25% lighter than its 

conventionally built predecessor (RTI did not ascertain the 

weight of each nozzle); additional savings come from more 

efficient fuel delivery achieved by an internal structure enabled 

by AM. A 2013 contest, sponsored by GE to redesign for AM a 

2,033-gram engine bracket (used by manufacturing and 

maintenance crews to manipulate the 6-ton engines), was won 

by M. Arie Kurniawan, an engineer from Indonesia. The winning 

design shaved 1,706 grams—worth $1,706 in annual fuel 

savings at today’s prices.

To bring the LEAP fuel nozzles into commercial service, GE 

made large investments in acquiring (through its acquisitions of

Morris Technologies and Rapid Quality Manufacturing) and 

developing in its R&D labs the formal knowledge needed to 

design, build, and qualify the 3D-printed nozzles. R&D 

investments on this scale are not feasible for many companies. 

Much of the knowledge generated by GE in this effort is not 

specific to the LEAP nozzle and certainly would have application 

well beyond the scope of even GE’s widely diversified 

technology portfolio.

It follows that private investment in generating formal 

knowledge about AM technology for high-value applications is 

likely to be less than optimal for at least two reasons: imperfect 

credit markets (characterized by information asymmetries 

between lenders and borrowers) will not fund every R&D 

project with positive expected net present value, and the 

expected return on R&D investment that determines a 

company’s willingness to invest will be limited to the scope of 

its own business strategies. Public investment in generating and 

disseminating formal knowledge can help to correct this market 

failure.

The need to qualify and certify flight-critical parts makes the 

need especially great for formal knowledge analogous to that 

now supporting qualification and certification of conventionally 

made parts for aerospace applications. As a well-respected 

senior engineer at a leading aerospace firm noted during an 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-10

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

interview with RTI, AM needs “objective evidence of compliance 

to design intent. When you pull a part out of the machine, how 

do you know it meets its design intent?” According to another 

respondent in the same industry, “[you need] empirical 

evidence of success to build customer confidence.” This is the 

ultimate goal for AM: achieving a level of confidence that a part 

be almost certainly free of deformations and functionally sound, 

while adhering to design standards and guidelines. Combining 

specialized scientific and engineering expertise with 

impartiality, NIST is especially well positioned to overcome this 

barrier—an uncertainty-based market failure—by acting as an 

honest broker among parties at different tiers of supply chains.

Non-flight-critical parts, including air grates, panel covers, and 

other interior parts, do not require the same level of standards 

as flight-critical parts (Hiemenz, 2013). Though these parts are 

not necessarily advanced in the nature of their functions, the 

ability to additively manufacture an air grate, for example, 

could still offer the economic advantages mentioned above.

Because the aerospace industry produces relatively low 

volumes of aircraft across markets, AM enables these markets 

to operate without economies of scale. A few advantages of 

additively producing parts for aircraft and other aerospace 

applications are as follows:

 This method achieves cost savings through reduced 

scrap rates, faster turnaround times, availability of 

replacement parts, and (potentially) on-site production.

 AM can produce lighter-than-usual parts compared with 

traditional manufacturing and, therefore, can improve 

fuel efficiency for aircraft; this advantage is primarily 

due to redesigns of (complex) customized parts that 

only AM can produce, thus achieving the same strength 

with less material.

 Design flexibility can lead to new innovations for 

aerospace applications. An additively manufactured part 

can be approximately one-third the weight of a 

subtractively manufactured part if part designs are 

optimized for AM fabrication (Hiemenz, 2013).

 Parts can be 3D-printed in a single piece, making welds 

unnecessary, thereby eliminating weakness and weight.

The potential for new designs and applications in aerospace is 

great, but AM can also serve to develop replacement parts for 

older aircraft in a very short time frame. Helicopters, for 
Section 3 

— Overview of Additive Manufacturing 3-11

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

example, have essentially the same mechanics today as they 

did decades ago. As the demand for new mechanics has 

slowed, the defense industry has continually upgraded 

helicopters that date back to the Vietnam War with new 

electronics and navigation systems.

Manufacturing replacement parts using traditional 

manufacturing processes such as casting is extremely time 

consuming and expensive because of the overhead costs of 

tooling, such as forging dies for a given part. An advantage of 

AM is that it can replace these parts essentially on demand, 

creating a more efficient manufacturing sector (Wysk, 2014).

AM is expected to become integral to aerospace design and 

production because many large defense contractors and 

aerospace companies are already working with additive 

manufacturers (Shipp et al., 2012). Many interviewees from 

firms and universities who work in aerospace stated that the 

field anticipates AM to steadily increase its share of 

manufacturing in this industry within the next 5 to 10 years.

3.3.4 Armaments

The weapons and military systems, or armaments, industry is 

similar to the aerospace industry in that many high-value parts 

are produced in relatively low volumes. Because of the 

significant overhead costs of traditional manufacturing, low-

volume production is not economically viable. AM enables cost-

effective low-value production of complex parts (Bourell, Leu, 

and Rosen, 2009). Of particular importance to the armaments 

industry is the opportunity for additively produced parts to be 

manufactured in remote locations.

Given the levels of defense spending, the market for 

armaments is an attractive one: in 2012, arms sales of the 

Stockholm International Peace Research Institute top 100 

arms-producing companies totaled $395 billion (excluding 

China) (Perlo-Freeman and Wezeman, 2014). Applications for 

weapons and military systems include  lightweight gear and armor for soldiers

,

 ground-based robots,

 customized gun components, and  camera mounts for military vehicles (Bourell, Leu, and 

Rosen, 2009; Gausemeier et al., 2011).
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-12

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

As additive processes and materials improve over the next 5 to 

10 years, the armaments industry is expected to be a major 

user of these technologies to produce a wide range of military 

supporting components (Bourell, Leu, and Rosen, 2009).

3.3.5 Automotive

The automotive industry is one of the major users of AM 

technology. As recent as 2009, the automotive industry 

contributed 17.5% to the total AM market volume, making it 

the largest AM user. In this industry, AM is primarily used for 

concept modeling, functional testing, and rapid prototyping of 

parts (Roland Berger, 2013; Frost and Sullivan, 2007). 

However, its usefulness in the motorsports industry has been 

realized because high performance and weight reduction are 

critical to racing cars (Gausemeier et al., 2011). Additionally, 

some low production volume luxury cars have used AM for 

some of their smaller, more complex parts and are considering 

AM for entire components because of the faster production time 

and reduced costs (RAE, 2013). Time to market, weight 

reduction, customization, and other business-side advantages 

of additively produced parts will benefit the automotive industry 

greatly in the medium- to long-term outlook.

3.3.6 Dental

Printing customized dental products such as crowns, bridges, 

custom orthodontic products, and braces is becoming more 

widespread in the dental industry. The technology 

advancements in AM allow significantly faster turnaround and 

greater production volume of dental products than traditional 

casting processes (from 20 up to 450 dental frames per day 

using additive processes) (Gausemeier et al., 2011). Although 

the dental industry is more mature—in terms of AM—than many 

other industries mentioned in this section, it is trending toward 

(1) less costly manufacturing techniques, (2) the development 

of new materials, and (3) a focus on aesthetics including 

coloring and shaping of teeth (Manning, 2013).

3.3.7 Biomedical

Implants, prosthetics, and tissue engineering are in early 

stages of development by companies and researchers alike to 

design and manufacturer customized parts. Because of the 

potential issues with biocompatibility (or how the artificial and 

biologic parts will interact), AM processes are only slowly 
Section 3 

— Overview of Additive Manufacturing 3-13

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

advancing toward the production of end-use applications. 

Applications in the biomedical industry range from joint 

replacement and prosthetics13 to printed tissues and organs 

(Melchels et al., 2012). The advantages of using AM for these 

applications are the ability to produce customized products, 

faster turnaround times, and reduced overhead costs.

Future applications for this industry have enormous potential 

and diversity. In the short term, more functional prosthetics 

and implants will likely aim to improve patient comfort and 

mobility. Tissue and organ transplant may be the most far-

reaching application, but early research on the repair and 

regeneration of tissues is promising (Melchels et al., 2012). 

Implantable devices for monitoring organ function, diagnostics, 

drug delivery, and communicating with remote devices are 

other promising applications of AM in combination with other 

new technologies.

3.3.8 Consumer Goods

AM in the sporting goods industry is frequently used for RP of 

shoes and other equipment but could be used to produce 

finished goods for athletes. Given the ever-growing safety 

concerns in collision sports, creating additively produced 

protective gear is a potential application in the industry. The 

complex internal structures that AM is capable of could help, for 

example, to absorb impacts. Other applications for AM include 

high-performance equipment such as snowboard bindings, 

bicycle parts, athletic shoes, and others, provided customers 

are willing to pay.

Other consumer goods are also exploring AM for more than RP. 

Textiles, jewelry, and toys are all candidates for additively 

produced goods. For these applications to be cost-competitive, 

however, products must feature high performance, complex 

designs, or customization.

3.4 STAKEHOLDERS

Despite the hype and promise of AM and its seemingly limitless 

possibilities, the technology still has a long way to go before 

printing becomes the go-to means of creating complex 

 

13 Common use includes custom surgical guides, hearing aids, and 

bone implants (e.g., titanium skull implants by Walter Reed 

Hospital).
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-14

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

mechanical parts. The growth and challenges of AM have 

created a need for new supporting technologies, working 

groups, and businesses.

3.4.1 Standards Organizations

Given the complexity of the technology, standards 

organizations are vital to the diffusion and application of the 

technology to small and medium enterprises (SMEs). ASTM and 

the International Organization for Standardization (ISO) are the 

two main organizations that have developed standards for AM, 

including standards for terminology and nomenclature, file 

formats, materials as they are applied to AM processes, 

coordinate systems, and test methods. Dozens of other 

standards are being developed by ASTM and ISO related to 

material consistency among suppliers, among other standards.

Specifically, the relevant committees are ASTM International 

Committee F42 and ISO Technical Committee 261.

Many other standards development organizations have 

appeared since 2015, including ASME Y14.46, SAE AM-AMS, 

and AWS D20. Coordination of AM standards development is 

important and currently in progress. One such effort is the 

America Makes & ANSI Additive Manufacturing Standardization 

Collaborative (AMSC), formally launched in March 2016.

3.4.2 Industry Associations

Stakeholders of AM have partnered to form consortia and other 

associations to tackle some of the core challenges of AM and 

push the technology forward. America Makes, founded in 

August 2012 as the National Additive Manufacturing Innovation 

Institute, consists of a network of more than 100 U.S.-based 

companies, nonprofits, universities, and government agencies. 

It is the largest AM industry association. The goal of America 

Makes is to accelerate the growth and adoption of AM in the 

United States to foster American competitiveness in the 

manufacturing sector. America Makes

 facilitates the open exchange of research data on AM 

systems, processes, and materials;

 conducts collaborative research to solve challenging 

problems at various stages of the product life cycle; and

 connects and engages stakeholders to improve the 

capabilities of their technologies and provide access to 

resources.
Section 3 

— Overview of Additive Manufacturing 3-15

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

The 3D Printing Association is a membership-based 

organization tasked with supporting and promoting 

stakeholders of AM. Education, information exchange, and 

networking are important components of the 3D Printing 

Association. Additionally, investment opportunities are available 

for start-ups and smaller companies.

Several other associations and consortiums exist that have 

activities relevant to AM, including the Additive Manufacturing 

Consortium (AMC), CAMM (Amtech effort), ASPE, ASME, SAE, 

and many others.

The Society of Manufacturing Engineers is a professional society 

of engineers, students, professors, and companies involved in 

all areas of manufacturing. AM is a focus area of the Society of 

Manufacturing Engineers in the Rapid Technologies and Additive Manufacturing group. Its primary goal is education, training, 

and awareness for AM technologies and their applications.

3.4.3 Federal Investment

President Obama’s Advanced Manufacturing Partnership has 

spurred the involvement of federal agencies and programs in 

AM R&D and grant funding opportunities. 

The Department of Defense (DoD) is one of the primary 

agencies focusing efforts toward more timely, cost-effective 

manufacturing methods. The Navy Manufacturing Technology 

Program, under the Office of Naval Research (ONR) and DoD, is 

conducting early research on hybrid AM systems. One of the 

interest areas for the Navy, as well as the other military 

branches, is local manufacturing capabilities. An effective AM 

machine aboard a naval ship could enable the rapid repair or 

building of parts in the event of a damaged or malfunctioning 

part. The ONR also oversees the Institute for Manufacturing and 

Sustainment Technologies (iMAST), part of the Applied 

Research Laboratory at Penn State. iMAST is exploring AM 

technologies, nondestructive testing, reverse engineering, and 

computer-integrated manufacturing. Other DoD-funded R&D 

programs focus on composite materials for lightweighting 

equipment in aircraft, ships, submarines, land vehicles, and 

weapons and missiles.

The National Science Foundation (NSF) is also targeting AM 

technologies. NSF has several programs dedicated to 

manufacturing systems in general, many of which involve 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

3-16

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

materials, information systems, and hardware for AM. Aside 

from the technical aspects of the manufacturing processes, NSF 

supports supply-chain management and digital integration 

among local and remote systems.

The Department of Energy (DOE) is investing in energy-capture 

technologies using AM materials and processes. Of interest to 

DOE is the efficiency and cost-savings opportunities that could 

make photovoltaics, organic light-emitting diodes, and other 

technologies more affordable and prevalent. DOE’s Critical 

Materials Institute is exploring materials development to be 

used as substitutes for difficult-to-extract, costly materials 

(such as rare earth elements) and others that may foster more 

efficient processes.

The National Aeronautics and Space Administration (NASA) is 

funding materials research to be applied to spacecraft and 

equipment. NASA is also funding the Made In Space program, 

which is developing an AM machine built for use in zero gravity. 

The printer developed by Made In Space launched in September 

2014, aboard a rocket directed to the International Space 

Station. The printer will serve as an on-site manufacturing 

system to build parts and tools in zero gravity. Made In Space 

was founded in 2010.

Oak Ridge National Laboratory (ORNL) and Lawrence Livermore 

National Laboratory (LLNL) have invested heavily in AM R&D. 

ORNL has partnered with the University of Cincinnati to develop 

a large-scale AM machine capable of printing polymer parts up 

to 10 times the current producible size and several hundred 

times faster than existing machines. LLNL is striving to 

accelerate the certification of mission and flight-critical parts 

through modeling and simulation rather than destructive 

testing.

Other federal connections to AM include the following: Defense 

Advanced Research Projects Agency (DARPA) Open 

Manufacturing funds several large AM efforts. Air Force 

Research Laboratory manages the award to America Makes. 

The America Makes public–private partnership includes Air 

Force, Army, Navy, Defense Logistics Agency, DARPA, DOE, 

NASA, NSF, NIST, DoEd, FDA, and FAA. The NASA Marshall 

Space Flight Center is a long-time AM user and has much 

experience. The FAA and FDA are determining their regulatory 

guidance for AM parts within their areas.
4

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

4

Quantitative Results 

and Economic 

Impact Analysis

This section summarizes industry stakeholders’ responses to 

quantitative interview questions, relating to the relative 

importance of meeting the identified technology infrastructure 

needs, and presents the potential economic impact of meeting 

those needs.

4.1 IMPORTANCE RATINGS OF 

INFRASTRUCTURE TECHNOLOGY NEEDS

The six technology needs identified through stakeholder 

interviews as the most pressing for industry are summarized 

with examples of potential impacts in Table4-1 (reprised from 

Table1-2 for convenient reference).

RTI collected ‘importance ratings’ for these needs to 

characterize their relative significance and urgency. We asked 

respondents to rate, using a Likert scale, the importance of 

solving each technology need.

Figure4-1 summarizes the importance of the technology needs 

based on interview feedback. The results are aggregated by 

four-digit NAICS code, plus a more general R&D category that 

includes researchers in academia and national laboratories. As 

evident in Figure4-1, standards and best practices were 

considered to be the most important technology need. In fact, 

no interview respondent rated it lower than a 3, or “neutral,”

and the median response was a 5, or “very important.”
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

4-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table 4-1. General Industry-Level Needs for Additive Manufacturing

Industry Needs Examples of Potential Impacts

Standards—standards, best practices, and 

reference data for materials and AM 

processes

• Improve confidence via reproducibility across 

manufacturing methods

• Provide greater assurance in raw materials

Metrology—real-time, in situ metrology, 

enabled by integrated sensors for real-time 

feedback during a build

• Identify in-build defects in time to correct and continue 

the build or scrap before using additional material

Design Allowables—design optimization 

tools and protocols for complex builds

• Improve “design to manufacture” guidance for 

designing and printing complex parts, including mesh, 

lightweight, and sacrificial support structures

• Reduce scrap rates and turnaround times and improve 

reliability and reproducibility of parts

Modeling and Simulation—high-fidelity 

process modeling and simulation for 

different materials and designs

• Improve yields, shorter and fewer R&D cycles

• Predict anomalies at various stages of a build

• Understand material-specific processes leading to new 

applications

Surface Finishing—cost-effective 

approaches to improve surface finishing of 

metal AM parts and standards for measuring 

surface finish and tolerances

• Eliminate or greatly reduce the degree of 

postprocessing required to make production-quality 

parts

Testing Procedures—innovative 

mechanical testing procedures

• Improve efficiency and cost savings from 

nondestructive and other test methods

• Improve confidence in AM processes and materials to 

speed up adoption and validation of high-value printed 

parts in various applications

Figure 4-1. Importance of Technology Needs

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Standards Metrology Design

Allowables

Modeling &

Simulation

Surface

Finishing

Testing

Procedures

Share of responses

3s and below 4s and 5s

4.6

Mean score

3.9 3.8 3.8 3.7 3.8
Section 4 

— Quantitative Results and Economic Impact Analysis 4-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

4.2 IMPACTS OF MEETING INFRASTRUCTURE 

TECHNOLOGY NEEDS

RTI quantified the impacts on the costs and production 

processes resulting from solving the technology needs in 

Table4-1 above. The potential expected cost reduction is $4.1 

billion—a 9% reduction as a factor of sales. The total cost of 

goods sold (COGS) for the AM industry is approximately 51% of 

sales revenue, or $22.3 billion. Therefore, an 18% reduction in 

the cost of goods sold is expected. Figure4-2 presents the 

range of expected impacts by industry. Table 4-2 breaks out

these impacts across capital (K), labor, energy, and materials

(KLEM).

Among KLEM cost components, meeting technology 

infrastructure needs is expected to have the greatest relative 

impact on labor cost, reducing labor costs by 27% on average. 

This reflects stakeholders’ view that AM is still a comparatively 

hands-on process, which some interviewees described as 

“artisan” rather than highly standardized and routinized. 

Iterative trial and error to identify the ideal process parameters 

and postprocessing steps were especially labor intensive. 

Enhanced infrastructure is also expected to reduce the cost of 

raw materials, principally the additive feedstocks, by 20% on 

average. This impact is expected to be realized mainly by 

reducing the need for iterative trial and error, increasing the 

ratio of successful to unsuccessful builds. Especially promising 

is the prospect of enhanced process monitoring and control that 

enables defects to be detected and ultimately eliminated in 

real-time.

Capital cost reductions (anticipated to be 11% on average) and 

energy cost reductions (anticipated to be 7% on average) were 

mainly associated with increased throughput—the increase in 

the number of parts successfully built per unit of operating time 

for a given AM machine. Respondents were somewhat divided 

in their opinions on the overall effect on capital cost. Some 

respondents believed that improvements in throughput would 

drive down the cost of capital overall. Others believed that the 

cost of capital would rise (offset by greater reduction in the cost 

of labor) as enhanced technology infrastructure enabled AM to 

become more routinized and automated.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

4-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Figure 4-2. Cost Reductions for Additive Manufacturing by Industry

Table 4-2. Economic Impact Summary Table

Additive Manufacturing 

Virtual Sales and Cost of 

Goods Sold (COGS) Cost Impacts ($ millions)

Sales

($ millions)

KLEM 

Expenditure K L E M Total

% 

Impact

Total 44,209 22,354 –32 –880 –22 –3,162 –4,096 -18.3%

Aerospace 9,499 5,177 +23 –153 –5 –580 –715 –13.8%

Consumer 

products/ 

Electronics

10,715 4,393 +18 –73 0 –527 –581 –13.2%

Industrial/ 

Business 

Machines

11,036 6,088 +70 –400 –7 –977 –1314 –21.6%

Medical/ 

Dental 6,962 2,503 –103 –109 –0 –181 –393 –15.7%

Motor 

Vehicles 4,541 3,333 –34 –110 –5 –780 –930 –27.9%

Other 1,456 860 –7 –35 –4 –115 –162 –18.9%

Notes: We say “virtual” because many AM-focused activities today are for companies’ internal use, such as 

prototyping and tooling applications that support the non-additive production of final goods. Sales and COGS 

figures were estimated based on industries’ expenditure on AM equipment. COGS includes: K, Capital; L, Labor; 

E, Energy; M, Materials.

 (1,800.00)

 (1,600.00)

 (1,400.00)

 (1,200.00)

 (1,000.00)

 (800.00)

 (600.00)

 (400.00)

 (200.00)

 -

Aerospace Consumer

Products/

Electronics

Industrial/

Business

Machines

Medical/

Dental

Motor

Vehicles

Other

Lower Bound Impacts Upper Bound Impacts Average Impacts
Section 4 — Quantitative Results and Economic Impact Analysis

4-5

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Underlying these KLEM impacts are impact estimates for the 

following production variables:

 time and cost to test and validate materials,

 time and cost to reach first successful build (product 

development), and

 scrap rate (wasted feedstock material and material used 

in unsuccessful builds).

In some cases, we were able to quantify these impacts, and 

these results are summarized in Table 4-3. To emphasize, this 

is a further breakdown of impacts reflected in Table 4-2, not 

additional impacts.

The impacts on these production processes could result in 

significant improvements to the current AM environment.

The materials validation component, which encompasses the 

time and cost to test and validate materials, is expected to drop 

by 44% on average. There is a wide range in this impact, 

however, as respondents in the aerospace industry suggest that 

it would only drop by approximately 10%, whereas a national 

laboratory (labeled as “government/military” in Table 4-3) 

suggested a 75% improvement. One respondent in the 

aerospace industry believes that materials validation would go 

up by as much as 50% in the short term as these new methods 

are integrated into current processes, which often requires a 

learning curve and transition period. Excluding this 

respondent’s input, the average cost reduction for materials 

validation is reduced further to −19%.

Table 4-3. Process Improvements

Industry

Materials 

Validation

Product 

Development Scrap Rate

Aerospace −10% −34% −18%

Consumer products/electronics −25% −15% −25%

Government/military −75% −50% 0%

Industrial/business machines −50% −18% −13%

Medical −34% −67% −10%

Motor vehicles −58% −64% −50%

Other −55% −43% −43%

Total −44% −41% −23%
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

4-6

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Product development, the time and cost required for a product 

to reach its first successful build as intended, is also expected 

to drop significantly. Similarly to the materials validation 

component, there is a wide range in responses, yet all 

respondents believed this value would be reduced.

All respondents but one indicated that the scrap rate, the rate 

at which defects are present during or after a part is printed, is 

expected to decrease. The average reduction was 23% 

assuming access to and availability of new technology tools and 

information.

4.3 IMPACTS APPORTIONED OVER 

TECHNOLOGY NEEDS

Figure 4-3 shows the distribution of total KLEM impacts 

apportioned across the six technology needs. The distribution of 

impacts reflects the importance scores provided by end users 

(shown in Figure 4-1). Enhanced standards, best practices, and 

reference data are associated with annual cost reductions of 

nearly $800 million. The cost impacts of meeting each of the 

other five industry needs is between $600 and $700 million.

A caveat to these results is that there are often strong 

complementarities or “interaction effects” among technology 

infrastructure elements that we were not able to quantify. For 

instance, high-fidelity predictive models would be a valuable 

tool for optimizing designs for 3D-printed parts and for 

qualifying parts for demanding applications with less need for 

destructive testing; building useful models requires large, highquality scientific and engineering databases linking materials, 

processes, process conditions, and surface finish with the 

performance characteristics of the finished part.

With strong complementarities among technology infrastructure 

elements that meet these needs, the cost of underproviding the 

elements most directly related to one need is not limited to the 

amount apportioned to that need in Figure 4-3 but spills over 

into other needs. For example, investing heavily in high-fidelity 

predictive models without adequate parallel investment in highquality data with which to calibrate those models would not 

realize the $661.5 million benefit and forego the $797.6 million 

benefit; rather, this unbalanced investment would likely fail to 

fully realize either potential impact.
Section 4 — Quantitative Results and Economic Impact Analysis

4-7

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Figure 4-3. Total Annual Impact, Apportioned by Technology Need (Millions of 2013 US$)

797.6 

680.4 667.8 661.5 635.0 657.7 

0

100

200

300

400

500

600

700

800

900

Standards Metrology Design

Allowables

Modeling &

Simulation

Surface

finishing

Testing

procedures
5

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

5 Qualitative Results: 

Stakeholder Views

This section summarizes insights into the identified 

infrastructure needs and qualitatively describes the potential 

impacts of meeting these needs.

5.1 MATERIALS STANDARDS, PROCESS 

STANDARDS AND REFERENCE DATABASES

Our interview sample was unanimous in their assessment that 

the most important infratechnology needs at this time are 

materials standards, process standards, and reference 

databases. Standards serve the industry by ensuring quality 

and consistency for the input materials, during a build, and 

following any postbuild processing.

One aspect of postbuild processing for which standards are 

important is treatment (for example, by heating or shot 

peening) to remove stresses and improve mechanical 

properties. Ideally, standards for these processes could be 

developed in concert with standards for characterizing 

properties so that resources are not wasted characterizing 

properties of additively built parts that are limited by 

suboptimal postbuild processing.

Some respondents expressed impatience over extant standards 

for AM falling short of meeting their needs. One end user

expressed the opinion that the standards are often vague and

thus tend to leave AM systems manufacturers with de facto 

decision-making authority over best practices.

To some extent, frustration on the part of some stakeholders 

that standards do not yet meet their specific needs is to be 

expected of early efforts, because the first standards are 

necessarily high-level documents.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

5-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

The standards are developed by industry consensus and 

endeavor to balance the interests of all stakeholders fairly, and 

ideally all participants have equal opportunity to drive the 

standards to meet their needs. The perception of some end 

users that certain gaps in standards may tend to favor the 

interests of systems manufacturers is worth noting, whether or 

not it is an issue that can be addressed in the short run as 

standards continue to take shape.

As the standards become more mature, more detailed 

specifications can be created for specific niche applications. AM 

technology is changing very quickly, so it is difficult to 

standardize the specifics of something until there is industry 

confidence, hence the current emphasis on higher-level 

standards.

A lack of fully mature standards forces firms to not only create 

their own standards, but also to expend additional resources to 

prove the quality and consistency of the products they build. 

Although this is less of a problem for large, multibillion dollar 

companies, small- to medium-sized firms may struggle to 

invest in this emerging technology. Additionally, the lack of 

standards has resulted in companies creating their own 

standards for a number of reasons:

1) to protect the intellectual property of their product, 

process, material, or other component;

2) to maintain a competitive advantage over other firms in 

the industry; and

3) industry consortia and collaborative research efforts can 

be unreliable and expensive.

Not only are materials standards needed for inputs (feedstock 

materials), but so are reference data for materials properties 

processed in different batches, under different conditions, and 

using different methods. Perhaps more important for AM metals 

are the postbuild heat treatments that are invariably used to 

remove the residual stresses created by the build process and 

those used to return the microstructure to one similar to those 

found for the same alloy in wrought or cast form. Process 

standards are also very valuable to understanding the best 

practices for producing parts. Materials and process standards 

are needed for all material classes, across product categories 

and AM manufacturing methods.
Section 5 

— Qualitative Results: Stakeholder Views 5-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

A respondent from a large, multinational company with a well-

known aerospace division noted that the company has spent

”multiple millions of dollars” (the respondent declined to be 

more specific) on developing their own central library of 

materials property data.

A key inhibitor to AM is convincing customers and certifying 

bodies that an additively produced part has the necessary 

quality to meet the application. One large manufacturing 

company shared that it spends $500,000 over a 6-month time 

frame to obtain mechanical properties just for a single part, 

made from a single material, using a specific additive 

manufacturing process with specific parameters. Over the long 

term, ensuring quality will require having access to an 

extensive, statistically significant database of materials of 

interest that one can build parts from and consistently build 

them using standard processes reliably at high quality. For any 

given firm, a reference database could accelerate development 

time by months, eliminating perhaps 20 to 30% of development 

time. It could also reduce the cost of development by enabling 

more reliable builds and thus reducing scrap rates.

Material-to-material and part-to-part reliability and 

reproducibility can depend on, for metal powders, for example, 

the powder properties and the process parameters in 

fabricating the powder. Variations exist among materials 

vendors, including differences in size, shape, and purity of a 

powder alloy. Powder vendors exhibit significant inconsistencies

and single producers report even batch-to-batch variability. 

Users and vendors alike need standard reference materials and 

a defined set of specifications to be provided. One interviewee 

would like to push standardization down to the powder 

suppliers to reduce the qualification costs they face. A small 

manufacturer said they were forced to use a more expensive 

branded powder because the supplier qualifies and publishes its 

data.

Each of the standard AM process categories has many process 

parameters; when combined with materials differences, the 

magnitude of variables has undoubtedly a significant effect on 

the outcome—the chemical, mechanical, and physical 

properties of the final part. In one specific example, consider a 

metal melting process. The metal purity, grain size, and the 

rate of melting and cooling of the material all play a role in 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

5-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

determining the part performance, such as the 

thermomechanical properties.

Thermal and mechanical properties are particularly critical for 

the transportation industry, and depending on processes, 

statistically significant data need to be available at a deep level 

of detail. One aerospace manufacturer invested more than $1.5 

million to study properties for one single part produced using 

only one powder and one process method. Small manufacturers 

have noted that they do not have the adequate resources to 

exhaustively test and validate part properties after fabrication 

and, thus, are prohibited from entering the transportation 

markets. Similarly, a second small supplier reported that the 

development cycle for new materials is too long. They have 

made new materials that have not been adopted because of the 

long qualification time and have resisted trying anything new to 

avoid wasting time and resources. A large engine manufacturer 

is targeting 2020 for a product launch because of the 

qualification challenges.

Property data for a set of common process–material pairs could 

accelerate the introduction of additively built parts into service 

in existing industries, as well as new industries, and open up 

additional opportunities for small suppliers and manufacturers.

But because of the process-material connection, and the many 

different process-material pairs relevant across applications 

(the lack of a single or even a few process-material pairs 

relevant to wide cross sections of industry), this task is 

probably beyond the resources, at least for the time being, 

even of national laboratories. What would be practical, and very 

useful, would be to standardize the testing protocols, 

standardize the database schema for what data to collect, make 

a database available to the public, and allow others to upload 

property data (obtained using standard procedures) to the 

database.

Further challenges exist with manufacturing efficiencies. One 

large manufacturer reported that 30 pounds of powder were 

needed to produce a 10-pound part, and reuse of powder was 

not an option for their application. Their primary target for 

reducing the overall metal AM manufacturing cost is improving 

powder efficiency. Some suppliers are beginning to perform 

recertification of powder for re-use, but the practice is not yet 

standardized.
Section 5 

— Qualitative Results: Stakeholder Views 5-5

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Lastly, hybrid processes are beginning to emerge to tackle 

parts with increased complexity or tighter tolerances; the 

forerunner is additive-subtractive manufacturing hybrids to 

address challenges associated with surface finishing following 

AM (reviewed further below). One interviewee specifically 

provides machine protocols in terms of defining hierarchies of 

operations. Establishing a classification system for hybrid 

processes would be particularly helpful to guide designers and 

operators in a common language.

5.2 DESIGN OPTIMIZATION FOR AM

Accelerating AM will require approaches for optimizing designs. 

One of the most significant benefits of AM is the ability to 

create 3D, complex, interlocking pieces in one process. In this 

manner, additively produced parts may have advantages in 

both economics and performance over their subtractively built 

counterparts, but guidance and data to support these novel 

designs (e.g., angles, sacrificial structures, meshes) are 

needed.

The challenge lies primarily in the design. With conventional 

manufacturing (such as castings or injection molded parts), the 

designer is forced to configure design rules for draft angles. 

Although design rules have been established for some 

manufacturing processes, there is no systematic listing of 

design rules for AM. An agreed-upon set of design rules must 

be established and communicated to the design community to 

ensure efficient design of parts for AM.AM design rule 

standards are now in development in ASTM F42/ISO TC261.

For many processes in AM, it is necessary to build support 

structures that are temporary parts of a build, subsequently 

removed and disposed of. More effort needs to be placed on 

establishing the minimum support structures as a function of 

process, material, and design. Interviewees suggested that a 

gap exists in materials development specifically for support 

structures, such that they could be made dissolvable (for 

polymer support structures) or easier to remove. Alternatively, 

are there alterations to design rules that enable manufacturers 

to avoid support structures altogether? The current function of 

these structures is to hold horizontal components in place 

during the build, but their presence is inherently restrictive of 

geometry and detrimental to the surfa

ce finish.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

5-6

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

One firm noted that when building an AM part for the first time 

from a CAD file, they are able to do it correctly only two out of 

three times. On the second attempt, there is a 90% success 

rate. This comment suggests that improvements to AM design 

rules could reduce scrap rates and result in more productive 

machine time.

5.3 MODELING AND SIMULATION

Respondents identified a wide range of opportunities for 

improving the modeling and simulating of AM parts, but there is 

particularly a need for life-cycle assessment studies. Tools are 

needed to model and simulate materials properties and 

establish robust process-structure-property relationships. Most 

AM modeling efforts are focused on creating predictive 

capabilities to understand resulting part properties, given 

material and process inputs. Time-temperature history 

determines material microstructure, which determines 

mechanical properties. Measurement and control of that timetemperature history is therefore important. For aerospace and 

energy applications, in particular, modeling and simulation tools 

are critical. To date, this field has been held back by the lack of 

quality inputs. The variability in raw materials and processes, 

the lack of consistent metrology data, and simply the low 

number of similar parts produced by AM all contribute to the 

gap. LLNL has developed 3D models for powder bed fusion AM 

processes. Because of the physical changes that occur when the 

powder is melted, sensitive areas of a part such as at 

overhangs and edges may be distorted. Models can therefore 

be used to determine the successful means of building a given 

part (e.g., temperature, materials, and part design) in advance 

of the actual build.

As in most emerging processes, history and time in use are 

lacking. The development of accelerated test methods and 

associated modeling tools could establish the baselines that 

already exist for mature technologies. The value in AM is the 

ability to make small volumes of specialized parts—a significant 

effort making large volumes of relatively simple parts is needed 

to develop the modeling and simulation tools for the future.
Section 5 

— Qualitative Results: Stakeholder Views 5-7

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

5.4 REAL-TIME METROLOGY

Additively manufactured parts have an advantage in that the 

inherent layer-by-layer production provides an opportunity to 

take a snapshot at each fractional stage of a product build. 

However, the metrology tools and associated real-time 

feedback processes remain in infancy. Most interviewees saw a 

need and value for real-time metrology, but few offered 

solutions or even topics for further research. Academic, 

government, and consortia groups are heavily pursuing this 

field, investigating optical (geometric), infrared, and thermal 

methods.

As reported by the companies surveyed, qualification is 

primarily done postproduction, with process and materials 

alterations done primarily by a trial-and-error method. The 

implementation of real-time metrology has clear benefits in 

efficiency, throughput, and related cost, replacing subjective 

reasoning with quantitative decision making. Given the 

variability in materials and processes as described above, real-

time metrology and feedback loops offer a means of control 

that could compensate for the inputs.

Much like metrology desires in other manufacturing processes, 

manufacturers seek metrology solutions that are rapid, 

quantitative, nondestructive, inexpensive, and high resolution

and that have wide dynamic range. The range of features that 

interviewees could monitor varies from geometric distortion to 

porosity to mechanical and thermal stress.

Interviewees report that standards for metrology are slowly 

being defined by groups including ASTM, ISO, ASME, SAE, 

AWS, and others. Consortium and other networks are 

conducting round robins of metrology and property testing for 

AM and will publicize the results. However, companies remain 

skeptical of the reliability and consistency of the aggregate data

without standardized methods for testing and data collection.

5.5 SURFACE FINISHING OF METAL ADDITIVE 

PARTS AND RELATED TESTING

Surface finishing is an ongoing issue for prototype and service 

parts where improved capabilities are needed. Additively built 

parts naturally have a rougher finish, similar to cast surfaces, 

requiring some postbuild machining. This surface roughness is 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

5-8

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

a function of both input materials (e.g., metal powder size

distribution) and process parameters (beam width, beam 

power, layer thickness) and is often correlated with the 

fabrication time.

Industry would like to see a more cost-effective approach to 

improving surface finishing developed. AM technology has 

matured and the current technology is being used more 

effectively than ever before. Innovations continue and 

performance continues to improve through increased 

understanding and better measurement methods. The 

combination of additive and subtractive processes, also known 

as “hybrid” manufacturing, is the focus of an AMTechsponsored industry consortium and is one of many AM-related 

technologies being advanced by America Makes. This process 

works by overbuilding a part additively and using subtractive 

manufacturing processes to 1) reduce its size to the desired 

specifications and 2) eliminate surface roughness. If finishing 

was automated or processed through hybrid manufacturing 

techniques, it would reduce labor time.

5.6 MECHANICAL TESTING PROCEDURES

Innovative mechanical testing procedures are needed, 

especially to enable nondestructive testing. Closely linked with 

the needs for high-quality scientific and engineering data and 

high-fidelity modeling and simulation based on established 

process-structure-property relationships, novel mechanical 

testing procedures are needed to qualify 3D-printed parts for 

critical applications in aerospace and medicine.

As reported by an interviewee, one challenge with AM 

technology relates to “objective evidence of compliance to 

design intent.” When a part is extracted from a machine, it 

needs to be evaluated to determine whether it meets the 

design intent. The surface geometry can be analyzed, but there 

is no nondestructive methodology for determining whether the 

metal chemistry meets design specifications. A firm can 

produce a part, but how does one inspect and validate it? There 

needs to be a methodology to tell an operator that part A 

matches the history of yield specimens. Presently, firms are 

using ultrasound, X-ray, and computerized tomography scans 

to determine some qualities of the final part, but more costeffective approaches are needed.
6

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

6 Conclusion

Through in-depth interviews with industry stakeholders, this 

study identified pressing needs for AM technology 

infrastructure—the currently unmet needs for measurement 

science, metrology and test methods, traceable reference data, 

and other formal knowledge—most closely aligned with NIST’s 

unique mission and capabilities. The potential economic impact of meeting these needs is 

estimated to be $4.1 billion per year. This impact reflects the 

costs that U.S. manufacturers could avoid if these needs were 

met. In practice, lowering AM-application-specific costs of 

capital, labor, energy, and materials for U.S. manufacturers 

would lead to lower prices for consumers of 3D-printed goods, 

which in turn would lead to the expansion of these market 

segments. Of even greater importance, albeit more difficult to 

quantify, meeting these needs would lead to improvements in 

the performance characteristics of AM parts, which would 

increase demand for AM parts and expand these market 

segments. The emergence of altogether new products and 

markets would almost certainly also be accelerated.

$4.1 billion is 18% of the annual $22.3 billion cost of goods 

sold for AM-focused manufacturing activities. We estimate that 

the (virtual) sales revenue of AM to be $44 billion. We say 

virtual because many AM-focused activities today are for 

companies’ internal use—prototyping and tooling applications 

that support the non-additive production of final goods. The

$4.1 billion impact is likely a conservative estimate, because it 

does not take into account the second-order effect of the 

growth AM would experience as a direct result of cost 

reductions being shared with consumers in the form of lower 

prices, moving AM outward along its demand curve. Our 

quantitative impact estimate also does not take into account 

that the demand for AM parts will increase as a direct result of 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

6-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

improvements in the performance characteristics of 3D-printed 

parts and end users enhanced ability to verify and certify those 

performance characteristics.
R

-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

References

Antonelli, C., and A. N. Link. 2014. Routledge Handbook of the 

Economics of Knowledge. New York, NY: Routledge.

Bourell, D., M. Leu, and D. Rosen. 2009. Roadmap for Additive 

Manufacturing—Identifying the Future of Freeform 

Processing. Austin, TX: The University of Texas.

Caffrey, T., and T. Wohlers. 2015. Wohlers Report 2015: 3D 

Printing and Additive Manufacturing State of the 

Industry Annual Worldwide Progress Report. Fort 

Collins: Wohlers Associates, Inc.

CAMM. 2015, December. Strategic Roadmap for the Next 

Generation of Additive Manufacturing Materials.

Frazier, W. E. 2014. “Metal Additive Manufacturing: A Review.” 

Journal of Materials Engineering and Performance

23(6):1917-1928.

Frost & Sullivan. 2007. World Rapid Prototyping Equipment 

Markets. Frost & Sullivan: San Antonio, TX.

Gausemeier, J., N. Echterhoff, M. Kokoschka, and M. Wall. 

2011. Thinking Ahead the Future of Additive 

Manufacturing—Analysis of Promising Industries. 

Paderborn, Germany: Heinz Nixdorf Institute, University of 

Paderborn.

GE Aviation. October 27, 2015. GE Aviation to build unique 

materials factories. [Press release]. 

http://www.geaviation.com/press/other/other_2015102

7.html 

Harrysson, O. L., O. Cansizoglu, D. J. Marcellin-Little, D. R. 

Cormier, and H. A. West II. 2008. “Direct Metal 

Fabrication of Titanium Implants with Tailored Materials 

and Mechanical Properties using Electron Beam Melting 

Technology.” Materials Science & EngineeringC

28(3):366-373.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

R-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Heavy Metal. May 3, 2014. The Economist (Berlin). 

http://www.economist.com/node/21601528/print.

Hiemenz, J. 2013. Additive Manufacturing Trends in Aerospace: 

Leading the Way. Eden Prairie, MN: Stratasys. 

http://web.stratasys.com/rs/objet/images/SSYS-WPAeroTrends-03-13-FINAL.pdf.

Jaffe, A. B., R. G. Newell, and R. N. Stavins. 2005. “A Tale of 

Two Market Failures: Technology and Environmental 

Policy.” Ecological Economics 54(2):164-174.

Kennedy, P. 2013, Nov 22. “Who Made That 3-D Printer?” The 

New York Times. Permalink: http://nyti.ms/1C188US.

Link, A. N., and J. T. Scott. 2010. Public Goods, Public Gains: 

Calculating the Social Benefits of Public R&D. New York, 

NY: Oxford University Press.

Manning, L. May 3, 2013. Dental Restoration Reaping Benefits 

of Additive Manufacturing. 

http://medicaldesign.com/design-engineering/dentalrestoration-reaping-benefits-additive-manufacturing.

Melchels, F.P., M.A. Domingos, T.J. Klein, J. Malda, P.J. Bartolo, 

and D.W. Hutmacher. 2012. “Additive Manufacturing of 

Tissues and Organs.” Progress in Polymer Science

37(8):1079–1104.

National Institute of Standards and Technology. May 2013. 

Measurement Science Roadmap for Metal-Based Additive 

Manufacturing. http://www.nist.gov/el/isd/upload/ 

NISTAdd_Mfg_Report_FINAL-2.pdf. 

Perlo-Freeman, S., and P. Wezeman. 2014. The SIPRI Top 100 

Arms-Producing and Military Services Companies, 2012.

Retrieved from 

http://www.sipri.org/research/armaments/production/re

cent-trends-in-arms-industry.

Petrovic, V., J. Vicente Haro Gonzalez, O. Jorda Ferrando, J. 

Delgado Gordillo, J. Ramon Blasco Puchades, and L. 

Portoles Grinan. 2011. “Additive Layered Manufacturing: 

Sectors of Industrial Application Shown through Case 

Studies.” International Journal of Production Research

49(4):1061-1079.

Roland Berger Strategy Consultants. 2013. Additive 

Manufacturing: A Game Changer for the Manufacturing 

Industry? Munich: Roland Berger Strategy Consultants.
References R-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Royal Academy of Engineers (RAE). May 23, 2013. Additive 

Manufacturing: Opportunities and Constraints. London: 

Royal Academy of Engineers. 

https://www.raeng.org.uk/news/publications/list/

reports/Additive_Manufacturing.pdf.

Shipp, S., N. Gupta, B. Lal, and J. Scott. 2012. Emerging Global 

Trends in Advanced Manufacturing. Alexandria, VA: 

Institute for Defense Analyses.

Tassey, G. 2008. “Modeling and Measuring the Economic Roles 

of Technology Infrastructure.” Economics of Innovation 

and New Technology 17(7-8):615-629.

Thomas, D.S. 2013. Economics of the U.S. Additive 

Manufacturing Industry. National Institute of Standards 

and Technology Special Publication 1163. 

http://dx.doi.org/10.6028/NIST.SP.1163.

Thomas, D.S., and S.W. Gilbert. 2014. Costs and Cost 

Effectiveness of Additive Manufacturing. National 

Institute of Standards and Technology Special

Publication 1176. 

http://dx.doi.org/10.6028/NIST.SP.1176.

West, K. February 13, 2011. “Melted Metal Cuts Plane’s Fuel 

Bill.” The Sunday Times. www.thesundaytimes.co.uk 

/sto/business/energy_and_environment/article547163.e

ce.

Wysk, R. April 18, 2014. North Carolina State University. 

Internal meeting.
This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Appendix A:

Interview Guide for 

Additive Systems 

Developers
A-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

The National Institute of Standards and Technology (NIST) in 

the U.S. Department of Commerce has contracted with RTI 

International to conduct an economic analysis of standards, 

measurement, and general purpose technology needs that 

inhibit efficient development and adoption of advanced 

manufacturing in the United States.

The objectives of this critical strategic planning study are to  identify current and emerging needs related to 

standards and measurement,

 estimate the economic impact of meeting these needs, 

and

 review public policy and investment options.

The study has a particular focus on 4 aspects of advanced 

manufacturing: (1) robotics and automation, (2) smart 

manufacturing processes, (3) 3D printing (additive 

manufacturing), and (4) roll-to-roll manufacturing. The focus of 

our conversation is additive manufacturing technology.

Your perspective will help guide NIST’s planning and investment 

process. Participation in this analysis is confidential; only 

aggregated information will be included in any deliverables or 

communications. Your name and your company’s name will not 

be disclosed. We do not wish to discuss specific products, 

strategies, or technologies; but rather your thoughts about how 

investments in standards and measurement technologies would 

affect your company and companies like yours.

Our research products will be an economic analysis, final 

report, and presentation materials. All deliverables will be 

publicly available in late 2015 and these will be shared with you 

as soon as they are released.

If you have questions, please contact:  Troy Scott, Case Study Lead, RTI, 503

-428-5680, 

tjscott@rti.org

 Alan O’Connor, Principal Investigator, RTI, 

919-541-8841 or oconnor@rti.org

 Gary Anderson, NIST Project Officer, NIST, 

301-975-5238 or gary.anderson@nist.gov

This collection of information contains Paperwork Reduction Act 

(PRA) requirements approved by the Office of Management and 

Budget (OMB). Notwithstanding any other provisions of the law, 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

A-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

no person is required to respond to, nor shall any person be 

subject to a penalty for failure to comply with, a collection of 

information subject to the requirements of the PRA unless that 

collection of information displays a currently valid OMB control 

number. Public reporting burden for this collection is estimated 

to be 35 minutes per response, including the time for reviewing 

instructions, searching existing data sources, gathering and 

maintaining the data needed and completing and reviewing the 

collection of information. Send comments regarding this burden 

estimate or any aspect of this collection of information, 

including suggestions for reducing this burden, to the National 

Institute of Standards and Technology, Attn., Gary Anderson, 

gary.anderson@nist.gov, (301) 975-5238. The OMB Control 

Number is 0693-0033, with an expiration date of 03/31/2016.

Respondent Background and Information

1. Please give a brief description of your experience with 

additive manufacturing. How did you come to be in your 

current position?

About Your Company

2. What types of additive manufacturing systems does your 

company develop? For which materials, methods?

3. Can you please describe your company’s supply chain for 

feedstock materials?

4. Approximately what percentage of your company’s sales 

revenue is associated with customers using additive 

manufacturing for the purposes of...

Application of AM Technology Customer Share

a Final goods and parts printing %

b Prototyping or design %

c Tooling %

d Repair %

e Research and Development and repair %

Industry Needs

Several industry-level needs have been identified, and 

discussions with experts have suggested measurement and test 

methods, material and process standards, reference databases, 

and general purpose technologies that could meet these needs.
Appendix A — Interview Guide for Additive Systems Developers

A-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table A-1 below provides a list of these needs and examples of 

the solutions to them. There are also two additional columns, 

and we ask that you please consider them from the perspective 

of your company’s products and business opportunities.

Table A-1. General Industry-Level Needs for Additive Manufacturing

Industry Needs Potential Impacts (examples)

Rating of 

Importance 

(1 to 5)

5=Most

1=Least

1. Standards, best practices, 

and reference data for 

materials and AM processes

• Improve confidence via reproducibility 

across manufacturing methods

• Greater assurance in raw materials

2. Real-time metrology—

integrated sensors for realtime feedback during a build

• Identify in-build defects in time to correct 

and continue the build or scrap before using 

additional material

3. Design optimization tools 

and protocols for complex 

builds

• “Design to manufacture” guidance for 

designing and printing complex parts, 

including mesh, lightweight, and sacrificial 

support structures

• Reduce scrap rates and turnaround times, 

and improve reliability and reproducibility of 

parts

4. Process modeling and 

simulation for different 

materials and designs.

• Improve yields, shorter and fewer R&D 

cycles

• Predict anomalies at various stages of a 

build

• Understand material-specific processes 

leading to new applications

5. Cost-effective approaches to 

improve surface finishing of 

metal AM parts, and 

standards for measuring 

surface finish and tolerances

• Eliminate or greatly reduce the degree of 

postprocessing required to make 

production-quality parts

6. Innovative mechanical 

testing procedures

• Improve efficiency and cost savings from 

nondestructive and other test methods

• Confidence in AM processes and materials to 

speed up adoption and validation of highvalue printed parts in various applications

5. Are there items not included in the table that you would 

include? If so, what are they?

6. Is your company currently investing in R&D towards any of 

the needs in Table 2, or any others that you have 

mentioned?
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

A-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

For questions 7–10, let’s assume NIST were to solve the 

relevant needs in Table A-1.

7. Can you describe any impacts on your company’s 

development and commercialization of additive 

manufacturing systems that you would expect to observe? 

Please consider:

a) R&D opportunities (i.e., niche areas)

b) Marketing opportunities (new markets, greater demand, 

etc.)

c) Improved performance and/or capabilities of your 

current AM machine models

d) Development of new AM machines with novel capabilities

e) Others

8. Could you describe any outcomes to the AM industry (or 

your customers, more specifically) that you would expect to 

observe? Please consider the following:

a) Market share of AM

b) Market penetration of AM

c) Lead times

d) Production costs (materials, energy, labor, capital)

e) Quality or performance of existing product lines

f) New product lines and/or applications

9. Can you describe changes to your company’s sales revenue 

or growth that you would expect to observe? By what 

percentage would your sales revenue change? A range is 

fine.

10. Would you expect any changes in your company’s 

investment patterns or risk tolerance? If so, what types of 

changes?

11. Would you say that your answers are representative of your 

industry (of companies developing/commercializing additive 

manufacturing technology), or of only a subset? Please 

explain briefly how, if at all, the anticipated impacts for your 

company may be different from the industry as a whole, or 

how different industry segments may be differently 

impacted.

12.Are there any additional comments you would like to share?
This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Appendix B:

Interview Guide for 

Additive End Users
B-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

The National Institute of Standards and Technology (NIST) in 

the U.S. Department of Commerce has contracted with RTI 

International to conduct an economic analysis of standards, 

measurement, and general purpose technology needs that 

inhibit efficient development and adoption of advanced 

manufacturing in the United States.

The objectives of this critical strategic planning study are to  identify current and emerging needs related to 

standards and measurement,

 estimate the economic impact of meeting these needs, 

and

 review public policy and investment options.

The study has a particular focus on 4 aspects of advanced 

manufacturing: (1) robotics and automation, (2) smart 

manufacturing processes, (3) 3D Printing (additive 

manufacturing), and (4) roll-to-roll manufacturing. The focus of 

our conversation is additive manufacturing technology.

Your perspective will help guide NIST’s planning and investment 

process. Participation in this analysis is confidential; only 

aggregated information will be included in any deliverables or 

communications. Your name and your company’s name will not 

be disclosed. We do not wish to discuss specific products, 

strategies, or technologies; but rather your thoughts about how 

investments in standards and measurement technologies would 

affect your company and companies like yours.

Our research products will be an economic analysis, final 

report, and presentation materials. All deliverables will be 

publicly available in late 2015 and these will be shared with you 

as soon as they are released.

If you have questions, please contact:  Travis Beaulieu, Case Study Lead, 919

-541-5820, 

tjbeaulieu@rti.org

 Alan O’Connor, Principal Investigator, RTI, 

919-541-8841 or oconnor@rti.org

 Gary Anderson, NIST Project Officer, NIST, 

301-975-5238 or gary.anderson@nist.gov

This collection of information contains Paperwork Reduction Act 

(PRA) requirements approved by the Office of Management and 

Budget (OMB). Notwithstanding any other provisions of the law, 
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

B-2

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

no person is required to respond to, nor shall any person be 

subject to a penalty for failure to comply with, a collection of 

information subject to the requirements of the PRA unless that 

collection of information displays a currently valid OMB control 

number. Public reporting burden for this collection is estimated 

to be 35 minutes per response, including the time for reviewing 

instructions, searching existing data sources, gathering and 

maintaining the data needed and completing and reviewing the 

collection of information. Send comments regarding this burden 

estimate or any aspect of this collection of information, 

including suggestions for reducing this burden, to the National 

Institute of Standards and Technology, Attn., Gary Anderson, 

gary.anderson@nist.gov, (301) 975-5238. The OMB Control 

Number is 0693-0033, with an expiration date of 03/31/2016.

Respondent Background and Information

1. Please give a brief description of your experience with 

additive manufacturing technology. How did you come to be 

in your current position?

About Your Company

2. How does your company use additive manufacturing 

technology?

a. For what applications (e.g., for prototypes, tooling, or 

final products)? What factors make additive attractive 

for those applications? What factors limit additive to only 

those applications?

b. What types of additive manufacturing technology do you 

use? In terms of materials, methods?

3. Approximately what percentage of your company’s sales 

revenue is currently associated with AM manufacturing? A 

range is fine.

4. As far as you are aware, is your division or company 

engaged with any industry consortia, standards 

organizations, or governing bodies specifically for additive 

manufacturing? If so, in which bodies do you participate and 

what are the underlying drivers for participation?

Industry Needs

Several industry-level needs have been identified, and 

discussions with experts have suggested measurement and test 

methods, material and process standards, reference databases, 

and general purpose technologies that could meet these needs.
Appendix B — Interview Guide for Additive End Users

B-3

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table B-1 below provides a list of these needs and examples of 

the solutions to them. There is also an additional (right-most) 

column that asks you to rate the importance of the technology 

need.

Table B-1. General Industry-Level Needs for Additive Manufacturing

Industry Needs Potential Impacts (examples)

Rating of 

Importance 

(1 to 5)

5=Most

1=Least

1. Standards, best practices, 

and reference data for 

materials and AM processes

• Improve confidence via reproducibility 

across manufacturing methods

• Greater assurance in raw materials

2. Real-time metrology—

integrated sensors for realtime feedback during a build

• Identify in-build defects in time to correct 

and continue the build or scrap before using 

additional material

3. Design optimization tools 

and protocols for complex 

builds

• “Design to manufacture” guidance for 

designing and printing complex parts, 

including mesh, lightweight, and sacrificial 

support structures

• Reduce scrap rates and turnaround times, 

and improve reliability and reproducibility of 

parts

4. Process modeling and 

simulation for different 

materials and designs.

• Improve yields, shorter and fewer R&D 

cycles

• Predict anomalies at various stages of a 

build

• Understand material-specific processes 

leading to new applications

5. Cost-effective approaches to 

improve surface finishing of 

metal AM parts, and 

standards for measuring 

surface finish and tolerances

• Eliminate or greatly reduce the degree of 

postprocessing required to make 

production-quality parts

6. Innovative mechanical 

testing procedures

• Improve efficiency and cost savings from 

nondestructive and other test methods

• Confidence in AM processes and materials to 

speed up adoption and validation of highvalue printed parts in various applications

5. Are there items not included in the table that you would 

include? If so, what are they?

6. In Table B-2 below, can you quantify the impacts on your 

company if these needs were met, in terms of the following 

production variables? A range is fine.
Economic Analysis of Technology Infrastructure 

Needs for Advanced Manufacturing: Additive Manufacturing

B-4

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table B-2. Impacts on Production Variables

Production Variables +/- % Change

a Time required to test/validate materials %

b Cost to test/validate materials %

c Lead times, or time required to reach first successful (production 

quality) build

%

d Cost required to reach first successful (production quality) build %

e Scrap rate and number of defects %

f Others

7. In Table B-3 below, could you quantify the impacts on your 

company if these needs were met in terms of the following 

production costs? A range is fine.

Table B-3. Impacts on Production Costs

Production Costs +/- % Change

a Cost of materials %

b Cost of energy/electricity %

c Cost of labor %

d Cost of capital equipment %

e Overall cost of production %

8. Switching from thinking about costs to thinking about your

company’s product offering, could you briefly describe what 

changes could be expected if these needs were all met 

today?

a. Quality of existing products? (e.g., lightweighting, 

tensile strength, durability)

b. Amount of customization within existing product lines?

c. Introduction of new products or product lines?

9. Could you quantify these impacts in terms of a relative 

change in your company’s sales? A range is fine.

10. From where do you expect these sources of sales revenue? 

Please see Table B-4.
Appendix B — Interview Guide for Additive End Users

B-5

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table B-4. Sources of Sales Revenue

Source of sales revenue % of total expected change in sales revenue

New or improved products or product lines

Entering new markets

Other
This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Appendix C:

Importance Scores
C-1

This publication is available free of charge from: http://dx.doi.org/10.6028/NIST.GCR.16-006

Table C-1. Rating of Importance of Capabilities/Needs (5=most important, 1=least 

important)

Standards and reference dataReal-time metrology

Design allowablesProcess modeling and simulationSurface finishingMechanical testing procedures

All Firms

4.5 4.0 3.9 3.9 3.5 3.7

Developers

Mean Score 4.2 4.1 4.0 4.0 3.1 3.5

End Users

Mean Score 4.6 3.9 3.8 3.8 3.7 3.8

Figure C-1. Rating of Importance of Capabilities/Needs (5=most important, 1=least 

important)

4.2 4.1 4.0 4.0

3.1

3.5

4.6

3.9 3.8 3.8 3.7 3.8

0

1

2

3

4

5

Standards and

reference data

Real-time

metrology

Design

allowables

Process

modeling and

simulation

Surface

finishing

Mechanical

testing

procedures

Developer User