NIST Special Publication 1163

Economics of the U.S. Additive 

Manufacturing Industry

Douglas S. Thomas
NIST Special Publication 1163

Economics of the U.S. Additive 

Manufacturing Industry

Douglas S. Thomas

Applied Economics Office

Engineering Laboratory

August 2013

U.S. Department of Commerce 

Rebecca Blank, Acting Secretary

National Institute of Standards and Technology 

Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director 
Certain commercial entities, equipment, or materials may be identified in this

document in order to describe an experimental procedure or concept adequately.

Such identification is not intended to imply recommendation or endorsement by the

National Institute of Standards and Technology, nor is it intended to imply that the

entities, materials, or equipment are necessarily the best available for the purpose. 

National Institute of Standards and Technology Special Publication 1163

Natl. Inst. Stand. Technol. Spec. Publ. 1163, 61 pages (August 2013)

CODEN: NSPUE2
iii

Abstract

There is a general concern that the U.S. manufacturing industry has lost competitiveness 

with other nations. Additive manufacturing may provide an important opportunity for 

advancing U.S. manufacturing while maintaining and advancing U.S. innovation.

Additive manufacturing is a relatively new process where material is joined together 

layer by layer to make objects from three-dimensional models as opposed to conventional 

methods where material is removed. The U.S. is currently a major user of additive 

manufacturing technology and the primary producer of additive manufacturing systems. 

Globally, an estimated $642.6 million in revenue was collected for additive manufactured 

goods, with the U.S. accounting for an estimated $246.1 million or 38.3 % of global 

production in 2011. Change agents for the additive manufacturing industry can focus their 

efforts on three primary areas to advance this technology: cost reduction, accelerating the 

realization of benefits, and increasing the benefits of additive manufacturing. Significant 

impact on these areas may be achieved through reduction in the cost of additive 

manufacturing system utilization, material costs, and facilitating the production of large 

products. There is also a need for a standardized model for cost categorization and 

product quality and reliability testing. 

Keywords: Additive manufacturing; manufacturing; 3D printing; supply chain; 

technology diffusion
iv

Preface

This study was conducted by the Applied Economics Office in the Engineering

Laboratory at the National Institute of Standards and Technology. The study provides 

aggregate manufacturing industry data and industry subsector data to develop a 

quantitative depiction of the U.S. additive manufacturing industry.

Disclaimer

Certain trade names and company products are mentioned in the text in order to adequately specify the 

technical procedures and equipment used. In no case does such identification imply recommendation or 

endorsement by the National Institute of Standards and Technology, nor does it imply that the products are 

necessarily the best available for the purpose.

Cover Photographs Credits

Microsoft Clip Art Gallery Images used in compliance with Microsoft Corporation’s non-commercial use 

policy.
v

Acknowledgements

The author wishes to thank all those who contributed so many excellent ideas and 

suggestions for this report. Special appreciation is extended to Christopher Brown and 

Simon Frechette of the Engineering Laboratory’s Systems Integration Division and to 

Kevin Jurrens of the Engineering Laboratory’s Intelligent Systems Division for their 

technical guidance, suggestions, and support. Special appreciation is also extended to Dr. 

David Butry, Dr. Stanley Gilbert, and Dr. Robert Chapman of the Engineering 

Laboratory’s Applied Economics Office for their thorough reviews and many insights 

and to Ms. Shannon Takach for her assistance in preparing the manuscript for review and 

publication. The author also wishes to thank Dr. Nicos Martys, Materials and Structural 

Systems Division, for his review. 
vi

Table of Contents

ABSTRACT............................................................................................................................................... III

PREFACE .................................................................................................................................................IV

ACKNOWLEDGEMENTS ............................................................................................................................V

TABLE OF CONTENTS...............................................................................................................................VI

LIST OF FIGURES.....................................................................................................................................VII

LIST OF TABLES.......................................................................................................................................VII

1 INTRODUCTION .............................................................................................................................. 1

1.1 BACKGROUND ...................................................................................................................................... 1

1.2 PURPOSE ............................................................................................................................................. 2

1.3 SCOPE AND APPROACH........................................................................................................................... 2

2 THE U.S. MANUFACTURING INDUSTRY ........................................................................................... 3

2.1 THE CURRENT STATE OF THE INDUSTRY ..................................................................................................... 4

2.2 SCIENCE AND TECHNOLOGY INNOVATION................................................................................................... 8

2.3 ADDITIVE MANUFACTURING.................................................................................................................... 9

3 ADDITIVE MANUFACTURING STAKEHOLDERS............................................................................... 11

4 INDUSTRY USE OF ADDITIVE MANUFACTURING ........................................................................... 17

4.1 PRODUCTS OF ADDITIVE MANUFACTURING .............................................................................................. 17

4.2 ADDITIVE MANUFACTURING SYSTEMS..................................................................................................... 22

4.3 ADDITIVE MANUFACTURING COSTS ........................................................................................................ 22

5 ADOPTION AND DIFFUSION OF ADDITIVE MANUFACTURING....................................................... 29

5.1 THE DIFFUSION PROCESS ...................................................................................................................... 29

5.2 FACTORS OF DIFFUSION........................................................................................................................ 31

5.3 DIFFUSION OF ADDITIVE MANUFACTURING.............................................................................................. 32

5.3.1 Perceived Attributes of Innovation ....................................................................................... 34

5.3.2 Change Agents...................................................................................................................... 36

6 OPPORTUNITIES FOR CHANGE AGENTS ........................................................................................ 37

7 CONCLUSION ................................................................................................................................ 41

APPENDIX A: SCHEMATIC DATA MAP .................................................................................................... 47

APPENDIX B: EQUATIONS AND ASSUMPTIONS ...................................................................................... 51
vii

List of Figures

Figure 2.1: UNSD Manufacturing Value Added, Top Ten Producers ............................... 5

Figure 2.2: UNSD Manufacturing Value Added Per Capita, Top Ten Producers.............. 6

Figure 2.3: Manufacturing Value Added Compound Annual Growth, 1985-2010 (UNSD)

............................................................................................................................................. 7

Figure 2.4: Manufacturing Value Added per Capita, Gross Operating Surplus per 

Expenditure Dollar, and Compensation per Hour, OECD STAN Data.............................. 8

Figure 3.1: Manufacturing Supply Chain ......................................................................... 12

Figure 4.1: Supply Chain for Additive Manufacturing Products, 2011............................ 19

Figure 4.2: Supply Chain for Additive Manufacturing Systems, 2011 ............................ 23

Figure 4.3: Cost Distribution of Additive Manufacturing of Metal Parts by varying 

Factors............................................................................................................................... 25

Figure 5.1: The Logistical S-Curve Model of Diffusion .................................................. 29

Figure 5.2: Rogers’ Model of Adoption (based on probability distribution).................... 30

Figure 5.3: Variables Determining the Rate of Adoption of Innovations......................... 31

Figure 5.4: Forecasts of U.S. Additive Manufacturing Shipments, by Varying Market 

Saturation Levels .............................................................................................................. 35

Figure 6.1: Impact of Change Agents on the Net Benefits and Return on Investment for 

Additive Manufactured Products...................................................................................... 37

Figure 6.2: Illustration of the Optimal use of Change Agent Funding for Six Alternative 

Investments....................................................................................................................... 38

List of Tables

Table 3.1: Stakeholders..................................................................................................... 13

Table 3.2: Stakeholder Benefits for Adopting Additive Manufacturing .......................... 16

Table 4.1: Additive Manufacturing Shipments................................................................. 18

Table 4.2: Pros and Cons in Product Lifecycle Management........................................... 24

Table 4.3: High Pressure Die Cast Manufacturing Costs vs. Additive Manufacturing 

Costs (Selective Laser Sintering)...................................................................................... 26

Table 5.1: Forecasts of U.S. Additive Manufacturing Shipments by Varying Market 

Potential ............................................................................................................................ 34

Table A.1: Supply Chain Components............................................................................. 48

Table A.2: Total Supply Chain Values for Industries Relevant to Additive 

Manufacturing, $million 2011 .......................................................................................... 49

Table A.3: Supply Chain Values for Additive Manufacturing by Industry, $million 2011

........................................................................................................................................... 50
1

1 Introduction

1.1 Background

In 2010, the world produced approximately $10.2 trillion in manufacturing value added,

according to United Nations Statistics Division (UNSD) data. The U.S. produced 

approximately 18 % of these goods, making it the second largest manufacturing nation in 

the world, down from being the largest in 2009. Many products and parts made by the 

industry are produced by taking pieces of raw material and cutting away sections to 

create the desired part; however, a relatively new process called additive manufacturing 

is beginning to take hold where material is aggregated together rather than cut away. 

Additive manufacturing is the process of joining materials to make objects from threedimensional (3D) models layer by layer as opposed to subtractive methods that remove 

material. The terms additive manufacturing and 3D printing tend to be used 

interchangeably to describe the same approach to fabricating parts. This technology is 

used to produce models, prototypes, patterns, components, and parts using a variety of 

materials including plastic, metal, ceramics, glass, and composites. Products with moving 

parts can be printed such that the pieces are already assembled. Technological advances 

have even resulted in a 3D-Bio-printer that one day might create body parts on 

demand.1, 2

Additive manufacturing is used by multiple industry subsectors, including motor 

vehicles, aerospace, machinery, electronics, and medical products.3 This technology dates 

back to the 1980’s with the development of stereolithography, which is a process that 

solidifies layers of liquid polymer using a laser. The first additive manufacturing system 

available was the SLA-1 by 3D Systems. Technologies that enabled the advancement of 

additive manufacturing were the desktop computer and the availability of industrial 

lasers. 

Although additive manufacturing allows the manufacture of increasingly complex parts, 

the slow print speed of additive manufacturing systems limits their use for mass 

production. 3D scanning technologies have enabled the replication of real objects without 

using molds, which can be difficult and expensive. As the costs of additive 

manufacturing systems decrease, this technology may change the way that consumers 

interact with producers. The customization of products will require increased data 

collection from the end user. Additionally, an inexpensive 3D printer allows the end user 

to produce polymer-based products in their own home or office. Currently, there are a 

number of systems that are within the budget of the average consumer.

 1 Economist. ”Printing Body Parts: Making a Bit of Me.” <http://www.economist.com/node/15543683> 2 GizMag. “3D Bio-printer to Create Arteries and Organs.” <http://www.gizmag.com/3d-bioprinter/13609/> 3 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012.
2

1.2 Purpose

Additive manufacturing technology opens up new opportunities for the economy and 

society. It can facilitate the production of strong light-weight products for the aerospace 

industry and it allows designs that were not possible with previous manufacturing 

techniques. It may revolutionize medicine with biomanufacturing. This technology has 

the potential to increase the well-being of U.S. citizens and improve energy efficiency in 

ground and air transportation. However, the adoption and diffusion of this new 

technology is not instantaneous. With any new technology, new standards, knowledge, 

and infrastructure are required to facilitate its use. Organizations such as the National 

Institute of Standards and Technology can enable the development of these items; thus, it 

is important to understand the size and extent of the additive manufacturing industry. 

Although many organizations provide estimates on the size of the industry, they are often 

not comparable to widely published industry data and statistics. This report examines the 

additive manufacturing industry in the U.S. and develops industry data that is comparable 

to that published by the U.S. Census Bureau. Additionally, it examines the adoption and 

diffusion of additive manufacturing technologies.

1.3 Scope and Approach

This report focuses on U.S. additive manufacturing; however, there is limited data on the 

nation’s activities in this area. Wohlers4 estimates that, globally, $1.714 billion in 

revenue was generated in the primary additive manufacturing market in 2011. This 

includes $834.0 million for additive manufacturing systems and materials; $642.6 million 

from the sale of parts produced from additive manufacturing systems; and $236.9 million 

for maintenance contracts, training, seminars, conferences, expositions, advertising, 

publications, contract research, and consulting. This report will focus on using these 

estimates combined with other figures to generate industry data on additive 

manufacturing that is comparable to industry data published by the U.S. Census Bureau. 

Data from the Annual Survey of Manufactures and methods developed by Thomas5 are 

used in the development of industry data. The report also examines the adoption and 

diffusion of additive manufacturing by examining costs and unit sales. 

There are variations between different types of additive manufacturing processes. These 

include photopolymer-based systems, powder-based systems, molten material systems, 

and solid sheet systems.

6 This report does not delve into the economic implications for

each system. Rather it approaches additive manufacturing as a whole. Examining these 

system-related details would require additional research. 

 4 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012.

5 Thomas, Douglas S. “The Current State and Recent Trends of the U.S. Manufacturing Industry”, NIST 

Special Publication 1142. December 2012. <http://www.nist.gov/manuscript-publicationsearch.cfm?pub_id=912933> 6 Gibson, Ian, David Rosen, and Brent Stucker. Additive Manufacturing Technologies. Springer: New 

York, 2010. 47-50
3

2 The U.S. Manufacturing Industry

Over time manufacturing processes have changed dramatically. Robotic arms and other 

machinery have radically changed the manufacturing environment. For instance, just a 

few decades ago a company such as Standard Motor Products, which produces 

replacement parts for car engines, had a number of employees who were illiterate. Today, 

many of the employees at Standard Motor Products not only need to be able to read, they 

need to know the computer language of the machinery producing the parts.7, 8 The

increase in productivity that is often the result of these changes means fewer employees 

are needed to make the same products, possibly resulting in lower employment levels in 

manufacturing. And, while American manufacturing efficiency is improving, other 

nations have been developing and improving their own manufacturing industries. 

Emerging economies such as China have gone from producing some manufactured goods 

to producing a significant amount of goods. Understanding the current state and recent 

trends of the U.S. manufacturing industry in light of these issues is difficult. Tassey’s 

“Rationales and Mechanisms for Revitalizing U.S. Manufacturing R&D Strategies”9 and 

the commentaries that follow it, illustrate that determining the current and future state of

U.S. manufacturing is controversial. Some experts have stated that U.S. multinationals 

have “abandoned” the U.S. and their global expansion “tends to ‘hollow out’” U.S. 

operations while exporting jobs abroad. Others counter that operations and investment of

U.S. multinationals are highly concentrated in the U.S. and maintain a large presence 

while increasing overseas activities.10, 11, 12

National economies are often compared to companies competing for market share. This is 

a common analogy made when discussing the U.S. manufacturing industry; 

unfortunately, this comparison can be rather misleading.13, 14, 15, 16, 17 A national economy 

 7 Davidson, Adam. “The Transformation of American Factory Jobs, In One Company.” NPR. January 13, 

2012. <http://www.npr.org/blogs/money/2012/01/13/145039131/the-transformation-of-american-factoryjobs-in-one-company?ft=1&f=100> 8 Davidson, Adam. “Making It in America.” The Atlantic. January/February (2012).

<http://www.theatlantic.com/magazine/archive/2012/01/making-it-in-america/8844/?single_page=true> 9 Tassey Gregory. “Rationales and Mechanisms for Revitalizing U.S. Manufacturing R&D Strategies.” 

Journal of Technology Transfer. 35 (2010): 283-333. 10 Slaughter, Matthew J. “How U.S. Multinational Companies Strengthen the U.S. Economy.” United 

States Council for International Business. (March 2010). 

<http://www.uscib.org/docs/foundation_multinationals.pdf> 11 National Science Foundation. “Asia’s Rising Science and Technology Strength.” May 2007. 

<http://www.nsf.gov/statistics/nsf07319/> 12 Sirkin, Harold L. “Made in the USA Still Means Something.” Bloomberg Businessweek. April 10, 2009. 

<http://www.businessweek.com/managing/content/apr2009/ca20090410_054122.htm> 13 Krugman, Paul R. “Making Sense of the Competitiveness Debate.” Oxford Review of Economic Policy. 

Vol 12, no. 3 (1996): 17-25. Paul Krugman won the 2008 Nobel Memorial Prize in Economic Sciences for 

his work on international trade and economic geography.

14 Krugman, Paul R. “Competitiveness, A Dangerous Obsession.” Foreign Affairs. Vol 73. Num 2. 

March/April (1994): 28-44. 15 The World Economic Forum defines competitiveness of a nation as “the set of institutions, policies, and 

factors that determine the level of productivity of a country.” This definition relates to productivity and is 

not consistent with the idea of countries competing for market share. World Economic Forum. The Global 
4

is the primary supplier of goods and services to its labor force, while a single company, 

generally, is not the primary supplier of goods and services to its employees. 

Additionally, a national economy provides the income for the majority of the nation’s 

consumers, while a business, generally, does not provide the income for the majority of 

its customers. Moreover, a national economy represents a system of exchange in which a 

company operates as one entity of that system. Companies can go out of business while 

nations do not. Domestic demand for goods and services constitutes a great proportion of 

the demand for a nation’s domestically-produced products, where the demand for goods 

and services from a company is primarily external. In addition to these types of analogies, 

frequently, anecdotal observations are used to characterize the manufacturing industry;18

however, the insight from these types of observations is somewhat limited, as the 

manufacturing industry includes hundreds of thousands of establishments with millions 

of employees making trillions of dollars worth of goods. Anecdotal observations provide 

a limited narrow scope of the industry that does not necessarily reflect or apply to the 

industry as a whole.

The primary goal of devoting resources toward manufacturing activities is to receive a 

form of benefit for oneself and/or for society as a whole. This is true for all industry 

stakeholders. Investments are often assessed by the resources devoted to the investment 

and the resources that are yielded from the investment. The return is then compared to the 

return on other, similar, ventures. Also considered is the extent or size of one’s 

investment. This is the approach that is taken in the following section to examine the 

manufacturing industry. Specifically, it examines the U.S. manufacturing industry from 

the stakeholder’s return on investment and compares it internationally. This approach 

provides a systematic examination of the primary goal of devoting resources to 

manufacturing and sets it in the context of international performance.

2.1 The Current State of the Industry

According to 2010 data from the UN Statistics Division, the U.S. is the second largest 

manufacturing nation in the world, with China producing just slightly more than the U.S. 

as seen in Figure 2.1. This figure contains the ten largest manufacturing nations and 

illustrates the magnitude and significance of the U.S. manufacturing industry to the 

global and domestic economy. As seen in the pie charts, the U.S. produced 28 % of the 

world’s goods in 1985. This value declined to 18 % in 2010. Although significant, it is 

important to note that in order for underdeveloped countries to become developed 

 

Competitiveness Report. 2010-2011. 

<http://www3.weforum.org/docs/WEF_GlobalCompetitivenessReport_2010-11.pdf> 16 Porter, Michael E. The Competitive Advantage of Nations. 1st ed. (New York: The Free Press, 1990). 17 Porter asserts that competitiveness is measured by productivity and that measuring a country’s 

competitiveness as its share of world markets is “deeply flawed.” Porter, Michael E. “Building the 

Microeconomic Foundations of Prosperity: Findings from the Business Competitiveness Index.” In Porter, 

Michael E., Klaus Schwab, Xavier Sala-i-Martin, and Augusta Lopez-Claros. The Global Competitiveness 

Report 2003-2004. (New York: Oxford University Press, 2004). 18 Greenwald, Bruce C.N. and Judd Kahn. Globalization: The Irrational Fear that Someone in China will 

Take Your Job. (Hoboken, NJ: John Wiley & Sons 2009). 
5

countries, their production and income will need to approach that of the developed world. 

This, inevitably, results in a decline in the proportion or market share that each developed 

country represents. In per capita terms, the U.S. is the fifteenth largest producer and far 

exceeds China (see Figure 2.2). However, the U.S. compound annual growth rate 

between 1985 and 2010 is 1.1%, putting it well below the 25th percentile of 181 nations 

as seen in Figure 2.3.

Using input-output analysis, the direct and indirect effects of U.S. manufacturing as a 

percent of output ranks 38th out of 45 countries; however, it is important to note that this 

Figure 2.1: UNSD Manufacturing Value Added, Top Ten Producers

0

500

1000

1500

2000

2500

3000

3500

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

$Billions 2010

India

Brazil

Republic of Korea

United Kingdom

France

Italy

Germany

China

Japan

United States

Other
6

Figure 2.2: UNSD Manufacturing Value Added Per Capita, Top Ten Producers

value tends to decrease as nations increase their per capita gross domestic product (GDP). 

This does not suggest that manufacturing is less important to wealthy nations. While 

these effects decrease as a percent of output they increase on a per capita basis. Thus, 

high income nations tend to also have high levels of per capita manufacturing. The 

correlation coefficient between per capita GDP and manufacturing effects as a share of 

output is 0.846, suggesting a significant connection.

With the primary goal of devoting resources toward manufacturing activities being to 

gain a form of benefit for oneself and/or for society as a whole, the best variable to 

compare the return on investment to owners and financiers is net income per expenditure 

dollar; however, the primary variable available to examine and compare the returns for 

owners and financiers internationally is gross operating surplus per dollar of expenditure. 

Gross operating surplus is gross output less a subset of costs (i.e., intermediate 

expenditures, compensation, and taxes less subsidies), but does not take into account the 

depreciation of capital; therefore, it does not fully represent a return on investment. 

However, it is the best variable available. Employees exchange their time for 

compensation or income and consumers exchange the purchase price for the utility 

gained from the product purchased. Unfortunately, data is not readily available to 

examine the utility of consumers. 

Among those countries for which data is available in the Organization for Economic 

Cooperation and Development’s Structural Analysis (OECD STAN) database, Finland 

and Austria were the only countries to exceed the U.S. in gross operating surplus per 

0

2000

4000

6000

8000

10000

12000

14000

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

$2 010 

India

Brazil

China

United Kingdom

France

Italy

Republic of Korea

United States

Germany

Japan
7

expenditure dollar, compensation per hour, and manufacturing valued added per capita

(Figure 2.4). Norway, Sweden, Germany, and Denmark have a higher per hour 

compensation and manufacturing value added per capita than the US, but have a 

significantly lower gross operating surplus per expenditure dollar. The U.S. 

manufacturing industry as a whole is just above the 62nd percentile for gross operating 

surplus per dollar of expenditure, with 14 out of 40 countries having a higher value. 

Compensation is ranked 9th among 20 countries for which data is available, putting the

U.S. at the 55th percentile. The Netherlands, Norway, Sweden, Germany, Denmark, and 

France have higher levels of per hour compensation. For every dollar of manufacturing 

value added, there is an estimated 49.5 cents of value added from suppliers of goods and 

services. The gross operating surplus per expenditure dollar for suppliers was $0.304 for 

the US, putting it at the 13th percentile. Indonesia had the highest level followed by 

Turkey, Greece, and Mexico. Compound annual growth in manufacturing between 1985 

and 2010 is 1.1% putting it well below the 25th percentile of 181 nations; however, the

U.S. continues to be the second largest manufacturing nation in the world, with China 

producing just slightly more than the US. In per capita terms, the U.S. is the fifteenth 

largest producer and far exceeds China. Its direct and indirect effects account for 28 % of

U.S. output. 19

Figure 2.3: Manufacturing Value Added Compound Annual Growth, 1985-2010 (UNSD)

 19 Thomas, Douglas. “National Industry Performance Metrics: A Case Study of U.S. Manufacturing.” 

National Institute of Standards and Technology. White paper. Available upon request.

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

25th 

Percentile

50th 

Percentile

United States

Canada

75th 

Percentile

United States

Canada

Japan

Germany

China

India

Norway

Austria Australia

Ireland
8

Figure 2.4: Manufacturing Value Added per Capita, Gross Operating Surplus per Expenditure 

Dollar, and Compensation per Hour, OECD STAN Data 

2.2 Science and Technology Innovation

According to the 2012 OECD Science and Technology Outlook, the U.S. is in a lead 

position for cutting-edge innovation. It maintains excellent higher education and leads the

OECD in shares of gross domestic expenditure on research and development (R&D)

(41 %), triadic patent families20 (29 %), and scientific publications (31 %). Large 

domestic firms contribute to an R&D intensive business sector amounting to 70 % of 

total gross domestic expenditure on research and development. Small and medium 

enterprises account for 17 % of business enterprise expenditures on research and 

development. Approximately 50 % of research and development performers are in hightechnology manufacturing.21

 20 Triadic patent families are defined at the OECD as a set of patents taken at the European Patent Office, 

Japanese Patent Office, and U.S. Patent and Trademark Office that share one or more priorities.

21 OECD (2012), OECD Science, Technology and Industry Outlook 2012, OECD Publishing. 

<http://dx.doi.org/10.1787/sti_outlook-2012-en>

Mexico

Poland

Hungary Slavak Republic

Czech Republic

Greece Korea

Spain

Ireland Canada

Italy

United States

Austria

SwedenNetherlands

France

Finland

Germany

Denmark

Norway

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

0.050 0.100 0.150 0.200 0.250 0.300

Compensation per Hour ($2005)

Gross Operating Surplus per Expenditure Dollar

$1000 Value Added per Capita

$5000 Value Added per Capita

$10 000 Value Added per 

Capita

Legend
9

According to adjusted OECD STAN data, the U.S. has the largest research and 

development expenditure for total manufacturing among those countries for which data is 

available. In per capita terms, Germany spends nearly as much as the U.S. in research and 

development for all manufacturing, while Japan exceeds the U.S. expenditure by more 

than 30 %. Among all OECD countries for which data are available, the U.S. ranks above 

the 95th percentile for total manufacturing research and development expenditures 

between 2001 and 2008. From 2001 through 2007, it was above the 90th percentile for all 

subsectors of manufacturing.22

OECD patent data includes the number of patents filed by the inventor’s country of 

residence for 48 countries, including China and India as well as a world estimate. Patents 

reflect inventive performance and, therefore, are a key measure of innovation. According 

to OECD patent data, between 1999 and 2007 the U.S. has ranked above the 90th 

percentile in terms of total number of patents and above the 80th percentile in terms of 

patents per capita. During that same period, U.S. patents represented between 30 % and 

41 % of total patents worldwide. This data is consistent with a patent analysis conducted 

by Thomson Reuters, which suggested that approximately 40 % of the top 100 global 

innovator companies are located in the United States.23 According to the OECD data, 

Japan is the only country that occasionally produced more patents than the U.S., while 

Luxembourg, Switzerland, and Japan produced more patents per capita in 2007.24

2.3 Additive Manufacturing

There is a general concern that the U.S. manufacturing industry has lost competitiveness 

with other nations; however, it still maintains a prominent position, as seen in the 

previous sections. The industry is the second largest in the world, but its growth is below 

the 25th percentile, placing it under that of Japan, Canada, Germany, and Australia among 

others. If the current trends in growth continue, by some measures, the U.S. 

manufacturing industry might be surpassed by other nations. According to the World 

Economic Forum’s Global Competitiveness Index, the U.S. ranked 4th in global 

competitiveness in 2010-2011, 5th in 2011-2012, and 7th in 2012-2013, setting a 

downward trend. Another concern is its rank in innovation which in 2012-2013 is 6th, 

down from 4th in 2010-2011. 

Additive manufacturing may provide an important opportunity for advancing U.S. 

manufacturing while maintaining and advancing U.S. innovation. The U.S. is currently a 

major user of additive manufacturing technology and the primary producer of additive 

manufacturing systems. One of the major benefits of this technology is in the area of 

product design. It allows the production of nearly any complexity of geometry without 

the need for tooling. Additionally, the complexity does not impact the cost in the same 

 22 Thomas, Douglas S. “The Current State and Recent Trends of the U.S. Manufacturing Industry”, NIST 

Special Publication 1142. December 2012. <http://www.nist.gov/manuscript-publicationsearch.cfm?pub_id=912933> 23 Thomson Reuters. “Top 100 Global Innovators, 2011.” <http://www.top100innovators.com/overview> 24 Ibid
10

way that it does for conventional manufacturing.25 This technology eliminates many of 

the restrictions of ‘Design for Manufacture and Assembly,’ opening a new realm of 

possibilities for new customized products at an affordable price point.

26, 27 To some 

degree, the success of this technology will rely on taking advantage of this benefit. With 

the U.S. being among the lead innovators and being the primary user of additive 

manufacturing, this technology may have the potential to significantly impact U.S. 

competitiveness.

Taking advantage of the opportunities that additive manufacturing offers may prove to be 

difficult. Designers and manufacturers have established practices and approaches to 

developing new products. Additive manufacturing presents new possibilities and, to some 

extent, requires new approaches. Changing the current practices in order to take 

advantage of new opportunities may be difficult. One such challenge is related to the 

customization of products to customer needs, which often requires a significant amount 

of input from the customer. Capturing this information could pose a new challenge to 

some manufacturers. Although the utility of consumers and end users is difficult to 

measure, these stakeholders will potentially be a major benefactor of additive 

manufacturing, as this technology enables rapid design-to-product transformation that 

enables new products to rapidly come to market.

Unfortunately, the available data does not allow an examination of the return on 

investment for stakeholders in additive manufacturing at this point in time. Section 4

discusses and estimates values for costs and profit; however, these are only reasonable 

approximations based on a combination of data sources. A comparison of return on 

investment using this data would not represent the true state of U.S. additive 

manufacturing.

Additive manufacturing may make the U.S. a more competitive place for manufacturing 

resulting in more goods being produced in the U.S.; however, it is important to note that 

productivity is a contributor to the reduction of manufacturing employment.28 Even if 

additive manufacturing results in a significant increase in productivity that attracts jobs 

from overseas, it may not result in a net increase in manufacturing employment; however, 

it is possible that additive manufacturing may facilitate a net increase in employment 

through new products or other means.

 25 Hopkinson, Neil, “Production Economics of Rapid Manufacture.” In Hopkinson, Neil, Richard Hague, 

and Philip Dickens. Rapid Manufacturing. (Hoboken, NJ: John Wiley & Sons, 2006). 147-157. 26 Boothroyd, Geoffrey, Peter Dewhurst, and Winston Knight. Product Design for Manufacture and 

Assembly. (New York: Marcel Dekker, Inc, 2009). 27 Mansour, S., Richard Hague. (2003) “Impact of Rapid Manufacturing on Design for Manufacture for 

Injection Molding.” Proceedings of the Institution of Mechanical Engineers, Part B: Journal of 

Engineering Manufacture. 28 McKinsey&Company. “Manufacturing the Future: The Next Era of Global Growth and Innovation.” 

November 2012. 

<http://www.mckinsey.com/insights/mgi/research/productivity_competitiveness_and_growth/the_future_of

_manufacturing>
11

3 Additive Manufacturing Stakeholders

This section identifies stakeholders and costs related to additive manufacturing. These 

items are relevant to understanding the adoption and diffusion of this technology. 

Individual manufacturing stakeholders are affected by the industry in different ways. 

Therefore, it is useful to identify individual stakeholders and classify them into 

stakeholder groups. This classification can then be used to identify the primary 

investment each stakeholder has in the manufacturing industry along with their expected 

return. Stakeholders evaluate benefits and costs of manufacturing industry investments 

purely from their “stakeholder” point of view; therefore, it is important to identify each 

stakeholder’s investment and expected return. These perspectives can provide some 

guidance to the adoption of additive manufacturing. 

There are a number of stakeholders for the additive manufacturing industry. The most 

direct and obvious ones are the owners and employees of manufacturing companies; 

these are the individuals directly responsible for production. As seen in the 

manufacturing supply chain in Figure 3.1, there are many suppliers of goods and services 

that also have a stake in the industry; these include resellers, providers of transportation 

and warehousing, raw material suppliers, suppliers of intermediate goods, and suppliers 

of professional services. The items in the figure colored in blue represent suppliers of 

services, computer hardware, software, and other costs. Tan represents refuse removal, 

intermediate goods, and recycling, while orange represents machinery, structures, and 

compensation, with red being the repair of the machinery and structures. Green represents 

the suppliers of materials. These items all feed into the design and production of 

manufactured goods that are inventoried and/or shipped. The depreciation of capital and 

net income are also included in the figure, which affect the market value of shipments. In 

addition to the stakeholders in the figure, there are also public vested interests, the end 

users, and financial service providers. 

As seen in Table 3.1, stakeholders may have a direct investment in manufacturing, such 

as industry owners and employees, or an indirect investment through supply chains or 

industry outputs. Each stakeholder is associated with a primary form of investment. For 

example, employees invest their labor, while owners invest land and capital. Owners 

often have labor and/or intellectual property invested as well; however, their primary 

investment is in the form of land and capital as seen in Table 3.1. Each stakeholder has 

invested these items with the expectation of receiving compensation or a return on 

investment. Employees, for instance, expect to be compensated for their labor and owners 
12

Figure 3.1: Manufacturing Supply Chain
13

Table 3.1: Stakeholders

Stakeholders Affiliation Primary Investment Expected Return

Owners Private Producers Land, Capital Goods, and Financial Capital Profit From Sales

Employees (manufacturing industry and suppliers) Laborers Labor Income

Resellers Private Distributer Land, Capital Goods, and Labor Profit From Markup

Retailers Private Distributer Land, Capital Goods, and Labor Profit From Markup

Wholesalers Private Distributer Land, Capital Goods, and Labor Profit From Markup

Standards and Codes Organizations Public/Private Interest Labor and Intellectual Property Economic Success

Transportation and Warehousing Support Service Land, Capital Goods, and Labor Profit From Fees

Air Transportation Providers Transportation Land, Capital Goods, and Labor Profit From Fees

Ground Transportation Providers Transportation Land, Capital Goods, and Labor Profit From Fees

Warehousing and Storage Providers Storage Facility Land and Capital Goods Profit From Fees

Professional Societies Public/Private Support Services Labor and Intellectual Property Economic Success and Profit from Fees

Finance Services Insurance and Finance Financial Capital Profit From Fees

Insurance Providers Insurance Financial Capital Profit From Fees

Health and Medical Insurance Providers Insurance Financial Capital Profit From Fees

Financiers Financier Financial Capital Capital Gains

Public Vested Interests Public Labor and Financial Capital Economic Success

Policy Makers Public Labor and Financial Capital Economic Success

Tax Payers Public Financial Capital Economic Success

Industry Suppliers Public/Private Suppliers Land, Capital Goods, and Labor Profit 

Mining Material Suppliers Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Agriculture Product Suppliers Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Electric Utility Suppliers Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Water Utility Suppliers Public/Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Natural Gas Suppliers Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Facility Construction Providers Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Maintenance and Repair Providers Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Communication Services Providers Private Support Services Land, Capital Goods, and Labor Profit From Fees

Other Fuel Suppliers Private Suppliers Land, Capital Goods, and Labor Profit From Sales

Refuse Removal Service Providers Private Support Services Land, Capital Goods, and Labor Profit From Fees

Professional Services Public/Private Support Services Land, Capital Goods, Labor, and Intellectual Property Profit From Fees

Legal Service Providers Public/Private Support Services Labor Profit From Fees

Information Service Providers Private Support Services Land, Capital Goods, and Labor Profit From Fees

Research Organizations Public/Private Suppliers Labor and Intellectual Property Profit From Fees

Accounting Service Providers Private Support Services Labor Profit From Fees

Engineering Service Providers Private Support Services Labor and Intellectual Property Profit From Fees

Computer Service Providers Private Support Services Labor Profit From Fees

Scientific and Technical Service Providers Private Support Services Labor and Intellectual Property Profit From Fees

Advertisers Private Support Services Labor and Intellectual Property Profit From Fees

Other Professional Services Private Support Services Labor and Intellectual Property Profit From Fees

Consumers/End User End User Product Purchasing Price Final Product Utilization
14

expect to receive a profit. There are six different categories of assets used in Table 3.1

that can be vested into the industry: financial capital, capital goods, land, labor, 

intellectual property, and the end users purchasing price. A successful industry might be 

considered one that has a suitable magnitude of production that results in competitive net 

benefits for its stakeholders. The expected returns from the industry include profits from 

sales, markup, or fees; income; industry success; capital gains; and utility from the final 

use of the product.

Summary of Primary Investments

Land: Naturally-occurring goods such as water, air, soil, mineral, and flora used in the 

production of products (i.e., the totality of goods or services that a company makes 

available).

Labor: Human effort used in production, which includes technical and marketing 

expertise.

Capital Goods: Human made goods used in the production of products.

Financial Capital: Funds provided by investors to purchase capital goods for production 

of products.

Intellectual Property: Ideas, trademarks, copyrights, trade secrets, and patents used to 

produce products

Purchasing Price: Market value of products sold

Summary of Expected Returns

Profit from sales: The financial benefit realized when revenues exceed costs and taxes for 

a product.

Capital Gains: An increase in the value of a capital asset

Income: Compensation for an individual’s service or labor

Profit from Markup: The difference between the cost of a product and its selling price.

Economic Success: A constant and suitable magnitude of production resulting in 

competitive benefits (profits, capital gains, income, and product utilization) for an 

industry’s stakeholders.

Profit from Fees: The financial benefit realized when revenues exceed costs and taxes for 

a service.

Table 3.2 provides a list of stakeholders and the potential impact additive manufacturing 

might have on them. The adoption of additive manufacturing is likely to have a 

significant impact on the consumer/end user, as this technology improves new products 

and facilitates the rapid production of new products. These individuals will be the 

primary beneficiaries of customized complex products that meet their individualized 

needs. 
15

Financiers, employers, and suppliers will benefit from the profit of new product sales; 

however, some of the new products will be replacing previously produced products and 

the source of revenue might just shift from one product to another. Additionally, any 

increased profit commanded from these products will be partially reduced through 

competition as more companies enter the market. The benefit of new customized 

complex products, however, will continue to benefit end users. It is possible that some of 

the largest benefits of additive manufacturing will be realized outside of the 

manufacturing industry. 

Table 3.2 also provides a list of costs to stakeholders, as the development and use of 

additive manufacturing technology has some costs associated with it. The owners invest 

in the research and development of this technology and also must purchase new 

machinery to replace traditional manufacturing machinery. Resellers may have to bear 

the burden of gathering information from customers for customized products. Some of 

these costs may be passed on to the consumers/end users through the purchase price. 
16

Table 3.2: Stakeholder Benefits for Adopting Additive Manufacturing

Stakeholders Primary Benefits of the Adoption of Additive Manufacturing Primary Costs to the Adoption of Additive Manufacturing

Owners New product sales, increased efficiency and productivity Cost of research and development, new machinery costs

Employees (manufacturing industry and suppliers) Reshoring of jobs, increase in income Labor, possible decrease in employment

Resellers New product sales Cost of gathering consumer data for customized products

Retailers New product sales Cost of gathering consumer data for customized products

Wholesalers New product sales Cost of gathering consumer data for customized products

Standards and Codes Organizations Economic success Cost of research and development

Transportation and Warehousing Increased demand, reduced vehicle weight Cost of new products

Air Transportation Providers Increased demand, reduced vehicle weight Cost of new products

Ground Transportation Providers Increased demand, reduced vehicle weight Cost of new products

Warehousing and Storage Providers Increased demand Decreased demand

Professional Societies Economic success Cost of research and development

Finance Services Profit, product reliability and reduced claims, increased demand Initial investment

Insurance Providers Product reliability and reduced claims Minimal cost

Health and Medical Insurance Providers Increased demand for services Cost of research and development

Financiers Profit from fees and capital gains Initial investment

Public Vested Interests Economic Success, increased standard of living Cost of research and development

Policy Makers Economic Success, increased standard of living Cost of research and development

Tax Payers Economic Success, increased standard of living Cost of research and development

Industry Suppliers Increased demand Cost of meeting increased demand

Mining Material Suppliers Increased demand Cost of meeting increased demand

Agriculture Product Suppliers Increased demand Cost of meeting increased demand

Electric Utility Suppliers Increased demand Cost of meeting increased demand

Water Utility Suppliers Increased demand Cost of meeting increased demand

Natural Gas Suppliers Increased demand Cost of meeting increased demand

Facility Construction Providers Increased demand, new construction materials Cost of meeting increased demand

Maintenance and Repair Providers Possible increased demand Cost of meeting increased demand, possible decrease in demand

Communication Services Providers Increased demand Cost of meeting increased demand

Other Fuel Suppliers Increased demand Cost of meeting increased demand

Refuse Removal Service Providers Reduced vehicle weight Cost of meeting increased demand, possible decrease in demand

Professional Services Increased demand Cost of meeting increased demand

Legal Service Providers Increased demand Cost of meeting increased demand

Information Service Providers Increased demand Cost of meeting increased demand

Research Organizations Increased demand Cost of meeting increased demand

Accounting Service Providers Increased demand Cost of meeting increased demand

Engineering Service Providers Increased demand Cost of meeting increased demand

Computer Service Providers Increased demand Cost of meeting increased demand

Scientific and Technical Service Providers Increased demand Cost of meeting increased demand

Advertisers Increased demand Cost of meeting increased demand

Other Professional Services Increased demand Cost of meeting increased demand

Consumers/End User New product utilization, cost reduction, increased efficiency Increased purchase price
17

4 Industry use of Additive Manufacturing

Value added is the best measure available for comparing the relative economic 

importance of manufacturing among various industries, as it avoids the duplication 

caused from the use of products of some establishments as materials in others. The 

Annual Survey of Manufactures, one of the datasets used in this report, calculates value 

added as the value of shipments less the cost of materials, supplies, containers, fuel, 

purchased electricity, and contract work (i.e., shipments less the suppliers of materials 

colored green in Figure 4.1). It is adjusted by the addition of value added by 

merchandising operations plus the net change in finished goods and work-in-process 

goods. It is important to note that this calculation of value added varies from that of other 

organizations. The U.S. Bureau of Economic Analysis (BEA), for example, calculates 

value added as “gross output (sales or receipts and other operating income, plus inventory 

change) less intermediate inputs (consumption of goods and services purchased from 

other industries or imported).”29 The primary difference is that the Annual Survey of 

Manufacture’s calculation of value added includes purchases from other industries such 

as mining and construction while BEA and other organizations do not include it (i.e., 

BEA calculates it as shipments less all costs colored blue, tan, orange, red, and green in 

Figure 4.1). Since this report uses data from the Annual Survey of Manufactures, it will 

maintain their method of calculating value added.

Although value added is discussed, most of the figures in this report are in terms of 

shipments, which is analogous to revenue. This value is used because the data collected 

on additive manufacturing is in terms of revenue; thus, in order to discuss value added,

additional assumptions must be made, which introduces additional imprecision.

4.1 Products of Additive Manufacturing

Globally, an estimated $642.6 million in revenue was collected for additive manufactured 

goods30 with the U.S. accounting for an estimated $246.1 million or 38.3 % of global 

production in 2011.

31 As seen in Table 4.1, these products are categorized as being in the 

following sectors: motor vehicles; aerospace; industrial/business machines; 

medical/dental; government/military; architectural; and consumer products/electronics, 

academic institutions, and other. The consensus among well-respected industry experts is 

that the penetration of the additive manufacturing market is 8 %;32 however, as seen in 

 29 Horowitz, Karen J. and Mark A. Planting. Concepts and Methods of the U.S. Input-Output Accounts.

Bureau of Economic Analysis. 2006. 30 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012: 129.

31 This value is calculated with the assumption that the U.S. share of additive manufacturing systems sold 

equates to the share of products produced using additive manufacturing systems. The share of additive 

manufacturing systems is available in Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 

3D Printing State of the Industry.” Wohlers Associates, Inc. 2012: 134. 32 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012: 130.
18

Table 4.1, goods produced using additive manufacturing methods represent between 

0.01 % and 0.05 % of their relevant industry subsectors. Thus, additive manufacturing 

has sufficient room to grow. 

Figure 4.1 provides an estimated supply chain for products of additive manufacturing

using the methods documented in NIST Special Publication 1142 combined with some 

additional assumptions.

33 The estimation method used provides rough estimates; thus, 

some caution should be used. Additional precision would require further data collection. 

The items in the figure colored in blue represent suppliers of services, computer 

hardware, software, and other costs. Tan represents refuse removal, intermediate goods, 

and recycling, while orange represents machinery, structures, and compensation, with red 

being the repair of the machinery and structures. Green represents the suppliers of 

materials. These items all feed into the design and production of manufactured goods that

are inventoried and/or shipped. The depreciation of capital and net income are also 

included in the figure, which affect the market value of shipments. The net income per 

expenditure dollar (i.e., return on investment) is approximately 0.205; however, this may 

have significant variation. The total number of employees estimated in U.S. additive 

manufacturing products is estimated at 658. The following sections discuss the various 

categories of manufacturing that use this technology.

Table 4.1: Additive Manufacturing Shipments

Category Relevant NAICS Codes

Percent of 

Total AM Made 

Products

Shipments of 

US Made AM 

Products 

($millions, 

2011)*

Total 

Shipments 

($millions, 

2011)

AM Share 

of Industry 

Shipments

Motor vehicles NAICS 3361, 3362, 3363 19.5% 48.0 445 289.4 0.01%

Aerospace NAICS 336411, 336412, 12.1% 29.8 157 700.7 0.02%

336413

Industrial/business machines NAICS 333 10.8% 26.6 365 734.8 0.01%

Medical/dental NAICS 3391 15.1% 37.2 89 519.5 0.04%

Government/military NAICS 336414, 336415, 6.0% 14.8 32 784.4 0.05%

336419, 336992

Architectural NAICS 3323 3.0% 7.4 72 186.9 0.01%

Consumer products/electronics, All other within NAICS 33.6% 82.7 895 709.8 0.01%

academic institutions, and other 332 through 339

TOTAL NAICS 332 through 339 100.0% 246.1 2 058 925.5 0.01%

* These values are calculated assuming that the percent of total additive manufacturing made products for each industry is the same 

for the U.S.as it is globally. It is also assumed that the U.S.share of AM systems sold is equal to the share of revenue for AM products

Note: Numbers may not add up to total due to rounding

 33 Each supply chain item is calculated for the NAICS codes listed in Table 4.1 and added together by the 

categories listed in the table using data from the Annual Survey of Manufactures. The values for additive 

manufacturing are calculated by assuming that the ratio of each supply chain item to the total value of 

shipments is the same for additive manufacturing. The ratios are then applied to data in the 2012 Wohlers 

Report. These assumptions have significant implications for precision; however, they are the best estimates 

available.
19

Figure 4.1: Supply Chain for Additive Manufacturing Products, 2011
20

Motor Vehicles: Shipments for the U.S. automotive industry (NAICS 3361, 3362, and 

3363) was estimated at $445 billion in 2011. Approximately 19.5% of additive 

manufacturing is within the automotive industry, with the U.S. share being estimated as 

$48.0 million or 0.01 % of the U.S. automotive industry. The industry frequently uses 

additive manufacturing technologies for rapid prototyping. It is also commonly used for 

complex, high-value, or custom parts for antique cars. Motorsports such as NASCAR and 

Formula 1 have also been a field for the application of this technology, which have some 

crossover with the aerospace industry. Both sectors have high demand for performance 

and weight reduction. 

Examples of motor vehicle applications include the following: 

• Intake valves, engine bay parts, gear boxes, and engine components

• Air inlet, engine control unit and lower fairing baffle

• Testing of parts

• Motorcycle engines

The restricted construction size of parts made from additive manufacturing has been a 

limiting factor for further adoption of this technology in the automotive industry. As the 

additive manufacturing industry develops the ability to produce larger components, the 

automotive industry is likely to adopt this technology more rapidly.34, 35, 36

Aerospace: Shipments for manufacturing in the U.S. aerospace industry (NAICS 336411, 

336412, and 336413) were estimated at $157.7 billion in 2011. Approximately 12.1 % of 

additive manufacturing is within this industry, with the U.S. share being estimated as 

$29.8 million or 0.02 % of the U.S. aerospace industry. Aerospace includes a range of 

vehicles including airplanes, unmanned vehicles, transport vehicles, and space vehicles. 

This industry has significant potential for increased use of additive manufacturing as it 

often requires strong geometrically complex parts, which must be especially light weight. 

Additionally, these parts are, typically, produced in small quantities, making them a 

likely candidate for additive manufacturing. 

Examples of aerospace applications include the following: 

• Structural parts

• Thrust reverser doors

• Landing gears

• Gimbal eye

• Fuel injection nozzles

 34 Gausemeier, Jurgen, Niklas Echterhoff, Martin Kokoschika, and Marina Wall. “Thinking Ahead the 

Future of Additive Manufacturing – Future Applications.” University of Paderborn, Direct Manufacturing 

Research Center. 

35 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012: 130. 36 Bourell, David L., Ming C. Leu, and David W. Rosen. “Roadmap for Additive Manufacturing: 

Identifying the Future of Freeform Processing.” University of Texas. 

<http://wohlersassociates.com/roadmap2009.html>
21

Similar to the automotive industry, the restricted construction size of additive 

manufacturing has likely been a limiting factor for further adoption of this technology in 

the aerospace industry. Additionally, materials, accuracy, surface finish, and certification 

standards have also played a role in limiting further adoption of this technology.37, 38, 39, 40

Industrial/Business Machines: Shipments in U.S. machinery manufacturing (NAICS 

333) were estimated at $365.7 billion in 2011. Approximately 10.8 % of additive 

manufacturing is within this industry, with the U.S. share being estimated at $26.6

million or 0.01 % of U.S. machinery manufacturing. Machinery manufacturing includes 

the creation of end products that apply mechanical force to perform work. Additive 

manufacturing technology has been used in the development and production of parts for

these machines. For example, a new drag chain link was developed and produced for the 

mining industry using additive manufacturing. 

Medical/Dental: Shipments for U.S. manufacturing of medical and dental products 

(NAICS 3391) amounted to $89.5 billion in 2011. Approximately 15.1 % of additive 

manufacturing is within this industry, with the U.S. share being estimated at $37.2

million or 0.04 % of medical/dental manufacturing. The need for custom-made products 

in the medical and dental industry creates a demand for products made using additive 

manufacturing methods. Items produced include custom implants, prosthetics, surgical 

tools, hearing aids, and drug delivery devices among other items. Emerging research and 

development has resulted in biomanufacturing, where the construction of tissue from 

living cells is used to “print” organs. Although this field is not fully developed, it is a 

promising area for applying additive manufacturing technology.

Government/Military: Shipments for U.S. manufacturing of products for the government 

and military (NAICS 336414, 336415, 336419, 336992) amounted to $32.8 billion in 

2011. Approximately 6.0 % of additive manufacturing is within this industry, with the

U.S. share being estimated at $14.8 million or 0.05 % of government/military 

manufacturing. The U.S. military has shown interest in advancing research and 

procurement of additive manufacturing for a number of components. The U.S. Air Force, 

for example, is conducting research on the use of additive manufacturing for metal parts, 

heat exchangers, and plastic resins for remotely piloted vehicles. The U.S. Navy is also 

investigating the use of this technology.41

 37 National Institute of Standards and Technology. “Roadmapping Workshop: Measurement Science for 

Metal-Based Additive Manufacturing.” <http://events.energetics.com/nistadditivemfgworkshop/index.html> 38 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012: 130.

39 Bourell, David L., Ming C. Leu, and David W. Rosen. “Roadmap for Additive Manufacturing: 

Identifying the Future of Freeform Processing.” University of Texas. 

<http://wohlersassociates.com/roadmap2009.html> 40 Gausemeier, Jurgen, Niklas Echterhoff, Martin Kokoschika, and Marina Wall. “Thinking Ahead the 

Future of Additive Manufacturing – Future Applications.” University of Paderborn, Direct Manufacturing 

Research Center. 

41 Scott, Justin, Nayanee Gupta, Christopher Weber, Sherrica Newsome, Terry Wohlers, and Tim Caffrey. 

“Additive Manufacturing: Status and Opportunities”, March 2012. 

<https://www.ida.org/stpi/occasionalpapers/papers/AM3D_33012_Final.pdf>
22

Architecture: Shipments for U.S. manufacturing of products for architecture (NAICS 

3323) amounted to $72.1 billion in 2011. Approximately 3.0 % of additive manufacturing 

is within this industry, with the U.S. share being estimated at $7.4 million or 0.01 % of 

architectural manufacturing. A major use of additive manufacturing for architecture is in 

the modeling of structures and designs. In the past, physical models were tediously built 

by hand. Additive manufacturing has revolutionized this process. 

Consumer Products/Electronics, Academic Institutions, and Other: Shipments for U.S. 

manufacturing for consumer products/electronics, academic institutions, and other 

amounted to $895.7 billion in 2011. Approximately 33.6 % of additive manufacturing is 

within this industry, with the U.S. share being estimated at $82.7 million or 0.01 % of 

this category of manufacturing. It includes many items produced using additive 

manufacturing technology, including toys, figurines, furniture, office accessories, musical 

instruments, art, jewelry, museum displays, and fashion products among other items. 

4.2 Additive Manufacturing Systems

Approximately 62.8% of all commercial/industrial units sold in 2011 were made by the 

top three producers of additive manufacturing systems: Stratasys, Z Corporation42, and 

3D Systems based out of the U.S. Approximately 64.4% of all systems were made by 

companies based in the U.S. The total global revenue from system sales was $502.5

million with U.S. revenue estimated at $323.6 million as seen in Figure 4.2.

43 The 

production of additive manufacturing systems or 3D printers can be categorized as being 

under NAICS 332: Industrial Machinery Manufacturing. Data from the Annual Survey of 

Manufactures for this sector was used to develop the estimates in Figure 4.2. The net 

income as a share of revenue (i.e., shipments) for Stratasys and 3D Systems, two of the 

three largest additive manufacturing system producers, was 0.144 and 0.178, while the 

estimate using data in Figure 4.2 is 0.152.

It is important to remember that additive manufacturing systems are already incorporated 

into the sales of products produced using this technology; thus, it would be unorthodox to 

add the value for additive manufactured products together with the value for the systems.

4.3 Additive Manufacturing Costs 

Manufacturing processes and manufacturing parts are becoming more and more complex. 

Additive manufacturing both reduces and adds to the complexity of this process. As seen 

in Table 4.2, there are a number of pros and cons involved with additive manufacturing. 

For instance, there are fewer parts to manage, more flexibility in design, and products can 

be individualized; however, there are higher calibration requirements, needed quality 

 42 Z Corporation was acquired by 3D Systems Inc. in 2012. 43 The dollar estimate is assumes that the share of U.S. revenue is equal to the share of U.S. unit sales, 

which is from Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the 

Industry.” Wohlers Associates, Inc. 2012: 134.
23

Figure 4.2: Supply Chain for Additive Manufacturing Systems, 2011
24

Table 4.2: Pros and Cons in Product Lifecycle Management

Pros Cons

More flexible development Software limitations

Freedom of design and construction High machine and material costs

Integration of functions High calibration effort

Less assembly Deficient quality

Fewer production tools necessary Parts often require reworking

Less spare parts in stock Building time depends on part height

Less complexity (fewer parts to manage)

Fewer tools needed

Less time-to-market

Rapid alterations

Individualized products

Source: Lindemann C., U. Jahnke, M. Moi, and R. Koch. “Analyzing Product Lifecycle Costs for a Better 

Understanding of Cost Drivers in Additive Manufacturing.” Proceedings of the 2012 Solid Freeform 

Fabrication Symposium. 

<http://utwired.engr.utexas.edu/lff/symposium/proceedingsArchive/pubs/Manuscripts/2012/2012-12-

Lindemann.pdf>

improvements, and parts often require reworking. The benefits of additive manufacturing 

are not limited to the producer, however, as the end user also benefits from increased 

functionality, reduced lifecycle costs, and new product utilization. Aerospace parts, for 

instance, have shown a weight reduction potential of up to 70% of the original part44 and 

a 1 kg reduction in weight saves an estimated $3000 of fuel annually45, not to mention 

the reduction in emissions.

Costs have been identified as being a significant factor in whether producers adopt 

additive manufacturing technologies. Hopkinson estimates that machine costs range 

between 50 % and 75 % of total cost, materials range between 20 % and 40 %, and labor 

ranges between 5 % and 30 %.46 The price for materials can vary somewhat. 

Stereolithography/epoxy-based resin is estimated at $175 per kilogram, selective laser 

sintering/nylon powder is $75, and fused deposition modeling/ABS filament is around 

$250. To put this in the perspective of conventional manufacturing, injection 

molding/ABS is about $1.80 and machining/1112 screw-machine steel is about $0.66.47

Other research on metal parts confirms that machine and material costs are a major cost 

driver for this technology as seen in Figure 4.3, which presents data for a sample part 

 44 Lindemann C., U. Jahnke, M. Moi, and R. Koch. “Analyzing Product Lifecycle Costs for a Better 

Understanding of Cost Drivers in Additive Manufacturing.” Proceedings of the 2012 Solid Freeform 

Fabrication Symposium. 

<http://utwired.engr.utexas.edu/lff/symposium/proceedingsArchive/pubs/Manuscripts/2012/2012-12-

Lindemann.pdf> 45 West, Karl. “Melted Metal Cuts Plane’s Fuel Bill.” The Sunday Times. Sunday 13 February 2011. 

<http://www.thesundaytimes.co.uk/sto/business/energy_and_environment/article547163.ece> 46 Hopkinson, Neil, “Production Economics of Rapid Manufacture.” In Hopkinson, Neil, Richard Hague, 

and Philip Dickens. Rapid Manufacturing. (Hoboken, NJ: John Wiley & Sons, 2006). 147-157. 47 Ibid
25

Figure 4.3: Cost Distribution of Additive Manufacturing of Metal Parts by varying Factors

Source: Lindemann C., U. Jahnke, M. Moi, and R. Koch. “Analyzing Product Lifecycle Costs for a Better 

Understanding of Cost Drivers in Additive Manufacturing.” Proceedings of the 2012 Solid Freeform 

Fabrication Symposium. 

<http://utwired.engr.utexas.edu/lff/symposium/proceedingsArchive/pubs/Manuscripts/2012/2012-12-

Lindemann.pdf>

Note: The orange star indicates the base model.

made of stainless steel. For this example, four cost factors are varied and the production 

quantity is a little less than 200 for the base case. This analysis provides insight into 

identifying the largest costs of additive manufacturing. The first cost factor that is varied 

is the building rate, which is the speed at which the additive manufacturing system 

operates. In this example, it is measured in cubic centimeters per hour. The second factor 

that is varied is the machine utilization measured as the number of hours per year that the 

machine is operated. The third factor is the material cost and the last factor is the machine 

investment costs, which include items related to housing, using, and maintaining the 

additive manufacturing system. Among other things, this includes energy costs, machine 

purchase, and associated labor costs to operate the system. The base model has a build 

rate of 6.3 ccm, a utilization of 4500 h/yr, a material cost of 89 €, and a machine 

investment cost of 500 000 €. For comparison, the base case is shown four times in the 

figure, with each one shown with a star. On average, the machine costs accounted for 

62.9 % of the cost estimates in Figure 4.3 (note that the base case is only counted once in 

the average). This cost was the largest even when building rate was more than tripled and 

other factors were held constant. This cost was largest in all but one case, where material 

costs were increased to 600 €/kg. The second largest cost is the materials, which, on 

average, accounted for 18.0 % of the costs; however, it is important to note that this cost

6.3 12 20 4500 6000 7800 40 89 600 200 320 500

Building rate in

ccm/h

Machine

Utilization h/yr

Material Costs 

(€/kg)

Machine 

investment costs 

(€ thousands)

Building process fix 2% 2% 3% 2% 2% 2% 2% 2% 1% 2% 2% 2%

Preparation costs 4% 7% 9% 4% 5% 6% 5% 4% 3% 6% 5% 4%

Oven 3% 4% 5% 3% 3% 4% 3% 3% 2% 4% 3% 3%

Material costs 11% 17% 23% 11% 14% 16% 5% 11% 46% 16% 14% 11%

postprocessing costs 7% 10% 13% 7% 8% 9% 7% 7% 4% 9% 8% 7%

Machine costs 74% 59% 47% 74% 69% 64% 78% 74% 45% 63% 68% 74%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Percent of Cost
26

is likely to decrease as more suppliers enter the field.48 Post processing, preparation, oven 

heating, and building process fix were approximately 8.4 %, 5.4 %, 3.3 %, and 1.9 %, 

respectively.

Plastic parts likely have a slightly different cost structure. A case study of a fluorescent 

lamp holder provides some insight. This case study examined two Electro Optical 

Systems that use selective laser sintering: P390 and P730. The P390 was more cost 

effective for this particular case study. The cost per part for this item was examined and 

revealed that for the P390, 58.7 % of the cost was machine cost, 9.9 % was machine 

operator cost, 30.4 % was material cost, and 1.0 % was assembly.49

For manufacturers, the cost advantage of additive manufacturing may vary. Typically, it 

is believed that this technology is competitive for low volume production. This can be 

illustrated in another case study of a landing gear assembly for a 1:5 scale model of the 

P180 Avant II by Piaggio Aero Industries S.p.A. As seen in Table 4.3, the per assembly 

cost of producing the landing gear using traditional manufacturing methods, in this case 

high pressure die casting, was 21.29 € plus 21 000 € divided by the lot size. The cost of 

additive manufacturing was 526.31 € per assembly; thus, below a lot size of 41 additive 

manufacturing is more cost effective. Above a lot size of 41 it was not cost effective. 

These cost estimates also illustrate how additive manufacturing does not follow 

traditional economies of scale, where large production runs reduce the per item cost; thus, 

Table 4.3: High Pressure Die Cast Manufacturing Costs vs. Additive Manufacturing Costs (Selective 

Laser Sintering)

Traditional Manufacturing 

(High Pressure Die Cast)

Additive Manufacturing 

(Selective Laser Sintering)

Material cost per part 2.59 € 25.81 €

Mould cost per part 21 000 €/N -

Pre-processing cost per part - 8.00 €

Processing cost per part 0.26 € 472.50 €

Post-processing cost per part 17.90 € 20.00 €

Linkages and assembly 0.54 € -

TOTAL COST PER ASSEMBLY 21.29 €+21 000 €/N 526.31 €

Note: N is the lot size or the number of consecutive assemblies produced 

Source: Atzeni, Eleonora, Luca Iuliano, and Alessandro Salmi. (2011) “On the Competitiveness of 

Additive Manufacturing for the Production of Metal Parts.” Proceedings of the 9th International 

Conference on Advanced Manufacturing Systems and Technology. 

 48 Lindemann C., U. Jahnke, M. Moi, and R. Koch. “Analyzing Product Lifecycle Costs for a Better 

Understanding of Cost Drivers in Additive Manufacturing.” Proceedings of the 2012 Solid Freeform 

Fabrication Symposium. 

<http://utwired.engr.utexas.edu/lff/symposium/proceedingsArchive/pubs/Manuscripts/2012/2012-12-

Lindemann.pdf>

49 Atzeni, Eleonora, Luca Iuliano, Paolo Minetola, and Alessandro Salmi. (2010) “Redesign and Cost 

Estimation of Rapid Manufactured Plastic Parts.” Rapid Prototyping Journal. 16(5): 308-317.
27

each assembly produced using additive manufacturing costs the same regardless of how 

many are produced. The cost effectiveness of using additive manufacturing relies on a 

number of factors, including the complexity of the part, amount of material, and the 

volume of production.
28
29

5 Adoption and Diffusion of Additive Manufacturing

5.1 The Diffusion Process

Disseminating a new idea or innovation so that it is widely adopted can be difficult, even 

if it has obvious advantages. A common challenge for many is how to speed up the rate 

of diffusion of an innovation. Diffusion, for the purpose of this report, is defined as, “the 

spread of an innovation throughout a social system,” while adoption is defined as, “the 

acceptance and continued use of a product, service, or idea.”50 The diffusion of new 

technologies or innovations tends to follow certain trends and the process is studied in 

several disciplines: economics, communications, sociology, and marketing. 

There is both a diffusion model and an adoption model. The diffusion model is illustrated 

by the logistic S-curve that evaluates the time it takes for an innovation to be diffused 

into an industry.51 Diffusion increases at an increasing rate up to time T1, and then at a 

decreasing rate thereafter (see Figure 5.1). 

Figure 5.1: The Logistical S-Curve Model of Diffusion

A simple logistic function may be defined by the following equation:

P(t) = 1

1 + e−t

 50 Koebel, C. Theodore, Maria Papadakis, Ed Hudson, Marilyn Cavell, The Diffusion of Innovation in the 

Residential Building Industry, PATH, p. 1. 51 Ibid, p. 2.

Cumulative 

Diffusion

Modified from Rogers, E. M., (1995). Diffusion of Innovations, Fourth Edition, (New York: 

The Free Press, 1995), 258.

Time

Decreasing 

Diffusion Rate

T1

Increasing 

Diffusion Rate
30

Where P represents the population of adopters and t is time. The early growth is 

exponential and decays after 50 % of adopters are reached and e is Euler’s number, the 

base of the natural system of logarithms.

52

In connection with the diffusion model, the adoption model focuses on the decision 

process of the individual or firm. This model is connected with Everett Rogers’ theory53

that the S-curve is normally distributed (see Figure 5.2). Most adopters act in the 

midrange of the adoption period timeline because of information diffusion. This is where 

the adoption rate is the highest. At the “early adopters” stage in Figure 5.2, relatively 

little is known about the new technology and the number of adopters is low. At the stage 

of the “majority of adopters,” a significant amount of information has been diffused. By 

the “late adopters” stage, there is little information remaining to be diffused. Each 

individual’s adoption of the technology is equivalent to a “learning trial” in the system. 

Over time, adopter distributions follow a bell shaped curve. 

Figure 5.2: Rogers’ Model of Adoption (based on probability distribution)

Modified from Rogers, E. M. (2003). Diffusion of Innovations, 5th Edition (New York: The Free Press, 2003), 111-

114.

Larsen stresses three explanatory innovation diffusion concepts: (1) cohesion, (2) 

structural equivalence, and (3) thresholds.54 Cohesion asserts that diffusion takes place by 

face-to-face contact between stakeholders, who are described as sharing a high degree of 

homophily; that is to say, they have a tendency to listen to people similar to themselves, 

whom they trust as friends. The stakeholder’s logic behind listening to trusted friends 

relates to the risk and uncertainty of adopting new technology. Structural equivalence

explains diffusion as a copycat approach. The decision to adopt is not based on sound 

judgment, but through fear and risk adversity. The last concept, thresholds, states that 

diffusion is a complex process that can be influenced by education, wealth, 

communication networks, and background. An innovation is not diffused over 

 52 Vishwanath, Arun and George Barnett. The Diffusion of Innovations. (New York: Peter Lang, 2011). 53 Rogers, E. M. (2003). Diffusion of Innovations, Fourth Edition (New York: The Free Press, 2003), p. 111-114. 54 Larsen, Graeme D., “Horses for Courses: Relating Innovation Diffusion Concepts to the Stages of the 

Diffusion Process,” Construction Management and Economics, Vol 23, October 2005, p. 787-792.

Time

Noncumulative 

number of 

adopters

Early 

Adopters

Late 

Adopters

Majority 

of 

Adopters

T1
31

homogenous people, but between diverse individuals with different backgrounds. 

According to the concept of thresholds, a stakeholder’s decision to adopt a new 

technology is interconnected with other stakeholders.

55

5.2 Factors of Diffusion

Some innovations, such as cellular phones, only take a few years to reach widespread 

adoption, while others can take decades. Characteristics of innovations can provide some 

explanation for this difference. Rogers identifies five primary characteristics as seen in 

Figure 5.3: relative advantage, compatibility, complexity, trialability, and observability.

The relative advantage is the extent that an innovation is perceived to be better than the 

current or previous idea. Compatibility is the extent that a new innovation is consistent 

with current values and needs. Innovations that are compatible with current norms and 

needs are likely to be adopted more rapidly than one that is not compatible. Complexity 

refers to the perception of how complicated a new innovation is to understand and use. 

Increased complexity slows the adoption of a new innovation. Trialability is the extent 

that a new innovation may be tested before fully adopting it. Observability is the extent 

that the use and results of a new innovation can be seen by would-be adopters.

The type of innovation decision is also a factor in the rate of adoption. Optional 

innovation decisions are decisions made by individuals independent of other members of 

a system; thus, the individual is the main unit of decision making. Collective innovation 

decisions are those decisions that are made by consensus among members of a system. 

Authority innovation decisions are those decisions to adopt or reject an innovation by a

Figure 5.3: Variables Determining the Rate of Adoption of Innovations

Rogers, E. M. (1995). Diffusion of Innovations, 5th Edition (New York: The Free Press, 2003), 222.

 55 Larsen, Graeme D., “Horses for Courses: Relating Innovation Diffusion Concepts to the Stages of the 

Diffusion Process,” Construction Management and Economics, Vol 23, October 2005, p. 787-792. 

I. Perceived Attributes of Innovations

i. Relative advantage

ii. Compatibility

iii. Complexity

iv. Trialability

v. Observability

II. Type of Innovation-Decision

i. Optional

ii. Collective

iii. Authority

III. Communication Channels

IV. Nature of the Social System

V. Extent of Change Agents’ Promotion 

Efforts

Rate of 

Adoption of 

Innovations
32

select few individuals who maintain power, status, or technical expertise. For example, a 

chief executive officer (CEO) who decides that all employees will wear a suit would be 

an authority decision. 

A communication channel, as referred to in Figure 5.3, is the means by which individuals 

communicate concerning an innovation. These might include the evaluation of an 

innovation by a peer or a review by an expert. One-on-one and other communications 

often take place within a social system. Communication may also occur through mass 

media. Communication channels are important in determining the diffusion of an 

innovation; however, it often requires in-depth investigation to understand these 

channels.

The nature of the social system, such as its norms and interconnectedness, is also an 

important factor in the diffusion of an innovation. This includes the system’s culture, but 

also includes the network of connections between potential adopters. This can be a 

significant factor in the diffusion of a technology, especially in the case where the 

preferred communication channel is one-on-one interaction. Similar to the 

communication channels, the nature of the social system is an important factor, but this 

type of information is not well documented. Additional research may be needed to 

develop a full understanding of both the social system and relevant communication 

channels.

The last variable is the change agent. Both public and private organizations strive to 

change the marketplace. Many entities provide incentives or subsidies in order to speed 

up the rate of adoption of innovations. For example, the federal government often creates 

incentives for individuals or businesses to adopt more environmentally friendly products 

such as energy efficient lighting. Other events, organizations, people, or items also act as 

a catalyst for change in an industry. 

5.3 Diffusion of Additive Manufacturing

Globally, 6494 industrial additive manufacturing systems were deployed in 2011 with a

cumulative total of 49 035 systems being deployed between 1988 and 2011. Of these, 

18 780 were deployed in the U.S. The growth in the cumulative number of additive 

manufacturing systems in the U.S. between 2010 and 2011 was 15.3 %.56

The status of some of the variables that affect the adoption of additive manufacturing 

technologies can be observed through existing articles and texts; however, many issues 

cannot be substantiated without gathering additional data. Surveys can often be used to 

assess a producer or user’s opinion of a new technology, but this is often a resource 

intensive process. Using the number of domestic unit sales57, the growth in sales can be 

fitted using least squares criterion to an exponential curve that represents the traditional 

 56 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012. 57 Wohlers, Terry. “Wohlers Report 2012: Additive Manufacturing and 3D Printing State of the Industry.” 

Wohlers Associates, Inc. 2012.
33

logistic S-curve of technology diffusion. The most widely accepted model of technology 

diffusion was presented by Mansfield58: 

p(t) = 1

1 + eα−βt

Where

p(t) = the proportion of potential users who have adopted the new technology by time t

α = Location parameter

β = Shape parameter (β > 0)

In order to examine additive manufacturing, it is assumed that the proportion of potential 

units sold by time t follows a similar path as the proportion of potential users who have 

adopted the new technology by time t. In order to examine shipments in the industry, it is 

assumed that an additive manufacturing unit represents a fixed proportion of the total 

revenue; thus, revenue will grow similarly to unit sales. The proportion used was 

calculated from 2011 data. The variables α and β are estimated using regression on the 

cumulative annual sales of additive manufacturing systems in the U.S. between 1988 and 

2011. U.S. system sales are estimated as a proportion of global sales. This method

provides some insight into the current trend in the adoption of additive manufacturing 

technology. Unfortunately, there is little insight into the total market saturation level for 

additive manufacturing; that is, there is not a good sense of what percent of the relevant 

manufacturing industries (shown in Table 4.1) will produce parts using additive 

manufacturing technologies versus conventional technologies. In order to address this 

issue, a modified version of Mansfield’s model is adopted from Chapman59:

p(t) = η

1 + eα−βt

Where

η = market saturation level

Because η is unknown, it is varied between 0.15 % and 100 % of the relevant 

manufacturing shipments, as seen in Table 5.1. The 0.15 % is derived from Wohlers 

estimate that the 2011 sales revenue represents 8 % market penetration, which equates to 

$3.1 billion in market opportunity and 0.15 % market saturation. At this level, additive 

manufacturing is forecasted to reach 50 % market potential in 2018 and 100 % in 2045, 

as seen in the table. A more likely scenario seems to be that additive manufacturing 

would have between 5 % and 35 % market saturation. At these levels, additive 

manufacturing would reach 50 % of market potential between 2031 and 2038 while 

 58 Mansfield, Edwin. Innovation, Technology and the Economy: Selected Essays of Edwin Mansfield. 

Economists of the Twentieth Century Series (Brookfield, VT: 1995, E. Elgar).

59 Chapman, Robert. “Benefits and Costs of Research: A Case Study of Construction Systems Integration 

and Automation Technologies in Commercial Buildings.” NISTIR 6763. December 2001. National 

Institute of Standards and Technology. 
34

reaching 100 % between 2058 and 2065, as seen in Table 5.1. The industry would reach 

$50 billion between 2029 and 2031 while reaching $100 billion between 2031 and 2044. 

As illustrated in Figure 5.4, it is likely that additive manufacturing is at the far left tail of 

the diffusion curve, making it difficult to forecast the future trends; thus, some caution 

Table 5.1: Forecasts of U.S. Additive Manufacturing Shipments by Varying Market Potential

Market 

Potential of 

Relevant 

Manufacturing 

(percent of 

shipments)

Market 

Potential, 

Shipments 

($billions 

2011)

Approximate 

Year 100% 

of Market 

Potential 

Reached

Approximate 

Year 50% of 

Market 

Potential 

Reached

Approximate 

Year $100 

Billion in 

Shipments is 

Reached

Approximate 

Year $50 

Billion in 

Shipments is 

Reached

R2

100.00 $2 058.9 2069 2042 2031 2028 0.948

75.00 $1 544.2 2068 2041 2031 2028 0.948

50.00 $1 029.5 2067 2039 2031 2029 0.948

45.00 $926.5 2066 2039 2031 2029 0.948

40.00 $823.6 2066 2038 2031 2029 0.948

35.00 $720.6 2065 2038 2031 2029 0.948

30.00 $617.7 2065 2037 2031 2029 0.948

25.00 $514.7 2064 2037 2032 2029 0.948

20.00 $411.8 2063 2036 2032 2029 0.948

15.00 $308.8 2062 2035 2032 2029 0.948

10.00 $205.9 2061 2033 2033 2029 0.948

5.00 $102.9 2058 2031 2044 2031 0.948

1.00 $20.6 2052 2025 - - 0.949

0.50 $10.3 2050 2023 - - 0.949

0.15 $3.1 2045 2018 - - 0.950

should be used when interpreting this forecast. The figure illustrates the diffusion at each 

market saturation level presented in Table 5.1 with the exception of the 0.50 % and 

0.15 % levels, as they are too small to be included in this graph.

5.3.1 Perceived Attributes of Innovation

Relative Advantage: The relative advantage of adopting additive manufacturing varies 

from industry to industry and is likely to increase over time as the technology 

advances.The per-unit cost of additive manufacturing appears to be a significant barrier 

for many would-be adopters. For some, the benefits outweigh the costs. For instance, 

lighter transportation equipment can significantly reduce costs for end users; thus, they 

might be willing to pay higher upfront costs to purchase lighter equipment made using 

additive manufacturing technologies. For others, however, the benefits of products made 

using this technology may not justify the higher costs for producers or end users. One 

possible challenge that could develop is communicating and convincing the end user of 
35

the benefits of a product made using additive manufacturing. For instance, this 

technology may allow for the design of a longer lasting product; however, the end user is 

only willing to pay for the additional costs of production if they are aware of and 

convinced of the benefits. 

One of the primary beneficiaries of additive manufacturing is the end user; thus, their role 

in persuading manufacturers to adopt additive manufacturing technology is a significant 

one. On the other hand, manufacturers may need to differentiate products made using 

additive manufacturing technology by indicating the benefits to the end user; otherwise, 

costumers may not be willing to pay the costs for these products. 

Compatibility: The limited size of the products that can be produced affects the 

compatibility of additive manufacturing for some manufactured products. Transportation 

Figure 5.4: Forecasts of U.S. Additive Manufacturing Shipments, by Varying Market Saturation 

Levels

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700

1800

1900

2000

2100

20102012201420162018202020222024202620282030203220342036203820402042204420462048205020522054205620582060

AM Shipments ($2011 Billion)

Market Potential: $2059 Billion

Market Potential: $1544 Billion

Market Potential: $1029 Billion

Market Potential: $927 Billion

Market Potential: $824 Billion

Market Potential: $721 Billion

Market Potential: $618 Billion

Market Potential: $515 Billion

Market Potential: $412 Billion

Market Potential: $309 Billion

Market Potential: $206 Billion

Market Potential: $103 Billion

Market Potential: $21 Billion

0

5000

10000

15000

20000

Cumulative AM 

Systems
36

equipment, for instance, involves large components that may be difficult to produce using 

additive manufacturing technology. 

Complexity, Trialability and Observability: Additive manufacturing systems can be 

costly; however, these systems are seemingly easy to illustrate and a significant amount 

of literature is available on them. Currently, there are journals and conferences that 

discuss this technology extensively. One challenge that seems to persist is cost 

categorization and analysis. This prevents a prospective manufacturer from observing the 

costs and benefits from adopting this technology. A number of developments have been 

made on this front; however, no model meets all criteria adequately. There is a need to 

bring together the strengths of existing cost models into one standardized model.60 This 

would allow would-be adopters to understand the benefits and costs more adequately. 

5.3.2 Change Agents

The last factor involves the efforts of change agents. These entities can be individuals, 

events, organizations, or some other entity that acts as a catalyst for change. They often 

accelerate the realization of benefits, reduce costs, and/or increase benefits of some trend 

in society or the economy. This change can often occur through research and 

collaboration efforts. For additive manufacturing, there are a number of organizations 

that strive to advance the current status. One newly created organization is the National 

Additive Manufacturing Innovation Institute (NAMII), which was formally established in 

2012 with an initial $30 million in federal funding matched by $40 million from a 

consortium of companies, universities, colleges, and non-profit organizations. The single 

focus of NAMII is to “accelerate additive manufacturing technologies to the U.S. 

manufacturing sector and increase domestic manufacturing competitiveness.”61 Likewise, 

the Additive Manufacturing Consortium (AMC) was launched by EWI. The mission of 

the AMC is to “bring together a diverse group of practitioners and stakeholders that 

together accelerate the innovation in AM technologies to move them into the mainstream 

of manufacturing technology from their present emerging position.”62

 60 Lindemann C., U. Jahnke, M. Moi, and R. Koch. “Analyzing Product Lifecycle Costs for a Better 

Understanding of Cost Drivers in Additive Manufacturing.” Proceedings of the 2012 Solid Freeform 

Fabrication Symposium. 

<http://utwired.engr.utexas.edu/lff/symposium/proceedingsArchive/pubs/Manuscripts/2012/2012-12-

Lindemann.pdf> 61 National Additive Manufacturing Innovation Institute. <http://namii.org/> 62 EWI. Additive Manufacturing Consortium. < http://ewi.org/additive-manufacturing-consortium/>
37

6 Opportunities for Change Agents

Metrics used to discuss national industries often involve examining the amount of 

research being conducted, factors that impact the industry, or the size of the industry. The 

primary purpose of investing resources into manufacturing activities, however, is to 

generate a benefit or return on investment. Arguably, those countries that exceed the U.S. 

in per capita size and benefits per unit of input, such as compensation per hour, have an 

industry that is more successful at the main objective of investing resources in 

manufacturing. The general purpose of an industry change agent is to create a net 

increase in the return on investment for stakeholders. For additive manufacturing, this 

might be accomplished by reducing costs, accelerating the realization of benefits, or 

increasing the net benefits as illustrated in the larger graph illustrated in Figure 6.1. These 

changes result in an increase in the marginal return on investment as illustrated in the 

Figure 6.1: Impact of Change Agents on the Net Benefits and Return on Investment for Additive 

Manufactured Products

Modified from Gallaher, Michael P., Thomas Phelps and Alan C. O’Connor. Planning Report 02-5: 

Economic Impact Assessment of the International Standard for the Exchange of Product Model Data 

(STEP) in Transportation Equipment Industries. RTI International and the National Institute of Standards 

and Technology. December 2002: 5-4.

With the 

change 

agent

Without the 

change agent

The change agent accelerates the 

realization of benefits

The change 

agent reduces 

costs

The change agent increases 

the net benefits

Net Benefits of Additive Manufactured Products

Time

Investment Level

Marginal Return on 

Investment

With the change agent

Without the change agent

The change 

agent 

increases ROI
38

smaller graph in the figure.

Generally, change agents want to maximize their impact for the amount of resources 

allotted to them; that is, they want the “biggest bang for the buck.” Investment in any 

particular change agent effort, traditionally, has decreasing returns to scale; that is, every 

additional dollar of investment has a little less impact than the previous dollar. Since a 

change agent wants to maximize their impact, it would want to allocate its funding in 

projects such that each dollar of investment has the maximum return possible. For 

instance, Figure 6.2 provides an illustration of five possible investments for a change 

agent with a budget constraint. The investments are referred to as efforts A through E. To 

maximize its impact, a change agent would first invest in Effort A. As it invests more 

and more in Effort A, it moves from the left to the right along the marginal return on 

Figure 6.2: Illustration of the Optimal use of Change Agent Funding for Six Alternative Investments

Note: The green lines represent the investment for each effort.

Effort E

Effort B

Effort C

Effort D

Marginal Return on Investment

Investment Level

Budget Expended

Point at which B becomes worthwhile

Point at which C becomes worthwhile

Point at which D becomes worthwhile

Effort A

Investment level for D

Investment level for C

Investment level for B

Investment level for A

Budget = OA + OB + OC + OD

O D C B A
39

investment line for the change agent. The agent would invest to the point where the 

marginal return on investment for its next dollar invested equals that of Effort B, which is 

referred to in the figure as the “Point at which B becomes worthwhile.” At this point, 

there is some indifference to investing in A or B because they have the same marginal

return on investment; however, as one invests in either A or B the return on investment in 

that effort decreases making the alternative more appealing. Therefore, the change agent 

would invest in both A and B or alternate between the two until the point at which the 

next effort becomes worthwhile. It would continue to do this until its entire budget is 

expended. In this example, effort E goes unfunded while efforts A through D are funded 

to where the bottom of each corresponding green line stops; thus, the total investment is 

the sum of the investment level for Effort A, B, C, and D. It is important to note, 

however, that not all of the costs and benefits of the manufacturing industry are able to be 

measured nor are the impact of the efforts of change agents; therefore, identifying the 

optimal use of funding can be rather problematic.

Change agents for the additive manufacturing industry can focus their efforts on three 

primary areas to advance this technology: cost reduction, accelerating the realization of 

benefits, and increasing the benefits of additive manufacturing. The costs include any of 

the investments made by the stakeholders listed in Table 3.2. These include the owners, 

employees, suppliers, and end users among others. The producer costs of additive 

manufacturing tend to be broken into preparation, materials, machine utilization, and post 

processing. As seen in some case studies in Section 4.3, the largest cost tends to be the 

machine operation cost followed by the material cost. The time it takes to produce a 

product may be a significant factor in the machine utilization cost. Since these two costs 

are the largest, there is a potentially high marginal return on investment for change agents 

that focus on reducing these costs; that is, focusing on these items may result in a higher 

return on investment for some change agents. However, examining these issues in detail 

provides some challenge as there is not a standard cost categorization. This prevents 

change agents from precisely identifying the major costs of this technology. A number of 

developments have been made on this front; however, no model meets all criteria 

adequately. There is a need to bring together the strengths of existing cost models into 

one standardized model.63 This might be another area that has a high return on 

investment for change agents.

As previously discussed, a major benefit of this technology is in the area of product 

design and how it allows the production of nearly any complexity of geometry without 

the need for tooling. Additionally, the complexity does not impact the cost in the same 

way that it does for conventional manufacturing. This technology eliminates many of the 

restrictions of ‘Design for Manufacture and Assembly’ opening a new realm of 

possibilities for new customized products at an affordable price point. To some degree, 

the success of this technology will rely on taking advantage of this benefit. In order to 

 63 Lindemann C., U. Jahnke, M. Moi, and R. Koch. “Analyzing Product Lifecycle Costs for a Better 

Understanding of Cost Drivers in Additive Manufacturing.” Proceedings of the 2012 Solid Freeform 

Fabrication Symposium. 

<http://utwired.engr.utexas.edu/lff/symposium/proceedingsArchive/pubs/Manuscripts/2012/2012-12-

Lindemann.pdf>
40

achieve this, the products must meet quality and reliability standards and there must be 

testing standards in place to verify their performance. For instance, the U.S. Federal 

Aviation Regulations have strict regulations for material performance related to fatigue, 

creep, flammability, and toxicity. Manufacturers rely on standards in materials and 

processes to ensure the performance of their products.64 The dissimilarities between 

conventional manufacturing processes and those of additive manufacturing are likely to 

require modifications to current performance validation processes.65 Standards and codes 

organizations will likely play a significant role in facilitating the adoption of additive 

manufacturing technology.

Although this technology can produce nearly any complexity of geometry, it is limited in 

the size of the components that can be constructed. Expanding the size while maintaining 

a reasonable price point is likely to increase the rate at which this technology is adopted 

and expand the market opportunity. Additionally, the quality of the product is a limiting 

factor. Materials or surface finish, for instance, can often be inadequate for parts and 

components.

 64 National Academy of Engineering. “Frontiers of Engineering 2011: Reports on Leading-Edge 

Engineering from the 2011 Symposium.” In National Academy of Engineering’s 2011 U.S. Frontiers of 

Engineering Symposium. Mountain View, CA. 2012

65 Scott, Justin, Nayanee Gupta, Christopher Weber, Sherrica Newsome, Terry Wohlers, and Tim Caffrey. 

“Additive Manufacturing: Status and Opportunities”, March 2012. 

<https://www.ida.org/stpi/occasionalpapers/papers/AM3D_33012_Final.pdf>
41

7 Conclusion

There is a general concern that the U.S. manufacturing industry has lost competitiveness 

with other nations; however, industry data suggests that the U.S. still maintains a 

prominent position. Additive manufacturing may provide an important opportunity for 

advancing U.S. manufacturing while maintaining and advancing U.S. innovation. The

U.S. is currently a major user of additive manufacturing technology and the primary 

producer of additive manufacturing systems. Globally, an estimated $642.6 million in 

revenue was collected for additive manufactured goods, with the U.S. accounting for an 

estimated $246.1 million or 38.3 % of global production in 2011. Approximately 62.8% 

of all commercial/industrial units sold in 2011 were made by the top three producers of 

additive manufacturing systems: Stratasys, Z Corporation, and 3D Systems based out of 

the U.S. Approximately 64.4% of all systems were made by companies based in the U.S. 

If additive manufacturing has a saturation level between 5 % and 35 % of the relevant 

sectors, it is forecasted that it might reach 50 % of market potential between 2031 and 

2038, while reaching 100 % between 2058 and 2065, as seen in Table 5.1. The industry 

would reach $50 billion between 2029 and 2031, while reaching $100 billion between 

2031 and 2044. Since it is likely that additive manufacturing is at the far left tail of the 

diffusion curve, making it difficult to forecast the future trends, some caution should be 

used when interpreting these estimates.

Change agents for the additive manufacturing industry can focus their efforts on three 

primary areas: costs, rate at which benefits are realized, or the benefits of additive 

manufacturing. Costs have been identified as being a significant factor in whether 

producers adopt additive manufacturing technologies. Hopkinson66 estimates that 

machine costs range between 50 % and 75 % of total cost, materials range between 20 % 

and 40 %, and labor ranges between 5 % and 30 %. Reducing these costs may have a 

significant impact on the adoption of additive manufacturing technologies. Additionally, 

quality, performance validation, and expanding size capabilities are likely to also have 

significant impacts. 

 66 Hopkinson, Neil, “Production Economics of Rapid Manufacture.” In Hopkinson, Neil, Richard Hague, 

and Philip Dickens. Rapid Manufacturing. (Hoboken, NJ: John Wiley & Sons, 2006). 
42
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47

Appendix A: Schematic Data Map

The Annual Survey of Manufactures (ASM) is conducted every year except for years 

ending in 2 or 7 when the Economic Census is conducted. The ASM provides statistics 

on employment, payroll, supplemental labor costs, cost of materials consumed, operating 

expenses, value of shipments, value added, fuels and energy used, and inventories. It uses 

a sample survey of approximately 50 000 establishments with new samples selected at 5-

year intervals. An establishment is an economic unit—business or industrial—at a single 

physical location where business is conducted or where services or industrial operations 

are performed. The ASM data allows the examination of multiple factors (value added, 

payroll, energy use, and more) of manufacturing at a detailed subsector level. The 

Economic Census, used for years ending in 2 or 7, is a survey of all employer 

establishments in the U.S. that has been taken as an integrated program at 5-year intervals 

since 1967. Both the ASM and the Economic Census use NAICS classification; however, 

prior to NAICS the Standard Industrial Classification system was used. Table A.1 

contains items from the Annual Survey of Manufactures. The color scheme matches that 

of the color scheme in the manufacturing supply chains presented previously in this 

report.

Each supply chain item is calculated for the NAICS codes listed in Table 4.1 and added 

together by the categories listed in the table using data from the Annual Survey of 

Manufactures seen in Table A.2. The values for additive manufacturing seen in Table A.3

are calculated by assuming that the ratio of each supply chain item to the total value of 

shipments from the data in Table A.2 is the same for additive manufacturing. The ratios 

are then applied to data in the 2012 Wohlers Report. These assumptions have significant 

implications for precision; however, they are the best estimates available.
48

Table A.1: Supply Chain Components

ASM Data Item Schematic name

Number of employees Payroll, Benefits, and employment

Annual payroll Payroll, Benefits, and employment

Total fringe benefits Payroll, Benefits, and employment

Employer's cost for health insurance 

Employer's cost for defined benefit pension plans 

Employer's cost for defined contribution plans 

Employer's cost for other fringe benefits 

Production workers avg per year

Production workers hours (1,000)

Production workers wages 

Total cost of materials 

Materials, parts, containers, packaging, etc. used Materials, parts, containers, packaging, etc used

Cost of resales Contract work and resales

Contract work Contract work and resales

Cost of purchased fuels Purchased fuels and electricity

Purchased electricity Purchased fuels and electricity

Quantity of electricity purchased

Quantity of generated electricity 

Quantity of electricity sold or transferred 

Total value of shipments Shipments

Value of products shipments 

Total miscellaneous receipts 

Value of resales 

Contract receipts 

Other miscellaneous receipts 

Value of interplant transfers 

Value added Value added

Total EOY inventories 

Finished goods inventories, EOY Net Inventories Shipped

Work-in-process inventories, EOY Net Inventories Shipped

Materials and supplies inventories, EOY 

Total BOY inventories 

Finished goods inventories, BOY Net Inventories Shipped

Work-in-process inventories, BOY Net Inventories Shipped

Materials and supplies inventories, BOY 

Total capital expenditures (new and used) 

Capital expenditures: buildings & other structures (new and used) Capital expenditures: buildings and other structures (new and used)

Capital expenditures: machinery and equipment (new and used) 

Capital expenditures: autos, trucks, etc. for highway use Capital expenditures: machinery and equipment (new and used)

Capital expenditures: computer and data processing equipment Computer hardware, software, and other equipment

Capital expenditures: all other machinery and equipment Capital expenditures: machinery and equipment (new and used)

Total depreciation Depreciation

Total rental payments 

Buildings rentals Capital expenditures: buildings and other structures (new and used): Rental

Machinery rentals Capital expenditures: machinery and equipment (new and used): Rental

Total other expenses 

Temporary staff and leased employee expenses Other costs

Expensed computer hardware and other equipment Computer hardware, software, and other equipment

Expensed purchases of software Computer hardware, software, and other equipment

Data processing and other purchased computer services Professional, technical, and data services

Communication services Communication services

Repair and maintenance services of buildings and/or machinery Maintenance and repair

Refuse removal (including hazardous waste) services Refuse removal

Advertising and promotional services Other costs

Purchased professional and technical services Professional, technical, and data services

Taxes and license fees Other costs

All other expenses Other costs

Volume of Production=total costs (blue plus orange plus red plus green plus gold)

Net Inventories Shipped=sum of EOY finished goods and work-in-process inventories less the sum of BOY finished goods and work-in-process inventories
49

Table A.2: Total Supply Chain Values for Industries Relevant to Additive Manufacturing, $million 2011

Communication 

Services Other Costs

Refuse 

Removal

Computer 

Hardware, 

Software, and 

other 

Equipment

Professional, 

Technical, 

and Data 

Services

Payroll, Benefits, 

and Employment

 

Employment

Capital 

Expenditures: 

Buildings and 

Other 

Structures

Capital 

Expenditures: 

Machinery 

and 

Equipment

Materials, Parts, 

Containers, 

Packageing, etc. 

Used

Motor vehicles 167 14 995 391 542 1 408 47 238 651 2 345 10 686 307 489

Aerospace 155 7 682 177 689 3 142 34 987 333 1 323 2 515 65 064

Industrial/business machines 528 22 773 475 1 351 2 863 70 427 965 3 802 8 876 169 346

Medical/dental 151 8 903 123 477 1 409 21 533 290 1 230 1 850 22 633

Government/military 52 1 813 57 192 341 11 024 82 380 407 9 482

Architectural 121 4 823 101 226 494 17 631 302 1 090 1 469 32 747

Consumer products/electronics, 

academic institutions, and other

1 854 64 203 1 629 4 540 7 819 205 764 2 894 11 589 26 634 338 544

Total 3 028 125 192 2 952 8 016 17 477 408 603 5 516 21 760 52 437 945 304

Contract Work 

and Resales

Purchased 

Fuels and 

Electricity

Maintenance 

and Repair

Volume of 

Production

Net 

Inventories 

Shipped Depreciation Net Income Shipments

Value Added 

(ASM)

Additive 

Manufacturing's 

Share of 

Shipments

Motor vehicles 9 300 2 806 2 116 399 482 -1 108 9 695 37 220 445 289 126 751 0.021%

Aerospace 7 739 1 257 611 124 628 -5 920 2 181 36 812 157 701 90 216 0.036%

Industrial/business machines 20 494 2 704 2 218 305 856 -4 414 6 477 57 815 365 735 177 486 0.014%

Medical/dental 4 446 525 450 63 730 -17 1 987 23 819 89 519 61 932 0.079%

Government/military 3 386 221 117 29 132 -323 468 3 507 32 784 18 350 0.086%

Architectural 4 934 723 441 64 799 -408 1 458 6 338 72 187 34 162 0.019%

Consumer products/electronics, 

academic institutions, and other 48 869 9 592 6 319 726 410 -5 886 22 966 152 219 895 710 505 513 0.018%

Total 99 168 17 828 12 273 1 714 038 -18 076 45 234 317 730 2 058 926 1 014 411 0.023%
50

Table A.3: Supply Chain Values for Additive Manufacturing by Industry, $million 2011

Communication 

Services Other Costs

Refuse 

Removal

Computer 

Hardware, 

Software, and 

other 

Equipment

Professional, 

Technical, 

and Data 

Services

Payroll, 

Benefits, and 

Employment Employment

Capital 

Expenditures: 

Buildings and 

Other 

Structures

Capital 

Expenditures: 

Machinery 

and 

Equipment

Materials, Parts, 

Containers, 

Packageing, etc. 

Used

Motor vehicles 0.02 1.6 0.04 0.1 0.2 5.1 70 0.3 1.2 33.1

Aerospace 0.03 1.5 0.03 0.1 0.6 6.6 63 0.2 0.5 12.3

Industrial/business machines 0.04 1.7 0.03 0.1 0.2 5.1 70 0.3 0.6 12.3

Medical/dental 0.06 3.7 0.05 0.2 0.6 8.9 120 0.5 0.8 9.4

Government/military 0.02 0.8 0.03 0.1 0.2 5.0 37 0.2 0.2 4.3

Architectural 0.01 0.5 0.01 0.0 0.1 1.8 31 0.1 0.2 3.3

Consumer products/electronics, 

academic institutions, and other

0.17 5.9 0.15 0.4 0.7 19.0 267 1.1 2.5 31.3

Total 0.4 15.7 0.3 1.0 2.5 51.5 658.3 2.6 5.8 106.0

Contract Work 

and Resales

Purchased 

Fuels and 

Electricity

Maintenance 

and Repair

Volume of 

Production

Net 

Inventories 

Shipped Depreciation Net Income Shipments

Value Added 

(ASM)

Additive 

Manufacturing's 

Share of total 

Shipments

Motor vehicles 1.0 0.3 0.2 43.1 -0.1 1.0 4.0 48.0 13.7 0.01%

Aerospace 1.5 0.2 0.1 23.5 -1.1 0.4 7.0 29.8 17.0 0.02%

Industrial/business machines 1.5 0.2 0.2 22.2 -0.3 0.5 4.2 26.6 12.9 0.01%

Medical/dental 1.8 0.2 0.2 26.5 0.0 0.8 9.9 37.2 25.7 0.04%

Government/military 1.5 0.1 0.1 13.1 -0.1 0.2 1.6 14.8 8.3 0.05%

Architectural 0.5 0.1 0.0 6.6 0.0 0.1 0.6 7.4 3.5 0.01%

Consumer products/electronics, 

academic institutions, and other

4.5 0.9 0.6 67.1 -0.5 2.1 14.1 82.7 46.7 0.01%

Total 12.3 2.0 1.4 202.1 -2.3 5.2 41.3 246.1 127.7 0.01%
51

Appendix B: Equations and Assumptions

The approximations for U.S. additive manufacturing activity rely on the assumption that 

the U.S. share of additive manufacturing systems sold equates to the share of products 

produced using additive manufacturing systems. This is represented as the following:

RUS = SUS

SG

RG

Where:

RUS = Revenue for additive manufacturing activities in the U.S.

SUS = Cumulative number of additive manufacturing systems sold in the U.S. between 

1988 and 2001

SG = Cumulative number of additive manufacturing systems sold globally between 1988 

and 2001

RG = Revenue from the global sale of parts produced from additive manufacturing 

systems

Shipments of additive manufactured parts and products by category (see 

Table 4.1) was estimated by assuming that the percent of additive manufacturing that 

each category represents is the same for the U.S. as it is globally. The calculation is 

represented as the following:

RUS,x = RG,x

RG

RUS

Where:

RUS,x = U.S. revenue for additive manufacturing activities for category x

RG,x = Global revenue for additive manufacturing activities for category x

RG = Global revenue for additive manufacturing

RUS = Revenue for additive manufacturing activities in the US