NISTIR 8102

End-to-end Demonstration of the Quality 

Information Framework (QIF) Standard 

at the International Manufacturing 

Technology Show (IMTS) 2014

Hui-Min Huang

John Michaloski

Daniel Campbell

Robert Stone

Thomas Kramer

Curtis Brown

Robert Brown

Gavrail Tatarliev

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.IR.8102
NISTIR 8102

End-to-end Demonstration of the Quality 

Information Framework (QIF) Standard 

at the International Manufacturing 

Technology Show (IMTS) 2014 

Hui-Min Huang

John Michaloski

Intelligent Systems Division

Engineering Laboratory

Daniel Campbell

Metrosage LLC

Robert Stone

Original International Corp.

Thomas Kramer

Intelligent Systems Division

Engineering Laboratory

Curtis Brown

Honeywell Federal Manufacturing & 

Technologies, LLC

Robert Brown

Mitutoyo America Corporation

Gavrail Tatarliev

Kotem, Ltd.

This publication is available free of charge from:

http://dx.doi.org/10.6028/NIST.IR.8102

March 2016

U.S. Department of Commerce 

Penny Pritzker, Secretary

National Institute of Standards and Technology 

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

Abstract

The “Silos of Quality” in manufacturing can be described as the proliferation of

customized quality languages for different stages of production. This quality “Tower of 

Babel” results in excessive translations causing loss of information, reduction of features 

or capabilities, and/or translation errors. The Quality Information Framework (QIF) is a 

standard to solve the “Silos of Quality” problem in the discrete manufacturing industry.

Because of the history with quality frameworks that suffered from a lack of adoption, a 

QIF demonstration was given at International Manufacturing Technology Show (IMTS) in 

2014 to promote the fact that QIF is a suitable and excellent quality framework for 

manufacturers. This paper discusses modern production practices, and QIF basic 

concepts. It also details what QIF demonstrated at IMTS 2014. 

Notation

AIAG Automotive Industry Action Group

ANSI American National Standards Institute

AP Application Protocol

APQP Advanced Product Quality Planning

ASQ American Society for Quality

BoC Bill of Characteristics 

CAD Computer-Aided Design 

CMM Coordinate Measuring Machine

DME Dimensional Metrology Equipment

DMIS Dimensional Measurement Interface Standard

DML Dimensional Markup Language

DMSC Dimensional Metrology Standards Consortium

FAI First Article Inspection

GD&T Geometric dimensioning and tolerancing

IMTS International Manufacturing Technology Show

ISO International Organization for Standardization

KPC Key Product Characteristics

LOTAR LOng Term Archiving and Retrieval

MBD Model Based Definition

MBE Model Based Enterprise

NIST National Institute of Standards and Technology

PDF Portable Document Format

PMI Product and Manufacturing Information

PPAP Production Part Approval Process

QMD Quality Measurement Data

SPC Statistical Process Control

STEP Standard for the Exchange of Product model data

QIF Quality Information Framework

XML Extensible Markup Language

XSD XML Schema Definition Language
1

1 Background

The Quality Information Framework (QIF) is a standard to solve the “Silos of Quality” 

problem in the discrete manufacturing industry. The “Silos of Quality” describes 

manufacturing elements using an individualized quality language but having difficulty in 

communicating quality information to other manufacturing facets. This problem can be 

attributed to the lack of a universal quality model and a standard representation, so that 

every quality manufacturing dialect requires translation into another representation 

resulting in information loss, lack of features or capabilities, or translation errors. 

So why are “Silos of Quality” such a problem? Although factory-quality standards are 

available to manufacturers, acceptance has been negligible within the discrete parts 

industry. The problem is evident in previous standardization attempts – Dimensional 

Markup Language (DML) [1], Quality Measurement Data (QMD) [2], ISO 10303

Application Protocol (AP) 219 [3], etc. These standards have flaws such as incomplete 

models, narrowly-focused technology, poorly conceived design, or inadequacy in 

addressing fundamental manufacturers’ quality requirements. QIF addresses these 

issues from the onset, bringing a comprehensive approach with a design that ensures 

thorough attention to manufacturers’ quality requirements. The result is a seamless 

quality-integration standard – for the complete product-quality lifecycle. Plus, QIF is an 

open, royalty-free standard based on a de facto exchange standard – Extensible Markup 

Language (XML) [4] that makes use more affordable and acceptance easier.

Because it is a comprehensive quality standard, QIF enables seamless information 

exchange and sharing across the entire product lifecycle – inside or outside the 

enterprise. The measurement plans, measurement resources, etc., that are represented

using QIF could be used by multiple sets of equipment or products in-house. It is 

desirable for all internal inspection functions to be interoperable among themselves. In 

addition, quality-data incompatibility affects the company’s supply chain. QIF can ease

bidirectional flow of quality information. Thus, the information generated by a quality 

process using QIF is readily useable by another quality process that adopts QIF. So, 

standardized formats mean quality exchange is possible between any two enterprises 

that adopt QIF.

The lack of acceptance of previous quality frameworks causes manufacturers to be wary 

of yet another quality approach. A QIF demonstration was given at IMTS in 2014 to 

convince skeptics that QIF is a suitable and excellent quality framework for 

manufacturers. We demonstrated an inspection application of QIF to a completemeasurement lifecycle. This QIF demonstration involved using a CAD design annotated 

with quality information, measurement equipment to inspect the produced parts to 

ensure that the parts are within the design specification, and reporting for statistical 

analysis of the quality results.

This paper focuses on the seamless integration of QIF knowledge throughout the 

production lifecycle. Section 2 describes modern manufacturing concepts with an 

emphasis on quality. Section 3 presents QIF and gives a brief background on some of its 
2

significant features. Section 4 presents the QIF demonstration given at IMTS 2014. 

Section 5 presents a discussion of the impact, benefits, and shortcomings of QIF at this 

stage of its deployment. 

1 Quality Modeling

Two-dimensional product information has seen its capabilities far exceeded by threedimensional modeling and analysis systems. Yet 2D drawings still retain a dominant role 

as contracting documentation. As manufacturing evolves, 3D-digital representations 

offer a better strategy since they supply more thorough and precise product 

information. In this 3D world, Product-and-Manufacturing Information (PMI) is 

emerging as a valuable development, since it includes not only digital design, but also 

facilitates a thorough 3D-annotation environment of quality information. PMI conveys 

design attributes necessary for manufacturing product components and assemblies, 

including geometric dimensions and tolerances, 3D annotation (text) and dimensions, 

surface finish, and material specifications. With PMI, the association of quality 

information, e.g., tolerances or surface finish, is expressly part of the product definition.

It is the expression of quality-PMI information within the design phase that enables a 

universal representation of the product that can then be distributed and shared 

throughout the product-manufacturing lifecycle. 

To better facilitate PMI, manufacturers are adopting the digital thread [5] concept to 

promote a model-based enterprise (MBE). The MBE goal is to streamline the flow of 

product information - interconnecting and sharing as much product information in the 

enterprise and supply chain as possible. It has the potential to save money by improving 

efficiency and accuracy and offering feedback and feedforward into the product 

lifecycle. In MBE, product information flows between all aspects of manufacture –

design, fabrication, assembly, and inspection. Feedforward refers to the use of 

information for adaptive control of downstream systems in the product lifecycle, i.e. or 

“later” in the lifecycle. For example, feedforward PMI could incorporate design 

information during fabrication of a product. Feedback refers to the use of information 

for adaptive control of upstream systems in the product lifecycle, i.e. or “earlier” in the 

lifecycle. For example, feedback could use fabrication information upstream in a revised 

design of a product to simplify manufacture.

Although the QIF, PMI, and MBE approach has significant advantages in efficacy and

agility, a large portion of the manufacturing industry still uses drawing-based practices.

For inspection, a human-based procedure would have shop-floor-quality personnel 

reviewing the inspection reports to determine how the products compared to the 

functional requirements. As such, often, quality engineers get hard copy Portable 

Document Format (PDF) reports on the quality inspections, or else receive data 

produced from one of many different coordinate-measuring machines (CMM) that 

would have to be translated and/or interpreted before being represented in the reports.

The desirable situation newly enabled by QIF is to be able to take the digital CAD with 

associated PMI, provide manufacturers with measurement plans, and receive from the 
3

manufacturers the measurement results in a standardized format. Since the quality 

reports can represent a large amount of data from various inspection machines, the 

standard format allows easier integration. With easier integration, it is now possible to 

have detailed and comparative analysis, thorough report generation, and reduction of 

errors previously caused by data transformations. In the foreseeable future, it will be 

desirable to use QIF results for the remediation of failures. This will require a deeper 

understanding of the correlation of the QIF results and production processes.

Figure 1: Quality Process

Product design has advanced from drawing based to model based. So too, the quality

process has evolved. Figure 1 shows the basic steps in a quality process that involves 

inspection and measurement resources. These steps include:

• Define product – take in functional requirements of the product, and 

represent quality using tolerance standards

• Determine measurement requirements – decide what to measure: part 

features/characteristics based on product-quality requirements and 

manufacturing processes available to make the product;

• Define measurement – assign resources and use metrology knowledge (e.g., 

inspection rules) to meet measurement-accuracy constraints;

• Execute the measurement on appropriate dimensional-metrology equipment 

(DME);

• Analyze quality data and report results with the goal of improvement.

2 Quality Information Framework Standard Architecture

Applying standards is a common way of achieving interoperability and integration. QIF

Version 2.0 is an approved ANSI standard [6]. Quality practitioners who use QIF can

benefit from its standardized model format, which enables:

 Eliminating human involvement through computerized information exchange;

Customer Requirements Tolerance Standards Define Product Determine Measurement Reqauirements Product Model

Quality RequirementsManufacturing Processes

Measurement Scope (whats) PMI with Criticalities Define Measurement Process Execute Measurement Process Analyze & Report Evaluation Quality Data Results

Part Report And

Analysis Inspection Plan (whats & hows) Perform DME Program Control

QUALITY METROLOGY ENTERPRISE
4

 Minimizing quality information translation errors;

 Supporting quality requirements related to the part manufacture or part 

procurement, but excluding quality requirements related to buildings, 

equipment, distribution, handling, etc.;

 Having different computer systems communicate quality information.

QIF satisfies numerous customer-use-case requirements. For example:

1. QIF covers all of ASME Y14.5-1994 Geometric dimensioning and tolerancing

(GD&T) functionality and some of ASME Y14.5-2009 excluding much of the 

composite extensions [7];

2. QIF covers all of First-Article-Inspection Reporting AS9102b; [8]

3. QIF covers parts of ISO 1101.3 standard where GD&T overlaps with the ASME 

Y14.5 standard, but there are differences between the ISO and ASME 

standards; [9]

The QIF standard specifies a set of information models in the form of XML schemas [10].

QIF enforces standardization by requiring that all the XML instance files conform to the 

QIF schemas. Thus, every XML instance file can be parsed and validated using the QIF 

XML schema files. In addition, QIF contains code to ensure that XML references don’t 

refer to missing information, or don’t refer to wrong types of data. QIF is well 

documented; readers are referred to [11] for a complete overview.

Figure 2 shows the QIF architecture. At the core of the QIF architecture is the reusable 

QIF Library that contains definitions and components that are referenced by the 

application areas. This QIF Library contains multiple sets of basic information models, 

such as primitive types for PMI, primitive types for product description, geometry for 

product descriptions, topology for product description, traceability information, and 

units. Around the QIF library core, Figure 2 shows the six QIF application area 

information models: Model-Based Definition (MBD) (QIFProduct), Plans, Resources, 

Rules, Results, and Statistics. The “QIF Execution” model is, in the current version of QIF, 

a placeholder for future standardization and is now handled by the Dimensional 

Measurement Interface Standard (DMIS) standard [12]. The order of generation of QIF 

data generally proceeds clockwise around the diagram, beginning with QIF MBD and 

ending with QIF Statistics. Users of QIF are not required to implement the entire model

or to use a particular sequence of activities.
5

Figure 2: QIF Lifesaver Architecture: Library and Application

QIF assigns identifiers whenever schema instances are created for any measurement 

object that is to be referenced (feature, characteristic, rule, resource, etc.). When 

related information is in a single file, it is either nested hierarchically or connected using 

identifiers (ids) that are local to the file. When related information is in separate files, it 

is connected using a combination of local ids and QIF Persistent Identifiers (QPIds), 

which are universally unique. [13]

QIF also includes manufacturing and metrology traceability. Traceability items include:

 The product/part model: the CAD system that was used to create it, the 

designer, the version, etc.

 The quality enterprise: performing organization, product/part references such as 

order number and its assembly path (AsmPath, see QIF v. 2.0, MBD section 7.4).

 Inspection scope: detail or assembly as used in AS9102A first article inspection,

 Inspection mode: 100 %, full/fail, partial/fail, or to follow one of the industry 

practices such as advanced product quality planning (APQP), key product 

Model-Based

Definition

(CADz,

STEP AP242)

QIFStatistics

QIF-Results

QIFRules

Whats Hows

QIF-Plans

QIFExecution

(DMIS)

QIFResources QIF-MBD

(PDPMI)

QIF

Library

XML Schema
6

characteristics (KPC)1[14], and production part approval process (PPAP) that 

industry groups such as the Automotive Industry Action Group (AIAG) and the 

American Society for Quality (ASQ) use [14] [15].

 Adopted standard: such as ASME-Y14.5 [7].

 Additional information that helps traceability: e.g., security classification 

(unclassified, for official use only, trademarked, trade secret, patented, EU 

Restricted, etc.).

3 IMTS QIF Interoperability Demonstration

A QIF demonstration was given at the 2014 International Manufacturing Technology 

Show (IMTS). IMTS is the largest manufacturing technology show in North America. 

More than 2,000 companies exhibit and over 100,000 individuals visit IMTS, which is 

held every even-numbered year in Chicago, Illinois, USA. At IMTS 2014, an end-to-end 

QIF demonstration was given to show how interoperability in quality processes could be 

successfully achieved with QIF. A video presentation of the IMTS demonstration hosted 

by Ray Admire of Lockheed Martin is available and titled, “IMTS 2014 - DMSC 

Demonstrates New QIF 2.0”. [16]

At IMTS, the integrated demonstration involved 13 companies facilitated by National 

Institute of Standards and Technology (NIST) and Dimensional Metrology Standards 

Consortium (DMSC). The demonstration workflow is shown in Figure 3. NIST is not a 

quality vendor, but offered services to assist in the demonstration planning and logistics. 

DMSC is the umbrella organization that sponsors QIF and acquired IMTS booth space.

 

1 There are additional, similar practices such as key process parameters (KPPs) and critical-toquality items (CTQs) as the referenced society describes.
7

Figure 3: IMTS 2014 QIF Workflow

The quality-measuring device was the Renishaw Equator. The Renishaw Equator is a 

low-cost and high-speed comparative gauge for inspection of manufactured parts.

Figure 4 shows the Renishaw Equator used for measurement at IMTS 2014. All other 

commercial products were software applications even though some of the vendors have 

measurement devices.

Figure 4 Renishaw Equator

Figure 5 shows the widget selected for the IMTS demonstration. The “QIF Widget” was 

chosen for the IMTS demo because the design features that it contains are 

representative of a wide range of industry applications. With this part, the IMTS demo 

participants were able to simulate the types of features, datums, datum-reference 

frames, and tolerances that end users are accustomed to working with.
8

Figure 5: IMTS 2014 QIF Demonstration Part 

Outside the current scope of QIF is CAD/PMI, which produces a Model-based definition 

(MBD). MBD uses a digital-data format to define a product or part, in terms of geometry 

and topology. The topology defines boundaries for the geometrical objects and includes

topological items such as body, shell, face, edge, and vertex for modeling parts or 

products. For manufacturing purposes (fabrication or quality), the MBD definition must 

be rich enough to contain all the required information, including part geometry and 

quality-functional requirements (e.g., GD&T and surface finish).

A commercial CAD system produced by PTC (formerly Parametric Technology 

Corporation) was used to create a MBD for the widget. The MBD contained geometric 

features and tolerances, and PMI; similar to that specified in ASME14.41 [17] and STEP 

(Product data representation and exchange) [18].

3.1 MBD into QIF MBD

A quality design using a proprietary format, even one with MBD, would have resulted in 

extra work for the quality engineer, as she/he would need to translate this format to be 

compatible with all the quality-inspection steps. This would less of a problem if the CAD 

system output MBD into a QIF format. Even then, MBD to QIF format depends on some 

simplifying assumptions for success. For IMTS 2014, the MBD was assumed to exhibit 

the following properties:

CAD MBD

QIF

MBD

QIF

Resource

QIF

Plan

DMIS

Execution

QIF

Results

QIF

Statistic
9

1) PMI exists and the PMI includes the quality and tolerance information that 

metrology needs;

2) Such PMI quality information is represented as semantic PMI, that is, in a 

standard digital format, is software interpretable, and is related to feature(s);

3) Mapping of MBD design features into QIF inspection features is limited to 

basic manufactured features (e.g., simple holes, surfaces). 

4) The translated QIF inspection feature(s) retain 100 % of the MBD PMI intent.

At IMTS, Capvidia [19] demonstrated MBDVidia for PTC Creo, which converts native PTC 

Creo MBD models into QIF MBD retaining all semantic PMI, notes, metadata, and saved 

views. MBDVidia for PTC Creo also automatically recognizes and generates metrological 

features and characteristics so that several downstream processes can use the resulting 

QIF model. A metrological feature is a physical portion of a part such as a surface, pin, 

hole, or slot or its representation on drawings, in models, or in digital data files [7]. A 

metrological characteristic is a control placed on an element of a feature such as its size, 

location or form, which may be a specification limit, a nominal with tolerance, a feature 

control frame, or some other numerical or non-numerical control [11]. 

Similarly at IMTS, the PAS Technology Company demonstrated its “Inspection Lifecycle 

Management (ILM) Suite” product to extract information from a 2D print of a part 

definition (a large portion of the industry still uses this method) and convert printed 

matter into a QIF plan.

3.2 QIF Plan 

Given a MBD in QIF format, Honeywell Federal Manufacturing and Technologies (FM&T) 

developed and used a model-based application (FBTOL) [20] that performs a semantic 

tolerance analysis on piece-part models. For the IMTS demonstration, FBTOL performed 

the “Define Measurement Process” work activity by reading a model-based definition 

with PMI (i.e., QIF MBD), performing a quick tolerance-definition check, and then 

producing a high-level QIF Plan representing an inspection scope. This scope contains a 

list of the characteristics with measurement elements that need verification. This list is 

commonly known as the Bill of Characteristics (BoC) for manufacturing-quality 

consumption. The FBTOL tool checks the correctness of the semantics of the tolerance 

specification. FBTOL generally needs to achieve near a 100 % correct score for a

measurement plan to be confidently created. 

Such a BoC plan would include all the main plan elements, such as human-readable 

designators and universally unique ID’s, traceability back to part features, datum 

definitions, datum-reference frames, tolerances, and even other product information 

(e.g., grain sizes and colors). A graphical representation of the resulting BoC is shown in

Figure 6.

CAD MBD

QIF

MBD

QIF

Resource

QIF

Plan

DMIS

Execution

QIF

Results

QIF

Statistic
10

Figure 6 FBTOL graphic representation of the resulting BoC

Metrosage demonstrated its Pundit CMM simulation software at IMTS. Metrosage’s 

simulation software requires part geometry and GD&T—and the semantic link between 

the two of them. As mentioned, applying GD&T manually to a model can be protracted

and subject to human transcription and interpretation errors. For this reason, data 

standards that support semantic PMI, such as QIF, are quickly becoming a leading 

format for transmitting fully semantic GD&T information. Metrosage’s Pundit CMM is 

built upon QIF and supports the QIF MBD format as a standard feature.

3.3 Executing QIF Plan and Generating QIF Results 

The current version of QIF, 2.0, does not include an inspection-execution component.

An adjunct DMSC metrology standard, the DMIS-programming standard may be used as 

the inspection language for executing the measurement plan. AT IMTS, Origin 

International Corp. [21] demonstrated an implementation of the DMIS code using the 

Renishaw Equator, and measured a cylinder identified in the BoC. 

Origin recorded the quality-measurement results in QIF after the execution of the 

detailed QIF Plan. The QIF measurement results were matched with the respective 

features using the QPIds in the demonstration. QPIds are essential within QIF. For 

example, when Renishaw’s Equator product finished executing a measurement plan, 

Origin International’s software matched QPId with the part and machine information to 

produce specific QIFResults files, that were later used by multiple demonstration 

participants.

CAD MBD

QIF

MBD

QIF

Resource

QIF

Plan

DMIS

Execution

QIF

Results

QIF

Statistic
11

The Mitutoyo America Corporation MeasurLink tool [22] consumes a QIF plan and 

displays it onscreen during execution or simulation. MeasurLink combines real-time online data collection with real-time statistical-process-control (SPC) charts and analysis 

for operators, and with real-time quality control / supervisor reports and alerts. Since 

MeasurLink is designed for integrated networks, comprehensive quality information 

sharing with QIF is possible.

Metrosage LLC demonstrated its Pundit [23] tool, which uses Monte-Carlo-simulation 

techniques to calculate task-specific measurement uncertainty, for example, the 

uncertainty for the measurement of a diameter tolerance of a feature. Metrosage 

uncertainty simulation software used QIF as the source for its measurement data. Figure 

7 illustrates the information requirements for the tool to run an uncertainty simulation. 

All of these inputs are supported by QIF. Complex feature geometry can be taken from 

QIF MBD data, while prismatic geometry can also be taken from the feature section of

simple QIF Results or QIF Plans files. The GD&T for the geometry is defined within the 

QIF Library. Sampling patterns can be taken either from a QIF Plans instance file or from 

a QIF Results instance file. A manufacturing-error signature of previously manufactured 

parts can be calculated by looking at QIF Results data. The measurement systems can be 

implemented using the QIF Resources model that contains all the required fields needed 

for the uncertainty simulation. Without QIF, these data sources are typically defined in 

different formats and require special processing before being entered into Pundit.

Figure 7: Measurement uncertainty simulation

3.4 QIFResults 

At IMTS, several companies demonstrated products that used QIF results (InfinityQS, 

Innovalia Metrology, IPI Solutions Ltd., Origin International Inc., and Kotem Hungary 

Ltd.). These results have the benefit of being free from possible human-interpretation 

errors, accurately retaining the design intent, and enabling automatic-quality processes.

CAD MBD

QIF

MBD

QIF

Resource

QIF

Plan

DMIS

Execution

QIF

Results

QIF

Statistic
12

1. InfinityQS International [24] consumes QIF Results, which could be from CMM 

or other measurement systems. QIF Results were combined to produce graphs 

and to produce different types of information such as statistics, alarms, 

histograms, capability reports, and respective indications on the part graphics.

2. Innovalia Metrology [25] demonstrated importing QIF Results from various 

measurement resources, analyzing QIF Results, and then generating reports.

3. IPI Solutions Ltd. [26] demonstrated Visual-IPI software that generated FAI or 

PPAP reports, commonly required by quality engineers. In the demonstration, 

Visual-IPI read and interpreted a 2D PDF drawing (but could also have accepted 

a 3D QIF MBD) to identify all the characteristics that are then used in a FAI or 

PPAP template. QIF files were then read for results to populate the report 

template. Any errors that occurred, such as out-of-tolerance or missing data, 

could be identified in the report. The benefit of using QIF is also evident in that 

the software is no longer required to convert all individual quality data formats, 

thus avoiding the “Silos of Quality” problem discussed earlier. 

4. Origin International Inc. [21] demonstrated loading results for graphic reporting 

and analysis. Figure 8 shows a graphical screenshot of the Origin report and 

analysis from the IMTS demonstration.

Figure 8 Origin International Graphical User Interface for Reporting and Analysis

5. Finally, Kotem Hungary Ltd. [27] demonstrated its SmartProfile tool, which 

involved reading QIF Results along with QIF MBD and other related information 

and analyzed the resulting part. Again the “Silos of Quality” problem was

avoided as the SmartProfile tool only needed to understand one data format, 

QIF. Kotem’s customers would benefit from the company’s ability to apply the 
13

PMI onto the relevant features without extra effort, thus avoiding potential 

errors as a result of translation of an already entered proprietary electronic 

representation.

3.5 QIFStatistics 

At IMTS, Mitutoyo America demonstrated its MeasurLink SPC data-management tool 

[22] consuming a plan (derived from the MBD) and mapping it to a measurement device 

for execution and statistical processing. Included in the SPC-graphical analyses were

statistical properties such as Cp and Cpk for capability and Pp and Ppk for process 

capability. [28] [29]

3.6 QIFResults collection for analysis

At IMTS, System Insights demonstrated its Vimana [30] tool that leveraged MTConnect 

[31] to collect shop-floor-real-time data and analyzed the data for metrics such as 

productivity, downtime, tool wear, deviations from plan, and cycle time. MTConnect is

able to provide QIF data as an “asset”. [32] This quality integration expands the flow of 

production data into a complete spectrum accessible by any system using the 

MTConnect standard.

4 Discussion

QIF model-based metrology offers significant advantages over the traditional practices.

One benefit is that QIF can incorporate MBD as a digital thread throughout the product 

lifecycle. Another benefit is that QIF facilitates a software component/library approach

so users or adopters don’t need to implement the entire QIF functionality. In this case, 

downstream-quality tools can import QIF data, and modify QIF data, without concern 

for which upstream tool generated the data. Standardization also means opening 

hidden information that was unavailable and inaccessible otherwise.

From the perspective of smart manufacturing, QIF should enable interaction among all 

the production-quality activities. Interim-quality results could be provided to other 

interested processes. QIF-enabled quality-data accessibility furthers the trend toward

digital manufacturing and Industry 4.0. [33] Inspection results should be easier to 

evaluate and customize, so improvements can be first identified within the inspection 

process and then applied to manufacturing processes. This pervasive quality interaction 

would improve machining processes, which in turn would improve product quality. On 

an even broader scale, the quality results could be fed back to the product-design stage 

for improvement of the product design/definition.

Currently QIF is in an adoption stage. Early adopters and their vendors are using QIF to 

standardize on a comprehensive quality standard throughout their enterprise. The “Silos 

CAD MBD

QIF

MBD

QIF

Resource

QIF

Plan

DMIS

Execution

QIF

Results

QIF

Statistic
14

of Quality” problem undermining an enterprise’s quest for excellence is a major driver in 

this QIF deployment. As more and more implementations arise, the QIF standard will 

evolve and new requirements and challenges will be addressed. In fact, a QIF version 2.1 

is underway. QIF 2.1 covers significant LOng Term Archiving and Retrieval (LOTAR)

requirements with recent additions to QIF made for this requirement. [34] 

Disclaimer

Commercial equipment and software, many of which are either registered or 

trademarked, are identified in order to adequately specify certain procedures. In no 

case does such identification imply recommendation or endorsement by the National 

Institute of Standards and Technology, nor does it imply that the materials or 

equipment identified are necessarily the best available for the purpose.

5 References

[1] AIAG, "AIAG D-23-2009 Dimensional Mark Up Language (DML) Version 3," 

Automotive Industry Action Group (AIAG), Southfield, MI , 2009.

[2] AIAG , "Quality Measurement Data (QMD)," Automotive Industry Action Group’s 

(AIAG) , Southfield, MI, 2009.

[3] ISO, "AP 219," [Online]. Available: http://isotc213.ds.dk/jgohf/main/s20th%20plenary%20meeting/ISOTC213N0822_Liaison_Report_on_STEP.pdf. 

[Accessed 27 9 2015].

[4] The World Wide Web Consortium, "Extensible markup language (XML) 1.0 (Fourth 

edition)," 2006.

[5] E. Kraft, "Expanding the Digital Thread to Impact Total Ownership Cost," in NIST 

MBE Summit, Gaithersburg, MD, 2013. 

[6] ANSI, "Quality Information Framework, v. 2.0," American National Standards 

Institute (ANSI) , 2014.

[7] American Society of Mechanical Engineers, "ASME Y14.5-2009 Dimensioning and 

Tolerancing - Engineering Drawing and Related Documentation Practices," 2009.

[8] SME International, "AS9102 - Aerospace First Article Inspection Requirement 

Revision B," 6 10 2014. [Online]. Available: http://standards.sae.org/as9102b/. 

[Accessed 22 8 2015].

[9] ISO, "ISO 1101:2012 - Geometrical product specifications (GPS) -- Geometrical 

tolerancing -- Tolerances of form, orientation, location and run-out," International 
15

Organization for Standardization, 2012.

[10] W3C, "XML Schema Part 0: Primer Second Edition," 2004. [Online]. Available: 

http://www.w3.org/TR/2004/REC-xmlschema-0-20041028/. [Accessed 26 8 2015].

[11] DMSC, "ANSI/QIF Part 1–2014: Quality Information Framework (QIF) – An 

Integrated Model for Manufacturing Quality Information Part 1: Overview and 

Fundamental Principles Version 2.0," Dimensional Metrology Standards 

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