This program addresses measurements and standards necessary to develop and deploy advances in measurement science that will enable rapid design-to-product transformation; material characterization; in-process process sensing, monitoring, and model-based optimal control; performance qualification of materials, processes and parts; and end-to-end digital implementation of Additive Manufacturing (AM) processes and systems. Reducing the barriers to widespread implementation and use of AM, such as process variability, fabrication speed, part accuracy, surface quality, and material properties will be a main goal of the program. The program will develop: standardized material characterization methods, exemplar data and databases to accelerate the design and use of AM parts; process metrology, sensing and control methods and algorithms to maximize part quality and production throughput in AM; test methods, protocols, and reference data to reduce the cost and time to qualify AM materials, processes, and parts; and an information systems architecture, including metrics, information models, and validation methods to shorten the design-to-product cycle time in AM. It is anticipated that this programmatic effort will facilitate: accelerated proliferation of AM parts in high-performance applications benefiting from AM's unique capabilities; improved quality and throughput for AM; rapid qualification of AM materials and processes leading to better understanding of AM and more confidence in AM products used in industry; and streamlined design-to-product transformations leading towards more accessible AM technologies for small and medium-sized companies, increasing industrial competitiveness.
Program and Strategic Goal:
To develop and deploy measurement science that will enable rapid design-to-product transformation through advances in; material characterization; in-process process sensing, monitoring, and model-based optimal control; performance qualification of materials, processes and parts; and end-to-end digital implementation of Additive Manufacturing processes and systems.
What is the problem?
The U.S. produces approximately 18 percent of the world's manufactured goods and U.S. manufacturing accounts for about $6.5 trillion or 28 percent of national output.1,2 Manufacturing also represented about 16 percent of global GDP, 70 percent of global trade, and 45 million advanced economy jobs in 2010. A number of major trends are shaping the future of manufacturing. Among them are the increase in the variety of products and shorter product cycles required to meet customer needs; greater intelligence in product design and manufacturing; and growing importance of innovative products and services.
The President's Council of Advisors on Science and Technology (PCAST) in its 2011 report stated that the Federal Government can promote advanced manufacturing in the U.S. by focusing on three broad areas of opportunity: advancing new technologies, supporting shared infrastructure, and dramatically rethinking of manufacturing process3. Rapid design-to-product transformation as an enabler for U.S. innovation and industrial competitiveness promotes such rethinking using new technologies such as Additive Manufacturing (AM).
AM refers to a class of emerging technologies for producing highly-complex, customized components by building up materials to make objects based on a three-dimensional (3D) computer model, typically built layer upon layer. Parts are fabricated directly from an electronic file representing the 3D part design that is virtually sliced into many thin layers and sent to an AM system where the layers are built up in sequence into a complete part.
Over the past two decades, several AM processes and systems have been developed and their capabilities have grown significantly4– ranging from rapid prototyping of simple physical concept models to help in product design, to creation of one-of-a-kind patterns necessary for metal casting processes, and more recently to direct fabrication of functional end-use parts. While early AM systems produced parts primarily in polymer (plastic) materials, systems now exist that produce metal parts. Metal-based additive processes form parts by melting or sintering material in powder form until all layers are completed.
AM provides the agility needed to rapidly make innovative customized complex products and replacement parts that are not realizable by more traditional manufacturing technologies or are required to be produced in low volumes.5,6 It offers additional advantages, including reduced material waste, lower energy intensity, reduced time-to-market, and just-in-time production.
Several technical barriers exist, however, that prevent AM processes from reaching their full potential. The recent roadmapping activities for AM7,8,9 outline research recommendations in several areas to advance the industry and emphasize that the ability to achieve predictable and repeatable operations is critical. The issues with surface quality, part accuracy, fabrication speed, material properties, and computational requirements are significant barriers to and/or limitations for widespread implementation of AM processes throughout U.S. manufacturers. To mitigate these challenges, this program focuses on the problems associated with AM material characterization, real-time control of AM processes, qualification methodologies and system integration for AM.
Why is it hard to solve?
A key to overcoming the barriers to wide spread use of AM is to address the lack of measurement science10 for obtaining material and process data, converting that data into actionable knowledge, incorporating knowledge into operating models, and using those operating models to optimize AM processes and equipment to produce high quality mission critical parts. Developing this measurement and standards infrastructure for AM is challenging because:
Some large U.S. companies in aerospace, defense and biomedical fields have made strategic decisions to adopt AM technologies for their high-value complex part manufacturing. These early adopters spend significant resources and efforts to learn how to use these technologies, how to optimize them to meet their own production and legal requirements, and how to test the products made by these technologies to integrate them into their overall production. However, due to the lack of adequate measurement science, all these usually are accomplished by empirical trial-and-error procedures. Therefore, any simple modification in materials, design, or end use requires them to go through costly efforts for finding optimal solutions. As a result, all the knowledge and experience gained within a company are highly protected, preventing effective collaborations among interested parties to advance the technology. Such protective environment also causes a significant knowledge and capability gap between these large companies and the second and third tier suppliers. This gap is also filled with more trial-and-error type costly learning process.
To address these challenges, there are several programs in the US and elsewhere to stimulate collaboration among AM vendors and users to advance these technologies. America Makes11 in the U.S. is an example of such effort in collaborative R&D aiming to advance AM in the U.S. Similarly, Standardization in AM (SASAM) project12 in EU intends to drive the growth of AM and creating and supporting a standardization organization in the field of AM. Fraunhofer AM Alliance13 in Europe provides another collaborative, interdisciplinary environment to develop new rapid strategies, concepts, technologies, and processes to enhance the performance and competitiveness of small and medium-sized AM enterprises in Europe.
NIST’s mission is to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life. NIST’s role is to provide measurement science solutions to problems that hinder the progress of smart manufacturing. The focus of this program is on projects that support enabling infrastructural metrology and technology that are not attractive to commercial investment, yet offer significant leverage in a broad range of AM applications across a wide range of manufacturing sectors.
Further validating this role, industry and government agency participants at a recent workshop on “Challenges to Innovation in Advanced Manufacturing”14 called for NIST leadership in infrastructural R&D to enable agile manufacturing, including standards and measurements to support and accelerate 1) consistent and enhanced systems integration, 2) new capabilities for increased flexibility and automation in manufacturing processes to improve production systems, 3) new approaches to reduce manufacturing costs while improving product quality and reliability, and 4) advanced modeling and simulation to reduce production cycle times and allow U.S. manufacturers to rapidly and efficiently respond to changes in customer demand, foreign competition, or raw material availability. Participants at a recent Smart Manufacturing workshop held in Washington D.C.15 identified similar roles for NIST.
What is the new technical idea?
The program focuses on the lack of measurement science capabilities in four areas in AM: (1) material characterization, (2) real-time process control, (3) process and product qualification, and (4) systems integration.
In the area of characterization of AM materials, the program will extend existing standardized methods for characterizing metal powders and mechanical properties of metal parts to develop new AM-specific characterization methods to qualify and quantify the unique attributes of AM materials.
In the area of real-time AM process control, the program will focus on real-time measurements of process parameters such as melt-pool temperatures, material microstructure, part dimensions and surface finish. To study the AM process as well as to develop and implement measurement and control algorithms, a small-scale metal laser sintering platform will be developed as a test bed.
To reduce the need for extensive empirical testing to fully qualify AM processes and parts, this program will develop measurement science to support equivalence-based qualification and model-based qualification.
Finally, to improve the performance of AM systems, the program will develop standards to support consistent data exchange among AM modeling and simulation tools as well as validation and verification methods for integration and exchange of AM models and data.
Why can we succeed now?
There is a tide of nationwide (as well as global) interest in AM technologies as evidenced by significant investments by governments and industry, as well as unprecedented levels of participation in technical conferences and industrial events with AM focus. Collaboration among small and large companies as well as academia is increasing, promising innovative solutions to many of the AM challenges. The AM industry has recently realized the necessity of standards and performance metrics for continued growth, with new standards committees formed in 2009 with NIST participation to address the needs for additive manufacturing technologies.16
In parallel, academia has been producing young scientists and engineers with proper backgrounds in AM to contribute further developments. This program plans to leverage the expertise in academia to the fullest extent by funding cooperative research agreements, creating postdoctoral research opportunities, as well as hiring three new graduates with AM expertise.
What is the research plan?
The program focuses on four areas which are closely interrelated: (1) material characterization, (2) real-time process control, (3) process and product qualification, and (4) systems integration.
In the material characterization area, in order to extend the existing characterization methods for metal powders and mechanical properties of metal parts to AM materials and parts, the existing methods will be analyzed for applicability to AM and to the unique AM induced properties. In this process, dependence of AM part mechanical properties on the input powder properties will be empirically determined. Based on these analyses, new characterization methods for measuring properties of AM parts and powders will be developed. The program will then design and construct an AM materials database for high-fidelity material data and populate this database with exemplar data, garnered from round robin tests following the previously mentioned characterization methods.
In the real-time process control area, the program will first focus on innovative process metrology to provide traceable and quantitative data for validating process models, calibrating in-process sensors, and determining optimal process conditions. The program will establish metrics and test methods for assessing the performance of process metrology sensors and instruments. Validated physics-based models will be used to develop reduced-order analytical models for use in the development of real-time control algorithms. Both iterative open-loop control with post-process feedback and real-time closed-loop control approaches will be tested. Performance metrics for both types of control methods will be developed. To implement the real-time closed loop control algorithms, a small scale powder bed fusion testbed will be developed in collaboration with PML. This open architecture test bed will be used to incorporate various process metrology instruments and control systems as a validation platform.
In the process and product qualification area, the program will establish foundations for equivalence-based qualification of materials, processes, and parts used in AM by developing novel test methods and protocols for round robin testing, as well as generating trusted data for sharing among the AM stakeholders. To enable model-based qualification, validated process models are needed. The program will partner with industrial and academic researchers for developing high-fidelity multi-physics process models and provide them with trusted data to be used from model validation. Examples of trusted data include traceable emittance and temperature values of melt pool with known uncertainties. Validated temperature models will feed material models that predict AM material and part performance. Methods will be developed for integrating pre-process, in-process, and post-process measurements to demonstrate that a part will perform to specifications.
In the systems integration area, the program will address the end-to-end digital implementations of AM processes. Digital implementations will be systematically configured to replicate physical transformation processes with models and simulations. Informational transformations will be facilitated through standard interfaces. The program will develop and test a federated information systems architecture for AM. The architecture will specify the product requirements, the stages of the product realization process, and the interfaces needed to link those stages together. Common data structures and interfaces will be developed to enable streamlined integration of AM systems to lower the cost of development and use of these technologies.
How will teamwork be ensured?
The program involves staff from three EL divisions as well as from PML, MML, and NCNR. They have demonstrated effective team work during the execution of previous research activities in the area of AM. They have also established strong interactions with industrial partners, academia as well as other government agencies. These interactions will be strengthened and leveraged to deliver maximum impact to our stakeholders. Interactions and information sharing among the project teams will be facilitated through periodic formal and informal meetings, topical seminars, as well as utilization of IT infrastructure such as Sharepoint. In addition to periodic project meetings, biweekly project leaders' meetings are scheduled to share important developments among projects.
1 Manyika, J. et al, Manufacturing the Future: The Next Era of Global Growth and Innovation, McKinsey Global Institute, November 2012.
2 Thomas, D.S., The Current State and Recent Trends of the U.S. Manufacturing Industry, NIST Special Publication 1142, December 2012.
3 The President's Council of Advisors on Science and Technology, Ensuring American Leadership in Manufacturing, Report to the President, June 2011.
4 Wohlers Report 2010, Additive Manufacturing State of the Industry, Annual Worldwide Progress Report, http://www.wohlersassociates.com/
5 National Research Council, “Visionary Manufacturing Challenges for 2020,” 1998, National Academy Press, http://www.nap.edu/catalog.php?record_id=6314
6 National Academy of Engineering, Lawrence Rhoades, “The Transformation of Manufacturing in the 21st Century,” 2005, http://www.nae.edu/File.aspx?id=7297
7 Roadmap for Additive Manufacturing (RAM): Identifying the Future of Freeform Processing, March 2009, sponsored by National Science Foundation (NSF) and Office of Naval Research (ONR), http://wohlersassociates.com/roadmap2009.pdf
8 Measurement Science Roadmap for Metal-Based Additive Manufacturing, May 2013, sponsored by NIST
9 A Technology Roadmap for Additive Manufacturing, February 2013 (draft), produced for NAMII
10 Measurement science as used here includes fundamental metrology, performance metrics, test methods, reference artifacts and data, reference architectures, and critical technical inputs to standards
14 NIST Workshop, “Challenges to Innovation in Advanced Manufacturing: Industry Drivers and R&D Needs,” November 3-4, 2009, Gaithersburg, MD.
15 Implementing 21st Century Smart Manufacturing, CTO-CXO Leadership Workshop, Washington, D.C., Sep. 14-15, 2010, http://smart-process-manufacturing.ucla.edu/workshops/2010. 16ASTM International, Technical Committee F42, Additive Manufacturing Technologies, http://www.astm.org/COMMIT/COMMITTEE/F42.htm
Start Date:October 1, 2013
Lead Organizational Unit:el
Related Programs and Projects:
Alkan Donmez, Program Manager
301 975 6618 Telephone
100 Bureau Drive, M/S 8230