Qualification and certification routes for additive manufacturing of mass produced metal components

Various strategic efforts have been conducted to develop AM [1,2] and define qualification and certification needs [3,4]
Yet, a current lack of standardised measurements science and protocols impedes the wider acceptance of industrial AM. Few companies can afford to develop their own internal foundations for qualification of materials, processes, and parts built with AM [5]. 

​There are generally three different paths to qualification [6]:

• Statistically-based qualification, based on extensive and expensive empirical testing;
• Equivalence-based qualification, achieved through moderate testing to demonstrate a new material or process is equivalent to a previously qualified material or process;
• Model-based qualification, where a material’s or process’ performance is demonstrated in a computer model and demonstrated with minimal testing.

​Statistical qualification processes for metallic materials require extensive testing that may cost millions of dollars and take up to 15 years to complete [7].The uncertainty in the production of a particular component is understood and mitigated by massive upfront testing, followed by ongoing quality control testing during production. It is very similar to the procedure that has long been used for aerospace castings [8] where deviations from the qualified procedure triggers a re-qualification process. The high cost in time and money encourage companies to keep the results data proprietary.

​Model based qualification requires a smaller number of tests to validate the model. However, developing reliable physics-based models is difficult given the rapid and complex nature of phenomena occurring in AM processes at the fundamental level. Predicting reproducible behaviour over a large set of parameters and materials is challenging. In addition, the proprietary process controls found in commercial AM machines drastically reduces the amount of data needed to calibrate and validate these theoretical models.

Selective laser melting

GE9X T25 Sensor [9-10]

​General Electric (GE) received Federal Aviation Administration (FAA) certification for fuel nozzle implementation in the GE LEAP engine, and GE Aviation will produce more than 100,000 3D-printed parts via laser-based powder bed AM by 2020 [9-11]. AM replaced complex brazing of multiple components to create a lighter, simpler, and more durable product.
GE [12] demonstrated the successful certification of GE9X T25 Sensor and the LEAP Fuel Nozzle without the need for new qualification standards.

GE LEAP fuel injector [10,11]

Direct laser deposition

​For components or repairs produced by direct deposition of Ti6Al4V, AMS standard 4999 A78 [13,14] prescribes feedstock and production conditions. Minimum tensile and fracture toughness properties are also defined. So are standardized testing procedures for each production run as well as re-test and rejection criteria.

The standard also suggests a three-stage qualification route:

1. source qualification;
2. approval of deposition or deposition/geometry parameters, with mechanical test samples produced to cover the processing space and geometrical parameters;
3. production qualification by destructive testing. 

​Upon qualification, each of the production parameters is fixed, with any deviations requiring additional testing. 

This procedure is best suited for serial production of numerous identical parts. For the production of customized, repair, and low-volume components, where AM techniques are often most desirable, a qualify-as-you-build scheme [15] that encompass pre-process, in-process, and post-process data should be used to validate part quality.

References
1. D.L. Bourell, M.C. Leu, and D.W. Rosen, Roadmap for Additive Manufacturing: Identifying the Future of Freeform Processing (2009).
2. C.B. Williams, T.W. Simpson, and M. Hripko, NIST Technical Note 1823—Additive Manufacturing Technical Workshop Summary Report (2013).
3. Energetics Incorporated, Measurement Science Roadmap for Metal-Based Additive Manufacturing—Workshop Summary Report (2013).
4. J.M. Waller, B.H. Parker, K.L. Hodges, E.R. Burke, J.L. Walker, and E.R. Generazio, Nondestructive Evaluation of Additive Manufacturing State-of-the-Discipline Report,(2014)
5. M. SEIFI, A SALEM, J BEUTH, O HARRYSSON, and J J. LEWANDOWSKI,  Overview of Materials Qualification Needs for Metal Additive Manufacturing JOM, Vol. 68, No. 3, 2016
6 http://www.nist.gov/el/isd/sbm/qammpp.cfm
7. C.A. Brice, Proceedings of the 1st World Congress on Integrated
Computational Materials Engineering, ICME (2011),
pp. 241–246.
8. J.E. Duven, Advisory Circular 25.621-1: Casting Factors
(2014), pp. 1–11.
9. http://www.gereports.com/post/116402870270/the-faa-cleared-the-first-3d-printed-part-to-fly/
10. http://www.gereports.com/post/91763815095/worlds-first-plant-to-print-jet-engine-nozzles-in/
11. http://www.cfmaeroengines.com/press/cfm-leap-1a-achieves-joint-easa-faa-certification/830
12. D.H. Abbott, SAE Specification Summit (2015).
13. http://www.asminternational.org/documents/10192/17000225/amp17202p18.pdf/d6753a69-4180-4b37-9bde-74c16ffc0580/17001408
14. http://standards.sae.org/ams4999/
15. http://www.nist.gov/el/isd/sbm/qammpp.cfm