Qualification and characterization of metal additive manufacturing

155 Pages·2016·13.89 MB·English

Qualification and Characterization of Metal Additive
Manufacturing
by
Andrew James Byron
B.S. Chemical Engineering, University of Maine, 2009
Submitted to the MIT Sloan School of Management and the Department of Aeronautics
and Astronautics in partial fulfillment of the requirements for the degrees of
Master of Business Administration
and
Master of Science in Aeronautics and Astronautics
in conjunction with the Leaders for Global Operations Program at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
June 2016
@ Andrew James Byron, MMXVI. All rights reserved.
The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic
copies of this thesis document in whole or in part in any medium now known or hereafter created.
Signature redacted
Signature of Authoiol ........................
MIT Sloan School ofM'anagement, Department of Aeronautics and Astronautics
May 6, 2016
Signature redacted
C ertified by ...................,T... ........................................................
Dr. Steven D. Eppinger, Thesis Supervisor
General Motors LGO Professor of Management, MIT Sloan School of Management
Signature redacted
C ertified by ........... ....................................................................
Brian L. Wardle, Thesis Supervisor
Professor of Aeronautics and Astronautics
S nature
.....................
Accepted by ...........
Maura Herson, Director of MIT Sloan MBA Program
MIT Sloan School of Management
Signature redacted
Accepted by.....Paulo
C. Lozano
MASSACHUSTS INSTITUTE Associate Professor of Aeronautics and Astronautics
OF TECHNOLOGY
Chair, Graduate Program Committee
JUN 0 8 2016
LIBRARIES
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Qualification and Characterization of Metal Additive
Manufacturing
by
Andrew James Byron
Submitted to the MIT Sloan School of Management and the Department of Aeronautics
and Astronautics on May 6, 2016, in partial fulfillment of the requirements for the degrees
of
Master of Business Administration
and
Master of Science in Aeronautics and Astronautics
Abstract
Additive manufacturing (AM) has emerged as an effective and efficient way to digitally man-
ufacture complicated structures. Raytheon Missile Systems seeks to gain limited production
capability with metals AM, which can only be achieved with qualified, predictable processes
that reduce variation. The project documented in this thesis produced two results needed
to qualify AM for use on flight-critical parts: i) creation of a standard qualification process
building upon Raytheon's product development knowledge, and ii) selection and identifica-
tion of key metals AM process factors and their corresponding experimental responses.
The project has delivered a qualification test plan and process that will be used next
year to drive adoption and integration of Raytheon's metals AM technology. The first phase
of the designed experiment on AM process factors was completed by experimenting with
coupon orientation, position on the build platform, coupon shape and hot isostatic pressing
(HIP) post-treatment for an Al alloy (AlSil0Mg) produced via laser powder bed fusion using
400-watt laser equipment. Only coupon orientation had a statistically significant effect
on dimensional accuracy, increasing the variance of y-axis (within the build plane) error
by ~50%, although this is considered a small increase. HIP decreased yield and ultimate
stresses by ~60% while increasing ultimate strain by ~250%. Vertical orientation of coupons
decreased yield and ultimate stresses by ~25% and increased ultimate strain by ~30%. Small
coupon area on the build platform, associated with thin rectangle coupons, decreased yield
stress and ultimate strain by ~5%. The processes and case study from this thesis represent
a general advance in the adoption of metals AM in aerospace manufacturing.
Thesis Supervisor: Dr. Steven D. Eppinger
Title: General Motors LGO Professor of Management, MIT Sloan School of Management
Thesis Supervisor: Brian L. Wardle
Title: Professor of Aeronautics and Astronautics
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Acknowledgments
I would like to give my thanks to all of the excellent people I worked with at many differ-
ent divisions of Raytheon during my project. My supervisors Manny Gamez and Tim Buss
were instrumental in shaping the direction of the project, while Teresa Clement provided
invaluable insight on operations at Raytheon as well as connecting me with anyone I needed
to know in Tucson. I could not have completed this work without the process qualification
project team of Manny Rodriguez, Viviana Aguero and Mark Middlestadt or the review
team of Heather Adams, Blake Bradford and Bryan Bergsma. I am indebted to the team
at Raytheon Precision Machining who partnered with me and executed on my experimental
vision, including Leah Hull, Bob Steffen, Judy Gill, Rosemarie Wickett and others. I owe
my success as a Raytheon intern to the logistical support of Shawn Cash, Trevor Schwartz
and Kim Ernzen. I will miss my temporary home in the MTE group filled with excellent
industrial engineers like Jack Lusk, Stephanie Mula and John Bares.
In addition, I had incredible support from faculty and staff at MIT. Dr. Steven Eppinger
and Dr. Brian Wardle provided guidance and advice from the earliest stages and continu-
ously sought to improve my work. The LGO staff made my two years as easy and successful
as possible and I enjoyed the multiple opportunities to work with Ted Equi and Patricia
Eames, in particular. I must also thank the program collaboration between both the MIT
Sloan School and the Department of Aeronautics and Astronautics that made my education
possible.
Finally, I cannot forget the love and support I received from family and friends through-
out my two years at LGO. Every car ride and free lunch was remembered and appreciated.
I owe LGO a debt of gratitude for introducing me to my fiancee Xiaodi and I thank her for
putting up with my homework complaints from three time zones away. Much love to my
family (as big as it is), my friends before LGO and my 49 new, amazing friends in the class
of 2016. I couldn't have done this without them, and I have no doubt they will go on to
change the world.
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Contents
1 Introduction 17
1.1 Purpose of Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
1.3 Problem Approach and Hypothesis . . . . . . . . . . . . . . . . . . . . . . . 19
1.4 Thesis Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2 Literature Review 21
2.1 Manufacturing Readiness Levels and Applications . . . . . . . . . . . . . . . 21
2.2 State of Metal AM Processes in Industry . . . . . . . . . . . . . . . . . . . . 23
2.2.1 Overview of Metal AM . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.2 Econom ics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.2.3 Competitor Research . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.3 Ongoing Research in Metal AM Qualification . . . . . . . . . . . . . . . . . . 30
2.3.1 Experimental Design . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.3.2 Material and Post-Processing . . . . . . . . . . . . . . . . . . . . . . 32
2.3.3 Process Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3 Advanced Metal Manufacturing at Raytheon 37
3.1 Background on Company . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.2 Overview on Advanced Metal Manufacturing . . . . . . . . . . . . . . . . . . 38
3.3 Metal Additive Manufacturing Progress . . . . . . . . . . . . . . . . . . . . . 39
3.4 Need for Metal Additive Manufacturing . . . . . . . . . . . . . . . . . . . . . 41
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4 Methodology 47
4.1 Data Collection Methods . . . . . . . . . . . . . . . . . . 47
4.2 Development of Qualification Plan . . . . . . . . . . . . . 48
4.3 Design of Experiment for AM Process Parameters . . . . 48
4.4 Key Performance Metrics . . . . . . . . . . . . . . . . . . 49
5 Additive Manufacturing Qualification Process 51
5.1 Overview of Qualification Process Map . . . . . . . . . . . . . . . . . . . . . 51
5.2 Process Capability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
5.2.1 Material Characterization . . . . . . . . . . . . . . . . . . . . . . . . 53
5.2.2 Equipment Qualification . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.2.3 NDE Qualification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.3 Design Feasibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.3.1 Part Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.3.2 Part Build Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.3.3 Proof Parts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
5.3.4 Preliminary Statistical Characterization . . . . . . . . . . . . . . . . 72
5.4 integration, Verification & Validation (IV&V) . . . . . . . . . . . . . . . . . 73
5.4.1 Statistical Sample Testing . . . . . . . . . . . . . . . . . . . . . . . . 73
5.4.2 Inspection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
5.4.3 Process Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
5.5 Assessment of MRL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6 Experimentation on AM Parameters 79
6.1 Experimental Approach . . . . . . . . . . . . . . . . . . 79
6.1.1 Identification of Potential Responses . . . . . . . 80
6.1.2 Identification of Potential Factors . . . . . . . . . 81
6.1.3 Selection of Experimental Factors and Responses 83
6.2 Experimental Design Development . . . . . . . . . . . . 85
6.2.1 Hypotheses . . . . . . . . . . . . . . . . . . . . . 85
6.2.2 Experiment Type Selection . . . . . . . . . . . . . 86
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6.2.3 Factor Level Descriptions . . . . . . . . . . . . . . . . . . . . . . . . 8 9
6.2.4 Experiment Design Evaluation . . . . . . . . . . . . . . . . . . . . . . 9 1
6.3 Experimental Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3
6.4 Discussion of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 8
6.4.1 Dimensional Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . 9 9
6.4.2 Surface Roughness . . . . . . . . . . . . . . . . . . . . . . . . .. . . . 1 0 3
6.4.3 Mechanical Properties..... . . . . . . . . . . . . . . . . . . . . . 1 0 4
7 Conclusions & Recommendations 113
7.1 Qualification Process ............... 113
7.2 Experimental Results ............... 114
7.3 Suggestions for Immediate Implementation 115
7.4 Long-Term Goals . . . . . . . . . . . . . . 116
A Material Properties Assessment 125
B Defect Criteria 127
C Factorial Experiment Examples 129
D Test Matrix 133
E Dimensional Accuracy and Surface Roughness Data Analysis Tables and
Figures 137
F Mechanical Properties Data Analysis Tables and Figures 149
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