Abstract

As additive manufacturing (AM) usage increases, designers who wish to maximize AM’s potential must reconsider the traditional manufacturing (TM) axioms they may be more familiar with. While research has previously investigated the potential influences that can affect the designs produced in concept generation, little research has been done explicitly targeting the manufacturability of early-stage concepts and how previous experience and the presenting of priming content in manufacturing affect these concepts. The research in this paper addresses this gap in knowledge, specifically targeting differences in concept generation due to designer experience and presenting design for traditional manufacturing (DFTM) and design for additive manufacturing (DFAM) axioms. To understand how designers approach design creation early in the design process and investigate potential influential factors, participants in this study were asked to complete a design challenge centered on concept generation. Before this design challenge, a randomized subset of these participants received priming content on DFTM and DFAM considerations. These participants’ final designs were evaluated for both traditional manufacturability and additive manufacturability and compared against the final designs produced by participants who did not receive the priming content. Results show that students with low manufacturing experience levels create designs that are more naturally suited for TM. Additionally, as designers’ manufacturing experience levels increase, there is an increase in the number of designs more naturally suited for AM. This correlates with a higher self-reported use of DFAM axioms in the evaluation of these designs. These results suggest that students with high manufacturing experience levels rely on their previous experience when it comes to creating a design for either manufacturing process. Lastly, while the manufacturing priming content significantly influenced the traditional manufacturability of the designs, the priming content did not increase the number of self-reported design for manufacturing (DFM) axioms in the designs.

References

1.
Attaran
,
M.
,
2017
, “
The Rise of 3-D Printing: The Advantages of Additive Manufacturing Over Traditional Manufacturing
,”
Bus. Horiz.
,
60
(
5
), pp.
677
688
.
2.
Durakovic
,
B.
,
2018
, “
Design for Additive Manufacturing: Benefits, Trends and Challenges
,”
Period. Eng. Nat. Sci.
,
6
(
2
), pp.
179
191
.
3.
Prabhu
,
R.
,
Miller
,
S. R.
,
Simpson
,
T. W.
, and
Meisel
,
N. A.
,
2020
, “
Teaching Design Freedom: Understanding the Effects of Variations in Design for Additive Manufacturing Education on Students’ Creativity
,”
ASME J. Mech. Des.
,
142
(
9
), p.
094501
.
4.
Prabhu
,
R.
,
Miller
,
S. R.
,
Simpson
,
T. W.
, and
Meisel
,
N. A.
,
2020
, “
Exploring the Effects of Additive Manufacturing Education on Students’ Engineering Design Process and Its Outcomes
,”
ASME J. Mech. Des.
,
142
(
4
), p.
042001
.
5.
Yang
,
S.
,
Page
,
T.
, and
Zhao
,
Y. F.
,
2019
, “
Understanding the Role of Additive Manufacturing Knowledge in Stimulating Design Innovation for Novice Designers
,”
ASME J. Mech. Des.
,
141
(
2
), p.
021703
.
6.
Starkey
,
E.
,
Toh
,
C. A.
, and
Miller
,
S. R.
,
2016
, “
Abandoning Creativity: The Evolution of Creative Ideas in Engineering Design Course Projects
,”
Des. Stud.
,
47
, pp.
47
72
.
7.
Lamb
,
R.
,
Akmal
,
T.
, and
Petrie
,
K.
,
2015
, “
Development of a Cognition-Priming Model Describing Learning in a STEM Classroom
,”
J. Res. Sci. Teach.
,
52
(
3
), pp.
410
437
.
8.
Jung
,
Y.
,
Kim
,
Y.
, and
Murphy
,
J.
,
2017
, “
The Role of Task Repetition in Learning Word-Stress Patterns Through Auditory Priming Tasks
,”
Stud. Second Lang. Acquis.
,
39
(
2
), pp.
319
346
.
9.
Sanders
,
E. B.-N.
,
Brandt
,
E.
, and
Binder
,
T.
,
2010
, “
A Framework for Organizing the Tools and Techniques of Participatory Design
,”
PDC'10: Proceedings of the 11th Biennial Participatory Design Conference
,
Sydney, Australia
,
Nov. 29–Dec. 3
, pp.
195
198
.
10.
Liao
,
T.
, and
MacDonald
,
E. F.
,
2021
, “
Priming on Sustainable Design Idea Creation and Evaluation
,”
Sustainability
,
13
(
9
), p.
5227
.
11.
Viswanathan
,
V. K.
, and
Linsey
,
J. S.
,
2013
, “
Design Fixation and Its Mitigation: A Study on the Role of Expertise
,”
ASME J. Mech. Des.
,
135
(
5
), p.
051008
.
12.
Liu
,
Y.-C.
,
Chakrabarti
,
A.
, and
Bligh
,
T.
,
2003
, “
Towards an ‘Ideal’ Approach for Concept Generation
,”
Des. Stud.
,
24
(
4
), pp.
341
355
.
13.
Parnes
,
S. J.
, and
Meadow
,
A.
,
1959
, “
“Effects of” Brainstorming” Instructions on Creative Problem Solving by Trained and Untrained Subjects
,”
J. Educ. Psychol.
,
50
(
4
), pp.
171
176
.
14.
Li
,
Y.
,
Wang
,
J.
,
Li
,
X.
, and
Zhao
,
W.
,
2007
, “
Design Creativity in Product Innovation
,”
Int. J. Adv. Manuf. Technol.
,
33
(
3–4
), pp.
213
222
.
15.
Cross
,
N.
,
2004
, “
Expertise in Design: An Overview
,”
Des. Stud.
,
25
(
5
), pp.
427
441
.
16.
Ahmed
,
S.
,
Wallace
,
K. M.
, and
Blessing
,
L. T.
,
2003
, “
Understanding the Differences Between How Novice and Experienced Designers Approach Design Tasks
,”
Res. Eng. Des.
,
14
(
1
), pp.
1
11
.
17.
Daly
,
S. R.
,
Yilmaz
,
S.
,
Christian
,
J. L.
,
Seifert
,
C. M.
, and
Gonzalez
,
R.
,
2012
, “
Design Heuristics in Engineering Concept Generation
,”
J. Eng. Educ.
,
101
(
4
), pp.
601
629
.
18.
Ratcliff
,
R.
, and
McKoon
,
G.
, “
A Retrieval Theory of Priming in Memory
,”
Psychol. Rev.
,
95
(
3
), pp.
385
408
.
19.
Tulving
,
E.
, and
Schacter
,
D. L.
,
1990
, “
Priming and Human Memory Systems
,”
Science
,
247
(
4940
), pp.
301
306
.
20.
Schacter
,
D. L.
, and
Buckner
,
R. L.
,
1998
, “
Priming and the Brain
,”
Neuron
,
20
(
2
), pp.
185
195
.
21.
Bonnardel
,
N.
, and
Marmèche
,
E.
,
2004
, “
Evocation Processes by Novice and Expert Designers: Towards Stimulating Analogical Thinking
,”
Creat. Innov. Manag.
,
13
(
3
), pp.
176
186
.
22.
Yilmaz
,
S.
,
Christian
,
J. L.
,
Daly
,
S. R.
,
Seifert
,
C.
, and
Gonzalez
,
R.
,
2012
, “
How Do Design Heuristics Affects Outcomes?
,”
International Design Conference – Design 2012
,
Dubrovnik, Croatia
,
May 21–24
, pp.
1195
1204
.
23.
Atatreh
,
S.
,
Alyammahi
,
M.
,
Susantyoko
,
R. A.
,
Ismail
,
H.
, and
Mohammed
,
A.
,
2021
, “
Innovative Approaches to Enhance Awareness on Additive Manufacturing in Engineering Education Towards Competencies for Industry 4.0
,”
Volume 9: Engineering Education
,
Virtual, Online
,
American Society of Mechanical Engineers
, p.
V009T09A038
.
24.
Lauff
,
C. A.
,
Perez
,
K. B.
,
Camburn
,
B. A.
, and
Wood
,
K. L.
,
2019
, “
Design Principle Cards: Toolset to Support Innovations With Additive Manufacturing
,”
Volume 4: 24th Design for Manufacturing and the Life Cycle Conference; 13th International Conference on Micro- and Nanosystems
,
Anaheim, CA
,
American Society of Mechanical Engineers
, p.
V004T05A005
.
25.
Laverne
,
F.
,
Segonds
,
F.
,
Anwer
,
N.
, and
Le Coq
,
M.
,
2015
, “
Assembly Based Methods to Support Product Innovation in Design for Additive Manufacturing: An Exploratory Case Study
,”
ASME J. Mech. Des.
,
137
(
12
), p.
121701
.
26.
Perez
,
A.
,
Hölttä-Otto
,
K.
, and
Wood
,
K.
,
2015
, “
Crowdsourced Design Principles for Leveraging the Capabilities of Additive Manufacturing
.”
International Conference on Engineering Design, ICED15
,
Milan, Italy
,
July 27–30
, pp.
1
10
.
27.
Lough
,
K. G.
,
Stone
,
R.
, and
Tumer
,
I. Y.
,
2009
, “
The Risk in Early Design Method
,”
J. Eng. Des.
,
20
(
2
), pp.
155
173
.
28.
Yilmaz
,
S.
, and
Seifert
,
C. M.
,
2010
, “
Cognitive Heuristics in Design Ideation
,”
DS 60: Proceedings of DESIGN 2010, the 11th International Design Conference
,
Dubrovnik, Croatia
,
May 17–20
, pp.
1007
1016
.
29.
Blösch-Paidosh
,
A.
, and
Shea
,
K.
,
2019
, “
Design Heuristics for Additive Manufacturing Validated Through a User Study
,”
ASME J. Mech. Des.
,
141
(
4
), p.
041101
.
31.
Blösch-Paidosh
,
A.
,
Ahmed-Kristensen
,
S.
, and
Shea
,
K.
,
2019
, “
Evaluating the Potential of Design for Additive Manufacturing Heuristic Cards to Stimulate Novel Product Redesigns
,”
Volume 2A: 45th Design Automation Conference
,
Anaheim, CA
,
American Society of Mechanical Engineers
, p.
V02AT03A036
.
32.
Watschke
,
H.
,
Bavendiek
,
A.-K.
,
Giannakos
,
A.
, and
Vietor
,
T.
,
2017
, “
A Methodical Approach to Support Ideation for Additive Manufacturing in Design Education
,”
DS 87-5 Proceedings of the 21st International Conference on Engineering Design (ICED 17) Vol 5: Design for X, Design to X
,
Vancouver, Canada
,
Aug. 21–25
, pp.
041
050
.
33.
Floriane
,
L.
,
Frédéric
,
S.
,
Gianluca
,
D.
, and
Marc
,
L. C.
,
2017
, “
Enriching Design With X Through Tailored Additive Manufacturing Knowledge: A Methodological Proposal
,”
Int. J. Interact. Des. Manuf.
,
11
(
2
), pp.
279
288
.
34.
Prabhu
,
R.
,
Leguarda
,
R. L.
,
Miller
,
S. R.
,
Simpson
,
T. W.
, and
Meisel
,
N. A.
,
2021
, “
Favoring Complexity: A Mixed Methods Exploration of Factors That Influence Concept Selection When Designing for Additive Manufacturing
,”
ASME J. Mech. Des.
,
143
(
10
), p.
102001
.
35.
Prabhu
,
R.
,
Miller
,
S. R.
,
Simpson
,
T. W.
, and
Meisel
,
N. A.
,
2020
, “
But Will It Build? Assessing Student Engineering Designers’ Use of Design for Additive Manufacturing Considerations in Design Outcomes
,”
ASME J. Mech. Des.
,
142
(
9
), p.
092001
.
36.
Sinha
,
S.
,
Chen
,
H.-E.
,
Meisel
,
N. A.
, and
Miller
,
S. R.
,
2017
, “
Does Designing for Additive Manufacturing Help Us Be More Creative? An Exploration in Engineering Design Education
,”
Volume 3: 19th International Conference on Advanced Vehicle Technologies; 14th International Conference on Design Education; 10th Frontiers in Biomedical Devices
,
Cleveland, OH
,
American Society of Mechanical Engineers
, p.
V003T04A014
.
37.
Seepersad
,
C. C.
,
2014
, “
Challenges and Opportunities in Design for Additive Manufacturing
,”
3D Print. Addit. Manuf.
,
1
(
1
), pp.
10
13
.
38.
Novak
,
E.
,
Brannon
,
M.
,
Librea-Carden
,
M. R.
, and
Haas
,
A. L.
,
2021
, “
A Systematic Review of Empirical Research on Learning With 3D Printing Technology
,”
J. Comput. Assist. Learn.
,
37
(
5
), pp.
1455
1478
.
39.
Swamidass
,
P. M.
, and
Winch
,
G. W.
,
2002
, “
Exploratory Study of the Adoption of Manufacturing Technology Innovations in the USA and the UK
,”
Int. J. Prod. Res.
,
40
(
12
), pp.
2677
2703
.
40.
Chryssolouris
,
G.
,
Mavrikios
,
D.
, and
Rentzos
,
L.
,
2016
, “
The Teaching Factory: A Manufacturing Education Paradigm
,”
Proc. CIRP
,
57
, pp.
44
48
.
41.
Salter
,
A.
, and
Gann
,
D.
,
2003
, “
Sources of Ideas for Innovation in Engineering Design
,”
Res. Policy
,
32
(
8
), pp.
1309
1324
.
42.
Janiszewski
,
C.
, and
Wyer Jr
,
R. S.
,
2014
, “
Content and Process Priming: A Review
,”
J. Consum. Psychol.
,
24
(
1
), pp.
96
118
.
43.
Valjak
,
F.
, and
Lindwall
,
A.
,
2021
, “
Review of Design Heuristics and Design Principles in Design for Additive Manufacturing
,”
Proc. Des. Soc.
,
1
, pp.
2571
2580
.
44.
Lindwall
,
A.
, and
Törlind
,
P.
,
2018
, “
Evaluating Design Heuristics for Additive Manufacturing as an Explorative Workshop Method
,”
International Design Conference – Design 2018
, pp.
1221
1232
.
45.
Duverger
,
P.
,
2012
, “
Using YouTube Videos as a Primer to Affect Academic Content Retention
,”
Metrop. Univ.
,
23
(
2
), pp.
51
66
.
46.
Arnott
,
D.
,
2006
, “
Cognitive Biases and Decision Support Systems Development: A Design Science Approach
,”
Inf. Syst. J.
,
16
(
1
), pp.
55
78
.
47.
Yates
,
J. F.
, and
Curley
,
S. P.
,
1986
, “
Contingency Judgment: Primacy Effects and Attention Decrement
,”
Acta Psychol.
,
62
(
3
), pp.
293
302
.
48.
Chapman
,
G. B.
,
Bergus
,
G. R.
, and
Elstein
,
A. S.
,
1996
, “
Order of Information Affects Clinical Judgment
,”
J. Behav. Decis. Mak.
,
9
(
3
), pp.
201
211
.
49.
Joshi
,
A.
,
Kale
,
S.
,
Chandel
,
S.
, and
Pal
,
D. K.
,
2015
, “
Likert Scale: Explored and Explained
,”
Br. J. Appl. Sci. Technol.
,
7
(
4
), pp.
396
403
.
50.
“Files—Made By Design Lab,” https://sites.psu.edu/madebydesign/files/, Accessed February 14, 2023.
51.
Gordon
,
M. J.
,
1991
, “
A Review of the Validity and Accuracy of Self-Assessments in Health Professions Training
,”
Acad. Med.
,
66
(
12
), pp.
762
769
.
52.
Prabhu
,
R.
,
Simpson
,
T. W.
,
Miller
,
S. R.
, and
Meisel
,
N. A.
,
2022
, “
Development and Validity Evidence Investigation of a Design for Additive Manufacturing Self-Efficacy Scale
,”
Res. Eng. Des.
,
33
(
4
), pp.
437
453
.
53.
Bralla
,
J. G.
,
1999
,
Design for Manufacturability Handbook
,
McGraw-Hill Education
,
New York
.
54.
Prabhu
,
R.
,
Bracken
,
J.
,
Armstrong
,
C. B.
,
Jablokow
,
K.
,
Simpson
,
T. W.
, and
Meisel
,
N. A.
,
2020
, “
Additive Creativity: Investigating the Use of Design for Additive Manufacturing to Encourage Creativity in the Engineering Design Industry
,”
Int. J. Des. Creat. Innov.
,
8
(
4
), pp.
198
222
.
55.
Williams
,
C. B.
, and
Seepersad
,
C. C.
,
2012
, “
Design for Additive Manufacturing Curriculum: A Problem-and Project-Based Approach
,”
University of Texas at Austin
,
Austin, TX
.
56.
Stern
,
A.
,
Rosenthal
,
Y.
,
Dresler
,
N.
, and
Ashkenazi
,
D.
,
2019
, “
Additive Manufacturing: An Education Strategy for Engineering Students
,”
Addit. Manuf.
,
27
, pp.
503
514
.
57.
Sullivan
,
G. M.
, and
Artino
,
A. R.
, Jr.
,
2013
, “
Analyzing and Interpreting Data From Likert-Type Scales
,”
J. Grad. Med. Educ.
,
5
(
4
), pp.
541
542
.
58.
Amabile
,
T. M.
,
1982
, “
Social Psychology of Creativity: A Consensual Assessment Technique
,”
J. Pers. Soc. Psychol.
,
43
(
5
), pp.
997
1013
.
59.
Baer
,
J.
, and
McKool
,
S.
,
2009
, “Assessing Creativity Using the Consensual Assessment Technique,”
Handbook of Research on Assessment Technologies, Methods, and Applications in Higher Education
,
C. S.
Schreiner
, ed., pp.
65
77
.
60.
Prabhu
,
R.
,
Masia
,
J. S.
,
Berthel
,
J. T.
,
Meisel
,
N. A.
, and
Simpson
,
T. W.
,
2021
, “
Maximizing Design Potential: Investigating the Effects of Utilizing Opportunistic and Restrictive Design for Additive Manufacturing in Rapid Response Solutions
,”
Rapid Prototyp. J.
,
27
(
6
), pp.
1161
1171
.
61.
Lorenz
,
K.
,
Jones
,
J.
,
Wimpenny
,
D.
, and
Jackson
,
M.
,
2015
, “
A Review of Hybrid Manufacturing
,”
University of Texas at Austin
,
Austin, TX
.
62.
Bartko
,
J. J.
,
1966
, “
The Intraclass Correlation Coefficient as a Measure of Reliability
,”
Psychol. Rep.
,
19
(
1
), pp.
3
11
.
63.
Weir
,
J. P.
,
2005
, “
Quantifying Test-Retest Reliability Using the Intraclass Correlation Coefficient and the SEM
,”
J. Strength Cond. Res.
,
19
(
1
), pp.
231
240
.
64.
Fleiss
,
J. L.
, and
Cohen
,
J.
,
1973
, “
The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability
,”
Educ. Psychol. Meas.
,
33
(
3
), pp.
613
619
.
65.
Lee
,
J.
,
Koh
,
D.
, and
Ong
,
C.
,
1989
, “
Statistical Evaluation of Agreement Between Two Methods for Measuring a Quantitative Variable
,”
Comput. Biol. Med.
,
19
(
1
), pp.
61
70
.
66.
Genco
,
N. E.
,
Holtta-Otto
,
K.
, and
Seepersad
,
C. C.
,
2011
, “
Factors That Influence the Creativity of Engineering Students
,”
ASEE Annual Conference
,
Vancouver, Canada
,
June 26–29
, pp.
1
15
.
67.
Taylor
,
R.
,
1990
, “
Interpretation of the Correlation Coefficient: A Basic Review
,”
J. Diagn. Med. Sonogr.
,
6
(
1
), pp.
35
39
.
68.
Hanusz
,
Z.
,
Tarasinska
,
J.
, and
Zielinski
,
W.
,
2016
, “
Shapiro–Wilk Test With Known Mean
,”
REVSTAT-Stat. J.
,
14
(
1
), pp.
89
100
.
69.
Mircioiu
,
C.
, and
Atkinson
,
J.
,
2017
, “
A Comparison of Parametric and Non-Parametric Methods Applied to a Likert Scale
,”
Pharmacy
,
5
(
2
), p.
26
.
70.
Murray
,
J.
,
2013
, “
Likert Data: What to Use, Parametric or Non-Parametric?
,”
Int. J. Bus. Soc. Sci.
,
4
(
11
), pp.
258
264
.
71.
Dinar
,
M.
, and
Rosen
,
D. W.
,
2017
, “
A Design for Additive Manufacturing Ontology
,”
ASME J. Comput. Inf. Sci. Eng.
,
17
(
2
), p.
021013
.
72.
Kirsh
,
D.
,
2000
, “
A Few Thoughts on Cognitive Overload
,”
Intellectica
,
1
(
30
), pp.
19
51
.
73.
Arnold
,
V.
,
Collier
,
P. A.
,
Leech
,
S. A.
, and
Sutton
,
S. G.
,
2000
, “
The Effect of Experience and Complexity on Order and Recency Bias in Decision Making by Professional Accountants
,”
Account. Finance
,
40
(
2
), pp.
109
134
.
74.
Blikstein
,
P.
, and
Krannich
,
D.
,
2013
, “
The Makers’ Movement and FabLabs in Education: Experiences, Technologies, and Research
,”
Proceedings of the 12th International Conference on Interaction Design and Children
,
New York, NY
,
June 24–27
,
ACM
, pp.
613
616
.
75.
Prabhu
,
R.
,
Miller
,
S. R.
,
Simpson
,
T. W.
, and
Meisel
,
N. A.
,
2018
, “
The Earlier the Better? Investigating the Importance of Timing on Effectiveness of Design for Additive Manufacturing Education
,”
American Society of Mechanical Engineers
, p.
V02AT03A041
.
76.
Maule
,
A. J.
, and
Edland
,
A. C.
,
2002
, “The Effects of Time Pressure on Human Judgement and Decision Making,”
Decision Making
,
G.
Wright
, ed.,
Routledge
, pp.
203
218
.
77.
Ordóñez
,
L.
, and
Benson
,
L.
,
1997
, “
Decisions Under Time Pressure: How Time Constraint Affects Risky Decision Making
,”
Organ. Behav. Hum. Decis. Process.
,
71
(
2
), pp.
121
140
.
78.
Einhorn
,
H. J.
,
1980
, “
Learning From Experience and Suboptimal Rules in Decision Making
,”
Cognitive Processes in Choice and Decision Behavior
.
79.
Christensen-Szalanski
,
J. J.
, and
Bushyhead
,
J. B.
,
1981
, “
Physicians’ Use of Probabilistic Information in a Real Clinical Setting
,”
J. Exp. Psychol. Hum. Percept. Perform.
,
7
(
4
), pp.
928
935
.
You do not currently have access to this content.