Page 22 - ESAM-1-4

Engineering Science in
Additive Manufacturing Experimental statistics in AM

and Test Method for Metallic Bone Plates. United States: accuracy when designing experiments. Behav Ecol Sociobiol.
ASTM International; 2019. 2025;79(106).
40. Food and Drug Administration. Technical Considerations for doi: 10.1007/s00265-025-03640-1
Additive Manufactured Medical Devices: Guidance for Industry 50. Tanco M, Viles E, Jesus Álvarez M, Ilzarbe L. Why is not
and Food and Drug Administration Staff. Washington, DC: US design of experiments widely used by engineers in Europe? J
Department of Health and Human Services; 2017. Appl Stat. 2010;37(12):1961-1977.
41. Vilanova M, Escribano-García R, Guraya T, San Sebastian M. doi: 10.1080/02664760903207308
Optimizing laser powder bed fusion parameters for
IN-738LC by response surface method. Materials (Basel). 51. Hoerl RW, Snee RD. Statistical engineering: An idea whose
2020;13(21):4879. time has come? Am Stat. 2017;71(3):209-219.
doi: 10.3390/ma13214879 doi: 10.1080/00031305.2016.1247015
42. Pfaff A, Jäcklein M, Schlager M, et al. An empirical approach 52. Shrout PE, Rodgers JL. Psychology, science, and knowledge
for the development of process parameters for laser powder construction: Broadening perspectives from the replication
bed fusion. Materials (Basel). 2020;13(23):5400. crisis. Annu Rev Psychol. 2018;69:487-510.
doi: 10.3390/ma13235400 doi: 10.1146/annurev-psych-122216-011845
43. Flores Ituarte I, Wiikinkoski O, Jansson A. Additive 53. Zhang W, Yan S, Tian B, Fei D. Statistical assumptions and
manufacturing of polypropylene: A screening design of reproducibility in psychology: Data mining based on open
experiment using laser-based powder bed fusion. Polymers science. Front Psychol. 2022;13:905977.
(Basel). 2018;10(12):1293. doi: 10.3389/fpsyg.2022.905977
doi: 10.3390/polym10121293 54. Frost J. Introduction to Statistics. Statistics by Jim Publishing;
44. Tyagi B, Dubey D, Sahai A, Sharma RS. Mechanical 2019. Available from: https://statisticsbyjim.com/basics/
properties evaluation of FFF-printed ABS samples based on correlations [Last accessed on 2025 Sep 27].
different process parameters combined with ANOVA and 55. Taguchi G. Introduction to Quality Engineering: Designing
regression analysis. Proc Inst Mech Eng C J Mech Eng Sci. Quality into Products and Processes. Tokyo: Asian
2023;238(7):09544062231151540. Productivity Organization; 1986.
doi: 10.1177/09544062231151540 56. Taguchi G. System of Experimental Design: Engineering
45. Roy RK. A Primer on the Taguchi Method. Michigan: Society Methods to Optimize Quality and Minimize Costs. Vol. 1.
of Manufacturing Engineers; 2010. Dearborn: UNIPUB/Kraus International Publications; 1987.
46. Vorland CJ, Brown AW, Dawson JA, et al. Errors in the 57. Borror CM, Montgomery DC. Mixed resolution designs as
implementation, analysis, and reporting of randomization alternatives to Taguchi inner/outer array designs for robust
within obesity and nutrition research: A guide to their design problems. Qual Reliab Eng Int. 2000;16(2):117-127.
avoidance. Int J Obes (Lond). 2021;45(11):2335-2346. doi: 10.1002/(SICI)1099-1638(200003/04)16:2<117:AID-
doi: 10.1038/s41366-021-00909-z QRE309>3.0.CO;2-0
47. Kang M, Ragan BG, Park JH. Issues in outcomes research: 58. Vining GG, Myers RH. Combining Taguchi and response
An overview of randomization techniques for clinical trials. surface philosophies: A dual response approach. J Qual
J Athl Train. 2008;43(2):215-221. Technol. 1990;22(1):38-45.
doi: 10.4085/1062-6050-43.2.215 doi: 10.1080/00224065.1990.11979204
59. Samuel S, König-Ries B. Understanding experiments and
48. Lynch CM, Montgomery DC. Optimal experimental designs
for hypothesis testing with multiple factors: Maximising research practices for reproducibility: An exploratory study.
power for the biological sciences. Int J Exp Des Process PeerJ. 2021;9:e11140.
Optim. 2024;7(2):105-114. doi: 10.7717/peerj.11140
doi: 10.1504/IJEDPO.2024.140455 60. Moylan S, Brown CU, Slotwinski J. Recommended protocol
for round robin studies in additive manufacturing. J Test
49. Lynch CM, Starkey M, Montgomery D, Pavlic TP,
Mizumoto N. More individuals or more groups? Eval. 2016;44(2):1009.
Incorporating sampling effort, statistical power, and model doi: 10.1520/JTE20150317

Volume 1 Issue 4 (2025) 16 doi: 10.36922/ESAM025340021