Optimizing Test and Inspection Operations in Complex Engineering Products

Susan Ferkau; Quinn Risch; Prashanth Bhat; Kevin Lynch

doi:doi:10.11648/j.ajomis.20210601.12

| Peer-Reviewed

Optimizing Test and Inspection Operations in Complex Engineering Products

Susan Ferkau, Quinn Risch, Prashanth Bhat, Kevin Lynch

Published in American Journal of Operations Management and Information Systems (Volume 6, Issue 1)

Received: 16 March 2021 Accepted: 30 March 2021 Published: 12 April 2021

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Delivery speed and product cost are critical to both our customers and our shareholders. Test cost has historically represented a third or more of overall product cost. Testing requires considerable time investments as well, especially given the nature of products in the aerospace domain, and their safety demands. In this paper we describe work in use today at a large aerospace manufacturer to optimize test and inspection operations in complex engineering products. We extend Deming’s work from the theoretical to application by applying a decision tree and data analytics to test information, resulting in significant savings in dollars and time for test and inspection operations. A bill-of-materials plus operations visualization is employed to initially identify test and inspection operation candidates for removal, and then Deming’s work is extended in this paper to determine the business case for removal, resulting in a final approval by experts driven by the underlying data. The decision tree is described, as well as algorithms to estimate failure rate and rework costs that are integral to applying Deming’s analysis. A small set of business case results for removing an inspection and a test operation using the applied analysis are shared.

Published in	American Journal of Operations Management and Information Systems (Volume 6, Issue 1)
DOI	10.11648/j.ajomis.20210601.12
Page(s)	9-15
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Test Optimization, Bill-of-Materials Plus Operations, Cost Reduction

References

[1]	Turino, J. (2012). Design to test: a definitive guide for electronic design, manufacture, and service. Springer Science & Business Media.
[2]	Lam, H. (2004, July). New design-to-test software strategies accelerate time-to-market. In Electronics Manufacturing Technology Symposium, 2004. IEEE/CPMT/SEMI 29th International (pp. 140-143). IEEE.
[3]	Fox, B., Boito, M., Graser, J. C., & Younossi, O. (2004). Test and evaluation trends and costs for aircraft and guided weapons (No. RAND/MG-109-AF). Rand Corp., Santa Monica, CA.
[4]	Ziomek, C. D., & Jenkins, D. J. (2005, September). The need for embedded intelligence in ATE. In IEEE Autotestcon, 2005. (pp. 398-401). IEEE.
[5]	Berryman, S., Brio, A., Burkhardt, A., Ferkau, S., Gharbiah, H., Hubner, G., Lynch, K., & Woudenberg, M. (2017, September). Concept of operations for test cost analytics in complex manufacturing environments. In 2017 IEEE AUTOTESTCON (pp. 1-8). IEEE.
[6]	Burkhardt, A., Berryman, S., Brio, A., Ferkau, S., Hubner, G., Lynch, K., Mittman, S., & Sonderer, K. (2018, September). Measuring Manufacturing Test Data Analysis Quality. In 2018 IEEE AUTOTESTCON (pp. 1-6). IEEE.
[7]	Maksi, L., Berryman, S., Brio, A., Burkhardt, A., Elder, S., Ferkau, S., Gharbiah, H., Lynch, K., & Risch, Q., Deriving Common Factory Test Platform Requirements Using Historical Test Data,” in the Journal of Information Technology and Software Engineering, October 31, 2018.
[8]	Deming, W. E. (2018). Out of the Crisis. MIT press, 411.
[9]	Bhat, P., Berryman, S., Burkhardt, A., Cho, M., Ferkau, S., Gharbiah, H., Johnston, K., Lynch, K., Mittman, S., Risch, Q., & Swansen, M. (2020, December). Manufacturing Bill-of-Materials Plus Operations Visualization Using D3, in the Journal of Information Technology and Software Engineering, Vol. 11, Issue 1.
[10]	Jiao, J., Tseng, M. M., Ma, Q., & Zou, Y. (2000). Generic bill-of-materials-and-operations for high-variety production management. Concurrent Engineering, 8 (4), 297-321.
[11]	Lee, Y. T. T. (2015). A Journey in standard development: the core manufacturing simulation data (CMSD) information model. Journal of research of the National Institute of Standards and Technology, 120, 270.
[12]	Bostock, M., Ogievetsky, V., & Heer, J. (2011). D³ data-driven documents. IEEE transactions on visualization and computer graphics, 17 (12), 2301-2309.
[13]	Clopper, C. J., & Pearson, E. S. (1934). The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika, 26 (4), 404-413.
[14]	Newcombe, R. G. (1998). Two‐sided confidence intervals for the single proportion: comparison of seven methods. Statistics in medicine, 17 (8), 857-872.
[15]	Reinertsten, D. G. (2009). The principles of product development flow: second generation lean product development. Celeritas.

Cite This Article

Plain Text BibTeX RIS

APA Style

Susan Ferkau, Quinn Risch, Prashanth Bhat, Kevin Lynch. (2021). Optimizing Test and Inspection Operations in Complex Engineering Products. American Journal of Operations Management and Information Systems, 6(1), 9-15. https://doi.org/10.11648/j.ajomis.20210601.12

Copy | Download

ACS Style

Susan Ferkau; Quinn Risch; Prashanth Bhat; Kevin Lynch. Optimizing Test and Inspection Operations in Complex Engineering Products. Am. J. Oper. Manag. Inf. Syst. 2021, 6(1), 9-15. doi: 10.11648/j.ajomis.20210601.12

Copy | Download

AMA Style

Susan Ferkau, Quinn Risch, Prashanth Bhat, Kevin Lynch. Optimizing Test and Inspection Operations in Complex Engineering Products. Am J Oper Manag Inf Syst. 2021;6(1):9-15. doi: 10.11648/j.ajomis.20210601.12

Copy | Download

@article{10.11648/j.ajomis.20210601.12,
  author = {Susan Ferkau and Quinn Risch and Prashanth Bhat and Kevin Lynch},
  title = {Optimizing Test and Inspection Operations in Complex Engineering Products},
  journal = {American Journal of Operations Management and Information Systems},
  volume = {6},
  number = {1},
  pages = {9-15},
  doi = {10.11648/j.ajomis.20210601.12},
  url = {https://doi.org/10.11648/j.ajomis.20210601.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajomis.20210601.12},
  abstract = {Delivery speed and product cost are critical to both our customers and our shareholders. Test cost has historically represented a third or more of overall product cost. Testing requires considerable time investments as well, especially given the nature of products in the aerospace domain, and their safety demands. In this paper we describe work in use today at a large aerospace manufacturer to optimize test and inspection operations in complex engineering products. We extend Deming’s work from the theoretical to application by applying a decision tree and data analytics to test information, resulting in significant savings in dollars and time for test and inspection operations. A bill-of-materials plus operations visualization is employed to initially identify test and inspection operation candidates for removal, and then Deming’s work is extended in this paper to determine the business case for removal, resulting in a final approval by experts driven by the underlying data. The decision tree is described, as well as algorithms to estimate failure rate and rework costs that are integral to applying Deming’s analysis. A small set of business case results for removing an inspection and a test operation using the applied analysis are shared.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Optimizing Test and Inspection Operations in Complex Engineering Products
AU  - Susan Ferkau
AU  - Quinn Risch
AU  - Prashanth Bhat
AU  - Kevin Lynch
Y1  - 2021/04/12
PY  - 2021
N1  - https://doi.org/10.11648/j.ajomis.20210601.12
DO  - 10.11648/j.ajomis.20210601.12
T2  - American Journal of Operations Management and Information Systems
JF  - American Journal of Operations Management and Information Systems
JO  - American Journal of Operations Management and Information Systems
SP  - 9
EP  - 15
PB  - Science Publishing Group
SN  - 2578-8310
UR  - https://doi.org/10.11648/j.ajomis.20210601.12
AB  - Delivery speed and product cost are critical to both our customers and our shareholders. Test cost has historically represented a third or more of overall product cost. Testing requires considerable time investments as well, especially given the nature of products in the aerospace domain, and their safety demands. In this paper we describe work in use today at a large aerospace manufacturer to optimize test and inspection operations in complex engineering products. We extend Deming’s work from the theoretical to application by applying a decision tree and data analytics to test information, resulting in significant savings in dollars and time for test and inspection operations. A bill-of-materials plus operations visualization is employed to initially identify test and inspection operation candidates for removal, and then Deming’s work is extended in this paper to determine the business case for removal, resulting in a final approval by experts driven by the underlying data. The decision tree is described, as well as algorithms to estimate failure rate and rework costs that are integral to applying Deming’s analysis. A small set of business case results for removing an inspection and a test operation using the applied analysis are shared.
VL  - 6
IS  - 1
ER  -

Copy | Download

Author Information

Susan Ferkau

Digital Technology, Raytheon Technologies, Waltham, USA
Quinn Risch

Digital Technology, Raytheon Technologies, Waltham, USA
Prashanth Bhat

Digital Technology, Raytheon Technologies, Waltham, USA
Kevin Lynch

Digital Technology, Raytheon Technologies, Waltham, USA

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Susan Ferkau, Quinn Risch, Prashanth Bhat, Kevin Lynch. (2021). Optimizing Test and Inspection Operations in Complex Engineering Products. American Journal of Operations Management and Information Systems, 6(1), 9-15. https://doi.org/10.11648/j.ajomis.20210601.12

Copy | Download

ACS Style

Susan Ferkau; Quinn Risch; Prashanth Bhat; Kevin Lynch. Optimizing Test and Inspection Operations in Complex Engineering Products. Am. J. Oper. Manag. Inf. Syst. 2021, 6(1), 9-15. doi: 10.11648/j.ajomis.20210601.12

Copy | Download

AMA Style

Susan Ferkau, Quinn Risch, Prashanth Bhat, Kevin Lynch. Optimizing Test and Inspection Operations in Complex Engineering Products. Am J Oper Manag Inf Syst. 2021;6(1):9-15. doi: 10.11648/j.ajomis.20210601.12

Copy | Download

@article{10.11648/j.ajomis.20210601.12,
  author = {Susan Ferkau and Quinn Risch and Prashanth Bhat and Kevin Lynch},
  title = {Optimizing Test and Inspection Operations in Complex Engineering Products},
  journal = {American Journal of Operations Management and Information Systems},
  volume = {6},
  number = {1},
  pages = {9-15},
  doi = {10.11648/j.ajomis.20210601.12},
  url = {https://doi.org/10.11648/j.ajomis.20210601.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajomis.20210601.12},
  abstract = {Delivery speed and product cost are critical to both our customers and our shareholders. Test cost has historically represented a third or more of overall product cost. Testing requires considerable time investments as well, especially given the nature of products in the aerospace domain, and their safety demands. In this paper we describe work in use today at a large aerospace manufacturer to optimize test and inspection operations in complex engineering products. We extend Deming’s work from the theoretical to application by applying a decision tree and data analytics to test information, resulting in significant savings in dollars and time for test and inspection operations. A bill-of-materials plus operations visualization is employed to initially identify test and inspection operation candidates for removal, and then Deming’s work is extended in this paper to determine the business case for removal, resulting in a final approval by experts driven by the underlying data. The decision tree is described, as well as algorithms to estimate failure rate and rework costs that are integral to applying Deming’s analysis. A small set of business case results for removing an inspection and a test operation using the applied analysis are shared.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Optimizing Test and Inspection Operations in Complex Engineering Products
AU  - Susan Ferkau
AU  - Quinn Risch
AU  - Prashanth Bhat
AU  - Kevin Lynch
Y1  - 2021/04/12
PY  - 2021
N1  - https://doi.org/10.11648/j.ajomis.20210601.12
DO  - 10.11648/j.ajomis.20210601.12
T2  - American Journal of Operations Management and Information Systems
JF  - American Journal of Operations Management and Information Systems
JO  - American Journal of Operations Management and Information Systems
SP  - 9
EP  - 15
PB  - Science Publishing Group
SN  - 2578-8310
UR  - https://doi.org/10.11648/j.ajomis.20210601.12
AB  - Delivery speed and product cost are critical to both our customers and our shareholders. Test cost has historically represented a third or more of overall product cost. Testing requires considerable time investments as well, especially given the nature of products in the aerospace domain, and their safety demands. In this paper we describe work in use today at a large aerospace manufacturer to optimize test and inspection operations in complex engineering products. We extend Deming’s work from the theoretical to application by applying a decision tree and data analytics to test information, resulting in significant savings in dollars and time for test and inspection operations. A bill-of-materials plus operations visualization is employed to initially identify test and inspection operation candidates for removal, and then Deming’s work is extended in this paper to determine the business case for removal, resulting in a final approval by experts driven by the underlying data. The decision tree is described, as well as algorithms to estimate failure rate and rework costs that are integral to applying Deming’s analysis. A small set of business case results for removing an inspection and a test operation using the applied analysis are shared.
VL  - 6
IS  - 1
ER  -

Copy | Download