Cloud-Based Scalability in Quality Management Systems: A Case Study on the Global Problem Solving System (GPSS) Migration
Keywords:
Cloud Migration; Quality Management Systems; Agile SCRUM; 8D Problem Solving; Process Re-EngineeringAbstract
Quality management systems in globally distributed manufacturing organizations increasingly strain against the limitations of on-premise infrastructure, where data silos and geographic latency slow the resolution of manufacturing nonconformances and erode cross-site visibility into corrective action status. This article presents a case study on the migration of the Global Problem Solving System (GPSS), an enterprise platform for tracking quality incidents and eight-discipline (8D) problem-solving. The migration moved GPSS from an on-premise architecture to a cloud-based environment within a global semiconductor manufacturing organization. This migration, conducted under an Agile SCRUM framework, required bridging information technology development teams and business stakeholders, translating operational requirements into user stories and managing a sprint backlog against an explicit definition of done. Process re-engineering accompanied the technical migration, mapping the data flow from failure notification through root cause analysis to permanent corrective action and standardizing workflows that had previously varied across manufacturing sites. A central innovation was the introduction of automated eight-discipline scoring, which checked structural elements such as the presence of a five-whys analysis and the identification of an escape point before engineers submitted records for final approval. Phase one deployment produced a productivity gain of approximately eighty hours per cycle for quality teams, attributed to reduced latency, automated documentation, and centralized tracking. The case study offers a practitioner framework for organizations weighing similar cloud migrations of quality-critical systems.
Downloads
References
W. E. Deming, Out of the Crisis, MIT Press, reprint, 1986. Available: https://studylib.net/doc/26316994/w.-edwards-deming-out-of-the-crisis-mit-press-2000
J. M. Juran, Juran on Planning for Quality, Collier Macmillan, 1988. Available: https://www.scirp.org/reference/referencespapers?referenceid=2871650
International Organization for Standardization, ISO 9001:2015 — Quality management systems — Requirements, ISO, 2015. Available: https://2015.iso.org/standard/62085.html
E. E. Broday, "The evolution of quality: From inspection to quality 4.0," International Journal of Quality and Service Sciences, vol. 14, no. 3, pp. 368-382, 2022. Available: https://doi.org/10.1108/IJQSS-09-2021-0121
M. Ghobakhloo, M. Iranmanesh, M.-L. Tseng, A. Grybauskas, A. Stefanini, and A. Amran, "Behind the definition of Industry 5.0: A systematic review of technologies, principles, components, and values," Journal of Industrial and Production Engineering, vol. 40, no. 6, pp. 432-447, 2023. Available: https://www.tandfonline.com/doi/full/10.1080/21681015.2023.2216701
M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, et al., "A view of cloud computing," Communications of the ACM, vol. 53, no. 4, pp. 50-58, 2010. Available: https://dl.acm.org/doi/fullHtml/10.1145/1721654.1721672
P. Mell and T. Grance, "The NIST definition of cloud computing," NIST Special Publication 800-145, 2011. Available: https://nvlpubs.nist.gov/nistpubs/legacy/sp/nistspecialpublication800-145.pdf
P. Jamshidi, A. Ahmad, and C. Pahl, "Cloud migration research: A systematic review," IEEE Transactions on Cloud Computing, vol. 1, no. 2, pp. 142-157, 2013. Available: https://ieeexplore.ieee.org/abstract/document/6624108
S. Gupta, R. Meissonier, V. A. Drave, and D. Roubaud, "Examining the impact of Cloud ERP on sustainable performance: A dynamic capability view," International Journal of Information Management, vol. 51, art. 102028, 2020. Available: https://www.sciencedirect.com/science/article/abs/pii/S0268401219308849
F. Aligarh, B. Sutopo, and W. Widarjo, "The antecedents of cloud computing adoption and its consequences for MSMEs' performance: A model based on the Technology-Organization-Environment (TOE) framework," Cogent Business & Management, vol. 10, no. 2, art. 2220190, 2023. Available: https://www.tandfonline.com/doi/full/10.1080/23311975.2023.2220190
E. Masanet, A. Shehabi, N. Lei, S. Smith, and J. Koomey, "Recalibrating global data center energy-use estimates," Science, vol. 367, no. 6481, pp. 984-986, 2020. Available: https://www.science.org/doi/abs/10.1126/science.aba3758
M. Ghobakhloo and M. Iranmanesh, "Digital transformation success under Industry 4.0: A strategic guideline for manufacturing SMEs," Journal of Manufacturing Technology Management, vol. 32, no. 8, pp. 1533-1556, 2021. Available: https://www.emerald.com/jmtm/article-abstract/32/8/1533/451180/
K. Schwaber and J. Sutherland, The Scrum Guide: The Definitive Guide to Scrum: The Rules of the Game, Scrum.org & Scrum Inc., 2020. Available: https://www.scirp.org/reference/referencespapers?referenceid=3975507
M. Hron and N. Obwegeser, "Why and how is Scrum being adapted in practice: A systematic review," Journal of Systems and Software, vol. 183, art. 111110, 2022. Available: https://www.sciencedirect.com/science/article/abs/pii/S0164121221002077
C. Verwijs and D. Russo, "A theory of Scrum team effectiveness," ACM Transactions on Software Engineering and Methodology, vol. 32, no. 3, pp. 1-51, 2023. Available: https://dl.acm.org/doi/full/10.1145/3571849
M. Khurana and K. Kaur, "Impact of agile scrum methodology on team's productivity and client satisfaction – a case study," in Proc. 2021 3rd Int. Conf. Advances in Computing, Communication, Control and Networking (ICAC3N), pp. 1686-1691, 2021. Available: https://ieeexplore.ieee.org/abstract/document/9725505
S. Elangovan, M. S. Jusoh, D. H. Muhd Yusuf, M. S. Ismail, and M. S. Hj Din, "8D problem solving methodology: Continuous improvement in automation organization," IOP Conference Series: Journal of Physics: Conference Series, vol. 2129, no. 1, art. 012017, 2021. Available: https://iopscience.iop.org/article/10.1088/1742-6596/2129/1/012017/meta
I. Nonaka, "The knowledge-creating company," in The Economic Impact of Knowledge, Routledge, 2009, pp. 175-187. Available: http://www.sietmanagement.fr/wp-content/uploads/2016/04/nonaka_1991.pdf
M.-A. Filz, J. P. Bosse, and C. Herrmann, "Digitalization platform for data-driven quality management in multi-stage manufacturing systems," Journal of Intelligent Manufacturing, vol. 35, no. 6, pp. 2699-2718, 2024. Available: https://link.springer.com/article/10.1007/s10845-023-02162-9
E. e Oliveira, V. L. Migueis, and J. L. Borges, "Automatic root cause analysis in manufacturing: An overview & conceptualization," Journal of Intelligent Manufacturing, vol. 34, no. 5, pp. 2061-2078, 2023. Available: https://link.springer.com/article/10.1007/s10845-022-01914-3
H. Tercan and T. Meisen, "Machine learning and deep learning based predictive quality in manufacturing: A systematic review," Journal of Intelligent Manufacturing, vol. 33, no. 7, pp. 1879-1905, 2022. Available: https://link.springer.com/article/10.1007/S10845-022-01963-8
H. Nayernia, H. Bahemia, and S. Papagiannidis, "A systematic review of the implementation of industry 4.0 from the organisational perspective," International Journal of Production Research, vol. 60, no. 14, pp. 4365-4396, 2022. Available: https://www.tandfonline.com/doi/full/10.1080/00207543.2021.2002964
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
