[논문]품질경영 관점에서 머신러닝 연구 패턴 분석

김예은; 송호준; 신완선

doi:10.7469/jksqm.2024.52.1.77

품질경영 관점에서 머신러닝 연구 패턴 분석
Analysis of Machine Learning Research Patterns from a Quality Management Perspective 원문보기

品質經營學會誌 = Journal of Korean society for quality management, v.52 no.1, 2024년, pp.77 - 93

김예은 (성균관대학교 산업공학과) , 송호준 (성균관대학교 산업공학과) , 신완선 (성균관대학교 시스템경영공학과)

Abstract ▼ AI-Helper

Purpose: The purpose of this study is to examine machine learning use cases in manufacturing companies from a digital quality management (DQM) perspective and to analyze and present machine learning research patterns from a quality management perspective. Methods: This study was conducted based on systematic literature review methodology. A comprehensive and systematic review was conducted on manufacturing papers covering the overall quality management process from 2015 to 2022. A total of 3 research questions were established according to the goal of the study, and a total of 5 literature selection criteria were set, based on which approximately 110 research papers were selected. Based on the selected papers, machine learning research patterns according to quality management were analyzed. Results: The results of this study are as follows. Among quality management activities, it can be seen that research on the use of machine learning technology is being most actively conducted in relation to quality defect analysis. It suggests that research on the use of NN-based algorithms is taking place most actively compared to other machine learning methods across quality management activities. Lastly, this study suggests that the unique characteristics of each machine learning algorithm should be considered for efficient and effective quality management in the manufacturing industry. Conclusion: This study is significant in that it presents machine learning research trends from an industrial perspective from a digital quality management perspective and lays the foundation for presenting optimal machine learning algorithms in future quality management activities.

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표/그림 (14)

그림 Figure 1. Multifaceted use of AI and machine learning in the manufacturing field
그림 Figure 2. Development process of quality management paradigm (Weckenmann et al., 2015)
표 Table 1. Review and redefine the scope of quality management in Industry 4.0
그림 Figure 3. ML classification diagram
표 Table 3. Systematic literature analysis procedure (Kitchenham 2004)
그림 Figure 4. Publication trends of selected major literature by year
그림 Figure 5. Raw data of selected documents (before document preprocessing)
표 Table 4. Assessment concept according to DQM system categories
표 Table 5. Classification of ML application fields according to DQM system category
그림 Figure 6. Proportion of ML literature composition by DAP category
그림 Figure 7. Literature publication trends
표 Table 6. ML technology trend analysis results from a DQM perspective
그림 Figure 8. ML utilization trends in DAP category
그림 Figure 9. Comparison of quality defect analysis, quality parameter optimization, and preventative quality management ML utilization

참고문헌 (23)

Aldag, M. C., & Eker, B. 2018. November. What is Quality 4.0 in the era of industry 4.0. In Proceedings of the？3rd International Conference on Quality of Life, Kopaonik, Serbia (pp. 28-30).
Bertolini, M., Mezzogori, D., Neroni, M., & Zammori, F. 2021. Machine Learning for industrial applications: A comprehensive literature review. In Expert Systems with Applications (Vol. 175). Elsevier Ltd. https://doi.org/10.1016/j.eswa.2021.114820
Carnerud, D., & Backstrom, I. 2021. Four decades of research on quality: summarising, Trendspotting and looking？ahead. Total Quality Management and Business Excellence 32(9-10):1023-1045. https://doi.org/10.1080/14783363.2019.1655397

상세보기
Chen, T., Sampath, V., May, M. C., Shan, S., Jorg, O. J., Aguilar Martin, J. J., ... & Calaon, M. 2023. Machine Learning？in Manufacturing towards Industry 4.0: From 'For Now'to 'Four-Know'. Applied Sciences 13(3):1903.
Dahlgaard-Park, S. M. 2011. The quality movement: Where are you going? Total Quality Management and Business？Excellence 22(5):493-516. https://doi.org/10.1080/14783363.2011.578481

상세보기
Dooley, K. 2000. The Paradigms of Quality: Evolution and Revolution in the History of the Discipline. In Advances？in the Management of Organizational Quality (Vol. 5). JAI Press. https://www.researchgate.net/publication/228598156
Durakovic, B., & Halilovic, M. (n.d.). INTERNATIONAL JOURNAL ON INFORMATICS VISUALIZATION journal homepage : www.joiv.org/index.php/joiv INTERNATIONAL JOURNAL ON INFORMATICS VISUALIZATION？Industry 4.0: The New Quality Management Paradigm in Era of the Industrial Internet of Things.？www.joiv.org/index.php/joiv
Fitzgerald, M., Kruschwitz, N., Bonnet, D., & Welch, M. 2013. Embracing Digital Technology A New Strategic？Imperative. http://sloanreview.mit.edu/faq/
Isniah, S., Hardi Purba, H., & Debora, F. 2020. Plan do check action (PDCA) method: literature review and research？issues. Jurnal Sistem Dan Manajemen Industri 4(1):72-81. https://doi.org/10.30656/jsmi.v4i1.2186
Johnson, S. 2019. Quality 4.0: A trend within a trend. Quality 58(2):21-23.
Kitchenham, B. 2004. Procedures for Performing Systematic Reviews.
Kitchenham, B., & Brereton, P. 2013. A systematic review of systematic review process research in software？engineering. In Information and Software Technology (Vol. 55, Issue 12, pp. 2049-2075). Elsevier B.V.？https://doi.org/10.1016/j.infsof.2013.07.010

상세보기
Matt, C., Hess, T., & Benlian, A. 2015. Digital Transformation Strategies. In Business and Information Systems？Engineering (Vol. 57, Issue 5, pp. 339-343). Gabler Verlag. https://doi.org/10.1007/s12599-015-0401-5

상세보기
Park, Y. T. 1994. 품질시스템의 발전과 품질경영. IE interfaces 7(2):11-19. (n.d.).
Pereira, A. C., & Romero, F. 2017. A review of the meanings and the implications of the Industry 4.0 concept.？Procedia Manufacturing 13:1206-1214. https://doi.org/10.1016/j.promfg.2017.09.032

상세보기
Prashar, A. 2023. Quality management in industry 4.0 environment: a morphological analysis and research agenda.？International Journal of Quality & Reliability Management 40(3):863-885.

상세보기
Radziwill, N. 2018. Let's Get Digital: The many ways the fourth industrial revolution is reshaping the way we think？about quality. arXiv 2018. arXiv preprint arXiv:1810.07829.
Ralea, C., Dobrin, O.-C., Barbu, C., & Tanase, C. (n.d.). PROCEEDINGS OF THE 13th INTERNATIONAL？MANAGEMENT CONFERENCE "Management Strategies for High Performance" LOOKING TO THE FUTURE:？DIGITAL TRANSFORMATION OF QUALITY MANAGEMENT.
Sanchez-Franco, M. J., Calvo-Mora, A., & Perianez-Cristobal, R. 2023. Clustering abstracts from the literature？on Quality Management (1980-2020). In Total Quality Management and Business Excellence (Vol. 34, Issues？7-8, pp. 959-989). Routledge. https://doi.org/10.1080/14783363.2022.2139674

상세보기
Santhanam, P. 2020. Quality Management of Machine Learning Systems. http://arxiv.org/abs/2006.09529
Shaposhnikov, S., Institute of Electrical and Electronics Engineers. Russia North-West Section., Sankt-Peterburgskii？gosudarstvennyi elektrotekhnicheskii universitet "LETI," & Institute of Electrical and Electronics Engineers.？(n.d.). Proceedings of the 2019 IEEE International Conference "Quality Management, Transport and？Information Security, Information Technologies" (IT & QM & IS) : September, 23-27, 2019, Sochy, Russia,？2019.
Weckenmann, A., Akkasoglu, G., & Werner, T. 2015. Quality management - History and trends. TQM Journal,？27(3):281-293. https://doi.org/10.1108/TQM-11-2013-0125

상세보기
Womack, J. P., Jones, D. T., & Roos, D. (n.d.). The Machine That Changed The World.

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