Development of an Explainable Expert System for Smart Factory Readiness Assessment in Manufacturing Industries
Keywords:
Smart Factory, Expert System, Industry 4.0, Explainable Artificial Intelligence, Readiness AssessmentAbstract
Smart Factory adoption has become a critical strategy for manufacturing industries seeking to improve productivity, operational flexibility, and global competitiveness in the era of Industry 4.0. However, many organizations still lack a systematic, reliable, and transparent approach to evaluating their readiness for Smart Factory implementation. This study aims to develop an Expert System for determining industry readiness for Smart Factories by integrating expert knowledge and Explainable Artificial Intelligence (XAI). Expert knowledge was acquired through interviews with Industry 4.0 specialists, manufacturing practitioners, and automation experts, as well as an extensive literature review to identify readiness criteria related to technology, organization, human resources, processes, and financial capability. To enhance transparency and user trust, Explainable AI techniques were incorporated to provide interpretable explanations and feature contribution analyses for readiness recommendations. The system was validated through expert evaluation and case studies involving manufacturing organizations. The results indicate that the proposed system successfully classified organizations into five readiness levels and generated clear, understandable explanations for each recommendation. Validation findings demonstrated a high level of agreement between system outputs and expert assessments, confirming the reliability and practical applicability of the proposed approach. Furthermore, feature contribution analysis revealed that automation level, workforce digital skills, and IoT infrastructure were the most influential determinants of Smart Factory readiness.
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Achour, S. L., Dojat, M., Rieux, C., Bierling, P., & Lepage, E. (2001). A UMLS-based knowledge acquisition tool for rule-based clinical decision support system development. Journal of the American Medical Informatics Association, 8(4), 351–360.
Ç?nar, Z. M., Zeeshan, Q., & Korhan, O. (2021). A framework for industry 4.0 readiness and maturity of smart manufacturing enterprises: a case study. Sustainability, 13(12), 6659.
Garzoni, A., De Turi, I., Secundo, G., & Del Vecchio, P. (2020). Fostering digital transformation of SMEs: a four levels approach. Management Decision, 58(8), 1543–1562.
Gunning, D., & Aha, D. W. (2019). DARPA’s explainable artificial intelligence program. AI Magazine, 40(2), 44–58.
Jerman, A., Peji? Bach, M., & Aleksi?, A. (2020). Transformation towards smart factory system: Examining new job profiles and competencies. Systems Research and Behavioral Science, 37(2), 388–402.
Jones, R. A., Jimmieson, N. L., & Griffiths, A. (2005). The impact of organizational culture and reshaping capabilities on change implementation success: The mediating role of readiness for change. Journal of Management Studies, 42(2), 361–386.
Jung, K., Kulvatunyou, B., Choi, S., & Brundage, M. P. (2016). An overview of a smart manufacturing system readiness assessment. IFIP International Conference on Advances in Production Management Systems, 705–712.
Kagermann, H. (2014). Change through digitization—Value creation in the age of Industry 4.0. In Management of permanent change (pp. 23–45). Springer.
Knauf, R., Gonzalez, A. J., & Abel, T. (2002). A framework for validation of rule-based systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 32(3), 281–295.
Lee, J., Jun, S., Chang, T.-W., & Park, J. (2017). A smartness assessment framework for smart factories using analytic network process. Sustainability, 9(5), 794.
Li, S., Peng, G. C., & Xing, F. (2019). Barriers of embedding big data solutions in smart factories: insights from SAP consultants. Industrial Management & Data Systems, 119(5), 1147–1164.
Linardatos, P., Papastefanopoulos, V., & Kotsiantis, S. (2020). Explainable ai: A review of machine learning interpretability methods. Entropy, 23(1), 18.
Liu, F., Zhu, W., Chen, Y., Xu, D., & Yang, J. (2017). Evaluation, ranking and selection of R&D projects by multiple experts: an evidential reasoning rule based approach. Scientometrics, 111(3), 1501–1519.
Machado, C. G., Winroth, M., Almström, P., Ericson Öberg, A., Kurdve, M., & AlMashalah, S. (2021). Digital organisational readiness: experiences from manufacturing companies. Journal of Manufacturing Technology Management, 32(9), 167–182.
Marinas, M., Dinu, M., Socol, A. G., & Socol, C. (2021). THE TECHNOLOGICAL TRANSITION OF EUROPEAN MANUFACTURING COMPANIES TO INDUSTRY 4.0. IS THE HUMAN RESOURCE READY FOR ADVANCED. Economic Computation & Economic Cybernetics Studies & Research, 55(2).
Martínez, I., Zalba, B., Trillo-Lado, R., Blanco, T., Cambra, D., & Casas, R. (2021). Internet of things (Iot) as sustainable development goals (sdg) enabling technology towards smart readiness indicators (sri) for university buildings. Sustainability, 13(14), 7647.
Osho, G. O., Omisola, J. O., & Shiyanbola, J. O. (2020). A conceptual framework for AI-driven predictive optimization in industrial engineering: Leveraging machine learning for smart manufacturing decisions. Unknown Journal.
Pirola, F., Cimini, C., & Pinto, R. (2020). Digital readiness assessment of Italian SMEs: a case-study research. Journal of Manufacturing Technology Management, 31(5), 1045–1083.
Powell, B. J., Waltz, T. J., Chinman, M. J., Damschroder, L. J., Smith, J. L., Matthieu, M. M., Proctor, E. K., & Kirchner, J. E. (2015). A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implementation Science, 10(1), 21.
Schuh, G., Anderl, R., Gausemeier, J., Ten Hompel, M., & Wahlster, W. (2017). Industrie 4.0 maturity index. Managing the Digital Transformation of Companies, 61.
Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia Cirp, 52, 161–166.
Setzu, M., Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., & Giannotti, F. (2021). Glocalx-from local to global explanations of black box ai models. Artificial Intelligence, 294, 103457.
Sjödin, D. R., Parida, V., Leksell, M., & Petrovic, A. (2018). Smart Factory Implementation and Process Innovation: A Preliminary Maturity Model for Leveraging Digitalization in Manufacturing Moving to smart factories presents specific challenges that can be addressed through a structured approach focused on people, processes, and technologies. Research-Technology Management, 61(5), 22–31.
Thakker, D., Mishra, B. K., Abdullatif, A., Mazumdar, S., & Simpson, S. (2020). Explainable artificial intelligence for developing smart cities solutions. Smart Cities, 3(4), 1353–1382.
Vishnubhatla, S. (2020). Adaptive Real-Time Decision Systems: Bridging Complex Event Processing And Artificial Intelligence. International Journal of Science, Engineering and Technology, 8(2).
Zhang, Y., & Chen, X. (2020). Explainable recommendation: A survey and new perspectives. Foundations and Trends® in Information Retrieval, 14(1), 1–101.
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