Machines Tool Operation Optimization Considering the Effective Criteria for Reliability in Industry 4.0

Industry 4.0 includes an important regeneration of production and management systems within manufacturing, where the majority of the procedures will be entirely or partially automated. However, there are insufficient research studies related to machines tool operation optimization considering the effective criteria for reliability in industry 4.0 to enable plants to measure their own conditions and to make future strategies for their activities in this field. Thus, this article proposes a decision-making model using a combination of DEMATEL, ANP and Shannon Entropy, and VIKOR methods with fuzzy features in cellular production systems, considering the effective criteria for reliability in Industry 4.0. Use of fuzzy features aims to bring the problem closer to the real world in this study. The efficiency of proposed model has been validated in a large automotive parts manufacturing plant as a case study. Based on the results, the most critical machine in the category of automatic lathe machines is Machine3, and the ordinary lathe machines is Machine31. Sensitivity analysis shows that changing the weights of criteria affects the individual prioritization of machines but does not have any impact on their overall prioritization. This prioritization has a high level of alignment in terms of priority and accuracy with the perspectives of experts and decision-making teams. The selected critical machine is a sensitive machine in plant and cannot be replaced throughout its equipment lifetime. Finally, practical recommendations for Machines Tool Operation Optimization have been provided in Industry 4.0.