AN INTEGRATED OPTIMIZATION OF PRODUCTION AND PREVENTIVE MAINTENANCE SCHEDULING IN INDUSTRY 4.0

Preventive Maintenance (PM) plays an important role in maximizing machine reliability, improving production efficiency and reducing repair costs. Due to the importance of PM in manufacturing environments, it is necessary to develop an integrated model for scheduling production jobs and maintenance interventions on the machines. On the other side, with the advent of Industry 4.0 and the transformation of factories into smart factories, the production and maintenance processes generate huge volume of data on real-time basis. Despite the importance of the issue and the competitiveness of manufacturing companies in the world, past studies show that the integration of production scheduling and maintenance in Industry 4.0 platform has not been paid much attention. Therefore, in this paper, we propose an optimal parallel machine-scheduling problem with PM activities. A mathematical model is formulated to optimize the scheduling of production and maintenance operations. Industry 4.0 conceptual model is also presented in this paper, in which the smart sensors are considered as the real enablers for industrial digitalization. The optimization problem is solved using GAMS software and branch and bound algorithm. The results of the model provide a suitable schedule for scheduling production and maintenance, and the comparison of solution methods shows that the branch-and-bound algorithm achieves a suitable output in a shorter time.