Hybrid proactive approach for solving maintenance and planning problems in the scenario of Industry 4.0

TL;DR

This paper presents a hybrid simheuristic approach integrating maintenance, lot-sizing, and scheduling in Industry 4.0, enhancing production robustness and reducing infeasibility due to machine failures.

Contribution

It introduces a novel hybrid method combining robustness and simheuristics for integrated maintenance and planning problems in Industry 4.0 environments.

Findings

Higher robustness reduces deviations in lot-sizing objectives.

Increased robustness lowers the probability of infeasibility after failures.

The approach effectively accounts for historical failure data in planning.

Abstract

Behind the concept of Industry 4.0, there are a number of principles and ideas; one of them is the integration of problems of different decision levels. In this work, we integrate maintenance with planning problems, aiming to take full advantage of the production capacity providing immediate delivery of products to customers and avoiding failures. We propose a hybrid approach for solving a maintenance problem integrated with the lot-sizing and scheduling problems. The approach is based on the concepts of robustness and simheuristics, considering preventive, predictive and corrective maintenances in a parallel machine environment. Simulations are performed to consider machine failures. Results indicate that as we increase the robustness parameter at the lot-sizing problem, we obtain lower deviations related to the initial objective function of the lot-sizing problem and lower probabilities of infeasibility after the occurrence of failures. The approach makes it possible to find an average expected result for each of the scenarios analyzed taking into account historical data on the behavior of the failures.