This paper aims to develop a maintenance optimization model to maintain a high level of efficiency and reliability of the machinery. The methodological approach is based on preventive maintenance through the partial or total replacement of critical components. Although an intermediate intervention control, the focus is on a particular machine that has stopped several times, reducing its operational availability and resulting in a high cost of non-production. This study uses a Weibull model to analyze and optimize the correct maintenance process of the machinery considered. The failure data are then analyzed and scheduled. The final purpose is to standardize the operators' intervention procedures to reduce the time for the same interventions.

This paper proposes a modified discrete firefly algorithm (DFA) applied to the machine loading problem of the flexible manufacturing systems (FMSs) starting from the mathematical formulation adopted by Swarnkar & Tiwari (2004). The aim of the problem is to identify the optimal jobs sequence that simultaneously maximizes the throughput and minimizes the system unbalance according to given technological constraints (e.g. available tool slots and machining time). The results of the algorithm proposed have been compared with the existing and most recent swarm-based approaches available in the open literature using as benchmark the set of ten problems proposed by Mukhopadhyay et al. (1992). The algorithm shows results that are comparable and sometimes even better than most of the other approaches considering both the quality of the results provided and the computational times obtained.