A GANetXL approach to an Optimal Maintenance Strategy in Food Manufacturing

Failure time parameters and cost data were obtained from a food manufacturing firm. The data obtained were applied to the mixed integer non-linear multi-objective optimization algorithm developed in this study, and solved using GANetXL.

Overall, the developed optimal maintenance strategy provided better cost savings at N7, 349,397 than the current maintenance cost and machine reliability of the industrial case study at N9, 207,979. In general, the developed optimal strategy would serve as a practical tool for adoption by food manufacturing companies and other manufacturing sectors in order to achieve optimum levels of system reliability while maintaining minimum cost expenditure through an efficient maintenance schedule.