A GANetXL approach to an Optimal Maintenance Strategy in Food Manufacturing

An optimal maintenance strategy for improved cost and machine reliability in food manufacturing was developed in this study. 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.本研究针对食品制造业开发了一种可优化成本并提升设备可靠性的最优维护策略。研究数据取自某食品制造企业的故障时间参数与成本数据。将所获数据应用于本研究开发的混合整数非线性多目标优化算法，并通过GANetXL进行求解。总体而言，所开发的最优维护策略可实现7,349,397奈拉的成本节约，优于该工业案例当前9,207,979奈拉的维护成本与设备可靠性水平。综上，本研究所开发的最优维护策略可作为实用工具，供食品制造企业及其他制造行业采用，通过高效的维护调度实现系统可靠性的最优水平，同时将成本支出控制在最低限度。