Gholizadeh Hadi, Chaleshigar Maedeh, Fazlollahtabar Hamed
Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran; Département de Génie Mécanique, Université Laval, Québec, Canada.
Department of Industrial Management of Shomal University, Amol, Iran.
ISA Trans. 2022 Sep;128(Pt B):54-67. doi: 10.1016/j.isatra.2021.11.041. Epub 2021 Dec 20.
Industrial companies would attempt to keep themselves agile in the dynamic market. Given the competition among industries, lean methods are employed to reduce costs in the system. Among them, maintenance is significant to have a system available for manufacturing tasks. Maintenance is identified as the largest cost control tools in the equipment-driven industry. Implementing an effectual plan for preventive maintenance helps to be much more flexible and create an innovative solution for planning in the production. In this vein, this paper introduces an optimization model related to flexible flow-shop system scheduling in a series-parallel production system of disposable appliances by considering the preventive maintenance (PM) policy. By planning preventive maintenance, extra operation time is incurred to the system which may influence the cycle time and lead to lost sales and back orders. Therefore, the paper proposes a mathematical model to consider both operations times and availability of the whole production system to minimize the delays to reach an optimal sequence of processing. Since uncertainty exists in real industrial systems, the processing times are uncertain here. To handle uncertainty, robust optimization has been applied to solve the problem. In addition, a scenario-based genetic algorithm (SBGA) and Particle Swarm Optimization (PSO) algorithm have been developed to solve the proposed model. The results indicate the appropriate performance of the proposed approach in terms of time-saving leads to saving the cost of PM.
工业公司会试图在动态市场中保持自身的灵活性。鉴于行业间的竞争，精益方法被用于降低系统成本。其中，维护对于使系统能够执行制造任务至关重要。维护被视为设备驱动型行业中最大的成本控制工具。实施有效的预防性维护计划有助于提高灵活性，并为生产计划创造创新解决方案。有鉴于此，本文通过考虑预防性维护（PM）策略，介绍了一种与一次性用品串并联生产系统中的柔性流水车间系统调度相关的优化模型。通过规划预防性维护，系统会产生额外的运行时间，这可能会影响周期时间，并导致销售损失和订单积压。因此，本文提出了一个数学模型，以同时考虑整个生产系统的运行时间和可用性，从而将延迟降至最低，以达到最优的加工顺序。由于实际工业系统中存在不确定性，这里的加工时间是不确定的。为了处理不确定性，已应用鲁棒优化来解决该问题。此外，还开发了一种基于场景的遗传算法（SBGA）和粒子群优化（PSO）算法来求解所提出的模型。结果表明，所提出的方法在节省时间方面具有适当的性能，从而节省了预防性维护成本。
