Joint optimization of opportunistic maintenance and production scheduling considering batch production mode and varying operational conditions
Joint optimization of opportunistic maintenance and production scheduling considering batch production mode and varying operational conditions
复制标题
考虑批量生产模式和变化运行条件的机会性维护和生产调度联合优化
DOI：
10.1016/j.ress.2020.107047
复制
发表时间：
2020-10
影响因子：
8.1
通讯作者：
Yaqin Zhou
中科院分区：
文献类型：
--
作者：
Lei Xiao;Xinghui Zhang;Junxuan Tang;Yaqin Zhou
生产调度与维护的联合优化一直是研究的热点。现有的大多数文献都假定机器在整个生产任务中的运行状态(OC)是恒定的。然而，实际情况是，由于不同工作的要求，一台机器可能会经历几个不同的接触网。不同的OC可能会影响机器的劣化及其维护决策。此外，在批量生产系统中，维护动作必须在处理批次之前提前或在处理批次之后推迟。即使对机器进行预防性维护，也不能更新，因为预防性维护(PM)通常是不完美的。此外，应该考虑最小限度的维修，这在机器故障时是昂贵和耗时的。上述关切是实际的，但没有得到充分的综合考虑。由于这种集成，增加了联合优化问题的复杂性。提出了一种基于随机密钥、凸集理论和Jaya算法的改进遗传算法，用于解决不同OCS条件下的批量生产系统中机会生产计划和生产调度的联合优化问题。通过一系列比较案例说明了所提方法的有效性。
The joint optimization of production scheduling and maintenance has been a hot topic. Most of the existing publications assume that the operational condition (OC) of a machine is constant during the entire production task. However, it is practical that a machine may experience several different OCs due to the requirement of different jobs. The varying OC may impact the deterioration of machines and their maintenance decisions. In addition, in a batch production system, a maintenance action has to be advanced before or postponed after a processing batch. Even if a machine is maintained preventively, it cannot be renewed since preventive maintenance (PM) is usually imperfect. In addition, minimal repair should be considered, which is costly and time consuming upon machine failure. The above concerns are practical but insufficiently considered in an integrated manner. Due to this integration, the complexity of the joint optimization problem is enhanced. An improved genetic algorithm (GA) based on random keys, convex set theory and the Jaya algorithm is proposed to solve the joint optimization problem of opportunistic PM and production scheduling in a batch production system under varying OCs. A series of comparative cases are conducted to illustrate the effectiveness of the proposed methods.
登录
查看更多内容
DOI：
10.1016/j.ejor.2014.08.004
发表时间：
2015-02
期刊：
Eur. J. Oper. Res.
影响因子：
--
作者：
Tangbin Xia;X. Jin;L. Xi;J. Ni
通讯作者：
Tangbin Xia;X. Jin;L. Xi;J. Ni
影响因子：
5.9
作者：
Richard Cassady;E. Kutanoglu
通讯作者：
Richard Cassady;E. Kutanoglu
具有可用性约束的模糊车间调度问题
DOI：
10.1016/j.cie.2010.01.002
发表时间：
2010-05
期刊：
Computers & Industrial Engineering
影响因子：
--
作者：
Lei, Deming
通讯作者：
Lei, Deming
可变运行条件下单机系统的预防性维护
DOI：
10.1177/1748006x16642332
发表时间：
2016-05
期刊：
Proceedings of the Institution of Mechanical Engineers - Part O: Journal of Risk and Reliability
影响因子：
--
作者：
Hu Jiawen;Jiang Zuhua;Wang Hong
通讯作者：
Wang Hong
DOI：
10.1002/9780470172254
发表时间：
1997
期刊：
--
影响因子：
--
作者：
M. Gen;Runwei Cheng
通讯作者：
M. Gen;Runwei Cheng