Duan Shengze, Kang Ling
The State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China.
Comput Intell Neurosci. 2022 Aug 28;2022:6289609. doi: 10.1155/2022/6289609. eCollection 2022.
Machine breakdowns (MB) often occur, resulting in changes in the production layout and the material flow and causing a surge in production cost. Obviously, it is imperative to consider MB in workshop layout. Scholars mainly focus on the double row layout problem in an ideal nonfailure condition while scarcely considering MB mentioned above in the layout field. This paper proposes an enhanced multiobjective double row layout model considering MB (MDRLP-MB) to fill the research gaps. That model adds redundancy to reduce the losses caused by machine failure based on the prediction of breakdowns. In MDRLP-MB, machines with the same machine type have the same size and failure rate. Besides, this paper redefines the biobjectives of material handling costs (MHC) and the utilization ratio based on the feature of MDRLP-MB. To reduce the complexity of the problem, a decision rule is developed to reduce the alternative machine types. Furthermore, it revises the NSGA-II to solve the MDRLP-MB effectively. Results of numerical experiments and application cases show MDRLP-MB can obtain the optimal set of Pareto solutions in the case of increasing different numbers of redundancy considering MB to provide a more refined layout scheme for decision making.
机器故障（MB）经常发生，导致生产布局和物料流发生变化，并使生产成本激增。显然，在车间布局中考虑机器故障势在必行。学者们主要关注理想无故障条件下的双排布局问题，而在布局领域几乎没有考虑上述机器故障。本文提出了一种考虑机器故障的增强型多目标双排布局模型（MDRLP-MB）来填补研究空白。该模型基于故障预测增加冗余以减少机器故障造成的损失。在MDRLP-MB中，相同机器类型的机器具有相同的尺寸和故障率。此外，本文基于MDRLP-MB的特点重新定义了物料搬运成本（MHC）和利用率这两个目标。为降低问题的复杂性，制定了一条决策规则以减少备选机器类型。此外，对NSGA-II进行了改进以有效求解MDRLP-MB。数值实验和应用案例结果表明，MDRLP-MB在考虑机器故障增加不同冗余数量的情况下能够获得帕累托最优解集，为决策提供更精细的布局方案。
