Given that a U-shaped assembly line is usually regarded as a serial flow production system, preventive maintenance (PM) on machines in any station of the line may lead to stoppage of the whole line and sequentially cause great loss of production cost. To improve production continuity during PM, this paper proposes multiple alternative assignment plans with interchangeable abilities to ascertain the production recovery from changes of line structure. A mixed-integer mathematical model is further formulated to make decisions on alternative assignment plans. In this model, cycle time and total assignment plan alteration cost are minimised simultaneously. And an enhanced JAYA algorithm is developed to obtain well-distributed Pareto frontier solutions effectively and efficiently. The proposed algorithm suggests a similarity-based selection and various crossover/neighbourhood search operators to enhance its search ability for global optima. Numerical experiment results prove the effectiveness of the proposed model and enhanced JAYA. This novel methodology of integration optimisation bridges assembly line balancing and PM, and thus promotes production continuity and achieves economic benefits under maintenance within large-scaled assembly lines in real situations. Furthermore, a real-world case study is conducted to illustrate the significance of this novel methodology.

考虑到U型流水线通常被认为是一个串行流生产系统，生产线任何一个工位的机器的预防性维护（PM）都可能导致整条线的停产，进而造成生产成本的巨大损失。为了提高 PM 期间的生产连续性，本文提出了多种具有互换能力的替代分配计划，以确定生产线结构变化后的生产恢复。进一步制定了混合整数数学模型，以对替代分配计划进行决策。在这个模型中，周期时间和总分配计划变更成本同时最小化。并开发了增强型JAYA算法以有效且高效地获得分布良好的Pareto前沿解。所提出的算法提出了基于相似性的选择和各种交叉/邻域搜索算子，以增强其对全局最优的搜索能力。数值实验结果证明了所提模型和增强型JAYA的有效性。这种集成优化的新方法将装配线平衡和 PM 连接起来，从而在实际情况下促进生产连续性并在大规模装配线维护下实现经济效益。此外，还进行了一个真实世界的案例研究，以说明这种新颖方法的重要性。这种集成优化的新方法将装配线平衡和 PM 连接起来，从而促进生产连续性并在实际情况下的大型装配线维护下实现经济效益。此外，还进行了一个真实世界的案例研究，以说明这种新颖方法的重要性。这种集成优化的新方法将装配线平衡和 PM 连接起来，从而促进生产连续性并在实际情况下的大型装配线维护下实现经济效益。此外，还进行了一个真实世界的案例研究，以说明这种新颖方法的重要性。