Modeling and analysis of a new production methodology for achieving mass customization
针对随机需求下的装配作业车间调度问题，提出一种名为“基于子装配通用性的按单装配”的新生产方法，旨在降低成本、减少库存损失并缩短交货时间，并通过算法验证其优于常用方法和商业求解器。
In this paper, we address a Stochastic-Demand Assembly Job Shop Scheduling Problem (SD-AJSSP) in the presence of the commonality of sub-assemblies across products. We propose a new production methodology, named Assemble-to-Order with Commonality of Sub-Assemblies (ATO-CS) to not only solve the SD-AJSSP, but also, achieve a successful implementation of a mass customisation system by collectively aiming to (1) keep the production costs low by leveraging upon commonality of sub-assemblies in products’ BOM and producing sub-assemblies on a mass scale during one of the two stages of production, (2) minimise the loss due to excess inventory build-up in anticipation of stochastic demand of products by postponing the production of certain apex sub-assemblies in products’ BOM until the actual demand is realised, and (3) reduce the time of the products’ delivery to customers. The ATO-CS method determines optimum production levels as well as schedules assembly operations/jobs over the machines at each stage of production, where the second stage is an assembly job shop and is shown to outperform commonly-used production methodologies. We also develop an algorithm for its implementation and show its efficacy over the use of the state-of-the-art commercial solver CPLEX® in obtaining a lower solution cost and smaller optimality gap.