Optimization of Fault-Tolerant Fabric-Cutting Table Planning in a Just-In-Time Apparel Manufacturing Environment

In apparel manufacturing, accurate upstream fabric-cutting planning is crucial for the smoothness of downstream sewing operations. Effective and reliable fabric-cutting schedules are difficult to obtain because the apparel manufacturing environment is fuzzy and dynamic. In this paper, genetic algorithms and fuzzy set theory are used to generate fault-tolerant fabric-cutting schedules in a just-in-time production environment. The proposed method is demonstrated by two typical cases with production data collected from a Hong Kong-owned garment production plant in China. Experimental results demonstrate that the genetically improved fault-tolerant schedules effectively satisfy demand of downstream production units, guarantee consistent and reliable system performance, and also reduce production costs through reduced operator idle time