Determination of fault-tolerant fabric-cutting schedules 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 cases with production data collected from a Hong Kong-owned garment production plant in China. Results of the two cases preliminarily show that the genetically improved fault-tolerant schedules effectively satisfy the demand for downstream production units, guarantee consistent and reliable system performance, and also reduce production costs through reduced operator idle time. More cases will be conducted in order to further validate the effectiveness of the proposed method.