System reliability assessment for production systems with product classification

This study investigates multi-class production systems in which products are categorized according to a key quality characteristic, namely their primary function, to satisfy diverse customer requirements. Unlike traditional models that treat all conforming products as fulfilling a single, homogeneous demand, the proposed approach explicitly considers distinct demand requirements for each class, thereby ensuring that products from one class cannot substitute for those of another. To assess the performance of production systems with product classification, system reliability is adopted as the performance metric, defined as the probability of successfully fulfilling the demands of all product classes. The production system is modeled as a multi-state production network (MPN), which captures uncertainties in workstation capacities and represents the manufacturing configuration through a network-based structure. An efficient algorithm is developed to assess system reliability based on the concept of the lower boundary vector. System reliability serves as a quantitative basis for decision-making in order acceptance and production planning under uncertainty.