A Model Considering the Correlation Between Batch Size and Quality for Serial Batch Scheduling in Flexibile Job Shop

In modern manufacturing, rational planning of production batch sizes is crucial for balancing production efficiency, product quality, and cost. However, existing research has shortcomings: while large-batch production can improve equipment utilization, it increases inventory costs and delivery lead times; whereas small-batch production reduces inventory, frequent batch changeovers decrease equipment utilization and lead to quality fluctuations. To address these issues, this paper constructs a quality modeling framework that comprehensively considers the relationship between product quality and processing batch size. It treats batch splitting, machine selection, and operation sequencing as decision variables, with the ultimate goal of optimizing the system's overall product revenue. Given the NPhard nature of the problem - characterized by high computational complexity that makes traditional solution methods inefficientthis paper adopts a genetic algorithm for resolution. Case study validation demonstrates that the proposed model can provide valuable guidance for production practices and enhance economic benefits.