Achieving yield confidence in a flow shop with single rework station via capacity expansion and process improvement

This paper provides an improvement strategy for a flow shop with single rework station by modeling the flow shop as a capacitated manufacturing network (CMN) to achieve the required yield confidence utilizing a confidence-based analysis. We define the yield confidence as a performance indicator to evaluate the probability that a specified level of demand will be satisfied. Specifically, this paper considers capacity expansion and process improvement issues. First, a model is proposed to represent the CMN and to characterize the probability that a unit of material is successfully transformed into a final product. This model further identifies the required amount of (ideal) input to satisfy the customer demand and to achieve the desired yield confidence. In particular, this ideal input can be seen as the least wasteful input for the CMN. Capacity expansion and process improvement are considered when the current capacity of the CMN is insufficient to process the ideal input. The approach identifies the target output ratios of stations needed to achieve a process improvement goal. Two benchmark examples are provided to demonstrate the model building, capacity expansion, and process improvement steps.