Cycle time prediction and improvement of chipset assembly and test production line based on variability

Abstract

Variability plays a very important role in the system performance in a chipset assembly and test production line with stochastic environment. So far only few variations have been considered in chipset assembly and test production line performance prediction and improvement. In this paper, a novel approach about cycle time prediction and improvement is proposed by combining with internal benchmarking and variability. Firstly, the composing of cycle time segment through queueing model based on Factory Physics is established, which is under the condition variability quantification and machine sudden large failure. Secondly, to obtain the optimal direction of the cycle time, an internal benchmarking is applied to analyze the influence of variability on cycle time among the workstations. Finally, a case study is performed to evaluate the effectiveness of the proposed method. Results show that the proposed method is an effective method to predict and improve the cycle time of the chipset assembly and test production line with variability.