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As the lot-streaming concept has been used widely to reduce the makespan in a production system, most research has investigated the flow shop production systems; however, jobshop production systems have received much less attention, relatively. This study more thoroughly investigates the application of lot splitting in a job shop production system with setup times, which cannot be omitted. The objective investigated not only minimises the makespan but also minimises the total production cost, which includes the material handling cost, the setup cost and the inventory cost. A disjunctive graph is first used to describe the addressed scheduling problem, and an integer programming model is then constructed to obtain an optimal solution. In order to investigate the influence of the number of sublots and sublot sizes on a job-shop production system with regard to the corresponding objective considered, some experiments are conducted and results presented as well.

In the area of quality control, several correlative quality characteristics may be considered simultaneously in a manufacturing process. In such a case, the Schewhart control charts neglect the influence of the correlation among these quality characteristics, leading to an incorrect judgment. Numerous methods have been proposed to control a process with multiple quality characteristics, however, most research emphasises only the variation of a process mean and devotes much less attention to the variation of a variance, relatively speaking. In this study, a neural network procedure is proposed for detecting variations in the variances, with the assumption that the mean value of the multiple quality characteristics of a process is under control. Two criteria, the average run length (ARL) and the average number of abnormal cases found, are used to evaluate the performance of the proposed procedure. The developed neural model is compared with the traditional |S| control method with regard to the aspect of detecting the variations in the variances in a process. The simulation results demonstrate the superiority of the proposed procedure in process control while multiple quality characteristics are simultaneously considered.