Integrated approach to part scheduling and inspection policies for a job shop manufacturing system

Abstract

The quality of a product greatly depends on the quality of its components. This requires that manufacturing specifications have to be met in the manufacturing environment and as a consequence inspection stations are present in many manufacturing systems and inspection policies must be adopted. One problem, which has been widely investigated, concerns the detection of the inspection points in the hypothesis that the action to be taken is known when a defective part is detected. If different jobs are to be produced, then operation scheduling becomes yet another complex problem needing to be solved. And while the problem of scheduling has received a great amount of attention from researchers, to our knowledge the interaction between the two problems has not been treated in job-shop environment. In the present paper three different control policies are preliminarily examined: they differ both in terms of the number of operations that are inspected, and with regard to the type of intervention carried out on detection of a defect. Each control policy affects the optimal inspection locations, which, in their turn, influence operation scheduling. As will be shown in the present paper, a sequential decision process based on separate optimization steps can lead to very poor final results. For this reason, an integrated approach is proposed, in an attempt to identify an optimal solution using a genetic algorithm.

Keywords:

• Job shop
• Scheduling
• Inspection policy
• Genetic algorithm