Dynamic scheduling of parallel heat treatment furnaces: A case study at a manufacturing system

In the present work, a case study focusing on online and dynamic scheduling of parallel heat treatment furnaces at a real manufacturing company is presented. The problem under consideration in this study involves release times, eligibility constraints, due dates, sequence-dependent setup times due to heating up or cooling down the furnaces, breakdowns and maintenance periods. Moreover, dynamic events, for instance, arrivals of rush orders, cancellations of already handled jobs, changes in due dates or in lot sizes exist in the nature of the problem considered here. Such dynamic factors make the introduced problem more challenging. One more difficulty is the vast variety of products at the firm. Generating a large-scaled setup matrix is neither practical nor reliable. Therefore, based on the distinctive attributes of the products, an implicit clustering is employed. As a solution approach, a multi-start and constructive search algorithm is proposed for this problem. Finally, as a dynamic scheduling module for the heat treatment furnaces, the proposed algorithm is embedded into the enterprise resource planning system of the company that is built on JAVA. The current system contributes to the firm by online scheduling of the heat treatment furnaces, generating online Gantt Charts for managers, online transmission of work orders and digitalized performance analysis reports. Thus, as demonstrated by numeric data presented in the present paper, a decrease in energy consumption and an increase in annual income are expected.