| Summary: | Production scheduling is a common problem that occurs in multi-product manufacturing facilities where a wide range of products are produced in small quantities, resulting in frequent changeovers. A plastics compounding plant offering tailor-made resins is a representative case. This kind of scheduling problem has already been extensively researched and published in the past. However, the concept of incorporating quality of the finished product has never been visited previously. There are many different factors that may affect the quality of polymer resins produced by extrusion. One such factor is temperature. A production schedule cannot be related to the temperature or quality in any direct manner, and any other indirect relationships are not very apparent. The key to a correlation between the temperature of the processed material and the production schedule is the extruder flow rate. The flow rate affects the temperature of the molten plastic inside the extruder barrel, which means it also directly affects the quality of the final resin. Furthermore, the extruder is the critical machine in the extrusion process. Therefore, it determines the processing time of an order, serving as the basis for the scheduling problem. The extruded polymer resin must undergo quality control testing to ensure that quantitative quality measurements must meet specifications. This is formulated as a constraint, where the extruder flow rate is determined to generate an optimized production schedule while ensuring the quality is within range. The general scheduling problem at a plastics compounding plant is formulated as a mixed integer linear programming (MILP) model for a semi-continuous, multi-product plant with parallel production lines. The incorporation of quality considerations renders the problem a mixed integer nonlinear program (MINLP).
Another objective of the proposed research deals with providing insight into the economic aspects of the scheduling process under consideration. The scheduling problem is analyzed and relations for its various cost components are developed. A total opportunity cost function was suggested for use as the comprehensive criterion of optimality in scheduling problems. Sensitivity analysis showed that none of the individual criteria gives optimal or near optimal results when compared to the total opportunity cost.
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