Dynamic job shop scheduling with random order arrival, processing time uncertainty and imperfect equipment availability****

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Triangle Kitchen Ltd. (Triangle) is a leading Canadian manufacturer of high quality cabinetry products . Despite heavy investments in equipment and systems, its main production facility at Dieppe, NB is facing difficulties in meeting the delivery deadlines promised to its customers. A major cause of the delay problem is the machine scheduling system currently used by Triangle, which relies on simplistic rules to deal with uncertainty resulting from the randomness of new orders arrival, uncertain processing times and machine breakdowns. In this project, we will work closely with Triangle to investigate, develop and implement new data-driven approaches for machine scheduling that are well-suited for dynamic and stochastic production environments, in contrast to traditional approaches that assume a static and deterministic environment. We aim to build schedules that are robust against disruptions while being efficient at the same time. Advanced techniques of stochastic optimization, data analysis and meta-heuristics will be combined and utilized to develop a general methodology for dynamic scheduling under uncertainty. The new scheduling approach is expected to significantly improve the competitiveness position of Triangle in the North American market by enabling it to enhance the utilization of its equipment and labor, minimize operational wastes and inefficiencies and increase customer satisfaction. Besides the direct benefits to Triangle, in terms of alleviating its late delivery problem, the outcomes of this project can be utilized by other Canadian manufacturing companies working in similar environments. ************