Litcius/Paper detail

Hybrid flow shop rescheduling for contract manufacturing services

Iracyanne Retto Uhlmann, Renata Mariani Zanella, Enzo Morosini Frazzon

2020International Journal of Production Research16 citationsDOI

Abstract

Several approaches for strategic and tactical integration of supply chains considering the demand management process have been proposed in the literature. However, in the context of Industry 4.0, there is a lack of studies related to the scheduling and rescheduling process integrating industries on the operational level. This paper proposes a novel hybrid flow shop rescheduling procedure to address the integration, on the operational level, of a contract manufacturer, who handles production execution and inventory control, and their industrial customers, who are in charge of the delivery planning process. The research question emerged from the empirical problem of connecting a contract manufacturer with its industrial customers. In alignment with the findings in the literature review, based on an updated conceptual model, a real hybrid flow shop was modelled using a multi-method approach that combines discrete event and agent-based simulation. The results show improvements in overall production and delivery performance. One can say that this is the first time that a production rescheduling problem is handled considering industries’ integration at the operational level. Even though the primary motivation of this research was to solve a production rescheduling issue in a Contract Manufacturer, the developed approach allows application in any B2B partnership.

Topics & Concepts

Computer scienceScheduling (production processes)Supply chainGeneral partnershipContext (archaeology)Production (economics)Process (computing)Operations researchDelivery PerformanceProcess managementOperations managementBusinessEngineeringEconomicsMarketingOperating systemMacroeconomicsFinancePaleontologyBiologyScheduling and Optimization AlgorithmsSupply Chain and Inventory ManagementAdvanced Manufacturing and Logistics Optimization