LAUSR

Abstract Demand fluctuations in make-to-order job shops lead to utilisation fluctuations and delivery delays, particularly in periods with high demand. Many job shop production companies therefore include some standardised products in their product mix and use a hybrid make-to-order/ make-to-stock production approach. However, as the control of a make-to-order job shop is usually focused on meeting due dates, which do not apply to make-to-stock items, integrating make-to-stock items in the control of a job shop is not straightforward. We propose four methods of integrating make-to-stock items in the control of a job shop and evaluate these using discrete event simulation in Python. We show that a popular but simple method of always giving priority to MTO items is strongly outperformed by more advanced methods of integrating MTS into job shop control as we have been able to reduce the MTS lost sales by a considerable 60%. We further show that considering up-to-date status information may improve the performance substantially. Loosening the due dates of MTS replenishment orders during periods of low MTS demand enables better use of the production capacity to maximise the delivery performance of MTO instead.