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Delivery time dynamics in an assemble-to-order inventory and order based production control system

Lin, Junyi, Naim, Mohamed and Spiegler, Virginia 2018. Delivery time dynamics in an assemble-to-order inventory and order based production control system. Presented at: Twentieth International Working Seminar on Production Economics, Innsbruck, Austria, 19-23 February.

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The dynamic performance of an inventory and order based production control system (IOBPCS) has traditionally been assessed via its service level capabilities, usually determined by capacity availability, measured by bullwhip, and net stock variance, with both having production costs implications. The underlying assumption in most analytical studies is that the IOBPCS is linear and the delivery time to the customer is negligible. Our aim is to incorporate delivery lead-time variance as the third measure, as part of the so-called ‘performance triangle’. The third, lead-time variance measure is especially important in nonlinear systems, due to capacity constraints, where products cannot always be delivered in the planned lead-time. Using the ‘performance triangle’, and adopting nonlinear control engineering techniques, we assess the dynamic behaviour of an assemble-to-order (ATO) production system, well-recognized in the electronics sector. We then exploit frequency response analysis to ensure a robust system design in all three measures of the performance triangle – capacity at the supplier, the customer order decoupling point (CODP) inventory and the delivery lead-time. Our findings suggest both bullwhip and delivery lead-time variance can be minimised by maintaining the ATO system as a true make-to-stock (MTS) / make-to-order (MTO) hybrid, by ensuring sufficient stock at the CODP. However, due to the nonlinearities, delivery lead-time variance is significantly increased if the hybrid ATO system 'switches' to a totally MTS state.

Item Type: Conference or Workshop Item (Paper)
Date Type: Completion
Status: Unpublished
Schools: Business (Including Economics)
Last Modified: 31 Jan 2020 03:25

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