Delivery time dynamics in an assemble-to-order inventory and order based production control system
System dynamics play a critical role in influencing supply chain performance. However, the dynamic property of the assemble-to-order (ATO) system remain unexplored. Based on control theory, the inventory and order based production control system (IOBPCS) family, can be utilized as a base framework f...
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Veröffentlicht in: | International journal of production economics 2020-05, Vol.223, p.107531, Article 107531 |
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Sprache: | eng |
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Zusammenfassung: | System dynamics play a critical role in influencing supply chain performance. However, the dynamic property of the assemble-to-order (ATO) system remain unexplored. Based on control theory, the inventory and order based production control system (IOBPCS) family, can be utilized as a base framework for assessing system dynamics. However, the underlying assumption in traditional IOBPCS-based analytical studies is that the system is linear and the delivery time to end customers is negligible or backlog is used as a surrogate indicator. Our aim is to incorporate customer delivery lead-time variance as the third assessment measure alongside capacity availability and inventory variance as part of the so-called ‘performance triangle’– capacity at the supplier, the customer order decoupling point (CODP) inventory and the delivery lead-time. Using the ‘performance triangle’ and adopting non-linear control engineering techniques, we assess the dynamic behaviour of an ATO system in the electronics sector. We benchmark the ATO system dynamics model against the IOBPCS family. We exploit frequency response analysis to ensure a robust system design by considering three measures of the ‘performance triangle’. The findings suggest delivery LT variance can be minimised by maintaining the ATO system as a true Push-Pull hybrid state with sufficient CODP stock, although increased operational cost driven by bullwhip and CODP variance need to be considered. However, if the hybrid ATO system 'switches' to the pure Push state, the mean and variance of delivery LT can be significantly increased.
•Assess system dynamics of the PC ATO system with emphasis on delivery lead-time dynamics.•Introduce the ‘Performance Triangle’ concept based on the ATO system dynamics performance.•Propose a linearisation method to analytically study the delivery lead-time dynamics.•Delivery lead-time variance can be minimised by maintaining the hybrid Push-Pull-Pull state.•Establish the concepts of Maximum Reasonable Lead-time (MRL) and Minimum Reasonable Capacity (MRC). |
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ISSN: | 0925-5273 1873-7579 |
DOI: | 10.1016/j.ijpe.2019.107531 |