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The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015

Lin, J., Naim, M. M. ORCID:, Purvis, L. ORCID: and Gosling, J. ORCID: 2017. The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015. International Journal of Production Economics 194 , pp. 135-152. 10.1016/j.ijpe.2016.12.003

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In 1994, through classic control theory, John, Naim and Towill developed the ‘Automatic Pipeline, Inventory and Order-based Production Control System’ (APIOBPCS) which extended the original IOBPCS archetype developed by Towill in 1982 ─ well-recognised as a base framework for a production planning and control system. Due to the prevalence of the two original models in the last three decades in the academic and industrial communities, this paper aims to systematically review how the IOBPCS archetypes have been adopted, exploited and adapted to study the dynamics of individual production planning and control systems and whole supply chains. Using various databases such as Scopus, Web of Science, Google Scholar (111 papers), we found that the IOBPCS archetypes have been studied regarding the a) modification of four inherent policies related to forecasting, inventory, lead-time and pipeline to create a ‘family’ of models, b) adoption of the IOBPCS ‘family’ to reduce supply chain dynamics, and in particular bullwhip, c) extension of the IOBPCS family to represent different supply chain scenarios such as order-book based production control and closed-loop processes. Simulation is the most popular method adopted by researchers and the number of works based on discrete time based methods is greater than those utilising continuous time approaches. Most studies are conceptual with limited practical applications described. Future research needs to focus on cost, flexibility and sustainability in the context of supply chain dynamics and, although there are a few existing studies, more analytical approaches are required to gain robust insights into the influence of nonlinear elements on supply chain behaviour. Also, empirical exploitation of the existing models is recommended.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Uncontrolled Keywords: IOBPCS; APIOBPCS; Production control; Planning control; Supply chain; Bullwhip effect
Additional Information: This journal has an embargo period of 36 months ( accessed 9.12.16
Publisher: Elsevier
ISSN: 0925-5273
Date of First Compliant Deposit: 8 December 2016
Date of Acceptance: 1 December 2016
Last Modified: 12 Nov 2023 00:40

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