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

Lin, Junyi, Naim, Mohamed Mohamed ORCID: https://orcid.org/0000-0003-3361-9400, Purvis, Laura ORCID: https://orcid.org/0000-0002-1425-5894 and Gosling, Jonathan ORCID: https://orcid.org/0000-0002-9027-9011 2016. The extension and exploitation of the inventory and order based production control system archetype from 1982-2015. Presented at: 19th International Working Seminar on Production Economics., Innsbruck, Austria, 18-22 February 2016.

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Abstract

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 (Towill 1982) ─ a well-recognized as a base framework for a production planning and control system. Due to the prevalence of two original models in the last three decades from academic and industrial communities, this paper aims to systematically review how the IOBPCS archetypes has been adopted, exploited and adapted to study the dynamics of individual production planning and control systems and whole supply chains. Using Scopus, Web of Science, Google Scholar, we found that the IOBPCS archetypes has 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 utilizing 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.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Completion
Status:	Unpublished
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > HD Industries. Land use. Labor
Date of First Compliant Deposit:	27 February 2017
Last Modified:	20 Jul 2023 18:21
URI:	https://orca.cardiff.ac.uk/id/eprint/98609

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