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

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  • Lin, J.
  • Naim, M.M.
  • Purvis, L.
  • Gosling, J.

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 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 (113 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.

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  • Lin, J. & Naim, M.M. & Purvis, L. & Gosling, J., 2017. "The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015," International Journal of Production Economics, Elsevier, vol. 194(C), pages 135-152.
  • Handle: RePEc:eee:proeco:v:194:y:2017:i:c:p:135-152
    DOI: 10.1016/j.ijpe.2016.12.003
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    Cited by:

    1. Zhou, Yuxuan & Wang, Xun & Naim, Mohamed M. & Gosling, Jonathan, 2022. "A system dynamics archetype to mitigate rework effects in engineer-to-order supply chains," International Journal of Production Economics, Elsevier, vol. 250(C).
    2. Dejian Yu & Zhaoping Yan, 2021. "Knowledge diffusion of supply chain bullwhip effect: main path analysis and science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8491-8515, October.
    3. Zhuoqun Li & Weiwei Fei & Ermin Zhou & Yuvraj Gajpal & Xiding Chen, 2019. "The Impact of Lead Time Uncertainty on Supply Chain Performance Considering Carbon Cost," Sustainability, MDPI, vol. 11(22), pages 1-19, November.
    4. Lin, Junyi & Naim, Mohamed M. & Spiegler, Virginia L.M., 2020. "Delivery time dynamics in an assemble-to-order inventory and order based production control system," International Journal of Production Economics, Elsevier, vol. 223(C).
    5. Yang, Y. & Lin, J. & Liu, G. & Zhou, L., 2021. "The behavioural causes of bullwhip effect in supply chains: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 236(C).
    6. Ponte, Borja & Cannella, Salvatore & Dominguez, Roberto & Naim, Mohamed M. & Syntetos, Aris A., 2021. "Quality grading of returns and the dynamics of remanufacturing," International Journal of Production Economics, Elsevier, vol. 236(C).
    7. Lin, Junyi & Zhou, Li & Spiegler, Virginia L.M. & Naim, Mohamed M. & Syntetos, Aris, 2022. "Push or Pull? The impact of ordering policy choice on the dynamics of a hybrid closed-loop supply chain," European Journal of Operational Research, Elsevier, vol. 300(1), pages 282-295.
    8. Ponte, Borja & Framinan, Jose M. & Cannella, Salvatore & Dominguez, Roberto, 2020. "Quantifying the Bullwhip Effect in closed-loop supply chains: The interplay of information transparencies, return rates, and lead times," International Journal of Production Economics, Elsevier, vol. 230(C).
    9. María Arquer & Borja Ponte & Raúl Pino, 2022. "Examining the balance between efficiency and resilience in closed-loop supply chains," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(4), pages 1307-1336, December.
    10. Lin, Junyi & Huang, Hongfu & Li, Shanshan & Naim, Mohamed M., 2023. "On the dynamics of order pipeline inventory in a nonlinear order-up-to system," International Journal of Production Economics, Elsevier, vol. 266(C).
    11. Plaza, Malgorzata & David, Iulian & Shirazi, Farid, 2018. "Management of inventory under market fluctuations the case of a Canadian high tech company," International Journal of Production Economics, Elsevier, vol. 205(C), pages 215-227.
    12. Ponte, Borja & Puche, Julio & Rosillo, Rafael & de la Fuente, David, 2020. "The effects of quantity discounts on supply chain performance: Looking through the Bullwhip lens," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    13. Ponte, Borja & Costas, José & Puche, Julio & Pino, Raúl & de la Fuente, David, 2018. "The value of lead time reduction and stabilization: A comparison between traditional and collaborative supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 165-185.
    14. Ponte, Borja & Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2022. "The implications of batching in the bullwhip effect and customer service of closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 244(C).
    15. Huthaifa AL-Khazraji & Colin Cole & William Guo, 2021. "Optimization and Simulation of Dynamic Performance of Production–Inventory Systems with Multivariable Controls," Mathematics, MDPI, vol. 9(5), pages 1-13, March.
    16. Cannas, Violetta Giada & Gosling, Jonathan, 2021. "A decade of engineering-to-order (2010–2020): Progress and emerging themes," International Journal of Production Economics, Elsevier, vol. 241(C).

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