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Improving production planning through finite-capacity MRP

Author

Listed:
  • Tommaso Rossi
  • Rossella Pozzi
  • Margherita Pero
  • Roberto Cigolini

Abstract

Materials Requirement Planning (MRP) technique is widely employed by most manufacturing companies, even though field applications point out some weaknesses, including ignored production capacity constraints and fixed lead-times. These weaknesses often lead to infeasible production schedules, which trigger fluctuating workloads over time, significant adjustment effort and eventually unpredictably long lead times. This paper introduces a capacity-oriented MRP procedure that combines the traditional MRP procedure with an approach based on linear programming: in this way, requirement of lead times pre-determined a priori outside the MRP procedure is overcome. The new procedure is then applied to a real-life company and results highlight that feasible plans of orders are generated without requiring lead-times as input and without relevant computational burden.

Suggested Citation

  • Tommaso Rossi & Rossella Pozzi & Margherita Pero & Roberto Cigolini, 2017. "Improving production planning through finite-capacity MRP," International Journal of Production Research, Taylor & Francis Journals, vol. 55(2), pages 377-391, January.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:2:p:377-391
    DOI: 10.1080/00207543.2016.1177235
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    Cited by:

    1. Fahad Kh. A.O.H. Alazemi & Mohd Khairol Anuar Bin Mohd Ariffin & Faizal Bin Mustapha & Eris Elianddy bin Supeni, 2021. "A Comprehensive Fuzzy Decision-Making Method for Minimizing Completion Time in Manufacturing Process in Supply Chains," Mathematics, MDPI, vol. 9(22), pages 1-39, November.
    2. Alireza Pooya & Morteza Pakdaman, 2019. "Optimal control model for finite capacity continuous MRP with deteriorating items," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2203-2215, June.
    3. Cannas, Violetta G. & Gosling, Jonathan & Pero, Margherita & Rossi, Tommaso, 2019. "Engineering and production decoupling configurations: An empirical study in the machinery industry," International Journal of Production Economics, Elsevier, vol. 216(C), pages 173-189.

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