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A model for supply management of agile manufacturing supply chains

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  • Costantino, Nicola
  • Dotoli, Mariagrazia
  • Falagario, Marco
  • Fanti, Maria Pia
  • Mangini, Agostino Marcello

Abstract

This paper addresses the configuration problem of Manufacturing Supply Chains (MSC) with reference to the supply planning issue. Assuming that the manufacturing system is composed of different stages, we present a technique for the strategic management of the chain addressing supply planning and allowing the improvement of the MSC agility in terms of ability in reconfiguration to meet performance. More in detail, we enhance a previous design method by some of the authors that employs digraph modeling and integer linear programming to optimally design the MSC. The original approach avoids supply chain disruption and stock out and, at the same time, can manage spare parts distribution. In order to take into account the level of demands and maximum production capacities with single/multiple sourcing, in this new formulation we introduce supplier capacity constraints. A case study is presented describing the optimal MSC configuration of an Italian manufacturing firm. The obtained results show that the design method provides managers with key answers to issues related to the supply chain strategic configuration and agility, e.g., choosing the right location for distributors and retailers for enhanced MSC flexibility and performance.

Suggested Citation

  • Costantino, Nicola & Dotoli, Mariagrazia & Falagario, Marco & Fanti, Maria Pia & Mangini, Agostino Marcello, 2012. "A model for supply management of agile manufacturing supply chains," International Journal of Production Economics, Elsevier, vol. 135(1), pages 451-457.
  • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:451-457
    DOI: 10.1016/j.ijpe.2011.08.021
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    References listed on IDEAS

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    1. Sujan Piya & Ahm Shamsuzzoha & Mohammad Khadem & Nasr Al-Hinai, 2020. "Identification of Critical Factors and Their Interrelationships to Design Agile Supply Chain: Special Focus to Oil and Gas Industries," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(3), pages 263-281, September.
    2. Iftikhar, Ilaria Giannoccaro & Anas, 2023. "Mitigating ripple effect in supply networks: the effect of trust and topology on resilience," OSF Preprints 2spt3, Center for Open Science.
    3. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    4. Yusuf, Yahaya Y. & Gunasekaran, Angappa & Musa, Ahmed & Dauda, Mohammed & El-Berishy, Nagham M. & Cang, Shuang, 2014. "A relational study of supply chain agility, competitiveness and business performance in the oil and gas industry," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 531-543.
    5. Ivanov, Dmitry & Pavlov, Alexander & Sokolov, Boris, 2014. "Optimal distribution (re)planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics," European Journal of Operational Research, Elsevier, vol. 237(2), pages 758-770.
    6. Sudip Adak & G. S. Mahapatra, 2021. "Effect of inspection and rework of probabilistic defective production on two-layer supply chain incorporating deterioration and reliability dependent demand," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 565-578, June.
    7. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    8. Thomé, Antonio Márcio T. & Scavarda, Luiz Felipe & Pires, Sílvio R.I. & Ceryno, Paula & Klingebiel, Katja, 2014. "A multi-tier study on supply chain flexibility in the automotive industry," International Journal of Production Economics, Elsevier, vol. 158(C), pages 91-105.
    9. Morteza Abbasi & Reza Hosnavi & Mehrdad Mohammadi, 2013. "Designing a Fuzzy Strategic Integrated Multiechelon Agile Supply Chain Network," Journal of Optimization, Hindawi, vol. 2013, pages 1-16, June.
    10. Ivanov, Dmitry & Pavlov, Alexander & Dolgui, Alexandre & Pavlov, Dmitry & Sokolov, Boris, 2016. "Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 7-24.
    11. Mohd Fadzil Harun & Nurul Fadly Habidin & Nor Azrin Md Latip, 2017. "The relationship between 5S lean tool and WP of FMCG Warehouse in Peninsular Malaysia," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 7(6), pages 1019-1025, June.
    12. Yang, Jie, 2014. "Supply chain agility: Securing performance for Chinese manufacturers," International Journal of Production Economics, Elsevier, vol. 150(C), pages 104-113.
    13. Yusuf, Yahaya Y. & Musa, Ahmed & Dauda, Mohammed & El-Berishy, Nagham & Kovvuri, Dharma & Abubakar, Tijjani, 2014. "A study of the diffusion of agility and cluster competitiveness in the oil and gas supply chains," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 498-513.
    14. Safaei, Mehdi, 2014. "An integrated multi-objective model for allocating the limited sources in a multiple multi-stage lean supply chain," Economic Modelling, Elsevier, vol. 37(C), pages 224-237.

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