Journal of Intelligent Manufacturing

, Volume 30, Issue 1, pp 59–78 | Cite as

Inventory management for a remanufacture-to-order production with multi-components (parts)

  • Fei Zhang
  • Zailin Guan
  • Li ZhangEmail author
  • Yanyan Cui
  • Pengxing Yi
  • Saif Ullah


In remanufacturing industries, inventory is significant because remanufacturing industries includes the stock of recycled products, stock of components (parts) after disassembly and refurbishing operation, stock of new parts purchased from manufacturers and stock of remanufactured products. Therefore, current research presents an approach to search an appropriate inventory policy for single product with multi-components for a third party remanufacturing company cooperated with the original equipment manufacturer (OEM). The third party for remanufacturing working in close cooperation with the OEM (such as dealer) can acquire the regional protection rules and can gain the technical support from the OEM. A general mathematical model is developed to describe the multiple components and multi-level inventory. Moreover, a case company problem is solved to validate the proposed model. Base on considered problem, the proposed model provided an efficient inventory management method to solve the situation in which remanufacturing company only recycled products but not components (parts). Furthermore, the presented model is significant to help the case company to set the best resource allocation by analyzing the impact on inventory policy from different replenishment quantities in remanufacturing process (recycling, disassembling and refurbishing). At last the proposed model is proved by a numerical experiment which used genetic algorithm (GA) to solve the inventory policy, and the result discusses the sensitivity analysis for model parameters in different replenishment quantities scenarios.


Remanufacturing Original equipment manufacturing Multiple varieties Multi-level inventory Inventory management 



This work has been supported by MOST (the Ministry of Science and Technology of China) under the Grants Nos. 2013AA040206, 2012BAF12B20, and 2012BAH08F04, and by the National Natural Science Foundation of China (Grants Nos. 51035001, 51121002 and 71131004), and National High Technology Research and Development Program of the P.R. China under Grant Nos. 2013AA040206

Conflict of interest

The author declares that there is no conflict of interests regarding the publication of this paper.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Fei Zhang
    • 1
  • Zailin Guan
    • 1
    • 2
  • Li Zhang
    • 1
    • 2
    Email author
  • Yanyan Cui
    • 1
    • 2
  • Pengxing Yi
    • 1
    • 2
  • Saif Ullah
    • 1
    • 2
    • 3
  1. 1.State Key Lab of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhanPeople’s Republic of China
  2. 2.HUST–SANY Joint Laboratory of Advanced Manufacturing TechnologyHuazhong University of Science and TechnologyWuhanPeople’s Republic of China
  3. 3.Department of Industrial EngineeringUniversity of Engineering and TechnologyTaxilaPakistan

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