IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v56y2018i22p6971-6992.html
   My bibliography  Save this article

Investigating the value of integrated operations planning: A case-based approach from automotive industry

Author

Listed:
  • Sandeep Kumar
  • Bhushan S. Purohit
  • Vikas Manjrekar
  • Vivek Singh
  • Bhupesh Kumar Lad

Abstract

During the last decade, many researchers have focused on joint consideration of various operations planning aspects like production scheduling, maintenance scheduling, inventory control, etc. Such joint considerations are becoming increasingly important from the point of view of current advancement in intelligent manufacturing, also known as Industry 4.0. Under the concept of Industry 4.0, advanced data analytics aim to remove human intervention in decision-making. Thus, the managerial level coordination of decisions taken independently by various departments will be out of trend. Therefore, developing an approach that optimises various operations planning decisions simultaneously is essential. Available literature on such joint considerations is more of the exploratory in nature and is limited to simplistic production environments. This necessitates the investigations of value of integrated operations planning for wide range of manufacturing scenarios. Present paper adopts a case-oriented approach to investigate the value of integrated operations planning. First, an integrated approach for simultaneously determining job sequencing, batch-sizing, inventory levels and preventive maintenance schedule is developed. The approach is tested in a complex production environment of an automotive plant and substantial economic improvement was realised. Second, a comprehensive evaluation is performed to study the robustness and implications of proposed approach for various production scenarios. Results of such pervasive performance investigations confirm the value of proposed approach over conventional approaches.

Suggested Citation

  • Sandeep Kumar & Bhushan S. Purohit & Vikas Manjrekar & Vivek Singh & Bhupesh Kumar Lad, 2018. "Investigating the value of integrated operations planning: A case-based approach from automotive industry," International Journal of Production Research, Taylor & Francis Journals, vol. 56(22), pages 6971-6992, November.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:22:p:6971-6992
    DOI: 10.1080/00207543.2018.1424367
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2018.1424367
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2018.1424367?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tambe, Pravin P. & Kulkarni, Makarand S., 2022. "A reliability based integrated model of maintenance planning with quality control and production decision for improving operational performance," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Anupama Prashar, 2023. "Title: production planning and control in industry 4.0 environment: a morphological analysis of literature and research agenda," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2513-2528, August.
    3. Delpla, Victor & Kenné, Jean-Pierre & Hof, Lucas A., 2023. "Integration of operational lockout/tagout in a joint production and maintenance policy of a smart production system," International Journal of Production Economics, Elsevier, vol. 263(C).
    4. Aseem K. Mishra & Divya Shrivastava & Devesh Tarasia & Abdur Rahim, 2022. "Joint optimization of production scheduling and group preventive maintenance planning in multi-machine systems," Annals of Operations Research, Springer, vol. 316(1), pages 401-444, September.
    5. Calabrese, Armando & Costa, Roberta & Tiburzi, Luigi & Brem, Alexander, 2023. "Merging two revolutions: A human-artificial intelligence method to study how sustainability and Industry 4.0 are intertwined," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:56:y:2018:i:22:p:6971-6992. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.