A deep learning approach for integrated production planning and predictive maintenance-Reference-Cited by-同舟云学术

A deep learning approach for integrated production planning and predictive maintenance

Published:2023-01-24 Issue:23 Volume:61 Page:7972-7991
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Dehghan Shoorkand Hassan¹²,Nourelfath Mustapha¹²,Hajji Adnène³²

Affiliation:

1. Department of Mechanical Engineering, Laval University, Quebec, Canada

2. Interuniversity Research Center on Enterprise Networks, Logistics and Transportation (CIRRELT), Quebec, Canada

3. Department of Operations and Decision Systems, Laval University, Quebec, Canada

Funder

Canadian Natural Science and Engineering Research Council

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2022.2162618

Reference56 articles.

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3. An integrated production and preventive maintenance planning model

4. New integration of preventive maintenance and production planning with cell formation and group scheduling for dynamic cellular manufacturing systems

5. Arani M. M. Dastmard Z. D. Ebrahimi M. Momenitabar and X. Liu. 2020. “Optimizing the Total Production and Maintenance Cost of an Integrated Multi–Product Process and Maintenance Planning (IPPMP) Model.” In IEEE International Symposium on Systems Engineering (ISSE) Vienna Austria 1–8. IEEE.

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