On the robustness of joint production and maintenance scheduling in presence of uncertainties
Abdelhamid Boudjelida ()
Additional contact information
Abdelhamid Boudjelida: Laval University
Journal of Intelligent Manufacturing, 2019, vol. 30, issue 4, No 1, 1515-1530
Abstract:
Abstract Production and preventive maintenance are very important functions in industry which act on the same resources. However, in most real workshops, the scheduling of their respective activities is independent and the constraint that they cannot be accomplished at the same time is rarely considered. Therefore, we are facing a joint scheduling problem of production and preventive maintenance tasks. In addition, this joint scheduling risks at any moment to deviate from the theoretical desired performances when facing disturbances due to various causes. Thus, we must still seek the most robust scheduling, i.e. the one that resists to uncertainties. This paper proposes a new approach to study robustness of joint production and maintenance scheduling in permutation flow shop workshops. The studied scheduling are generated according to two strategies: sequential and integrated. As methods of scheduling resolution, we will consider the well-known ants colony optimization, genetic algorithm, tabu search and some hybridizations of these methods. Our approach can be applied to other joint scheduling generating methods. In particular, we study how insertion of maintenance tasks can contribute to the robustness of production scheduling and how some scheduling strategies and methods are more robust than others. Several experimental results show the merits of our approach.
Keywords: Production scheduling; Maintenance; Robustness; Uncertainties; Flow shop; Metaheuristics (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://link.springer.com/10.1007/s10845-017-1303-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:30:y:2019:i:4:d:10.1007_s10845-017-1303-9
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845
DOI: 10.1007/s10845-017-1303-9
Access Statistics for this article
Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak
More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().