Integrated Workforce Allocation and Scheduling in a Reconfigurable Manufacturing System Considering Cloud Manufacturing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F21%3A00351242" target="_blank" >RIV/68407700:21730/21:00351242 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-85902-2_57" target="_blank" >https://doi.org/10.1007/978-3-030-85902-2_57</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-85902-2_57" target="_blank" >10.1007/978-3-030-85902-2_57</a>
Alternative languages
Result language
angličtina
Original language name
Integrated Workforce Allocation and Scheduling in a Reconfigurable Manufacturing System Considering Cloud Manufacturing
Original language description
The reconfigurable manufacturing system (RMS) has been acknowledged as an effective manufacturing paradigm to tackle high volatility in demand types and amounts. However, the reconfiguration needs an amount of time and leads to some level of resource wastage. Accordingly, a high frequency in the system’s reconfiguration may have a negative impact on its performance. In this regard, this paper investigates the advantage of using cloud manufacturing (CMfg) resources in enhancing the performance of an RMS system. A novel mathematical model is developed for the integrated workforce allocation and production scheduling problem utilizing the CMfg under a non-permutation flow shop setting. This model simultaneously makes decisions on the utilization of the CMfg capacity for performing some jobs, and for the remaining jobs, determination of machines’ configurations for each job, scheduling of the jobs on the machines, and allocation of operators to machines as well. This model aims to minimize the sum of job processing costs, overtime costs, and the cost of utilizing the CMfg resources. Finally, a computational experiment is conducted, which shows a promising improvement in the total cost of the production system by utilizing the CMfg capacity.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000466" target="_blank" >EF15_003/0000466: Artificial Intelligence and Reasoning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems
ISBN
978-3-030-85901-5
ISSN
1868-4238
e-ISSN
1868-422X
Number of pages
9
Pages from-to
535-543
Publisher name
Springer
Place of publication
Cham
Event location
Nantes
Event date
Sep 5, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000719354900057