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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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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