Identifying bottlenecks in manufacturing systems using stochastic criticality analysis

J.P. Nogueira Bastos, L.J. van der Sanden, O. Donk, J.P.M. Voeten, S. Stuijk, R.R.H. Schiffelers, H. Corporaal

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaties (Scopus)

Uittreksel

System design is a difficult process with many design-choices for which the impact may be difficult to foresee. Manufacturing system design is no exception to this. Increased use of flexible manufacturing systems which are able to perform different operations/use-cases further raises the design complexity. One important criterion to consider is the overall makespan and associated critical path for the different use-cases of the system. Stochastic critical path analysis plays a fundamental role in providing useful feedback for system designers to evaluate alternative specifications, which traditional fixed-time analysis cannot. In this paper, we extend our formal model-based framework, for the specification and design of manufacturing systems, with stochastic analysis abilities by associating a criticality index to each action performed by the system. This index can then be visualized and used within the framework such that a system designer can make better informed decisions. We propose a Monte-Carlo method as an estimation algorithm and we explicitly define and use confidence intervals to achieve an acceptable estimation error. We further demonstrate the use of the extended framework and stochastic analysis with an example manufacturing system.

TaalEngels
TitelFDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages
Plaats van productiePiscataway
UitgeverijIEEE Computer Society
Pagina's1-8
Aantal pagina's8
Volume2017-September
ISBN van elektronische versie978-1-5386-4733-2
ISBN van geprinte versie978-1-5386-1152-4
DOI's
StatusGepubliceerd - 27 feb 2018
Evenement2017 Forum on Specification and Design Languages, FDL 2017 - Verona, Italië
Duur: 18 sep 201720 sep 2017

Congres

Congres2017 Forum on Specification and Design Languages, FDL 2017
LandItalië
StadVerona
Periode18/09/1720/09/17

Vingerafdruk

Critical path analysis
Systems analysis
Specifications
Flexible manufacturing systems
Error analysis
Monte Carlo methods
Feedback

Trefwoorden

    Citeer dit

    Nogueira Bastos, J. P., van der Sanden, L. J., Donk, O., Voeten, J. P. M., Stuijk, S., Schiffelers, R. R. H., & Corporaal, H. (2018). Identifying bottlenecks in manufacturing systems using stochastic criticality analysis. In FDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages (Vol. 2017-September, blz. 1-8). [8303901] Piscataway: IEEE Computer Society. DOI: 10.1109/FDL.2017.8303901
    Nogueira Bastos, J.P. ; van der Sanden, L.J. ; Donk, O. ; Voeten, J.P.M. ; Stuijk, S. ; Schiffelers, R.R.H. ; Corporaal, H./ Identifying bottlenecks in manufacturing systems using stochastic criticality analysis. FDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages. Vol. 2017-September Piscataway : IEEE Computer Society, 2018. blz. 1-8
    @inproceedings{a99c3c0396fb4377aa7351420ac1540b,
    title = "Identifying bottlenecks in manufacturing systems using stochastic criticality analysis",
    abstract = "System design is a difficult process with many design-choices for which the impact may be difficult to foresee. Manufacturing system design is no exception to this. Increased use of flexible manufacturing systems which are able to perform different operations/use-cases further raises the design complexity. One important criterion to consider is the overall makespan and associated critical path for the different use-cases of the system. Stochastic critical path analysis plays a fundamental role in providing useful feedback for system designers to evaluate alternative specifications, which traditional fixed-time analysis cannot. In this paper, we extend our formal model-based framework, for the specification and design of manufacturing systems, with stochastic analysis abilities by associating a criticality index to each action performed by the system. This index can then be visualized and used within the framework such that a system designer can make better informed decisions. We propose a Monte-Carlo method as an estimation algorithm and we explicitly define and use confidence intervals to achieve an acceptable estimation error. We further demonstrate the use of the extended framework and stochastic analysis with an example manufacturing system.",
    keywords = "Bottleneck identification, Criticality analysis, Formal specification, Manufacturing systems",
    author = "{Nogueira Bastos}, J.P. and {van der Sanden}, L.J. and O. Donk and J.P.M. Voeten and S. Stuijk and R.R.H. Schiffelers and H. Corporaal",
    year = "2018",
    month = "2",
    day = "27",
    doi = "10.1109/FDL.2017.8303901",
    language = "English",
    isbn = "978-1-5386-1152-4",
    volume = "2017-September",
    pages = "1--8",
    booktitle = "FDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages",
    publisher = "IEEE Computer Society",
    address = "United States",

    }

    Nogueira Bastos, JP, van der Sanden, LJ, Donk, O, Voeten, JPM, Stuijk, S, Schiffelers, RRH & Corporaal, H 2018, Identifying bottlenecks in manufacturing systems using stochastic criticality analysis. in FDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages. vol. 2017-September, 8303901, IEEE Computer Society, Piscataway, blz. 1-8, Verona, Italië, 18/09/17. DOI: 10.1109/FDL.2017.8303901

    Identifying bottlenecks in manufacturing systems using stochastic criticality analysis. / Nogueira Bastos, J.P.; van der Sanden, L.J.; Donk, O.; Voeten, J.P.M.; Stuijk, S.; Schiffelers, R.R.H.; Corporaal, H.

    FDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages. Vol. 2017-September Piscataway : IEEE Computer Society, 2018. blz. 1-8 8303901.

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    TY - GEN

    T1 - Identifying bottlenecks in manufacturing systems using stochastic criticality analysis

    AU - Nogueira Bastos,J.P.

    AU - van der Sanden,L.J.

    AU - Donk,O.

    AU - Voeten,J.P.M.

    AU - Stuijk,S.

    AU - Schiffelers,R.R.H.

    AU - Corporaal,H.

    PY - 2018/2/27

    Y1 - 2018/2/27

    N2 - System design is a difficult process with many design-choices for which the impact may be difficult to foresee. Manufacturing system design is no exception to this. Increased use of flexible manufacturing systems which are able to perform different operations/use-cases further raises the design complexity. One important criterion to consider is the overall makespan and associated critical path for the different use-cases of the system. Stochastic critical path analysis plays a fundamental role in providing useful feedback for system designers to evaluate alternative specifications, which traditional fixed-time analysis cannot. In this paper, we extend our formal model-based framework, for the specification and design of manufacturing systems, with stochastic analysis abilities by associating a criticality index to each action performed by the system. This index can then be visualized and used within the framework such that a system designer can make better informed decisions. We propose a Monte-Carlo method as an estimation algorithm and we explicitly define and use confidence intervals to achieve an acceptable estimation error. We further demonstrate the use of the extended framework and stochastic analysis with an example manufacturing system.

    AB - System design is a difficult process with many design-choices for which the impact may be difficult to foresee. Manufacturing system design is no exception to this. Increased use of flexible manufacturing systems which are able to perform different operations/use-cases further raises the design complexity. One important criterion to consider is the overall makespan and associated critical path for the different use-cases of the system. Stochastic critical path analysis plays a fundamental role in providing useful feedback for system designers to evaluate alternative specifications, which traditional fixed-time analysis cannot. In this paper, we extend our formal model-based framework, for the specification and design of manufacturing systems, with stochastic analysis abilities by associating a criticality index to each action performed by the system. This index can then be visualized and used within the framework such that a system designer can make better informed decisions. We propose a Monte-Carlo method as an estimation algorithm and we explicitly define and use confidence intervals to achieve an acceptable estimation error. We further demonstrate the use of the extended framework and stochastic analysis with an example manufacturing system.

    KW - Bottleneck identification

    KW - Criticality analysis

    KW - Formal specification

    KW - Manufacturing systems

    UR - http://www.scopus.com/inward/record.url?scp=85045630106&partnerID=8YFLogxK

    U2 - 10.1109/FDL.2017.8303901

    DO - 10.1109/FDL.2017.8303901

    M3 - Conference contribution

    SN - 978-1-5386-1152-4

    VL - 2017-September

    SP - 1

    EP - 8

    BT - FDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages

    PB - IEEE Computer Society

    CY - Piscataway

    ER -

    Nogueira Bastos JP, van der Sanden LJ, Donk O, Voeten JPM, Stuijk S, Schiffelers RRH et al. Identifying bottlenecks in manufacturing systems using stochastic criticality analysis. In FDL 2017 - Proceedings of the 2017 Forum on Specification and Design Languages. Vol. 2017-September. Piscataway: IEEE Computer Society. 2018. blz. 1-8. 8303901. Beschikbaar vanaf, DOI: 10.1109/FDL.2017.8303901