Using social network analysis for industrial plant layout analysis in the context of Industry 4.0

Leonilde Varela, Vijay Manupati, Suraj Panigrahi, Eric Costa, Goran Putnik

    Research output: Contribution to journalArticlepeer-review


    Social network analysis (SNA) is a widely studied research topic,
    which has been increasingly applied for solving different kinds of problems,
    including industrial manufacturing ones. This paper focuses on the application
    of SNA on an industrial plant layout problem. The study aims at analysing the
    importance of using SNA techniques to study the important relations between
    entities in a manufacturing environment, such as jobs and resources in the
    context of industrial plant layout analysis. Here, performance measures such as
    maximum completion time of jobs (makespan), resource utilisation, and
    throughput time have been considered to evaluate the system performance.
    Later, with the simulation analysis, the relationships between entities and their
    impact on the system performance is evaluated. The experimental results
    revealed that the proposed SNA approach supports to find the key machines of
    the systems that ultimately lead to the effective performance of the whole
    system. Finally, the identification of relations among these entities supported
    the establishment of an appropriate plant layout for producing the jobs in the
    context of industry 4.0.
    Original languageEnglish
    Pages (from-to)1-19
    JournalInternational Journal of Industrial and Systems Engineering
    Issue number1
    Publication statusAccepted/In press - 6 Apr 2018


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