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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