Intelligent real time control of disturbances in manufacturing systems

A. W. Labib*, M. N. Yuniarto

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Purpose - This paper aims to address the problem of real-time control and monitoring of a failure prone manufacturing system in an intelligent and optimum way. This paper also aims to bridge the existence of a gap between maintenance systems and production systems. Design/methodology/approach - A fuzzy logic based controller is used to achieve the desired target. Monitoring the process is performed by means of using supervisory control and data acquisition (SCADA) system. The integration between the fuzzy logic controller (FLC) and SCADA system is also presented. The software is developed and used to monitor and control a miniaturised system in online and real-time condition. Findings - This paper shows that by using fuzzy logic, the relationship between inputs and outputs is clearly shown, which eventually provide more tractable result than the dynamical analysis one. Moreover, the response surface generated by the fuzzy logic offers visual aid, adaptive and flexible operation to investigate the inputs and outputs relationships. Research limitations/implications - Future research direction would be to embed such a model into a user-friendly software. A further development would be to investigate means of generating the rule-based directly from the data without the need for eliciting knowledge from experts. Practical implications - This paper provided a practical applications that can help solving the problem of lack of real-time control and monitoring of a failure prone manufacturing system in an intelligent an optimum way. This paper also helped in bridging the existing gap between maintenance systems and production systems. Originality/value - The results of the performance comparisons show that in most studied cases, the performance of the developed system is better than the classical analytic approach.

Original languageEnglish
Pages (from-to)864-889
Number of pages26
JournalJournal of Manufacturing Technology Management
Volume16
Issue number8
DOIs
Publication statusPublished - 2005

Keywords

  • Fuzzy logic
  • Manufacturing industries
  • Manufacturing systems
  • Optimal control

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