Intelligent real time control of disturbances in manufacturing systems

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.

Citation

Labib, A.W. and Yuniarto, M.N. (2005), "Intelligent real time control of disturbances in manufacturing systems", Journal of Manufacturing Technology Management, Vol. 16 No. 8, pp. 864-889. https://doi.org/10.1108/17410380510627861