Optimal control of an unreliable machine using fuzzy-logic control: from design to implementation

Abstract

In this paper, the development, implementation and validation of fuzzy logic to control an unreliable machine in manufacturing systems are presented. The fuzzy-logic controller developed in this context is based on the optimal control policy using hedging-point methodology. The fuzzy-logic controller has two-subsets of fuzzy-logic controls. The first provides a decision whether the system should produce part at make-to-stock or at make-to-order mode. The decision provided by the first fuzzy-logic control is then used by the second fuzzy-logic control to specify at what production rate the part should be produced. Simulation and implementation have been performed by controlling an unreliable machine using the developed fuzzy-logic controller. Then, the simulation results are compared with the simulation results given by the optimal control policy (hedging-point methodology). The results show that the performance of the developed fuzzy logic outperforms and is more precise than the hedging-point method under certain conditions.

Keywords:

• Fuzzy logic
• Hedging point
• Intelligent manufacturing system
• Optimal control
• Unreliable machine

Acknowledgements

We are grateful to the reviewers for their comments, which have made arguments for using fuzzy-logic control clearer. We have therefore decided to include our response in section 6. The authors would like to thank the European Commission and the partners of the Innovative Production Machines and Systems (I*PROMS) Network of Excellence (www.iproms.org), QUE-Project Indonesia and ORS Scheme for their supports.