Optimization of process parameters through fuzzy logic and genetic algorithm – A case study in a process industry

• Sugar mill industry has been taken for investigation.
• Failures of the boiler during the co generation process.
• Failures occur in the screw conveyor, drum feeder and grate.
• Critical parameters are identified by FMEA and fuzzy FMEA.
• Parameters are optimized by Taguchi method. Failures are minimized.
• Further optimized by Genetic algorithm. Failure free system has been obtained.

The simultaneous generation of steam and power, which is commonly referred to as cogeneration, has been adopted by many sugar mills in India to overcome the power shortage. It becomes an increasingly important source of income for sugar factories. The problems faced by the sugar mill industry arise mainly due to failures of either the complete system or some specific components during the cogeneration process. This paper presents the failure analysis of the boiler during the cogeneration process and provides solution to overcome these failures. The failures frequently occur in the screw conveyor and in the drum feeder of fuel feeding system and the grate of the boiler. In this research work, the statistical tools viz., Failure Mode and Effect Analysis (FMEA) and the Taguchi method have been applied to investigate and alleviate these failures. Since conventional FMEA has some limitations and Taguchi method does not give better solution, fuzzy FMEA has been employed to overcome the limitations and genetic algorithm technique has been applied to obtain failure – free system during the cogeneration process.

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