Title: Multi performance parameters analysis in a manufacturing system using fuzzy logic and optimal neural network model
Authors: R. Prasanna Lakshmi; P. Nelson Raja
Addresses: Fatima Michael College of Engineering and Technology, Madurai, India ' Fatima Michael College of Engineering and Technology, Madurai, India
Abstract: Support operations enhance machine conditions; additionally involve potential creation time, conceivably postponing the client orders. The target of this paper is to decide execution parameters in every work stations with foresee the cost, dependability and accessibility of the business. This estimate examination considers two sorts of various methodologies, for example, FLP ideal neural system model. At first utilising FLP to foresee the exhibitions parameters and expanding the exactness of examination by means of ANN with motivated enhancement procedure to upgrade the weights in structure. All the ideal results exhibit the way that the accomplished mistake values between the yield of the trial values and the anticipated qualities are firmly equivalent to zero in the planned system. From the outcomes the proposed KHO-based ideal neural system demonstrates the exactness is 98.23% it is contrasted with the Pareto improvement model.
Keywords: preventive maintenance; optimisation; neural network; fuzzy logic and manufacturing industry.
International Journal of Business Intelligence and Data Mining, 2018 Vol.13 No.4, pp.406 - 424
Accepted: 19 Dec 2016
Published online: 17 Jan 2018 *