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Optimization of spinning process using hybrid approach involving ANN, GA and linear programming

The spinning process is one of the important production processes in the textile industry. Yarn is created using Cotton Fibre on a rotor or ring spinning machine. The quality of resulting yarn is very important in determining their application possibilities. An important aspect of production process is selection of raw material, quality of resulting yarn and cost. The yarn should have Optimal Product Characteristics with minimum cost.
 The proposed paper aims to study profitability and predictability by developing computational model. ANN is used for prediction of yarn properties from fibre properties. These fibre properties are optimized using Genetic Algorithm(GA). GA also considers available stock into account. Linear Programming is used to decide proportionality of fibres in cotton bled and cost optimization. The result shows that the accuracy of proposed integrated approach is higher than Industrial Standards