Engineering design of woven fabrics using non-traditional optimization methods: A comparative study

• Published in: Fibers and polymers Vol. 14; no. 9; pp. 1562 - 1567
• Main Authors: Das, Subhasis, Ghosh, Anindya, Banerjee, Debamalya
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-09-2013; Springer Nature B.V
• Subjects: Chemistry; Chemistry and Materials Science; Counting; Engineering design; Fabrics; Manufacturing costs; Optimization; Polymer Sciences; Simulated annealing; Swarm intelligence; Weaving; Fabric quality; Genetic algorithm; Simulated annealing; Fabric GSM; Particle swarm optimization; Weave parameters; Constrained optimization
• ISSN: 1229-9197; 1875-0052
• DOI: 10.1007/s12221-013-1562-9

This work aims to design woven fabrics with desired quality at optimum manufacturing cost by choice of suitable weaving parameters such as count, crimp and thread spacing of warp and weft yarns. To fulfill this goal, we endeavor to devise search based non-traditional optimization methods such as genetic algorithm, particle swarm optimization and simulated annealing for efficiently finding the appropriate combination of weave parameters. The quick response capability of the non-traditional optimization methods would benefit the fabric manufacturers for efficient determination of the required weaving parameters to produce the engineered fabrics. The experimental validation confirms that the particle swarm optimization is most suitable technique for engineering design of woven fabrics.