Modelling the woven fabric strength using artificial neural network and Taguchi methodologies

Purpose - Jacquard woven fabrics are widely used in various sections of upholstery industry, where mattress cover is one of them. Strength of jacquard woven mattress fabric depends on several factors. The objective of this study is to model the multi-linear relationship between fibre, yam and fabric parameters on the strength of fabric using artificial neural network (ANN) and Taguchi design of experiment (TDOE) methodologies. Design/methodology/approach - TDOE was applied to determine the optimum design values and the contribution of each parameter. Robustness (performance) of models is measured by root mean squared error (RMSE). These tools will enable the user to predict the fabric strength from number of given inputs. It also provides the knowledge related to the contribution of fibre, yam and fabric parameters oil fabric strength. Fabrics tested in this study made from different fibre types and max/min level for several fabric and yam-related parameters. The models generated with TDOE and ANN methodologies were compared with the actual experimental data. Findings - It was found that ANN model gives better approximation with the minimum RMSE. Research limitations/implications; - The data taken from factory are related with jacquard woven fabric. Practical implications - This study has many practical implications that brings up a general approach for textile industry. During manufacturing, waste or scrap ratio can be reduced and production planning become more efficient. Originality/value - Firstly, before starting manufacturing in factory, we can easily predict the strength of woven fabric using the defined factors. This makes the model usable at the planning stage of the fabric. Secondly, the contribution of factors affecting fabric strength was determined. The ANN model generated in this study helps the engineers of planning department at the company easy to plan the manufacturing of fabric with a good estimation of fabric strength before the production order.