Statistical Model for Predicting Compressed Air Consumption on Air-Jet Looms

Abstract

Compressed air is a major component of energy costs incurred in the weaving of textile fabrics on air-jet looms. The consumption of compressed air in air-jet weaving depends on different process variables. In this study, the effect of weft yarn count, reed count, fabric width and loom speed on the compressed air consumption of air-jet loom was determined using response surface methodology. Fabric width was found to be the most dominant factor affecting the air consumption followed by loom speed, reed count, and weft yarn count respectively. A statistical model for predicting the compressed air consumption on air-jet loom was developed. The prediction ability and accuracy of the developed model was assessed by the fitted line plot between the predicted and actual air consumption values. The prediction model may be used for optimizing the production planning, estimating the share of compressed air cost in weaving a particular fabric style, and in identifying any air wastages in the weaving shed by comparing the actual compressed air consumption with that predicted by the model which was developed under controlled conditions without any air leakages.