Optimisation of a Textile Process Using Taguchi Method

Abstract

Taguchi Method is explained in brief and one of the textile processes, called spinning process, is optimised by using Taguchi method for manufacturing optimum packing density of different technologies yarns. The effect of process variables like: lap hank, card draft, draft/doublings and drafts at speed frame, ring frame, rotor and air-jet spinning ma- chine on packing density parameters of respective technology yarn was analysed. The effect of noise variables was also accounted for. The trends of change in packing density with process variables are opposite to those of yarn diameter and helix angle of ring, rotor and air-jet yarns studied. The packing density is found to be the highest in air-jet yarn and the lowest in rotor yarn. Increase in draft in air-jet spinner and decrease in rotor spinner increase packing density of the re- spective yarns. The change in noise variables does affect the packing density parameters of yarns. Result analysis using Taguchi Method was according to the perception of some of the previous researcher on the subject. Hence, Taguchi method can be also used to optimise a textile process, where the product quality is highly variable and dependent on the combination of number of processes as well as on machine parameters. The application of Design of Experiment technique on the optimisation of an industrial process is being frequently used. These designs are considered as extremely useful tools in the modern industry. Infact, experimental designs have been used in the chemical industry for a long time and are now being increasingly used in other industries too. Several textile problems have also been studied by means of these techniques, though some of them are rather restricted in scope. Moreover, the optimisation of textile processes is quite cumbersome because it is affected by a number of fac- tors which may or may not be controllable. There are various ways to optimise the effect of controllable variables by using Designs of Experiments like Factorial, Central composite, Box - Behnken etc. The main draw back of all these tech- niques is their inability to take in to account the effect of uncontrollable factor, like environmental conditions, spindle to spindle variation etc. The replications used in these de- signs bring out the variability under similar experimental conditions and process parameters.