Evaluating sewing thread consumption of jean pants using fuzzy and regression methods

Abstract

This study focuses on the evaluation of sewing thread consumption of jean pants using the fuzzy logic theory. Referring to literature works, fuzzy logic method remains an accurate method that allows a new level of flexibility over traditional mathematical methods in defining and evaluating constraints. The application of fuzzy rules and fuzzy memberships is discussed and investigated. Using the influential parameters and optimized sewing conditions (suitable adjusted regulations of each input) such as thread composition, needle size and fabric weight, the results show that sigmoid membership gives better fitting of experimental results. Compared with the experimental consumptions, theoretical findings of the jean pant can be predicted in the desired field of interest. The results also indicate that the pant consumed thread remains influenced especially by the thread properties and the needle size as well. Compared with regression model, the fuzzy model gives a more accurate prediction and provides widely the amount of sewing thread than the regression model.