Evaluation of wet pneumatically spliced elastic denim yarns with fuzzy theory

Abstract

This paper focuses on the evaluation of wet pneumatic spliced elastic yarn performance using the fuzzy logic theory. Referring to Altinoz's study (Altinoz & Winchester, 2001), fuzzy logic method 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 suitable parameters and optimized splicing conditions such as yarn count, length of splice and duration of water joining, the results show that triangular membership gives better fitting of experimental results. Compared to the experimental properties, theoretical performances of the wet splice can be predicted in the desired field of interest. Our results also indicate that the splice performance remains influenced especially by the elastic yarn count and the splice length as well. In this work, the expert's opinions using our fuzzy logic model were formalized with precision. Compared with regression model, the fuzzy model gives a more accurate prediction than the regression model.