Abstract
Purpose The focus of this research is to identify the optimum commercial grade sewing thread and stitch density to be used with woven linen shirting fabric used in making men’s formal shirt. Maximum seam efficiency and interaction between the process parameters were assessed. Design/methodology/approach The classical method of optimisation involves varying one variable at a time and keeping the others constant. This is often useful, but it does not explain the effect of interaction between the variables under consideration. In this study, the response surface methodology was used for securing a more accurate optimisation of seam quality (seam efficiency) of woven linen shirting fabric. The response surface method is an empirical statistical technique used for multiple regression analysis of quantitative data obtained from statistically designed experiments by solving the multivariate equations simultaneously. Through this system, the input level of each process parameter, i.e. variable and the level of the selected response (seam efficiency), can be quantified. The central composite, Box–Behnken, is the common design used here. Findings The maximum seam efficiency is 79.62 per cent and 83.13 per cent in warp and weft direction, respectively, with optimum areal density (G) of 110 g/m2 of woven linen shirting fabric. The most suitable stitch density and ticket number of commercial grade sewing thread for woven linen shirting fabric are 13-13.5 and 40, respectively. Practical implications This study could help apparel manufacturers to evaluate seam quality, i.e. seam efficiency of woven linen fabric for men’s shirting, more effectively from the proposed regression model. The optimisation of the commercial grade sewing thread size and stitch density used in this study for woven linen shirting fabric within the range of 110-150 g/m2 will facilitate apparel engineers in production planning and quality control. Originality/value There is dearth of research on seam quality for woven linen shirting fabric using commercial grade sewing thread and engineering of prediction regression model for the estimation of seam efficiency by using process parameters, namely, fabric G, thread size and thread density and their interaction.
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