Understanding the drivers of marker efficiency for improved fabric utilization in apparel production: an analytical approach

Purpose: This study aims to investigate and identify the critical factors that exert a statistically significant influence on marker efficiency, with the ultimate goal of optimizing fabric utilization and minimizing material wastage in readymade garment (RMG) production. Methods: A quantitative research approach was utilized, analyzing primary data from 56 woven markers collected across three factories. The analysis employed Pearson Correlation Coefficients for relationship assessment, one-tailed hypothesis testing to confirm directional impact, and Multiple Linear Regression (MLR) followed by an ANOVA Test to assess the collective predictive power of the independent variables. Results: The MLR model predicting Marker Efficiency was statistically significant Prob (F-statistic = 0.000), explaining 32.72% (R2) of the variance. The Hypothesis Testing confirmed a statistically significant positive impact from Marker Length (r =0.4901), the strongest correlation). Marker Pieces (r = 0.3536). Functional Area (r = 0.3515). In contrast, Marker Width was found to have no statistically significant linear relationship (p = 0.1861). An almost perfect positive correlation was observed between Marker Efficiency and Fabric Utilization (r=0.9985).