Analysis of efficiency ladders used in apparel manufacturing line performance forecasting

Abstract

Apparel manufacturing is a highly labor-intensive industry where the most operations require highly skilled human worker involvement. Therefore the production performance of apparel manufacturing is mainly worker-dependent. Workers improve their performance in a task as repetitions take place. This phenomenon is called as the “Learning Curve”, studied by researchers and is largely prevalent in the apparel industry. Apparel manufacturers use production data of manufacturing/sewing lines and experience of the production-floor management staff to define an “Efficiency Ladder (EL)” to forecast the performance with task repetition. Our study investigated an average “Learning Curve (LC)” for sewing lines, which acts as a measurement and a forecasting tool for the production performance. Empirical data from a high end apparel manufacturer were collected to model the LC. Then the forecasting accuracy of the fitted LC was compared with the EL. This paper provides empirical evidence to the fact that LC is accurate in forecasting the performance increment with repetitions on daily basis; thus better to use in production planning than the EL.