The main aim of this research was to implement appropriate Statistical Process Control (SPC) techniques for quality characteristics on sewing floor of garment Industry. Among different SPC quality improvements tools, control charts have been selected. After analyzing and selecting different critical parameters based on company and customer requirements, the X-bar and R charts for variable and c-charts for attribute quality characteristics have been identified and implemented in the trouser sewing lines for quality improvement. The check points for selected control chart implementation have also been designed. Remedial action plans for the occurred special cause variations and process stability were developed. The project incorporated theoretical and on-job training schemes for different quality team members, to understand the SPC concept and its implementation procedure. After implementation, significant improvements in the sewing section were achieved. The four months analysis before and after implementation of the SPC tools showed that the rejection percentage was reduced from 9.141% to 6.4%. Successful implementation of the result of this project can significantly improve process performance of other similar manufacturing units with appropriate modification.
Apparel industry is not only one of the oldest, largest, labor-intensive, and most global industries but also the typical “starter” industry for countries engaged in export-orientated industrialization. To achieve such dreams, the industry has looked over different inter-dependable factors while producing different products. In this study, an effort has been made to establish a correlation between standard allowed minutes (SAMs) and efficiency of sewing section using different variables, including production rate, number of workstations, and operation breakdown, having a differential impact on both the selected variables. All the empirical analyses were planned in a vertically integrated textile company called Almeda Textile Private Limited Company (PLC), Ethiopia, starting from the basic product category (such as V-neck shirt) up to complicated workwear including military clothing and federal police uniforms of Ethiopia. The Pearson correlation coefficient method was chosen to find the relationship between bivariate linearly scaled variables using Statistical Package for Social Science (SPSS) software. The expected outcome will help in identifying the type of correlation and its significant level as well as its impact on the overall productivity of the sewing section which eventually leads to fulfilling the mission of attaining sustainable production capacity of the mentioned vertically integrated manufacturing company.