A Novel Approach for Improving Quality and Process Optimization in the Garment Industry

Abstract

The garment industry is one of the intensive manufacturing industries operating in Sri Lanka, catering to the world’s number one brands from the US and Europe. Its contribution to the economy is immense. Given the situation explained above, we need to improve the technical know-how and the product quality for meeting the deadline with regards to on-time delivery. To be more competitive in the market to improve productivity and the quality of the product along with optimizing the process workflow with using improved techniques is a must. Due to the poor workmanship and other human errors and poor human supervision, the quality of products tends to decrease. Therefore, increasing efficiency and decreasing quality cost are the main objectives. This paper presents suitable solution using machine learning techniques such as a method to identify defect co-occurrences using association rule mining, a method to optimize employee leave management using classification techniques, a method to optimize seating arrangement in sewing lines using Genetic Algorithms, and a method to implement predictive maintenance of machinery using classification techniques in data mining.