| Abstract [eng] |
Production industry plays a significant role in contributing to the global economy market; the real challenge of these industries is to sustain their position in the market. The industry‘s value and place in the market are determined with the quality of the product it produces. The quality of the final product is very significant in any industry, and the same applies to the textile industry. This project focuses on the quality inspection techniques in the textile industry by analysing some of the defects present in the fabric with Image J as image analysis software and also on how the industry can improve its quality inspection technique. To study the quality inspection technique practically an industrial visit to Penguin Apparel (P) Ltd, Madurai India was made. The company was using textile fabric quality inspecting machine working according to ASTM D 5430-04 standard. The defects of textile fabric were compared with the standard four-point system based on which the material is accepted or rejected in the quality department. With the knowledge on the quality inspecting machines, for the research the defects were simulated in a Laboratory set up on four knitted fabric and scanned with V370 Epson scanner. The simulated faults (coloured defects, holes and oil stains) were initially measured manually. The scanned image of the fabric surface with defect was prepared for using the Image J software, where defects were measured and graded according to the defect shape and size. The results of image analysis were compared with the manually measured defect, which showed that both measurements had little variations. Proposed quality inspection process with adopted image analysis technique can be a part of an automated quality inspection process of textile production and sewing company. Implementing automated systems for the production and quality management could boost profit and growth rate of the company, and it targets on increasing its efficiency rate in the market with minor defects in future. Proposed image analysis technique can be replicated in large scale production; for the measurement images in a large screen can be used, and defects can be easily predicted with the human eye also. Further, quality inspection supplemented by image analysis eliminates human error and makes the process more fast, reducing time and also cutting labour costs. Automation of quality control and production could contribute to increasing the profit and efficiency of the chosen company. |
