Abstract
A computer vision system is implemented to detect errors in the cutting stage within the manufacturing process of garments in the textile industry. It provides solution to errors within the process that cannot be easily detected by any employee, in addition to significantly increase the speed of quality review. In the textile industry as in many others, quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years. For this reason, the objective of this project is to design a quality control system using computer vision to identify errors in the cutting stage within the garment manufacturing process to increase the productivity of textile processes by reducing costs.
Highlights
In the textile industry, quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years, observing the product, analysing it, classifying it and discovering its imperfections
It is necessary to evaluate methods to increase the efficiency of these processes, focusing on the use of automatic machines to find small details that those in charge of the inspection cannot observe, so that the quality control is a competitive advantage in the textile industry [1]
As for the device being implemented for processing, it is an embedded system Raspberry Pi 3 (Fig. 1), which has an operating system based Linux, Raspbian, in which an application compiled in OpenCV or free software to make it possible the implementation of complete computer vision system [2], [3]
Summary
Quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years, observing the product, analysing it, classifying it and discovering its imperfections. It is necessary to evaluate methods to increase the efficiency of these processes, focusing on the use of automatic machines to find small details that those in charge of the inspection cannot observe, so that the quality control is a competitive advantage in the textile industry [1]. The Raspberry Pi 3 system has been chosen due to its hardware performance and the relative ease of using Raspbian for the intended implementation; some other development boards, such as Arduino, would force a more complex computer vision program with no apparent benefit compared to Raspberry Pi 3, in turn, the low consumption and small dimensions of the Raspberry Pi 3 make it ideal for its handling, assembly and operation, compared to a conventional computer
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