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http://dx.doi.org/10.14775/ksmpe.2016.15.4.051

Customized Pattern-Recognition Technique using Vision Measurement System Development in New Car Manufacturing Process  

Lee, Gyung-Il (Department of Mechanical System Engineering, Graduate School of Chosun University)
Kim, Jae-yeol (Department of Mechanical System Engineering, Chosun University)
Roh, Chi-sung (Department of Mechanical System Engineering, Graduate School of Chosun University)
Choi, Choul Jun (Dept. of Advanced Parts & Materials, Graduate School of Chosun University)
Publication Information
Journal of the Korean Society of Manufacturing Process Engineers / v.15, no.4, 2016 , pp. 51-59 More about this Journal
Abstract
Measurements of the automobile manufacturers are available anywhere and anytime, directly based on the criterion of failure is measured. The maintenance of high-precision production activities is direct evidence of the fact that competitive manufacturing activities are very important in determining the success of companies to recall defective starting from raw material costs. The current manufacturing sites produce calipers and clearance gauge the degree of tool only specific. Therefore, judging the quality, including the number of errors, requires a lot of attention to the dimension failures in day-to-day measurements and measurement tasks and duties repeated in difficult situations. In this paper, we aim to develop a vehicle manufacturing plant site using each of the manufacturing processes while operating a measurement tool. We display it using the Image Processing PC-based S/W with all those visual facts by management and recorded as image information a more accurate and current situation to obtain information and share visual measurements. We carry out research on the design and development vision inspection algorithm applied for pattern-recognition techniques that can help manufacturing site quality control.
Keywords
Patten Recognition Method; Vision Inspection; Image Processing; Vehicle Component;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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