Abstract
Present day consumers have wide variety of demands and needs leads to increased complexity in automobiles. The price war and high quality, imposes the automobile manufacturers to have flexible design with zero defects in a highly competitive market. Unlike other industry, the quality of automobile depends on parts (manufactured and supplied by third party supplier) used and on the assembling the vehicle. To achieve the high quality that is demanded by the customers, manufacturers and their suppliers must rely on Machine Vision to prevent defects at multiple stages of production. Machine Vision can be used to inspect the quality of automobile parts, pick and place using robots, assembly line (inspection before, after and placement verification), to find missing parts, completeness, welding and painting guiding on finished automotive bodies. In addition to this, Machine Vision is also used for parts traceability decoded by reading OCR, data matrix and barcode. Different automobiles can have different quality of parts depending on price range. Machine Vision can also be used to classify automotive parts based on the required quality using measurements. This publication explains the basics of machine vision and explore the solutions that can be used in automobile industry at different stages of production.
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Bhanu Prasad, P., Radhakrishnan, N., Bharathi, S.S. (2014). Machine Vision Solutions in Automotive Industry. In: Patnaik, S., Zhong, B. (eds) Soft Computing Techniques in Engineering Applications. Studies in Computational Intelligence, vol 543. Springer, Cham. https://doi.org/10.1007/978-3-319-04693-8_1
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DOI: https://doi.org/10.1007/978-3-319-04693-8_1
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