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Cognex VIDI Kit: Deep Learning for the Automotive Industry - COGNEX Industrial IoT Case Study
Cognex VIDI Kit: Deep Learning for the Automotive Industry
The piston's compression ring serves several functions in a reciprocating engine, including sealing the combustion chamber and regulating fuel consumption. Defects on the compression ring are difficult to detect due to the reflective metal surface of the piston. The cylindrical shape of the piston is sometimes blurred and out of focus in the image. Normal variations in metal surface texture are expected as part of the manufacturing process, and some of these variations are acceptable, including rust spots, white areas, and surface cracks and fissures. But some long scratches that affect piston performance and threaten compression levels in the cylinder are the real flaws. The inspection system must be able to ignore normal variations and insignificant anomalies on the compression ring surface while identifying longer scratch defects.To program such complex inspections to rule-based algorithms would require complex defect databases. While manual detection is more flexible, it is too slow.
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Electric Vehicle Solutions Guide - COGNEX Industrial IoT Case Study
Electric Vehicle Solutions Guide
Low quality of human inspection in EV manufacturing
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Vision-guided Robots Simplify Component Production and Inspection - COGNEX Industrial IoT Case Study
Vision-guided Robots Simplify Component Production and Inspection
Executing the pick and place processes for simultaneous delivery and quality control of raw materials and finished components on the production line.
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