Modern Manufacturing for Alloy Wheel Defect Detection using Image Processing and Application - Tuaniai Archevapanich; Woranidtha Krungseanmuang; Vasutorn Chaowalittawin; Posathip Sathaporn; Punyisa Chaowalittawin; Boonchana Purahong (My University, 2024)
This paper presents an innovative approach to identifying defects in alloy wheel production by integrating image processing techniques with a mobile application platform. The system receives X-ray alloy images from the factory via mobile phone, processes them using image processing techniques to enhance clarity and readiness for defect detection, and then transmits the processed images to a Django framework via a uniform resource locator (URL). Subsequently, the system detects defects in the images, encodes them in Base64 format, and sends them to the mobile application through an API (Application Program Interface) for display on the user interface. This well-designed system architecture offers manufacturers a comprehensive solution to ensure product quality, reduce costs, and enhance customer satisfaction.
Keywords: Industrial Vision Systems and Defect Detection; Metallurgy and Material Forming