AI-based Product Quality Controlling in an Anodizing Process

Product quality is a crucial factor of customer satisfaction and thus directly influences the competitiveness company. In manufacturing companies production processes obviously has significant impact on product quality. Therefore, establishing automated control offers considerable leverage for improving without necessarily increasing work efforts costs. this paper an artificial intelligence based pattern recognition method output anodising process aluminium parts discussed. use case presented here, customers have high aesthetic requirements regarding products which are used in expensive market segment with only limited fault tolerance. Preparation before going through manual, tedious, error-prone task that nevertheless requires highest precision. Small deviations can lead to problems causing rejections enforcing repetitions production. We discuss application visual image processing algorithm integrated into information system company monitor prevent human errors. Results show our approach reaches accuracy potentially improve delivery reliability respect time quantity by reducing cost-intensive