A Demo of Microservice for Customized Faulty Product Detection System in Smart Manufacturing

Abstract

Product failure detection in smart manufacturing is important because it allows manufacturers to quickly identify and isolate faulty products before they reach the end of the production line. In today’s fast-paced and highly competitive business environment, manufacturers need to quickly and accurately identify product failures to stay competitive and meet customer expectations. Previously the product quality was inspected manually and now it is examined using a machine learning algorithm to overcome the limitations of manual inspection. However, in the latter case AI and ML experts are required to do the task. Therefore, to overcome such dependency, this work proposes a microservice to allow the end user (an industry person, as well as an automated hardware/software agent) to test different combinations of data science and AI tools and technologies without any AI expertise. The proposed microservice exposes APIs that make it possible to select different combinations of feature selection, sampling, and classification algorithm. A demo environment with a Postman collection that includes few API calls to demonstrate how the proposed module enables customized selection to detect faulty products, is also discussed.