AI Machine Learning Application to E-coat Process
Attendees will learn AI and machine learning concepts, a data centered management of a machine learning project, the training of a machine learning model, and the verification of a machine learning model. The power and limitations of applying machine learning to E-coat process will also to discussed.
AI Machine Learning (ML) has become more and more popular with time because businesses and industries are generating huge amounts of data, and the fast increasing power and speed of computers have made it possible to use machine learning algorithms to discover hidden information and correlations from the huge amounts of data. Many big companies have been increasingly making data-based decisions on product development, market research, and manufacturing process improvements. As a smart industrial company, Deere & Company has been using Machine Learning in its smart connected factories. Now, we have a project to develop a ML application to the E-coat process to optimize paint consumption and ensure paint quality. Through this project, we will understand the power and limitations of ML when applied to E-coat process. An E-coat system generates a huge amount of process data. ML modeling will be used in this project to discovery the hidden correlation between the process data and process efficiency and product quality. This project is targeted for completion by the end of this year. The presentation will share the highlights of the ML application to the E-coat process.
Learning Station III: Management in Today's Smart Industries