Abstract
Advancement in the production industry moves towards automation due to an increase in demand. Artificial intelligence (AI) has been introduced in industrial applications to this scope. With the help of AI, industrial applications become more efficient, accurate, and adaptive. Machine learning (ML) is a branch of AI and a popular tool for the improvement of the industrial operations. Many believe that it is a suitable tool for the evolution of traditional manufacturing systems into Industry 4.0. Top manufacturing companies started to use ML to enhance their applications in production. The main objective of this research is to present a classification framework for the use of ML in design and manufacturing. The proposed framework includes four steps: design, material selection, testing, and decision-making steps. The classification framework methodology is validated with examples from the available literature. The framework highlights the areas most supported by ML in manufacturing and presents their potential integration as an open issue.