Industrial AI in Manufacturing


Authors : Amulya Tiwari; Tanishk Verma; Dr. A.K Madan

Volume/Issue : Volume 7 - 2022, Issue 5 - May

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3NkhT9d

DOI : https://doi.org/10.5281/zenodo.6609306

Engineering expertise and the digitization of all business operations are the important factors in today's industrial firms' success. The engineer's design process and expertise are highly personal, and rulebased procedure explanations are almost always difficult and/or time-consuming. As a result, passing on existing information to new engineers, particularly training effort, is very challenging. Another issue is the lack of an overview of the company's existing components. Multiple designs and engineers spend their valuable time as a result of this. The goal of this approach is to use machine learning techniques to extract information from current CAD models and codify it. Furthermore, proper categorization and similarity analysis should reveal existing components rapidly.For this, an AI-based support system will be developed. Engineers merely need to adjust the parameters of the proposed components based on the application. The assistant should then be able to recommend an appropriate next design step based on the existing CAD data and design history. As a result, current CAD models' implicit empirical knowledge supports production-friendly design and the avoidance of design errors.

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