The Digital Twin of Manufacturing Process Optimization in the Design Phase Using Genetic Algorithms and Al

Abstract

This paper explores the application of artificial intelligence, genetic algorithms, and digital twins to design-level manufacturing process optimization. A digital twin is a computerized model of the real process used to research and model various design scenarios. To effectively examine the design space and identify the best solutions, genetic algorithms inspired by nature's selection have been used. AI learns from previous modelling techniques and evolving scenarios for optimal performance. This includes attempting to reduce costs, increase time-to-market, and maximize industrial productivity.