Algorithm based Digital Twinning for different stages of Microelectronic Manufacturing Cycle

The emerging globalization trend in the silicon manufacturing cycle has added vulnerabilities in production at different stages. Time-to-market requirements make the manufacturing process even more challenging. Digital twinning is one such recent method that can be used to model real things through input data sets. This technique mimics the real manufacturing process with the help of input data sets. The mentioned proposed framework introduces the use of algorithms with digital twinning for semiconductor manufacturing environments after taking all specified and interesting requirements and possible vulnerabilities in terms of feasible solutions and security liabilities into account, directly mimicking real design as it is through simulation upgrade digital twinning with algorithms at different stages of development and can ease learning and feedback to improve the performance of the manufacturing process. Usually, the silicon production cycle includes interpretation of ai artificial intelligence framework with formulations. These functions of objects are formed after expert analysis to enhance these models, algorithmic approaches can be used. This framework directs potential research possibilities in using DT (Digital Twins) for different stages of silicon manufacturing using Algorithms.