Abstract
Industries are required to enhance their production continuously in the contemporary environment. This can be achieved using a digital twin (DT), a physical object in a virtual version with artificial intelligence (AI). It closes the current gap between design and efficient information flow during the product manufacturing phase. Data gathering, statistical modeling, AI/machine intelligence, visualization, as well as monitoring are the pipeline phases. The many technology categories in the Permeability Model are connected to big data and AI technologies, wherein the choices are made by the DT system. A data-driven DT combined with first-order physical models is referred to as a hybrid DT. This chapter aims to explain the cutting-edge assessment of DT with AI that helps in efficient decision-making. A case study based on DT in industry, data acquisition, maintenance of industrial machinery and case study of JSC 120, a DT with AI in manufacturing, is described.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
