An analysis of the application of digital twin technology for the optimization of automotive processes

A computational resource, such as a computer, server, or other piece of hardware, or a software-based resource, such as an operating system, can be created in a virtual form through virtualization. A method known as "digital twins," which compares digital objects with physical ones, was developed by researchers from the aerospace administration and was first proposed many years ago. The physics-controlled system may be edited, simulated, and examined using the digital models, which are based on digital twins. Due to the quickly shifting client demands, car manufacturers are currently dealing with a number of difficulties in meeting the delivery date. This happens as a result of several kinds of car bodywork being manufactured on the same line to satisfy the demands of various models' short life cycles. Accordingly, many facilities are needed for each step since different kinds of vehicle body manufacturers must be carried out. Due to the substantial quantity of machinery required, the manufacturing facility has a convoluted production chain. As a result, there are malfunctions at various facilities, which leads to faulty goods. The aforementioned issues make it impossible to follow the manufacturing schedule. In vehicle manufacturing facilities, it can be difficult to meet delivery deadlines since unplanned anomalous occurrences, such as product faults and equipment failures, regularly happen. Private information that has unanticipated, undesirable impacts on the subject's (driver's) privacy may be included in the data acquired. The scenario's goal is to demonstrate how the Digital Twin can be used as a tool to enhance privacy that links dynamic privacy data to the services of various stakeholders, produces fresh insights into privacy parameters, and spots privacy anomalies that can then be automatically reported back to the subjects. This review paper addresses the use of digital twin technology for the betterment of Automotive technology such as production lines, privacy use and Electric Vehicles.