A Comprehensive Framework for Digital Twin-Enabled Industry 4.0: Integration, Challenges and Future Prospects
Keywords:
Digital Twin (DT), Industry 4.0, Smart Manufacturing, Simulation Modeling, Cyber-Physical Systems (CPS)Abstract
A basic Industry 4.0 breakthrough, Digital Twin (DT) enables businesses in many industries to monitor operations in real-time and forecast maintenance needs, hence optimizing production processes. Researchers use a method combining real-world case data and deployment outcomes with textual research from published literature using quantitative evaluation. coupled with identification of adoption problems and highlighting useful examples from manufacturing alongside construction and supply chain management sectors, the systematic literature study reveals crucial DT adoption trends coupled with implementation technologies. The SWOT analysis evaluates DT integration by means of thorough study of its internal and external components, therefore exposing both favorable features as well as limiting ones. Different DT framework comparisons help to expose ideal practices by improving knowledge of interoperability coupled with standardizing and scalability across systems. By measuring performance and safety gains, predictive modeling via simulations examines how DT changes operational processes in industry. The study illustrates the main advantages of DT as it addresses important issues such cyber security risks and computing needs and standardizing standards, thus improving both manufacturing operational efficiency and sustainability. Researchers examine how block chain coupled with AR/VR and newly developed technologies such 5G help to advance DT capabilities. This study executes investigations of DT applications in healthcare and smart cities while emphasizing on policy platforms coupled with standardized techniques for broad DT adoption. Finding important research gaps that researchers should fill will help to guide the future paths for the development of DT technology.
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