Authors: Shyam Sharma, Pawan Deshmukh, Nilesh K. Borkar
Abstract: Modern manufacturing industries facing rapidly changing product demand, shorter product life cycles and increasing customization requirements. Traditional fixed manufacturing lines are less flexible and difficult to adapt for new product variants. Digital twin technology provide virtual representation of physical production systems and enable real-time monitoring, simulation and optimization. This paper review concept of digital twin-based dynamic manufacturing line reconfiguration, where production lines can be adjusted, balanced or restructured using virtual models before implementing changes in physical shop floor. Architecture, enabling technologies, modelling approaches and reconfiguration strategies are discussed. Benefits such as reduced downtime, improved productivity and enhanced decision support are analysed. Challenges including data integration, interoperability and computational complexity also highlighted. Finally, future research directions toward autonomous and self-reconfigurable factories are presented. Keywords: Digital twin, manufacturing line reconfiguration, smart factory, Industry 4.0, cyber-physical systems, dynamic production systems
Abstract: Modern manufacturing industries facing rapidly changing product demand, shorter product life cycles and increasing customization requirements. Traditional fixed manufacturing lines are less flexible and difficult to adapt for new product variants. Digital twin technology provide virtual representation of physical production systems and enable real-time monitoring, simulation and optimization. This paper review concept of digital twin-based dynamic manufacturing line reconfiguration, where production lines can be adjusted, balanced or restructured using virtual models before implementing changes in physical shop floor. Architecture, enabling technologies, modelling approaches and reconfiguration strategies are discussed. Benefits such as reduced downtime, improved productivity and enhanced decision support are analysed. Challenges including data integration, interoperability and computational complexity also highlighted. Finally, future research directions toward autonomous and self-reconfigurable factories are presented. Keywords: Digital twin, manufacturing line reconfiguration, smart factory, Industry 4.0, cyber-physical systems, dynamic production systems
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