Digital Twins in Mechanical Engineering, and a Brief Overview on Decarbonization and Sustainable System Optimization


Authors : Prasanna Adhithya Balagopal

Volume/Issue : Volume 10 - 2025, Issue 9 - September


Google Scholar : https://tinyurl.com/5f3arzc6

Scribd : https://tinyurl.com/ymnrx55j

DOI : https://doi.org/10.38124/ijisrt/25sep049

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Abstract : Climate change is pushing industries to cut down emissions fast, and mechanical engineering is playing a key role in that shift. One technology making a real difference is the digital twin — a live, virtual model of a machine or system that mirrors what’s happening in real life. It lets engineers track performance, test ideas, and catch problems early, all without interrupting operations. This paper looks at how digital twins are helping reduce carbon emissions across fields like manufacturing, energy, transport, and industrial systems. The benefits are clear: more efficient designs, better maintenance planning, and smarter use of energy. DTs also help track emissions in real-time and spot patterns that wouldn’t be obvious otherwise. In some setups, they've helped cut operational emissions by nearly 30%. Still, the use of digital twins isn’t as widespread as it could be. A lot of companies struggle with setup, especially when different machines and platforms don’t work well together. There’s also a lack of training and no strong, shared framework for using DTs in mechanical systems specifically. This paper explores those challenges and suggests how industries can move forward — by improving standards, encouraging collaboration, and giving engineers the tools and knowledge to apply this technology well. Digital twins aren’t just helpful add-ons; they have the potential to reshape how we design, monitor, and improve mechanical systems for a low- carbon future.

Keywords : Digital Twin, Mechanical Engineering, Decarbonization, Carbon Footprint, Sustainability, Real-time Simulation, Energy-efficient Design, Predictive Maintenance, Emission Tracking, System Optimization, Lifecycle Management, Low-carbon Innovation.

References :

  1. K. Iranshahi, J. Brun, T. Arnold, T. Sergi, and U. C. Müller, “Digital twins: Recent advances and future directions in engineering fields,” Intelligent Systems with Applications, vol. 26, p. 200516, 2025, doi: 10.1016/j.iswa.2025.200516.
  2. Dr. Mahalingam College of Engineering and Technology (MCET), “Digital twins and simulation: The future of mechanical engineering design,” MCET Blog, n.d.
  3. S. P. Ajegaonkar, A. R. Katoke, S. V. Bhingare, and S. R. Mane, “Development of digital twin model for mechanical application,” Journal of Physics: Conference Series, vol. 2601, no. 1, p. 012033, 2023, doi: 10.1088/1742-6596/2601/1/012033.
  4. M. N. Erofeev, I. N. Kravchenko, and M. V. Kryukov, “Integration of digital twins in mechanical engineering: Information support, modeling, and management of the product lifecycle,” Journal of Machinery Manufacture and Reliability, vol. 54, pp. 210–215, 2025, doi: 10.1134/S1052618824701747.
  5. C. C. Ohueri, M. A. N. Masrom, and T. E. Seghier, “Digital twin for decarbonizing operating buildings: A systematic review and implementation framework development,” Energy and Buildings, vol. 320, p. 114567, Oct. 2024, doi: 10.1016/j.enbuild.2024.114567.
  6. G. Barbano, A. Maguire, H. Singh, Z. Batayneh, L. De Donatis, N. Byrne, E. Heyvaert, R. Baeten, and C. Vandenhouten, “A physics-based digital twin baseline to decarbonize the built environment of airports: The Brussels Airport case,” Frontiers in Built Environment, vol. 10, Oct. 2024, doi: 10.3389/fbuil.2024.1393682.
  7. A. Tanase and C. Croitoru, “Optimizing building performance with digital twins: Pathways to energy efficiency and decarbonization,” E3S Web of Conferences, vol. 608, p. 01004, Jan. 2025, doi: 10.1051/e3sconf/202560801004.
  8. L. R. G. Cano, “How digital twins can make decarbonization a reality in the oil and gas industry,” IoT World Today, Dec. 6, 2023.
  9. “How pairing digital twin technology with AI could boost buildings’ emissions reductions,” Emerging Technologies, Mar. 19, 2024.

Climate change is pushing industries to cut down emissions fast, and mechanical engineering is playing a key role in that shift. One technology making a real difference is the digital twin — a live, virtual model of a machine or system that mirrors what’s happening in real life. It lets engineers track performance, test ideas, and catch problems early, all without interrupting operations. This paper looks at how digital twins are helping reduce carbon emissions across fields like manufacturing, energy, transport, and industrial systems. The benefits are clear: more efficient designs, better maintenance planning, and smarter use of energy. DTs also help track emissions in real-time and spot patterns that wouldn’t be obvious otherwise. In some setups, they've helped cut operational emissions by nearly 30%. Still, the use of digital twins isn’t as widespread as it could be. A lot of companies struggle with setup, especially when different machines and platforms don’t work well together. There’s also a lack of training and no strong, shared framework for using DTs in mechanical systems specifically. This paper explores those challenges and suggests how industries can move forward — by improving standards, encouraging collaboration, and giving engineers the tools and knowledge to apply this technology well. Digital twins aren’t just helpful add-ons; they have the potential to reshape how we design, monitor, and improve mechanical systems for a low- carbon future.

Keywords : Digital Twin, Mechanical Engineering, Decarbonization, Carbon Footprint, Sustainability, Real-time Simulation, Energy-efficient Design, Predictive Maintenance, Emission Tracking, System Optimization, Lifecycle Management, Low-carbon Innovation.

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Paper Submission Last Date
31 - December - 2025

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