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Digital Twin for Energy-Intelligent Bakery Operations: Concepts and Applications

Author

Listed:
  • Tsega Y. Melesse

    (Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, 09124 Cagliari, Italy)

  • Mohamed Shameer Peer

    (Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, 09124 Cagliari, Italy)

  • Suganthi Ramasamy

    (Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, 09124 Cagliari, Italy)

  • Vigneselvan Sivasubramaniyam

    (Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, 09124 Cagliari, Italy)

  • Mattia Braggio

    (Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, 09124 Cagliari, Italy)

  • Pier Francesco Orrù

    (Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, 09124 Cagliari, Italy)

Abstract

The bakery industry is undergoing a profound digital transformation driven by the increasing need for enhanced energy efficiency, operational resilience, and a commitment to environmental sustainability. Digital Twin (DT) technology, recognized as a fundamental component of Industry 4.0, provides advanced capabilities for intelligent energy management across bakery operations. This paper utilizes a narrative and integrative review approach, conceptually integrating emerging developments in using DT with respect toenergy management in the baking industry, including real-time energy monitoring, predictive maintenance, dynamic optimization of production processes, and the seamless integration of renewable energy sources. The study underscores the transformative benefits of adopting DT technologies, such as improvements in energy utilization, greater equipment reliability, increased operational transparency, and stronger alignment with global sustainability objectives. It also critically examines the technical, organizational, and financial barriers limiting broader adoption, particularly among small and medium-sized enterprises (SMEs). Future research directions are identified, emphasizing the potential of artificial intelligence-driven DTs, the adoption of edge computing, the development of scalable and modular platforms, and the necessity of supportive policy frameworks. By integrating DT technologies, bakeries can shift from traditional reactive energy practices to proactive, data-driven strategies, paving the way for greater competitiveness, operational excellence, and a sustainable future.

Suggested Citation

  • Tsega Y. Melesse & Mohamed Shameer Peer & Suganthi Ramasamy & Vigneselvan Sivasubramaniyam & Mattia Braggio & Pier Francesco Orrù, 2025. "Digital Twin for Energy-Intelligent Bakery Operations: Concepts and Applications," Energies, MDPI, vol. 18(14), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:14:p:3660-:d:1699106
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    References listed on IDEAS

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