Digital Twins in the Industry 4.0
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: closed (30 May 2025) | Viewed by 1237
Special Issue Editor
Interests: decentralized manufacturing optimizations; multi-agent systems; robotics; Industry 4.0; digital twins
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As we enter the era of Industry 4.0, the concept of "digital twins" is revolutionizing industries, blending physical and digital worlds to create smarter, more efficient systems. This Special Issue (SI), “Digital Twins in Industry 4.0”, aims to explore the dynamic role that digital twins play in transforming industries, enhancing operations, and unlocking new opportunities for growth and optimization.
A digital twin is a virtual replica of a physical object, system, or process that mirrors its real-time performance, environment, and usage. In the context of Industry 4.0, digital twins enable industries to leverage advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), and data analytics to simulate, predict, and optimize processes across a wide array of sectors. From manufacturing and logistics to healthcare and energy, digital twins are helping industries achieve unprecedented levels of accuracy, control, and efficiency.
This SI will delve into how digital twins are accelerating the shift towards smart factories, predictive maintenance, and agile supply chains. By integrating real-time data and advanced analytics, digital twins allow for the continuous monitoring and optimization of equipment, production lines, and processes, significantly reducing downtime and costs.
One of the key objectives of this SI is to promote practical case studies from leading researchers and industries that have successfully implemented digital twin technologies. By describing real-world applications, participants will demonstrate how digital twins are used to enhance productivity, improve quality control, and streamline operations. This SI intends to include predictive maintenance in manufacturing, where digital twins help monitor machinery, detect early signs of wear, and prevent costly breakdowns. In logistics, digital twins are helping optimize supply chains, anticipate disruptions, and enhance the overall efficiency. Moreover, the role of digital twins in smart cities and sustainable infrastructure development will also be explored.
Beyond the technical aspects, this SI aims to emphasize the strategic importance of digital twins in shaping future industry trends and driving competitiveness. By bridging the gap between physical and digital domains, companies can create highly adaptive, resilient, and scalable systems, which are crucial for maintaining a competitive edge in today's rapidly evolving markets.
Authors are invited to submit original contributions on methods, models, and control architectures dealing with the intelligent control of future supply chains, including but not limited to the following topics:
- Digital twins and smart manufacturing;
- Industrial robotics and digital twins for automation;
- Predictive maintenance using digital twins in Industry 4.0;
- Digital twins in supply chain optimization;
- The optimization of production processes with digital twins;
- Digital models for product lifecycle management (PLM);
- Human–machine interactions in smart factories via digital twins;
- Achieving energy efficiency and sustainability using digital twins;
- Digital twins in quality control and inspections;
- Cyber-physical systems (CPSs) and digital twins in Industry 4.0.
Case studies, theoretical models, design methodologies, and literature reviews are especially welcome.
Dr. Silviu Rǎileanu
Guest Editor
Manuscript Submission Information
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Keywords
- digital twins
- Industry 4.0
- industrial robots
- Internet of Things
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