Engineering Optimization and Industrial Applications Based on Industry 4.0/5.0
A special issue of Applied Sciences (ISSN 2076-3417).
Deadline for manuscript submissions: 31 March 2027 | Viewed by 261
Editor
Interests: Industry 4.0/5.0; reliability analysis; maintenance engineering; quality engineering; six sigma; AI; supply chain management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid evolution of industrial technologies has significantly transformed modern engineering practices, particularly through the emergence of Industry 4.0 and the more recent paradigm of Industry 5.0. These frameworks integrate advanced digital technologies with traditional manufacturing and engineering systems, enabling more efficient, adaptive, and intelligent industrial environments. Within this context, engineering optimization plays a crucial role in improving productivity, resource management, and decision-making processes across various industrial sectors. By leveraging data-driven approaches and computational intelligence, modern optimization techniques allow engineers to design systems that are not only technically efficient but also economically and environmentally sustainable.
Industry 4.0 introduced the widespread use of cyber–physical systems, the Internet of Things, and advanced data analytics in industrial operations. These technologies enable real-time monitoring and control of manufacturing processes, generating large volumes of operational data that can be analyzed to optimize system performance. Through the application of machine learning and predictive modeling, engineers can identify inefficiencies, forecast equipment failures, and optimize production workflows. As a result, industries can reduce downtime, enhance product quality, and improve overall operational efficiency.
Building upon these developments, Industry 5.0 shifts the focus toward a more human-centric and sustainable approach to industrial innovation. In this paradigm, advanced automation and intelligent systems are designed to collaborate with human expertise rather than replace it. Engineering optimization in this context involves balancing technological efficiency with human creativity, safety, and ethical considerations. Furthermore, sustainability has become a key objective, encouraging the development of energy-efficient processes, circular production models, and environmentally responsible manufacturing practices.
The goal of this Special Issue is the integration of optimization techniques with Industry 4.0 and Industry 5.0 technologies, representing a significant step toward the creation of intelligent and resilient industrial systems. Moreover, by combining advanced computational methods, real-time data analysis, and human–machine collaboration, modern engineering can address complex industrial challenges and contribute to the development of more efficient, adaptive, and sustainable production environments.
Prof. Dr. Panagiotis Tsarouhas
Guest Editor
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Keywords
- engineering optimization
- Industry 4.0
- Industry 5.0
- smart manufacturing
- industrial automation
- digital transformation
- internet of things
- cyber–physical systems
- machine learning
- artificial intelligence
- data analytics
- predictive maintenance
- smart supply chain
- industrial internet
- intelligent production systems
- human–machine collaboration
- advanced manufacturing systems
- smart factories
- digital twins
- process optimization
- industrial robotics
- sustainable manufacturing
- energy efficiency
- data-driven decision making
- autonomous systems
- lean/six sigma
- ιndustrial analytics
- industrial innovation
- digital manufacturing
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