Special Issue "Data Mining Applications in Industry 4.0"
Deadline for manuscript submissions: closed (30 January 2022) | Viewed by 10987
Interests: industrial engineering; industrial symbiosis; energy management; sustainability; circular economy; additive manufacturing; lean manufacturing; quality management systems; sustainable energy systems
Special Issues, Collections and Topics in MDPI journals
Special Issue in Applied Sciences: Sustainable Energy Systems: Optimization and Efficiency
Special Issue in Electronics: Industrial Applications of Power Electronics
Special Issue in Journal of Sensor and Actuator Networks: Advanced Instrumentation for Power Converter Applications
Topical Collection in Sustainability: Industrial Symbiosis and Sustainability
Special Issue in Applied Sciences: Resilient and Sustainable Distributed Energy Systems
Special Issue in Energies: Planning, Integration and Management in Sustainable Energy Systems
Special Issue in Sustainability: Additive Manufacturing and Sustainability in the Digital Age: People, Factories and Businesses of the Future
Special Issue in Electronics: Industrial Applications of Power Electronics II
Special Issue in Electronics: Recent Advanced Applications of Virtual Industrial Informatics and Robotics
Special Issue in Energies: Sustainable and Smart Energy Management Systems: Energy 4.0 in Supply and Demand Side
Topical Collection in Sustainability: Industrial Symbiosis
Special Issue in Applied Sciences: Digital, Resilient and Sustainable Supply Chains: Research Trends and Future Challenges
Interests: business interoperability; supply chain management; knowledge management; information systems; business process modelling; multiple-criteria decision-making; computer simulation; axiomatic design
In the current economic and political environment, being able to gain a competitive edge is a priority for the industrial sector. Companies of all sizes are extremely interested in the possibilities and opportunities that Industry 4.0 offers. New tools available at industry’s disposal such as data mining, Internet of Things (IoT) and digital twins open up the possibility of production being more intelligently structured in the future, with more information at its disposal. The Internet of Things will find its way into all areas of demand in an intelligent and networked world. However, this means that enormous amounts of data will accumulate in all the production areas of the manufacturing industry. The challenge lies in identifying suitable technologies and then being able to smartly employ them to optimize production processes.
Large amounts of data can be utilized efficiently for production control. The predictive management and evaluation of production data and their analysis requires the implementation of suitable tools. The traceability allows saving valuable time and effort when analysing the production process. Big data and machine learning tools can also be used to optimize machine settings. Implementing them in the production process brings many advantages.
There is still much to explore regarding this new set of tools in the proactive and predictive use of the existing production data. This Special Issue intends to deepen the knowledge of data mining applications, one of the main aspects of Industry 4.0. The potential benefits that data mining applications can bring are diverse; therefore, contributions from different areas of research are welcome. Researchers are encouraged to submit contributions that touch on several aspects of data mining applications in the Industry 4.0 context and its relationship with several contiguous topics.
Dr. Radu Godina
Dr. Pedro Espadinha da Cruz
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- Industry 4.0
- Data mining
- Big data
- Smart factories
- Machine learning
- Industrial Internet of Things
- Smart manufacturing
- Cyber-physical systems
- Virtual reality
- Decision support systems
- Digital twins
- Augmented reality
- 3D printing
- Cloud computing