Recent Advances in Data Mining for Industrial Engineering Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 260
Special Issue Editor
Interests: data mining; social networking; quality management; customer relationship management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the rapid development of big data and machine learning technologies, the field of industrial engineering is undergoing a digital revolution. The advancement of Industry 4.0 has made data mining methods a powerful tool for industrial engineers, enabling them to optimize production processes, enhance quality, reduce costs, and increase competitiveness. We particularly welcome submissions on the following topics (but they are not limited to):
- The application of data mining in the manufacturing industry, including production process monitoring, quality control, and supply chain management;
- Data analysis methods for industrial forecasting and predictive maintenance;
- The application of data mining in energy management and environmental protection;
- Intelligent decision support systems in industrial engineering;
- The use of data mining in the context of the Internet of Things (IoT);
- Machine learning algorithms and models in industrial engineering.
Prof. Dr. Long-Sheng Chen
Guest Editor
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Industry 4.0
- deep learning
- decision making
- forecasting and predictive maintenance
- production and marketing
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