Computer Science: Latest Advances and New Trends in Maintenance and Performance Measurement
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (25 May 2022) | Viewed by 616
Special Issue Editors
Interests: machine learning; big data analysis; complex system; IoT; natural language processing
Special Issues, Collections and Topics in MDPI journals
Interests: information security; machine learning; big data analysis; complex system; IoT; artificial intelligence; social networking
Special Issues, Collections and Topics in MDPI journals
Interests: primarily concern analysis of the reliability; safety and maintenance of industrial plants; job safety; multicriteria decision making methodologies applied to industrial plant engineering and operations
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This issue aims at covering all the aspects related to the use of computer science in the maintenance and performance management of industrial systems. Business value creation requires companies to produce products and services enhancing the operational effectiveness and profitability of production assets. Thus, new production paradigms that benefit computer science advances, mainly in supporting decisions and analyzing process and asset performance, have been developed. Maintenance management is crucial for guaranteeing the operational performance, safety and sustainability of processes. Historical data analysis, typical for reliability and quality engineering and real time monitoring, together with advanced data analytics tools, spanning from artificial intelligence (AI) and machine learning (ML) to big data analytics, can create the base of knowledge necessary for improving decisions at operational, tactical and strategic levels, allowing better maintenance planning and scheduling, the adaptation of maintenance policies (preventive or predictive maintenance), maintenance service optimization, and business continuity.
This Special Issue seeks to share the experience from the different fields of engineering, industry and computer science and data analysis, for collecting and analyzing information on production flow and asset management in order to provide managers with new perspectives and tools useful for optimizing the maintenance planning of systems, to obtain the best operational performance. Moreover, this Special Issue seeks to discuss the state of the art of tools and models in both industrial applications and academia.
TOPICS
- Machine learning
- Internet of Things
- Natural language processing
- Complex system
- Data-driven maintenance
- Predictive maintenance
- Business process management
- Data security
- Innovative computing technologies for reliability
- Statistical process quality
- Decision support systems
APPLICATION AREAS
- Manufacturing
- Chemical and process industry
- Oil and gas industry
- Energy
- Facility management
- Critical infrastructures
- Cyberphysical systems
Prof. Vincenza Carchiolo
Prof. Michele Malgeri
Prof. Natalia Trapani
Guest Editors
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