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 545

Special Issue Editors


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Guest Editor
Dipartimento di Matematica e Informatica, University of Catania, Catania, Italy
Interests: machine learning; big data analysis; complex system; IoT; natural language processing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Dipartimento di Ingegneria Elettrica, Elettronica Informatica (DIEEI), Università di Catania, I95125 Catania, Italy
Interests: information security; machine learning; big data analysis; complex system; IoT; artificial intelligence; social networking
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Dipartimento Ingegneria Elettrica, Elettronica e Informatica, Università degli Studi di Catania, I95125 Catania, Italy
Interests: maintenance modeling and applications; system reliability; prognostics and health management; asset management
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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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.

Published Papers

There is no accepted submissions to this special issue at this moment.
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