The Application of Big Data and Artificial Intelligence in Equipment Maintenance Support

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Engineering".

Deadline for manuscript submissions: closed (20 April 2024) | Viewed by 207

Special Issue Editor

School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi’an 710129, China
Interests: reliability engineering; system reliability analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Equipment maintenance support is an important component of generating modern combat equipment, and is necessary for military forces to carry out combat tasks. With the rapid development of combat theory, weapons, and equipment, maintenance support is developing in a manner that prioritizes intelligence, agility, and initiative . In order to solve common problems in the field of equipment maintenance support, such as insufficient data fusion, insufficient decision-making support, incomplete situation assessment, and inaccurate resource allocation, it is necessary to introduce emerging information technologies such as big data and artificial intelligence; connect data and the decision-making chain across the entire field of equipment maintenance support; and integrate the physical data of equipment maintenance support and the quantitative description of support elements. It is also important to develop models and algorithms for generating maintenance support plans, optimizing resource allocation trade-offs, simulating support effectiveness, and conducting situational awareness and early warning studies pertaining to typical combat operations; achieve the deep integration of elements in the field of equipment maintenance support, the real-time visualization of situations, the autonomous calculation of requirements, data-driven decision making, intelligent resource configuration, and risk pre-warning; and promote equipment maintenance support to enable precise perception, data decision making, and agile responses.

We welcome papers on the following topics:

  • digital portrait and quantitative evaluation technology for equipment maintenance support;
  • technology for the construction and simulation of multi-agent models for equipment maintenance support;
  • autonomous generation and design optimization technology for equipment maintenance support plans;
  • intelligent analysis and configuration optimization technology for equipment maintenance support resources;
  • equipment support system situation assessment and dynamic adjustment technology;
  • intelligent perception and early warning control technology for equipment maintenance and security situations.

Dr. Feng Zhang
Guest Editor

Manuscript Submission Information

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Keywords

  • equipment maintenance support
  • big data
  • artificial intelligence
  • data decision-making

Published Papers

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