Aims and Scope
Research on Intelligent Manufacturing and Assembly (RIMA) (ISSN: 2972-3329) is an open access, continuously published, international, refereed journal publishing original peer-reviewed scholarly articles that are of general significance to technologies developed and studied for design, analysis, manufacturing and operation of Intelligent Manufacturing and Intelligent Equipment to provide a vital link between the research community and practitioners in industry.
Topics of interest include, but are not limited to the following:
• Digital design and manufacturing
• Theory, method and system of intelligent design
• Intelligent processing
• Intelligent monitoring and control
• Modelling, operation, control, optimization and scheduling of manufacturing system
• Manufacturing system simulation and digital twin
• Industrial control and industrial internet of things
• Safety critical equipment and reliability assessment
• Intelligent equipment
• Intelligent robot
Current Issue
Research Article
Detection of abnormal situations in the operation of communication channels
Currently, many countries have high expectations for the digitalization of economies, meaning various elements of automation. One of the most effective tools in achieving a new level of digitalization can be the Internet of Things (IoT). The development of IoT provokes the fourth industrial revolution (Industry 4.0), which will be marked by the transition to fully automated digital production, the use of cyber-physical systems and cloud computing. Processes will be controlled by "smart" devices online. An example of such smart devices is modern telecommunications equipment, the operation of which accumulates large amounts of data - telemetry of various kinds. This "big data" can be used to predict possible future failures and other faults (abnormal situations) in the equipment itself. This article is devoted to the issue of creating models of normal behavior of various characteristics of communication channels, which is central in creating predictive diagnostics systems. Examples of such models are given.
ISSN: 2972-3329 Abbreviation: Res Intell Manuf Assem Editor-in-Chief: Dr. Matthew Chin Heng Chua (Singapore) Publishing Frequency: Continuous publication Article Processing Charges (APC): 0 Publishing Model: Open Access |