LonWorks-based Virtual Device Network (VDN) for predictive maintenance

2003 ◽  
Vol 18 (1-3) ◽  
pp. 67-79 ◽  
Author(s):  
Ki Won Song ◽  
Gi Sang Choi ◽  
Gi Heung Choi ◽  
Jung Soo Kim
Keyword(s):  
Predictive Maintenance ◽  
Virtual Device

The Convergence between Predictive Maintenance and Augmented Reality to Aid Renewable Energy Equipment Availability

2014 ◽  
Vol 2 (5) ◽  
pp. 152
Author(s):  
José Manuel Torres Farinha ◽  
Inácio Adelino Fonseca ◽  
Rúben Silva Oliveira ◽  
Fernando Maciel Barbosa
Keyword(s):  
Renewable Energy ◽  
Augmented Reality ◽  
Predictive Maintenance ◽  
Equipment Availability ◽  
Energy Equipment

Nonlinear Trend Analysis of Mill Fan System Vibrations for Predictive Maintenance and Diagnostics

2012 ◽  
Vol 58 (4) ◽  
pp. 351-356
Author(s):  
Mincho B. Hadjiski ◽  
Lyubka A. Doukovska ◽  
Stefan L. Kojnov
Keyword(s):  
Power Plant ◽  
Trend Analysis ◽  
Thermal Power Plant ◽  
Power Plants ◽  
Thermal Power ◽  
Balkan Peninsula ◽  
Predictive Maintenance ◽  
Nonlinear Trend ◽  
The Subject ◽  
The Given

Abstract Present paper considers nonlinear trend analysis for diagnostics and predictive maintenance. The subject is a device from Maritsa East 2 thermal power plant a mill fan. The choice of the given power plant is not occasional. This is the largest thermal power plant on the Balkan Peninsula. Mill fans are main part of the fuel preparation in the coal fired power plants. The possibility to predict eventual damages or wear out without switching off the device is significant for providing faultless and reliable work avoiding the losses caused by planned maintenance. This paper addresses the needs of the Maritsa East 2 Complex aiming to improve the ecological parameters of the electro energy production process.

Predictive Maintenance based on mechanical unbalance severity analysis of rotating machines

2017 ◽  
Author(s):  
Dionisio Martins ◽  
Thiago de Moura Prego ◽  
Amaro Lima ◽  
Douglas Hemerly ◽  
Fabrício Lopes e Silva
Keyword(s):  
Predictive Maintenance ◽  
Rotating Machines

DESIGN OF THE VIRTUAL DEVICE FOR THE SIGNAL SPECTRUM CALCULATION IN THE LABVIEW ENVIRONMENT

2019 ◽  
Author(s):  
Tossenko O.M.
Keyword(s):  
Virtual Instrument ◽  
Spectral Characteristics ◽  
Spectral Composition ◽  
Automated System ◽  
Signal Spectrum ◽  
Measuring Instruments ◽  
Specific Information ◽  
Measuring Device ◽  
Virtual Device ◽  
Graphical Tool

The development of measuring instruments requires a specialist to know the principles of operation of advanced measuring systems. This article describes guidelines for creating a virtual appliance in LabVIEW. LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is a graphical application programming environment used as a standard tool for measuring, analyzing their data, further ma­ naging devices and objects under study. LabVIEW language is not like other programming languages. It does not create a program, but a virtual tool, designed not only for the simulation of certain processes, but also for the management of hardware and the study of real physical objects. The article deals with the task of designing application software for a specific information-measuring device, analyzes the capabilities of the LabVIEW environment for spectral analysis of various signals, outlines the basic principles and techniques of programming within the framework of the LabVIEW graphical environment during the basic stages of development. The procedure for creating a virtual device is described, which allows to evaluate the spectral composition of the signals, presents a graphical code of execution (diagram) to the program and a graphical tool interface of the virtual device. A number of basic elements used to develop the program are described. The simplicity of the graphic designs, the ease of installation on the field of the program, the clarity and readability of the program — all of which makes LabVIEW preferred over other languages of programming. In most cases, the experiment is the only source of reliable information. And the result is achieved much faster than the methods of "pure" theory. The article substantiates the effectiveness of using a development tool that allows to obtain a software product and ensure the fulfillment of all the basic functions of an automated system. Developing a software algorithm for calculating statistical parameters will help engineering students understand the order of determining spectral characteristics and their place in the structure of experimental research.

IoT based Predictive Maintenance in Manufacturing Sector

2020 ◽  
Author(s):  
Shikhil Nangia ◽  
Sandhya Makkar ◽  
Rohail Hassan
Keyword(s):  
Manufacturing Sector ◽  
Predictive Maintenance

scholarly journals The Role of Industry 4.0 and BPMN in the Arise of Condition-Based and Predictive Maintenance: A Case Study in the Automotive Industry

2021 ◽  
Vol 11 (8) ◽  
pp. 3438
Author(s):  
Jorge Fernandes ◽  
João Reis ◽  
Nuno Melão ◽  
Leonor Teixeira ◽  
Marlene Amorim
Keyword(s):  
Business Process ◽  
Automotive Industry ◽  
Industry 4.0 ◽  
Process Model ◽  
Business Process Management ◽  
Process Management ◽  
Predictive Maintenance ◽  
The Evolution Of Industry

This article addresses the evolution of Industry 4.0 (I4.0) in the automotive industry, exploring its contribution to a shift in the maintenance paradigm. To this end, we firstly present the concepts of predictive maintenance (PdM), condition-based maintenance (CBM), and their applications to increase awareness of why and how these concepts are revolutionizing the automotive industry. Then, we introduce the business process management (BPM) and business process model and notation (BPMN) methodologies, as well as their relationship with maintenance. Finally, we present the case study of the Renault Cacia, which is developing and implementing the concepts mentioned above.

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