Condition Based Maintenance
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2020 IEEE 18th International Conference on Industrial Informatics (INDIN)
INDIN focuses on recent developments, deployments, technology trends, and research results in Industrial Informatics-related fields from both industry and academia
ISIE focuses on advancements in knowledge, new methods, and technologies relevant to industrial electronics, along with their applications and future developments.
All topics related to engineering and technology management, including applicable analytical methods and economical/social/human issues to be considered in making engineering decisions.
The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.
The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...
Component parts, hybrid microelectronics, materials, packaging techniques, and manufacturing technology.
Electrical insulation common to the design and construction of components and equipment for use in electric and electronic circuits and distribution systems at all frequencies.
The magazine covers theory, analysis, design (computer-aided design), and practical implementation of circuits, and the application of circuit theoretic techniques to systems and to signal processing. Content is written for the spectrum of activities from basic scientific theory to industrial applications.
IET and IAM Asset Management Conference 2011, 2011
Physical assets in the electricity transmission and distribution networks are aging in such a complicated way that this process is difficult to fully reproduce in a laboratory environment. This leads to the underdevelopment of knowledge rules for diagnosis methods. In this paper, we interpret this underdevelopment as a "diagnosis error indicator" and integrate it with a simple reliability model of ...
2011 IEEE International Conference on Information Reuse & Integration, 2011
In condition-based maintenance (CBM), the item is preventively replaced if failure risk exceeds a pre-determined threshold. The optimal replacement threshold is often determined such that the average maintenance costs per unit time due to preventive and failure replacements is minimized. It is assumed that inspections are performed at equal time intervals with no cost. However, in many practical situations, inspection ...
2012 IEEE International Conference on Condition Monitoring and Diagnosis, 2012
PLN P3B Jawa Bali is changing its maintenance strategy from time-based and corrective-based maintenance to a combination of time-based, corrective-based and condition-based maintenance. Because of its crucial function in a power grid, PLN P3B Jawa Bali is developing the condition-based maintenance for 500 kV circuit breakers. The keys of such maintenance strategy are inspections and assessment. This paper discusses the ...
IEEE Transactions on Instrumentation and Measurement, 2011
A new concept of nonparametric signal detection and classification technique is proposed using mutual information measures in the time-frequency domain. The time-frequency-based self-information and mutual information are defined in terms of the cross time-frequency distribution. Based on time-frequency mutual information theory, this paper presents applications of the proposed technique to real-world vibration data obtained from a dedicated condition- based-maintenance experimental ...
2012 5th Robotics and Mechatronics Conference of South Africa, 2012
Intelligent systems have greatly contributed in automating the process segments that includes the maintenance function in the manufacturing industries. The purpose of this research was to come up with an intelligent monitoring tool to reduce the number of breakdowns in Krones machinery. The objective of the research was motivated by considering Human Machine Interface (HMI) and automatic monitoring of the ...
Heuristics for Design for Reliability in Electrical and Electronic Products
A Transformer-Based Inverted Complementary Cross-Coupled VCO with a 193.3dBc/Hz FoM and 13kHz 1/f3 Noise Corner: RFIC Interactive Forum
How to Cope with an Increasing Number of Objectives in Optimization - Xin Yao - WCCI 2016
Cryogenics for Applied Superconductivity - ASC-2014 Plenary series - 11 of 13 - Friday 2014/8/15
Uncovering the Neural Code of Learning Control - Jennie Si - WCCI 2012 invited lecture
EDOC 2010 - Sylvain Halle - Best Paper Presentation
EPICS In IEEE Spotlight - NJIT 2016 Project
5G & the Role of AI - Keynote Jennifer Yates - IEEE Sarnoff Symposium, 2019
Owning a Tesla, Going Electric - IEEE Southern Minnesota presentation
2015 IEEE Honors: IEEE Richard M. Emberson Award - Raymond Sverre Larsen
Single Frame Super Resolution: Fuzzy Rule-Based and Gaussian Mixture Regression Approaches
Vint Cerf: A Globecom 2019 Keynote
A High-Efficiency Linear Power Amplifier for 28GHz Mobile Communications in 40nm CMOS: RFIC Interactive Forum 2017
Designing for Sustainability - GHTC 2012 Session - Christopher Freitas
Autonomous Systems: Managing Risk and Reward - IEEE AI & Ethics Summit 2016
Energy Efficient Single Flux Quantum Based Neuromorphic Computing - IEEE Rebooting Computing 2017
Prototyping & Feasibility of Palpitation Display Apparatus - Sakura Sikander - IEEE EMBS at NIH, 2019
Micro-Apps 2013: Precision RF/MW Cable and Antenna Test in the Field
Large Scale Data Mining Using Genetics-Based Machine Learning 1
Physical assets in the electricity transmission and distribution networks are aging in such a complicated way that this process is difficult to fully reproduce in a laboratory environment. This leads to the underdevelopment of knowledge rules for diagnosis methods. In this paper, we interpret this underdevelopment as a "diagnosis error indicator" and integrate it with a simple reliability model of power cables. Based on the model, failures, replacements and diagnoses are simulated in order to understand the life cycle cost when time-based maintenance (TBM) or condition-based maintenance (CBM) is applied. The simulation results show that the profitability of CBM relies heavily on the readiness of knowledge rules. In the final conclusion, a "transitional" maintenance strategy is proposed for the initial stage of the application of diagnostic tools, in order to avoid the excessive cost of CBM caused by incomplete and unfinished knowledge rules.
In condition-based maintenance (CBM), the item is preventively replaced if failure risk exceeds a pre-determined threshold. The optimal replacement threshold is often determined such that the average maintenance costs per unit time due to preventive and failure replacements is minimized. It is assumed that inspections are performed at equal time intervals with no cost. However, in many practical situations, inspection cost is considerable and, thus, it is reasonable to inspect less during the time the item is in healthier states, and, to perform more inspections as the item degrades, namely, using a condition-based inspection scheme as opposed to a constant interval inspection scheme. In this paper a two-step approach, for the determination of the replacement threshold and a cost-effective condition-based inspection scheme for CBM, is proposed. In the first step, assuming that inspections are performed at equal time intervals with no cost, the optimal replacement threshold is determined. This assumption is, then, relaxed and its consequences on total average cost are evaluated using a proposed iterative procedure to obtain the condition-based inspection scheme. The proposed approach is illustrated through a numerical example.
PLN P3B Jawa Bali is changing its maintenance strategy from time-based and corrective-based maintenance to a combination of time-based, corrective-based and condition-based maintenance. Because of its crucial function in a power grid, PLN P3B Jawa Bali is developing the condition-based maintenance for 500 kV circuit breakers. The keys of such maintenance strategy are inspections and assessment. This paper discusses the methodology of the improved maintenance strategies which aims to recognize the condition of a 500 kV circuit breaker. The concept development of the condition-based maintenance for 500 kV circuit breakers was approached by using the FMEA/FMECA technique. Accordingly, we need to implement visual inspection and in-service measurement as well as offline measurement.
A new concept of nonparametric signal detection and classification technique is proposed using mutual information measures in the time-frequency domain. The time-frequency-based self-information and mutual information are defined in terms of the cross time-frequency distribution. Based on time-frequency mutual information theory, this paper presents applications of the proposed technique to real-world vibration data obtained from a dedicated condition- based-maintenance experimental test bed. Baseline, unbalanced, and misaligned experimental settings of helicopter drivetrain bearings and shafts are quantitatively distinguished by the proposed techniques. With imbalance quantifiable by variance in the in-phase mutual information and misalignment quantifiable by variance in the quadrature mutual information developed and presented herein, machine health classification can be accomplished by use of statistical bounding regions.
Intelligent systems have greatly contributed in automating the process segments that includes the maintenance function in the manufacturing industries. The purpose of this research was to come up with an intelligent monitoring tool to reduce the number of breakdowns in Krones machinery. The objective of the research was motivated by considering Human Machine Interface (HMI) and automatic monitoring of the plant while in the office. The case of a local beverage manufacturer was used who has installed a bottle washer manufactured by the Krones. The Fuzzy Logic system was derived among other artificial intelligent systems as best appropriate in order to solve the breakdown challenges automatically. The bottle washer is complex so much that it is not easy to carry out a successful troubleshooting; for instance, the pneumatic valve could just stick and cause production to stop immediately. The researchers carried out a company audit, interviews and questionnaires in order to gather relevant data. The results of which were used in intelligent condition-based-maintenance modelling to solve the problem using fuzzy logic system. Matlab software was used as a means for data modelling and manipulation and the researchers recommended the use of this intelligent monitoring tool to all beverage manufacturers who have installed the krones machinery.
Reliability is an important index for decision-making in power system. The traditional reliability calculation which is based on time cannot meet the demand of condition-based maintenance (CBM) decision-making. Now power equipment's health state can be quantified by related state evaluation guidelines, so a reliability model which is based on power equipment's health state is put forward to calculate fault rate. The main difficulty of applying the model is to get the two parameters, which are scaling parameter and curvature parameter. Someone uses statistical inversion method to get them, which needs a large scale of samples, neglects samples' health state variability, and can't reflect maintenance's impact on reliability. This paper proposes a new parameter calculation method which is based on power equipment's life cycle health state. By means of this method, we can not only overcome the shortcomings of inversion method, but can also build several kinds of state reliability models, such as state reliability model of one category power equipments, single equipment and single equipment's different life stages. After obtaining power equipment's reliability model based on health state, condition-based maintenance decision-making can be executed further. The target of decision-making is to find out the best maintenance mode such as overhaul or minor repair, which is a best balance between reliability and economy. Different maintenance modes need different maintenance costs, and have different impacts on equipment's health state. By means of analyzing each maintenance mode's ability to improve equipment's health state, we can predict reliability scientifically. Then condition-based maintenance decision-making can be carried out by calculating each maintenance mode's reliability increment per maintenance cost. The paper also gives a numerical example which shows that the decision-making method proposed here is more simple, precise and operational for condition-based maintenance management.
Maintenance on high Voltage/Extra High Voltage equipment can be divided into preventive maintenance and corrective maintenance. Mostly, the cost for doing a corrective maintenance is much higher than the preventive maintenance, beside of when an equipment break down, it will cause another problem such as customer dissatisfaction. These reasons bring the consequence to any electricity utility like PLN P3B Jawa and Bali to do a reliable preventive maintenance. There are two types of preventive maintenance, e.g. scheduled maintenance and condition based maintenance. For years, most of the maintenance methods were done under scheduled maintenance (oil replacement, shutdown inspection/measurement, etc), but this method is less cost-efficient and less reliable on preventing the failure. The time interval in scheduled maintenance is based on the statistical data, which usually came from the factory recommendation (with some safety factor) or based on PLN P3B Jawa Bali experience, while the time interval in condition based maintenance is based upon the degradation of some parameters of the equipment. So, the knowledge of condition degradation on an equipment is important in condition based maintenance. This paper will present about condition assessment on power transformer as a part of condition based maintenance process. The causal method based on FMEA and FMECA of power transformer will be discussed first to get the information about critical component and the suitable monitoring needed at sub system levels. The next part will explain about how to compile the maintenance data into a management report which mainly giving the information whether the power transformer is in good/deteriorated or already in bad condition. The data presented here are based on 500/150 kV power transformer in P3B Jawa Bali.
The condition-based maintenance (CBM) focuses on the prediction of aging, degradation, and failure process of data center at the levels of components and systems. The benefits of CBM are increasing system availability, mission effectiveness, and reducing maintenance costs. In this paper, we propose an innovative concept of decision support methodology for system failure diagnosis and prognosis in complex systems of data center power distribution systems. This paper proposes an action research of a new decision support methodology for system failure diagnosis and prognosis in data center power distribution systems. Shifting from time-based maintenance (TBM) to CBM using automated prognostics and diagnostics to identify and resolve issues before they become problems of data center downtime costs.
It is a common trend of power companies to progressively change its equipment maintenance strategies from relying on purely time-based preventive tasks to more condition-based predictive tasks. An important prerequisite of condition based maintenance is condition monitoring. Results of condition monitoring on power equipment form useful information in formulating asset strategies in the most cost effective manner while maximising the availability and enhancing reliability of the equipment. This paper describes the road of CLP Power Hong Kong in developing strategies and plans for condition monitoring and its roadmap to prepare for the implementation of condition based maintenance.
The interest in maintainability, availability and the techniques to evaluate it had an exponential growth in the last few years, in particular for systems involved in mission-critical environments: these applications demand both high performance and high availability. Maintainability is directly associated to the concept of availability assessment since it concerns failure and recovery aspects of a system. This paper deals with Condition-based Maintenance (CBM) and Markov Modelling and their application on avionics devices. CBM is a maintenance program referred to the information collected through condition monitoring. One of the best method to carry on availability analysis is the condition based maintenance modelling using Markov analysis.
This recommended practice provides overhead contact system maintenance practices and procedures including maintenance techniques, site inspection and test procedures, and maintenance tolerances, for heavy rail, light rail, and trolley bus systems.
This standard provides the basic principles for design qualification of safety systems equipment used in nuclear power generating stations.
Aeromechanical Research Engineer - ATAS
Georgia Tech Research Institute (GTRI)