Conferences related to Life Data Analysis

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2021 IEEE Photovoltaic Specialists Conference (PVSC)

Photovoltaic materials, devices, systems and related science and technology


2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 59th IEEE Conference on Decision and Control (CDC)

The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Power Modulator and High Voltage Conference (IPMHVC)

This conference provides an exchange of technical topics in the fields of Solid State Modulators and Switches, Breakdown and Insulation, Compact Pulsed Power Systems, High Voltage Design, High Power Microwaves, Biological Applications, Analytical Methods and Modeling, and Accelerators.


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Periodicals related to Life Data Analysis

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Advanced Packaging, IEEE Transactions on

The IEEE Transactions on Advanced Packaging has its focus on the modeling, design, and analysis of advanced electronic, photonic, sensors, and MEMS packaging.


Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Reviews in

The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


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Most published Xplore authors for Life Data Analysis

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Xplore Articles related to Life Data Analysis

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Life data analysis with applications to aircraft modeling

2017 Annual Reliability and Maintainability Symposium (RAMS), 2017

As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which ...


Statistical life data analysis for electricity distribution cable assets — An Asset Management approach

IET and IAM Asset Management Conference 2011, 2011

Nowadays, power utilities are adopting Asset Management as their framework in order to cope with the challenges introduced by the privatization and market competition in this sector. Stedin, a Dutch Distribution System Operator recognized the vital role that an Asset Management system has for its organization. Therefore, Stedin, has adopted the publicly available specification, BSLPAS55, as a standard to perform ...


Using Design of Experiments in Combination with Life Data Analysis for Complexity Reduction

2018 Annual Reliability and Maintainability Symposium (RAMS), 2018

Design of Experiments (DOE) with Life Data Analysis is a powerful combination for not only optimizing designs, but for reducing also the complexity arising from the variety of combinations of a component or system within any organization. This is especially important in cases where multiple concepts or options exist to provide the same function or functions. Differentiation and variety makes ...


Life data analysis using the competing failure modes technique

2015 Annual Reliability and Maintainability Symposium (RAMS), 2015

As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which ...


Life data analysis with applications for the airline industry

2016 Annual Reliability and Maintainability Symposium (RAMS), 2016

As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which ...


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Educational Resources on Life Data Analysis

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IEEE-USA E-Books

  • Life data analysis with applications to aircraft modeling

    As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which the design is maturing; while classical qualitative methods do not provide the level of detail and granularity required by the designers to make high-quality risk informed decisions. Every company is dependent on some type of asset that keeps the business in business - be it a computer, a centrifuge or a megawatt transformer. In a large enterprise, reducing costs related to asset maintenance, repair and ultimate replacement is at the top of management concerns [1]. Downtime in any network, manufacturing or computer system ultimately results not only in high repair costs, but in customer dissatisfaction and lower potential sales. In response to these concerns, this paper presents a methodology for using Life Data Analysis (LDA) techniques for evaluating new product innovation and projecting product performance due to several failure modes. The paper presents an application for the airline industry where the technique was used in determining the right failure mode as well as enable the program to compare improvements to the fleet.

  • Statistical life data analysis for electricity distribution cable assets — An Asset Management approach

    Nowadays, power utilities are adopting Asset Management as their framework in order to cope with the challenges introduced by the privatization and market competition in this sector. Stedin, a Dutch Distribution System Operator recognized the vital role that an Asset Management system has for its organization. Therefore, Stedin, has adopted the publicly available specification, BSLPAS55, as a standard to perform the Asset Management responsibilities and tasks of their electricity and gas networks. Equipment life cycle and technical performance activities form an integral part of the implementation of an Asset Management system. In this context, Stedin felt the strong need to have access to systematic techniques and guidelines on how to deal with information of equipment lifetimes. In this paper a systematic method, based on Statistical Life Data Analysis, which deals with limited or incomplete life time data of large populations of assets with the aim of obtaining an indicator of the future failure expectancy is discussed. The methods and analytical tools developed in this contribution share a basic framework for decision-making and specify the evolution of the failures of asset population over time.

  • Using Design of Experiments in Combination with Life Data Analysis for Complexity Reduction

    Design of Experiments (DOE) with Life Data Analysis is a powerful combination for not only optimizing designs, but for reducing also the complexity arising from the variety of combinations of a component or system within any organization. This is especially important in cases where multiple concepts or options exist to provide the same function or functions. Differentiation and variety makes ample sense if the variety would contribute to customer value. There exists multiple scenarios where part proliferation, due to historical reasons, gives rise to non-value added complexity thereby impacting product reliability and cost. This paper focuses on the complexity reduction problem as an engineering optimization problem.

  • Life data analysis using the competing failure modes technique

    As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which the design is maturing; while classical qualitative methods do not provide the level of detail and granularity required by the designers to make high-quality risk informed decisions. Every company is dependent on some type of asset that keeps the business in business - be it a computer, a centrifuge or a megawatt transformer. In a large enterprise, reducing costs related to asset maintenance, repair and ultimate replacement is at the top of management concerns [1]. Downtime in any network, manufacturing or computer system ultimately results not only in high repair costs, but in customer dissatisfaction and lower potential sales. In response to these concerns, this paper presents a methodology for using Life Data Analysis (LDA) techniques for evaluating new product innovation and projecting product performance due to several failure modes. The paper presents an application for a brake design where the technique was used in determining the right failure mode based on failure mechanisms.

  • Life data analysis with applications for the airline industry

    As demand for highly reliable complex systems increases, engineers are being forced to consider the risk implications of design decisions earlier in the conceptual phase of projects and with greater accuracy. Standard probabilistic risk assessments (PRA) usually employed to verify that a product meets requirements are too resource intensive and too slow to keep up with the speed at which the design is maturing; while classical qualitative methods do not provide the level of detail and granularity required by the designers to make high-quality risk informed decisions. Every company is dependent on some type of asset that keeps the business in business - be it a computer, a centrifuge or a megawatt transformer. In a large enterprise, reducing costs related to asset maintenance, repair and ultimate replacement is at the top of management concerns [1]. Downtime in any network, manufacturing or computer system ultimately results not only in high repair costs, but in customer dissatisfaction and lower potential sales. In response to these concerns, this paper presents a methodology for using Life Data Analysis (LDA) techniques for evaluating new product innovation and projecting product performance due to several failure modes. The paper presents an application for a brake design where the technique was used in determining the right failure mode based on failure mechanisms.

  • Automated reliability life data analysis of missiles in storage and flight

    Life-data analysis is the process of fitting failure distributions to reliability data. The methodology underlying a computer tool known as RAMFIT is described. It was developed to perform automated life-data analysis on missiles using interval data for missiles in storage or continuous data for missiles flown and carried in airplanes (the captive carry environment). RAMFIT is integrated into the US Air Force's reliability asset monitoring (RAM) database. This database captures data generated from a variety of sources including storage inspection tests, flightline tests, shop-level repairs, and missile firing.<<ETX>>

  • Application of Life Data Analysis in the aging power system

    The power distribution system underwent many changes in the recent decades. Because of the changing regulatory and economic conditions, utilities transform their operation and business policies. They are looking for different options to reduce their expenditure while complying with the regulatory and consumer expectations. One of the results of this transformation is the wide application of asset management techniques. The operational costs and reliability of the power system are defined by the properties (type, age, condition and the effectiveness of operation etc.) of the equipment. Due to long operation time, the condition of the equipment is deteriorating. In the electricity system of most of the countries, major part of the devices has reached their designed life. Therefore it is important to estimate the future failures and costs. The application of life data analysis is difficult because of the often poor reliability and availability of data. Usually most of the failure and age distribution data are incomplete. In this paper, life data analysis has been used to estimate the number of future failures with the above mentioned difficulties.

  • Life Data Analysis and evaluation of the performance characteristics of PICKER MODULE

    In this competing world, there is a need of measuring the performance of the products throughout their life to remain on the edge of this level of competition. Life Data analysis accomplishing this task, many industries have been considering it as their improvement strategy. Companies that are unable to measure the performance of their product development processes have little or no chance of successfully competing with today's best-in-class product makers. Life Data Analysis is a method that is analyzing the life of system, modules, sub-modules and even goes up to the small components to calculate the performance characteristics such as Reliability, failure rate, MTBF by fitting a Best Distribution to the data. The objective of this project is to analyze the Life of “PICKER MODULE” to know the failure behaviour over a period of time, prediction of future performance and also to evaluate the Life Characteristics of module such as Reliability, Probability of failure at specific time and Mean life based on the present data that is collected from Field by using statistical software tool Weibull++ version 9.0.16 developed by ReliaSoft.

  • Analysis of parameter-degradation data using life-data analysis programs

    A new application of existing reliability software packages is proposed to analyze parameter-degradation data. This new implementation of existing tools is applicable to a large class of degradation phenomena described by the power law or the stretched exponential law. When these laws are used to model parameter-degradation paths, the parametric drift can be treated as an explanatory variable, on equal footing with conventional explanatory variables such as temperature, electrical stress, or humidity. Thin film integrated circuit resistor degradation data and the STAR (Statistical Analysis of Reliability) software package are used to illustrate the authors' approach. Other degradation phenomena that can be studied using the proposed method include hot carrier degradation in metal-oxide-silicon (MOS) transistors, laser degradation, and degradation of light emitting diodes.<<ETX>>

  • Censored life data analysis in software testing

    The main idea is to adapt the censored life testing model to a computer software testing problem. Therefore the goal is not only to compute mean line code to failure (MLTF) or mean time to failure (MTTF), but also the reliability of the software product at a given time "t" or "line of code". It must be also noted that all computations to analyze the system are performed by regarding two types of censoring called Type I and Type II. The numerical applications indicate that the censored results approach the true but unknown uncensored (complete) estimators as the degree of censoring is reduced to zero towards the end of completed life test study. Further, a bias correction procedure for the reliability is implemented.<<ETX>>



Standards related to Life Data Analysis

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IEEE Guide for Selecting and Using Reliability Predictions Based on IEEE 1413

Processes and methodologies for conducting reliability predictions for electronic systems and equipment.


IEEE Recommended Practice for the Selection, Field Testing, and Life Expectancy of Molded Case Circuit Breakers for Industrial Applications

To provide the user with a recommended procedure that is safe and easily understood, for the selection, application, and determination of the remaining life in molded case circuit breakers.


IEEE Recommended Practice on Software Reliability

Software reliability (SR) models have been evaluated and ranked for their applicability to various situations. Many improvements have been made in SR modeling and prediction since 1992. This revised recommended practice reflects those advances in SR since 1992, including modeling and prediction for distributed and network systems. Situation specific usage guidance was refined and updated. The methodologies and tools included ...


IEEE Standard for Design Qualification of Safety Systems Equipment Used in Nuclear Power Generating Stations

This standard provides the basic principles for design qualification of safety systems equipment used in nuclear power generating stations.


IEEE Standard Methodology for Reliability Predictions and Assessment for Electronic Systems Equipment

A standardized medium for developing reliability predictions of electronic systems and equipment.



Jobs related to Life Data Analysis

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