Reliability prediction system based on the failure rate model for electronic components

Lee, Seung Woo; Lee, Hwa Ki

doi:10.1007/s12206-008-0212-4

Cited by 23 publications

(6 citation statements)

References 10 publications

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“…Prediction method II is a combination of prediction method I and data from laboratories according to the specific criteria of Telcordia SR-332. Prediction method III 1 1 exp 4 060…”

Section: Telcordia Sr-332 Predictive Methodsmentioning

confidence: 99%

“…At present the reliability of electronic components can be predicted through the following methods: the statistical method (standard handbook), similarity analysis method based on operation & maintenance data (reliability database) and reliability test method base on the physics-of-failure approach [1]. Each approach has its unique advantages and disadvantages.…”

Section: Introductionmentioning

confidence: 99%

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Methodologies for Reliability Prediction of Electronic Component in Military Vehicles

Bui²

2019

AiMT

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Reliability prediction is conducted in all phases of the product life cycle. The purpose of these predictions is to identify the potential weaknesses in design, to evaluate the design feasibility, to compare alternative designs, to provide the model for reliability analysis, to track reliability improvement, etc. Reliability of electronic component is predicted by using statistical prediction methods (standards-based), statistical analysis of operation & maintenance data or by performing reliability testing. The article describes statistical prediction methods such as MIL-HDBK-217, RIAC 217Plus, FIDES Guide 2009, which are widely used for predicting the reliability of electronic components. In addition, we have calculated and compared the failure rate of electronic components in military vehicles conducted with the use of these different methods.

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“…Prediction method II is a combination of prediction method I and data from laboratories according to the specific criteria of Telcordia SR-332. Prediction method III 1 1 exp 4 060…”

Section: Telcordia Sr-332 Predictive Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Methodologies for Reliability Prediction of Electronic Component in Military Vehicles

Bui²

2019

AiMT

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“…According to Lee and Lee (2008) there are three different techniques for prediction: statistical methods, similarity analyses using failure rate databases, and physics-of-failure methods. Goel and Graves (2006) classify the techniques into two groups: empirical-based models and physics-of-failure models.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting Failure Rates of Electronic Goods by Using Decomposition and Fuzzy Clustering of Empirical Failure Rate Curves

Jónás

Árva

Tóth

2017

Period. Polytech. Soc. Man. Sci.

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In this paper a novel methodology founded on the joint application of analytic decomposition of empirical failure rate time series and soft computational techniques is introduced in order to predict bathtub-shaped failure rate curves of consumer electronic goods. Empirical failure rate time series are modeled by a flexible function the parameters of which have geometric interpretations, and so the model parameters grab the characteristics of bathtub-shaped failure rate curves. The so-called typical standardized failure rate curve models, which are derived from the model functions through standardization and fuzzy clustering processes, are applied to predict failure rate curves of consumer electronics in a method that combines analytic curve fitting and soft computing techniques. The forecasting capability of the introduced method was tested on real-life data. Based on the empirical results from practical applications, the introduced method can be considered as a new, alternative reliability prediction technique the application of which can support the electronic repair service providers to plan their resources in the long run.

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“…Cassanelli et al suggested a reliability assessment method for new products by collecting empirical data and reliability information on similar components. Lee and Lee developed a Web system‐based electronic components reliability prediction system based on the failure model and created a database from them. Campbell et al studied the reliability behavior of electronic components as a function of time.…”

Section: Literature Reviewmentioning

confidence: 99%

Clustering Empirical Failure Rate Curves for Reliability Prediction Purposes in the Case of Consumer Electronic Products

Dombi

Jónás

Tóth

2015

Quality & Reliability Eng

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In this paper, a methodology based on the combination of time series modeling and soft computational methods is presented to model and forecast bathtub-shaped failure rate data of newly marketed consumer electronics. The timedependent functions of historical failure rates are typified by parameters of an analytic model that grabs the most important characteristics of these curves. The proposed approach is also verified by the presentation of an industrial application brought along at an electrical repair service provider company. The prediction capability of the introduced methodology is compared with moving average-based and exponential smoothing-based forecasting methods. According to the results of comparison, the presented method can be considered as a viable alternative reliability prediction technique. Copyright

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Reliability prediction system based on the failure rate model for electronic components

Cited by 23 publications

References 10 publications

Methodologies for Reliability Prediction of Electronic Component in Military Vehicles

Methodologies for Reliability Prediction of Electronic Component in Military Vehicles

Forecasting Failure Rates of Electronic Goods by Using Decomposition and Fuzzy Clustering of Empirical Failure Rate Curves

Clustering Empirical Failure Rate Curves for Reliability Prediction Purposes in the Case of Consumer Electronic Products

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