Consideration of component failure mechanisms in the reliability assessment of electronic equipment-addressing the constant failure rate assumption

Mortin, D.E.; Krolewski, J.G.; Cushing, Michael J.

doi:10.1109/rams.1995.513224

Cited by 8 publications

(11 citation statements)

References 5 publications

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“…A major complaint by handbook critics is that at the component level, it assumes a constant failure rate over the useful life. Other errors in MIL-HDBK-217's approach [39], [40] are the assumption of the basis of assigning the component failure-rate Pi-factors and the omission of equipment design and development procedures from the prediction process.…”

Section: A Empirical-based Modelsmentioning

confidence: 99%

Electronic System Reliability: Collating Prediction Models

Goel

Graves

2006

IEEE Trans. Device Mater. Relib.

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This paper summarizes research done in the area of electronic system reliability and assesses the approaches used in the calculation of electronic system failure rates. A detailed literature survey is conducted to investigate the various available reliability prediction models.The paper starts with a definition of reliability, briefly discusses various regions of system failure rate in time, justifies the role of reliability prediction methods, provides a historical overview, classifies the traditional models into easy to understand categories and discusses the advantages and disadvantage, reviews the key models that are currently in use, and compares the first and most widely used model (i.e., MIL-HDBK-217) with the most recently introduced model (i.e., PRISM).Index Terms-Electronic component reliability, empiricalbased models, failure rate, MIL-HDBK-217, physics-of-failure, prediction models.

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Section: A Empirical-based Modelsmentioning

confidence: 99%

Electronic System Reliability: Collating Prediction Models

Goel

Graves

2006

IEEE Trans. Device Mater. Relib.

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“…• Sequential probability ratio testing assumes a constant failure rate. The concept of a constant failure rate is currently being questioned within the electronics industry where a decreasing failure rate is now considered more appropriate 10 . • The infancy mortality period is ignored.…”

Section: Limitations Of Reliability Demonstration Testingmentioning

confidence: 99%

Total System Reliability: Integrated Model for Growth and Test Termination

Donovan

Murphy

2005

Qual. Reliab. Engng. Int.

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Reliability demonstration testing is not the most efficient method of assuring product reliability prior to shipment. It is costly, time consuming and has inherent technical and social limitations. The dilemma facing the reliability and quality engineer is whether to continue demonstration testing and risk shipping a product late or ship the product and risk warranty and field service returns. Either option can cause the company to lose significant market share and profit. This paper sets out to solve this dilemma by meeting both the time to market constraints and the product reliability goals. The weaknesses of existing reliability demonstration techniques are explored and a comprehensive methodology is introduced involving controlled development processes, stress testing, root cause determination and process change feedback mechanisms. All prototype products are manufactured on the final volume process line resulting in the early identification and correction of processrelated problems. Testing commences on the first available prototypes with system stress/robust testing being employed to stimulate failures, determine their root cause and correct them. Reliability growth modelling assesses the ongoing improvements occurring in reliability during the development cycle, while a statistical stopping rule is used to determine the optimal product release time without risking product warranty. The approach is applicable to systems incorporating both hardware and software elements. The methodology has been validated on three development projects of telecommunication systems comprising hardware and software. In addition to enhancing team behaviour and performance, the development times have been reduced by 14% and the ramp-up time to full worldwide product shipments has been reduced by 50%.

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“…Bellcore's, has been extensively reported (see e.g. References [3][4][5][6]). The situation is illustrated by Tables 1 and 2.…”

Section: Problems In Reliability Predictionmentioning

confidence: 99%

“…The errors in MIL-HDBK-217's approach and that of similar tabulations have been widely discussed (see e.g. References [5] and [7]). Major mistakes are (a) the assumption of constant component failure rate, (b) the basis of assigning the component failure-rate Pifactors, especially the quality factor, and (c) the omission of equipment design/development procedures and disciplines from the prediction process.…”

Section: Problems In Reliability Predictionmentioning

confidence: 99%

“…The argument is that knowledge and understanding of the device failure mechanisms will not only permit improving device technologies but will also provide knowledge of the expected life of devices, failure becoming a deterministic and not probabilistic event. The first claim is more valid than the second: manufacturing variabilities, particularly before manufacturing maturity has been gained or when there are quality control problems, can result in dispersions of up to three or four in the generally met lognormal life distribution [5]. This causes substantial uncertainty as to when failure will occur.…”

Section: Problems In Reliability Predictionmentioning

confidence: 99%

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The challenge of quantitative reliability

Blanks¹

1998

Qual. Reliab. Engng. Int.

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After examining the need of the equipment/system user to receive, collect, analyse and supply quantitative reliability information, this paper discusses the methods, existing and potential, of satisfying this need. It does so against the background of the now widely acknowledged inaccuracy of traditional methods of reliability prediction, the recognition that the conventional failure‐rate bathtub curve is an oversimplification and the difficulty of gathering adequate test and field failure data on increasingly high‐reliability product in an age of fast technology evolution and short new product lead‐time markets. There are three important tasks for the equipment user: (a) establishment of an efficient system of failure data collection and analysis; (b) utilization of these data in all business and organizational activities; (c) participation in the creation of an accurate method of reliability prediction by providing feedback of field reliability data to product manufacturers. © 1998 John Wiley & Sons, Ltd.

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Consideration of component failure mechanisms in the reliability assessment of electronic equipment-addressing the constant failure rate assumption

Cited by 8 publications

References 5 publications

Electronic System Reliability: Collating Prediction Models

Electronic System Reliability: Collating Prediction Models

Total System Reliability: Integrated Model for Growth and Test Termination

The challenge of quantitative reliability

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