Weibull analysis of ceramics and related materials: A review
It has been realized throughout the years that an ideal combination of high toughness, hardness and strength is required in many engineering applications that need load-bearing capabilities. Ceramics and related materials have significant constraints for structural and particular non-structural appl...
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Published in | Heliyon Vol. 10; no. 12; p. e32495 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
30.06.2024
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | It has been realized throughout the years that an ideal combination of high toughness, hardness and strength is required in many engineering applications that need load-bearing capabilities. Ceramics and related materials have significant constraints for structural and particular non-structural applications due to their low toughness and limited strength while having substantially superior hardness than typical metallic materials. For example, hydroxyapatite (HAp) has gained attention for applications in orthopaedic implants, dental materials, drug delivery, etc. Researchers have continued to strive to produce HAp materials with reliable properties within the acceptable Weibull modulus (m) for load bearing. The Weibull analysis (WA) is a statistical analysis adopted widely in reliability applications to detect failure periods. Researchers have confirmed it to be an effective technique to get results on the reliability of materials at a moderately low rate with assured reliability of the material or component. This review summarizes the WA and the steps in the Weibull method for its reliability analysis to predict the failure rate of ceramics like HAp and other related materials. Also, the applications of WA for these materials were reviewed. From the review, it was discovered that Weibull distribution is proven to confer to the feeblest-link concept. For brittle materials, it was revealed that the Weibull Modulus ranges from 2 to 40, and environment, production processes, and comparative factors are well-thought-out contributing factors for reliability. In addition, the confidence interval can be up to 95 %. The frequently used technique for reliability valuation is to syndicate the Weibull statistics. Also, a very narrow distribution is desirable to offer the expected likelihood. Furthermore, when paired with trials, Monte Carlo simulations prove to be a very helpful tool for forecasting the dependability of different estimate techniques and their optimization. Finally, if the equivalent m is anticipated to be high, it signifies that the material has a high degree of homogeneity of properties and high reliability. WA can find application in predicting the dependability and lifetime of materials, making it widely utilized in engineering and other disciplines. It is especially useful for analysing data in which the likelihood of failure per unit of time varies over time. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
ISSN: | 2405-8440 2405-8440 |
DOI: | 10.1016/j.heliyon.2024.e32495 |