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Weibull analysis of ceramics and related materials: A review

威布尔模量 威布尔分布 可靠性(半导体) 材料科学 脆性 可靠性工程 陶瓷 韧性 计算机科学 复合材料 统计 工程类 数学 功率(物理) 物理 量子力学
作者
Obinna Anayo Osuchukwu,Abdu Salihi,Abdullahi Haruna Ibrahim,Adamu Abdullahi Audu,Mahdi Makoyo,Sikiru Adepoju Mohammed,Mohammed Y. Lawal,Precious Osayamen Etinosa,Ibitoye Opeyemi Isaac,Peter Gbenga Oni,Oreoluwa Oginni,David O. Obada
出处
期刊:Heliyon [Elsevier BV]
卷期号:10 (12): e32495-e32495 被引量:5
标识
DOI:10.1016/j.heliyon.2024.e32495
摘要

It has been realized throughout the years that an ideal combination of high toughness with high hardness and strength is required in many engineering applications needing 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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