Procedure for assessing the quality of explanations in failure analysis

IF 1.7 3区 工程技术 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing Pub Date : 2022-08-08 DOI:10.1017/S0890060422000099
Kristian González Barman
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引用次数: 2

Abstract

Abstract This paper outlines a procedure for assessing the quality of failure explanations in engineering failure analysis. The procedure structures the information contained in explanations such that it enables to find weak points, to compare competing explanations, and to provide redesign recommendations. These features make the procedure a good asset for critical reflection on some areas of the engineering practice of failure analysis and redesign. The procedure structures relevant information contained in an explanation by means of structural equations so as to make the relations between key elements more salient. Once structured, the information is examined on its potential to track counterfactual dependencies by offering answers to relevant what-if-things-had-been-different questions. This criterion for explanatory goodness derives from the philosophy of science literature on scientific explanation. The procedure is illustrated by applying it to two case studies, one on Failure Analysis in Mechanical Engineering (a broken vehicle shaft) and one on Failure Analysis in Civil Engineering (a collapse in a convention center). The procedure offers failure analysts a practical tool for critical reflection on some areas of their practice while offering a deeper understanding of the workings of failure analysis (framing it as an explanatory practice). It, therefore, allows to improve certain aspects of the explanatory practices of failure analysis and redesign, but it also offers a theoretical perspective that can clarify important features of these practices. Given the programmatic nature of the procedure and its object (assessing and refining explanations), it extends work on the domain of computational argumentation.
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评估失效分析中解释质量的程序
摘要本文概述了在工程失效分析中评估失效解释质量的程序。该程序将解释中包含的信息结构化,以便能够找到弱点,比较相互竞争的解释,并提供重新设计的建议。这些特点使该程序成为对失效分析和重新设计的某些工程实践领域进行批判性反思的良好资产。该程序通过结构方程来构造解释中包含的相关信息,从而使关键要素之间的关系更加突出。一旦构建好,信息就会被检查其追踪反事实依赖关系的潜力,方法是为“如果事情本来是不同的”相关问题提供答案。这一解释善的标准源于科学文献的科学解释哲学。本文通过两个案例分析说明了该方法,一个是机械工程中的失效分析(车辆轴断裂),另一个是土木工程中的失效分析(会议中心倒塌)。该程序为故障分析人员提供了一个实用的工具,用于对其实践的某些领域进行批判性反思,同时提供了对故障分析工作的更深层次的理解(将其构建为解释性实践)。因此,它允许改进故障分析和重新设计的解释性实践的某些方面,但它也提供了一个理论视角,可以澄清这些实践的重要特征。鉴于该过程及其对象(评估和精炼解释)的程序化性质,它扩展了计算论证领域的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.40
自引率
14.30%
发文量
27
审稿时长
>12 weeks
期刊介绍: The journal publishes original articles about significant AI theory and applications based on the most up-to-date research in all branches and phases of engineering. Suitable topics include: analysis and evaluation; selection; configuration and design; manufacturing and assembly; and concurrent engineering. Specifically, the journal is interested in the use of AI in planning, design, analysis, simulation, qualitative reasoning, spatial reasoning and graphics, manufacturing, assembly, process planning, scheduling, numerical analysis, optimization, distributed systems, multi-agent applications, cooperation, cognitive modeling, learning and creativity. AI EDAM is also interested in original, major applications of state-of-the-art knowledge-based techniques to important engineering problems.
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