TY - JOUR
T1 - The development of a generic failure analysis expert system based on case-eased reasoning
AU - Graham-Jones, PJ
AU - Mellor, BG
PY - 1996/1/1
Y1 - 1996/1/1
N2 - Failure analysis is a complex task, requiring considerable knowledge and skill, some of which might |)e outside the experience of the engineer concerned. To help the engineer, a case-based reasoning to al (Failure Analysis Diagnostic Expert System) is beiig developed, using a systemic approach to failuire diagnostic problems, which not only interactively ic entines the failure modes and the critical factors in the design, processing, and end use which cause failures to originate but also suggests methods to improve the reliability of the products. This approach applies a Windows artificial intelligent case-based reasoning technique to generic failure diagnostic problems. Currently, the research is based around the elicitation of failure analysis knowledge and the structuring and planning of this knowledge so that t te expert system behaves in an intelligent and responsive manner. Many problems have arisen, such is understanding what information is required to ideniijy the failure mode and in designing a consistent aijtd economical set of questions that are integrated into an efficient questioning strategy. For the behavio ^r of the system to be intelligent and responsive, research into interface design and the understanding )f human cognitive models for failure analysis decision-making is proposed. The development of structure models will show which factors are critical in a given situation and aid failure analysis diagnosis.
AB - Failure analysis is a complex task, requiring considerable knowledge and skill, some of which might |)e outside the experience of the engineer concerned. To help the engineer, a case-based reasoning to al (Failure Analysis Diagnostic Expert System) is beiig developed, using a systemic approach to failuire diagnostic problems, which not only interactively ic entines the failure modes and the critical factors in the design, processing, and end use which cause failures to originate but also suggests methods to improve the reliability of the products. This approach applies a Windows artificial intelligent case-based reasoning technique to generic failure diagnostic problems. Currently, the research is based around the elicitation of failure analysis knowledge and the structuring and planning of this knowledge so that t te expert system behaves in an intelligent and responsive manner. Many problems have arisen, such is understanding what information is required to ideniijy the failure mode and in designing a consistent aijtd economical set of questions that are integrated into an efficient questioning strategy. For the behavio ^r of the system to be intelligent and responsive, research into interface design and the understanding )f human cognitive models for failure analysis decision-making is proposed. The development of structure models will show which factors are critical in a given situation and aid failure analysis diagnosis.
M3 - Conference proceedings published in a journal
SN - 0361-4409
VL - 0
JO - NACE - International Corrosion Conference Series
JF - NACE - International Corrosion Conference Series
IS - 0
ER -