Abstract
Decision-making in product quality is indispensable in order to keep product development at the lowest risk. Based on discussion of the deficiencies of Quality Function Deployment (QFD) and Failure Modes and Effects Analysis (FMEA), a novel decision-making method is presented concentrated on the knowledge network of failure scenarios. An ontological expression of failure scenario is presented together with a framework of failure knowledge network (FKN). A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the Measurement Assisted Assembly (MAA) process to solve the problem of prioritizing measurement characteristics. A mathematical model and algorithms of Analytic Network Process (ANP) are introduced into calculating the priority of manufacturing characteristics. Therefore, this study provides a practical approach for decision-making in product quality.
Keywords
- Quality Function Deployment
- Analytic Network Process
- Subject Matter Expert
- Failure Scenario
- Risk Priority Number
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Dai, W., Maropoulos, P., Tang, X. (2010). Failure knowledge based decision-making in product quality. In: Hinduja, S., Li, L. (eds) Proceedings of the 36th International MATADOR Conference. Springer, London. https://doi.org/10.1007/978-1-84996-432-6_33
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DOI: https://doi.org/10.1007/978-1-84996-432-6_33
Publisher Name: Springer, London
Print ISBN: 978-1-84996-431-9
Online ISBN: 978-1-84996-432-6
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