Failure Verification of Products with Quantitative Modeling of Behavior and Cause-and-effect Relationships among Physical Phenomena.
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- AKASHI Kazuki
- Osaka University, Division of Materials and Manufacturing Science
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- MORINAGA Eiji
- Osaka University, Division of Materials and Manufacturing Science
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- WAKAMATSU Hidefumi
- Osaka University, Division of Materials and Manufacturing Science
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- KURAHASHI Ryu
- Osaka University, Division of Materials and Manufacturing Science
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- ARAI Eiji
- Osaka University, Division of Materials and Manufacturing Science
Bibliographic Information
- Other Title
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- 挙動・事象因果の定量的表現に基づく製品の不具合検証
Abstract
<p>With the progress of recent globalization in industries, the number of failures and troubles of products caused by using them in unexpected ways has increased. To avoid such troubles, it is necessary not only to assume various ways of use thoroughly, but to verify whether the design plan can fulfill required functions when the product is utilized in those ways. From this point of view, the authors proposed a functional failure verification method considering ways of use based on qualitative modeling of behavior and cause-and-effect relationships among physical phenomena using Petri nets. However, it is not possible to verify failures concerning to specification which requires dealing with quantitative information. This paper provides a method for quantitative modeling of behavior and cause-and-effect relationships among physical phenomena. Two types of tokens were defined for dealing with positive and negative values and four types of arcs were for controlling changes of those values. This made it possible to represent behavior and cause-and-effect relationships quantitatively. Application of this new modeling method enabled automatic detection of failures of both functions and specification.</p>
Journal
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- The Proceedings of Design & Systems Conference
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The Proceedings of Design & Systems Conference 2016.26 (0), 2216-, 2016
The Japan Society of Mechanical Engineers
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Details 詳細情報について
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- CRID
- 1390282680868552320
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- NII Article ID
- 130007154169
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- ISSN
- 24243078
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed