Representation of Functional Relations Among Parts And Its Application to Product Failure Reasoning

Hata, Tomoyuki; Kobayashi, Noritomo; Kimura, Fumihiko; Suzuki, Hiromasa

doi:10.1515/ijmsp.2000.3.2-4.77

Cited by 10 publications

(8 citation statements)

References 4 publications

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“…These approaches have presented a common platform for the analysis and comparison of various knowledge representation models. In this line of work, the functional representation scheme developed by Hata et al (2000) is a commendable effort as a direct application to product failure reasoning. In the field of artificial intelligence, qualitative reasoning (refer: De Kleer and Brown 1984;Forbus 1984) has been the mainstay in behavioral as well as functional modeling of physical entities.…”

Section: Motivation and Outline Of Proposed Workmentioning

confidence: 99%

Cognitive map-based system modeling for identifying interaction failure modes

et al. 2011

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Past few decades have seen an upsurge in failure analysis techniques capable of dealing with reliability issues up front in the early stages of the product development process. Most of these approaches are centered on component-specific failures. However, with the advent of highly complex systems that derive functionalities from multiple physical phenomena domains, more emphasis is required on identifying failures arising due to various system interactions, which is largely absent in existing failure analysis approaches. Owing to the causal nature of system interaction failures, the use of cognitive maps in system modeling and simulation for failure analysis is highly suitable. This paper proposes a structured framework for the development and use of cognitive mapbased system models capable of capturing all types of failure modes, including interaction failures. The applicability of the proposed framework is demonstrated with the example of an electric water heater.

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Section: Motivation and Outline Of Proposed Workmentioning

confidence: 99%

Cognitive map-based system modeling for identifying interaction failure modes

et al. 2011

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“…[50,51]) using behavioral models to simulate device behaviors. The model-based diagnosis community uses sophisticated qualitative reasoning to identify faulty components (e.g.…”

Section: Unintended Behaviorsmentioning

confidence: 99%

Deployment of an ontological framework of functional design knowledge

Kitamura

Kashiwase

Fuse

et al. 2004

Advanced Engineering Informatics

172

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“…Thus, generation of 'straightforward' violations may already help the designer. Such an approach is very similar to the generation of failure modes in computer-aided FMEA [8]. For the more complex forms of unintended use, including atypical user behavior, the deviation knowledge in the ontology could be supplied manually with concepts of unintended use from non-formalized sources such as company experience, historical data, user-panel testing results, etc.…”

Section: Finding Unintended Forms Of Usementioning

confidence: 99%

“…Information flow of working with a design-support system featuring ontology-based modeling of the use process of a product.users and the environment together with product behavior, can be considered related to our work; the extensions outside the 'focus' area inFigure 2are typically not included. Work in the area of computer-aided failure-mode and effects analysis (FMEA) as presented by Kmenta & Ishii, Hata et al, and by Lee focuses on unintended behavior (failure, in particular), but it tends to concentrate on internal behavior of the product[7][8][9].…”

mentioning

confidence: 99%

Coping With Unintended Behavior of Users and Products: Ontological Modelling of Product Functionality and Use

Vegte

Kitamura

Koji

et al. 2004

Volume 4: 24th Computers and Information in Engineering Conference

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The function-behavior representation language FBRL was originally devised for modeling and knowledge management of intended product behavior. This paper explores its potential for application to other-than-intended behavior in a product-use context by introducing consideration of the user and the environment. We found that slightly adapted building blocks from as-is FBRL can be applied to behavior that is unintended and/or not performed by the product. To support anticipation of unintended behavior in design, special attention has to be paid to the knowledge that connects product functions, user actions and environment behavior. We distinguish typical and atypical forms of unintended use. Some forms of typical unintended use can be directly derived from the intended use. Yet, most forms of unintended use require additional knowledge, e.g., from user observations. To include such knowledge, subsequent effort has to be put into its systematization. In this paper, an ontological scheme is presented for models of the product, the user and the environment and related use processes. We present an example and discuss how supporting tools can help designers to deal with unintended use. In the example case, a modeling schema for unintended behaviors of products is extended towards unintended behaviors of users.

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Representation of Functional Relations Among Parts And Its Application to Product Failure Reasoning

Cited by 10 publications

References 4 publications

Cognitive map-based system modeling for identifying interaction failure modes

Cognitive map-based system modeling for identifying interaction failure modes

Deployment of an ontological framework of functional design knowledge

Coping With Unintended Behavior of Users and Products: Ontological Modelling of Product Functionality and Use

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