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Parameterizing and capturing diagnos...

Rahimpour, Roozbeh.

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Parameterizing and capturing diagnostics information during design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Parameterizing and capturing diagnostics information during design./
作者:	Rahimpour, Roozbeh.
面頁冊數:	117 p.
附註:	Source: Masters Abstracts International, Volume: 37-01, page: 0358.
Contained By:	Masters Abstracts International37-01.
標題:	Engineering, System Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MQ30975
ISBN:	0612309754

Parameterizing and capturing diagnostics information during design.
Rahimpour, Roozbeh.

Parameterizing and capturing diagnostics information during design. - 117 p.

Source: Masters Abstracts International, Volume: 37-01, page: 0358.

Thesis (M.A.Sc.)--University of Windsor (Canada), 1997.

This thesis presents a new methodology for constructing a device's computer model to be used as the knowledge-base component of the model-based diagnostics expert system of the device. It is shown that parameterized functional and behavioural knowledge of a device could be applied to the diagnostics action to pin point the root cause of a fault. Four underlying concepts which are examined and deployed in this thesis to support the proposed methodology are: Parametric and feature based design, object oriented methodology for analysis and design, manufacturing as incorporating useful information into material, and using functional knowledge in diagnosing faults. The intended area of research explored in this project is Applications of Artificial Intelligence in manufacturing. To demonstrate the steps involved in implementing the proposed methodology, a prototype system is presented for diagnosing faults of a hair dryer based on its functional and behavioural parameters.

ISBN: 0612309754Subjects--Topical Terms:

1018128
Engineering, System Science.

Parameterizing and capturing diagnostics information during design.
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520 $a This thesis presents a new methodology for constructing a device's computer model to be used as the knowledge-base component of the model-based diagnostics expert system of the device. It is shown that parameterized functional and behavioural knowledge of a device could be applied to the diagnostics action to pin point the root cause of a fault. Four underlying concepts which are examined and deployed in this thesis to support the proposed methodology are: Parametric and feature based design, object oriented methodology for analysis and design, manufacturing as incorporating useful information into material, and using functional knowledge in diagnosing faults. The intended area of research explored in this project is Applications of Artificial Intelligence in manufacturing. To demonstrate the steps involved in implementing the proposed methodology, a prototype system is presented for diagnosing faults of a hair dryer based on its functional and behavioural parameters.
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