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Development of Data Models and Adapt...

Rehman, Hamood Ur,

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Development of Data Models and Adaptation Strategy for Self-Configuring Production Systems /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Development of Data Models and Adaptation Strategy for Self-Configuring Production Systems // Hamood Ur Rehman.
作者:	Rehman, Hamood Ur,
面頁冊數:	1 electronic resource (457 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-12, Section: A.
Contained By:	Dissertations Abstracts International86-12A.
標題:	Decomposition. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32092126
ISBN:	9798283477350

Development of Data Models and Adaptation Strategy for Self-Configuring Production Systems /
Rehman, Hamood Ur,

Development of Data Models and Adaptation Strategy for Self-Configuring Production Systems /Hamood Ur Rehman. - 1 electronic resource (457 pages)

Source: Dissertations Abstracts International, Volume: 86-12, Section: A.

Manufacturing intelligence is the ability to gather and analyse data for decision-making in production systems towards reaching an objective. This project involves introducing intelligence in production systems for achieving self-configuration. This is done by conceptualising and developing the intelligent components that act as building blocks of the self-configuring production systems and their application in the system. The approach taken for the project is iterative and built from the bottom-up. A classification tool is developed to study the capability of self-configuration in the current industrial production system, followed by insight gathered through surveys. The theoretical aspects involving self-configuration are discussed, and a general adaptation strategy is developed that integrates self-configuration capabilities in the intelligent components. These components are then manipulated and controlled through the use of technologies. Tools and techniques involving asset administration shell, state charts/state machines, multi-agent system, information model and machine learning approaches were studied. These technologies were implemented to achieve self-configuration, leveraging data gathered during operation. This research is applied to use cases of an industrial leak test equipment MALT and on a force testing station of the PRIME assembly system. The dissemination of work is highlighted, and future possibilities are expanded.

English

ISBN: 9798283477350Subjects--Topical Terms:

3561186
Decomposition.

Development of Data Models and Adaptation Strategy for Self-Configuring Production Systems /
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