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A framework for product data
DOI:10.1109/69.542033.png)
摘要
En 中文
Improved support for engineering using information technology involves the integration of existing, evolving and future product data, and software that processes that data. For this reason, there is increasing interest in the representation of product data in the computer to support computer-aided engineering applications. To avoid duplication and inconsistency, and to support the use of new implementation technology as it emerges, conceptual models of product data are required. Such models are independent of the software and hardware environments in which they are implemented. System architectures to support the integration of applications at implementation time are becoming an accepted part of engineering information systems. We contend that, to use these software support environments effectively, integrated product data is required. Further, it must be possible to extend the integrated product data in a controlled fashion ii it is to evolve to support future engineering applications effectively. A framework that is a part of the product data, at the conceptual modeling (rather than the implementation) stage, is shown to help to satisfy these requirements. The framework presented here is a structure for the information content of product data rather than for the implementation of such data. Our research has shown that product data based on the framework can be successfully implemented in a number of different forms, for example, network, relational, and object-oriented databases. This paper describes a framework for electromechanical product data that has been implemented in a structure editor and is currently being used to support a range of engineering applications. We show that the process of product data integration can be improved by using existing integration strategies in conjunction with a framework that provides an overall organization for the data.
Keyword:
application
architecture
computer-aided engineering
framework
integration
product data model
product model
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期刊
IF:
10.4
论文数:
6.9K
被引数:
3.8W
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