Engineering product and process models are essential for the success of the implementation of IT systems in manufacturing companies. They need to have commonly recognized, unified, and global definitions of product entities and process resources and also can be interpreted by various computer programs. For product modeling, four classes of modeling methods are reviewed, i.e., solid product modeling, feature-based product modeling, knowledge-based product modeling, and integrated product modeling. For process modeling, an example application, i.e., chemical process engineering is discussed first to appreciate the modeling elements and constraints. Then a few generic engineering processes, such as engineering change management, are reviewed.
Semantic Modeling and Interoperability in Product and Process Engineering
year
2013
pages
31--51
publisher
Springer
crossref
Ma2013
file
Springer4Pro:2013/SajadfarXieEtAl13p31.pdf:PDF;Springer for Professionals:http\://www.springerprofessional.de/002---a-review-of-data-representation-of-product-and-process-models/4458410.html:URL
%0 Book Section
%1 SajadfarXieEtAl13p31
%A Sajadfar, Narges
%A Xie, Yanan
%A Liu, Hongyi
%A Ma, Y.-S.
%B Semantic Modeling and Interoperability in Product and Process Engineering
%C London
%D 2013
%E Ma, Yongsheng
%I Springer
%K 01624 springer paper ai knowledge processing factory process product engineering design database
%P 31--51
%R 10.1007/978-1-4471-5073-2_2
%T A Review of Data Representation of Product and Process Models
%X Engineering product and process models are essential for the success of the implementation of IT systems in manufacturing companies. They need to have commonly recognized, unified, and global definitions of product entities and process resources and also can be interpreted by various computer programs. For product modeling, four classes of modeling methods are reviewed, i.e., solid product modeling, feature-based product modeling, knowledge-based product modeling, and integrated product modeling. For process modeling, an example application, i.e., chemical process engineering is discussed first to appreciate the modeling elements and constraints. Then a few generic engineering processes, such as engineering change management, are reviewed.
@incollection{SajadfarXieEtAl13p31,
abstract = {Engineering product and process models are essential for the success of the implementation of IT systems in manufacturing companies. They need to have commonly recognized, unified, and global definitions of product entities and process resources and also can be interpreted by various computer programs. For product modeling, four classes of modeling methods are reviewed, i.e., solid product modeling, feature-based product modeling, knowledge-based product modeling, and integrated product modeling. For process modeling, an example application, i.e., chemical process engineering is discussed first to appreciate the modeling elements and constraints. Then a few generic engineering processes, such as engineering change management, are reviewed.},
added-at = {2014-04-14T14:02:28.000+0200},
address = {London},
author = {Sajadfar, Narges and Xie, Yanan and Liu, Hongyi and Ma, Y.-S.},
biburl = {https://www.bibsonomy.org/bibtex/2b92fd403103e91af2a7f03f091ee93af/flint63},
booktitle = {Semantic Modeling and Interoperability in Product and Process Engineering},
crossref = {Ma2013},
doi = {10.1007/978-1-4471-5073-2_2},
editor = {Ma, Yongsheng},
file = {Springer4Pro:2013/SajadfarXieEtAl13p31.pdf:PDF;Springer for Professionals:http\://www.springerprofessional.de/002---a-review-of-data-representation-of-product-and-process-models/4458410.html:URL},
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intrahash = {b92fd403103e91af2a7f03f091ee93af},
keywords = {01624 springer paper ai knowledge processing factory process product engineering design database},
pages = {31--51},
publisher = {Springer},
timestamp = {2017-07-13T17:15:15.000+0200},
title = {A Review of Data Representation of Product and Process Models},
username = {flint63},
year = 2013
}