Layered Product Knowledge Representation and Reasoning With OWL and SWRL

2008 ◽  
Author(s):  
Jung-Do Noh ◽  
Hyo-Won Suh
Keyword(s):  
Product Development ◽  
Data Model ◽  
Description Logic ◽  
Knowledge Representation And Reasoning ◽  
Design Knowledge ◽  
Design Decision ◽  
Product Knowledge ◽  
Product Data ◽  
Ontology Language ◽  
Product Data Model

Traditionally, product development process has required knowledge management techniques to capture information and knowledge about design. In the meantime, the necessity for sharing and exchanging not only product data but also semantics of product data has been arisen because of the use of various software tools and product data models in distributed product development environment. The main focus of this research has been on exploiting implicit engineers’ design knowledge by explicitly expressing and sharing the knowledge through terms representing semantics of product data. In particular, it considers that distributed product design data can be semantically integrated by using ontology on which implicit design knowledge can be captured in the form of IF-THEN rule. Thus, in this paper, we use the Web Ontology Language (OWL), which is a Description Logic based ontology language, to represent product data and the Semantic Web Rule Language (SWRL), which is a rule based ontology language, to express design knowledge for car air purifiers in Prote´ge´. Then, this paper shows how OWL product data model and SWRL design knowledge can support design decision making of car air purifiers by their reasoning. In addition, it also demonstrates how SWRL can complement OWL to build product data model as well.

Intelligent Product Data Exchange

1999 ◽  
Author(s):  
Karl-H. Grote ◽  
Soeren Schumann
Keyword(s):  
Engineering Design ◽  
Data Model ◽  
Data Exchange ◽  
Product Data ◽  
Engineering Design Process ◽  
Problems And Solutions ◽  
Computer Based ◽  
Software Platforms ◽  
Product Data Model ◽  
Intelligent Product

Abstract The computer based engineering design process today is characterized by a large variety of (specialized) systems. This and the ongoing globalization and outsourcing of engineering services and competencies causes an increased need for data exchange over the borders of the numerous CAx-systems. Under these circumstances, data exchange has been playing an important role for time and cost sensitive development and manufacturing in every field of industry. This paper presents actual problems and solutions of data exchange over the borders of modern software platforms. It includes the description of possible influences on a product data model and introduces the latest data exchange concepts.

Integration of Heterogeneous Product Information for Industrial Cluster

2012 ◽  
Vol 201-202 ◽  
pp. 898-901
Author(s):  
Jun He Yu ◽  
Hong Fei Zhan
Keyword(s):  
Data Model ◽  
Product Information ◽  
Industrial Cluster ◽  
Structure And Properties ◽  
Integration Framework ◽  
Product Data ◽  
Product Data Model ◽  
Model Class ◽  
And Function ◽  
Classification Structure

This paper analyzed the heterogeneous product information for industrial cluster. It plays an important role in collaboration of enterprise and product information inquires in industrial cluster. The paper presented globe product data model based on PLIB standard. The globe classification structure and properties definition were given as the globe ontology for industrial cluster. The product class was expressed by general model class and function model class. The class is defined with the properties. The class and properties for injection machine were described as an example. According to the globe product data model, the integration framework can make the integration of heterogeneous product information and provide the unique inquire interface for the end customer. The integration framework was presented and analyzed.

Decision Retrieval and Storage Enabled Through Description Logic

2007 ◽  
Author(s):  
Gregory M. Mocko ◽  
David W. Rosen ◽  
Farrokh Mistree
Keyword(s):  
Knowledge Representation ◽  
Product Development ◽  
Cantilever Beam ◽  
Description Logic ◽  
Decision Models ◽  
Design Decision ◽  
Engineering Knowledge ◽  
Query Concepts ◽  
And Storage

The problem addressed in the paper is how to represent the knowledge associated with design decision models to enable storage, retrieval, and reuse. The paper concerns the representations and reasoning mechanisms needed to construct decision models of relevance to engineered product development. Specifically, AL[E][N] description logic is proposed as a formalism for modeling engineering knowledge and for enabling retrieval and reuse of archived models. Classification hierarchies are constructed using subsumption in DL. Retrieval of archived models is supported using subsumption and query concepts. In our methodology, design decision models are constructed using the base vocabulary and reuse is supported through reasoning and retrieval capabilities. Application of the knowledge representation for the design of a cantilever beam is demonstrated.

Fuzzy Declaration Modeling of Data Models Using EXPRESS

2004 ◽  
Author(s):  
Z. M. Ma
Keyword(s):  
Data Model ◽  
Incomplete Data ◽  
Product Life Cycle ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Product Data ◽  
Intelligent Manufacturing System ◽  
Design And Manufacturing ◽  
Engineering Information ◽  
Product Data Model

Information with imprecision and uncertainty is inherently presented in engineering design and manufacturing. The nature of imprecision and uncertainty is incompleteness. Product data model, being a core of intelligent manufacturing system, consists of all concerned data in the product life cycle. It is possible that crisp data as well as incomplete data are involved in product data model. So EXPRESS, being a powerful tool to develop a product data model, should be extended for this purpose. This paper extends the declaration in EXPRESS to make it possible to model fuzzy engineering information.

The product data model as a pool for CAD-FEA data

1998 ◽  
Vol 14 (2) ◽  
pp. 115-122 ◽  
Author(s):  
U. Gabbert ◽  
P. Wehner
Keyword(s):  
Data Model ◽  
Product Data ◽  
Product Data Model
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