Expressions With Fuzzy Information in EXPRESS/STEP

2005 ◽  
Author(s):  
Z. M. Ma
Keyword(s):  
Data Model ◽  
Product Life Cycle ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Fuzzy Information ◽  
Product Data ◽  
Imperfect Data ◽  
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 imperfect 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 expressions in EXPRESS to make it possible to model fuzzy engineering information.

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.

Fuzzy Data Type Modeling With EXPRESS

2001 ◽  
Author(s):  
Z. M. Ma ◽  
W. J. Zhang ◽  
W. M. Ma
Keyword(s):  
Data Model ◽  
Incomplete Data ◽  
Product Life Cycle ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Fuzzy Information ◽  
Data Types ◽  
Product Data ◽  
Design And Manufacturing ◽  
Product Data Model

Abstract 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 data types in EXPRESS to make it possible to represent fuzzy information.

Evaluating a Change Process Product Data Model for an Analysis Driven Supply Chain Case Study

1999 ◽  
Author(s):  
Tal Cohen ◽  
Russell S. Peak ◽  
Robert E. Fulton
Keyword(s):  
Supply Chain ◽  
Change Management ◽  
Data Model ◽  
Product Life Cycle ◽  
Analysis Data ◽  
Product Analysis ◽  
Standard Format ◽  
Product Data ◽  
Product Data Model

Abstract This paper introduces a change management case study using Product Data-Driven Analysis scenarios from TIGER [TIGER, 97] — a supply chain case study — and an associated mapping to a STEP data model, a standard format product data model terminology. The case study describes supply chain scenarios that involve prime with contractors, subcontractors and consulting entities. The core activity within these scenarios is an engineering analysis of Printed Wiring Boards (PWB) with a focus on modeling product analysis data. Analysis of PWB can involve an iterative process that translates to changes to the product data. Application protocol 208 [STEP, Part 208/CD] is an underdeveloped part of the STEP standard and deals with product life cycle and change management. These changes are incorporated into the case study scenarios and the capability of AP 208 to capture them is evaluated.

Extending Express-G to Model Fuzzy Information in Product Data Model

2000 ◽  
Author(s):  
Z. M. Ma ◽  
W. J. Zhang ◽  
W. Y. Ma ◽  
G. Q. Chen
Keyword(s):  
Product Design ◽  
Engineering Design ◽  
Data Model ◽  
Product Life Cycle ◽  
Database Systems ◽  
Typical Feature ◽  
Design Calculation ◽  
Uncertain Information ◽  
Product Data ◽  
Product Data Model

Abstract Information with uncertainty and imprecision is inherently presented in engineering design and manufacturing. The nature of uncertainty and imprecision is incompleteness. The incompleteness is a typical feature in earlier product design phases. Product design is essentially viewed as a process of reducing the incompleteness in the description of conceptual design. Some methods and strategies for the preliminary engineering design, calculation, and modeling in relational database systems have been proposed to process imprecise and uncertain information. Product data model, being a core of intelligent manufacturing system, consists of all concerned data in the product life cycle. EXPRESS-G is a powerful tool to develop a product data model. This paper extends the EXPRESS-G to make it possible to represent information with uncertainty and imprecision.

scholarly journals A Data Management Approach Based on Product Morphology in Product Lifecycle Management

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1235
Author(s):  
Gang Liu ◽  
Rongjun Man ◽  
Yanyan Wang
Keyword(s):  
Data Management ◽  
Data Model ◽  
Product Life Cycle ◽  
Digital Products ◽  
Product Data ◽  
Core Data ◽  
The Core ◽  
Product Data Model ◽  
Single Data ◽  
Product Forms

In the product life cycle from conception to retirement, there are three forms: conceptual products, digital products and physical products. The carriers of conceptual products are requirements, functions and abstract structures, and data management focuses on the mapping of requirements, functions, and structures. The carrier of digital products is digital files such as drawings and models, and the focus of data management is the design evolution of product. Physical products are physical entities, and their attributes and states will change over time. Existing data model research often focuses on one or two forms, and it is even impossible to integrate three forms of data into one system. So, a new data management method based on product form is presented. According to the characteristics of the three product form data, a conceptual product data model, a digital product data model, and a physical product data model are established to manage the three forms of data, respectively, and use global object mapping to integrate them into a unified data model. The conceptual product data model has a single data model for a single business stage. The digital product data model uses the core data model as the single data source, and uses one stage rule filter to add constraints to the core data model for each business stage. The physical product data model uses the core data model to manage the public data of the physical phase, and the phase private data model focuses on the private data of each business phase. Finally, a case of Multi-Purpose Container Vessel is studied to verify the feasibility of the method. This paper proposes three product forms of product data management and a unified data management model covering the three product forms, which provides a new method for product life cycle data.

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.

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