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.

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.

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 Manufacturing System of Product Life Cycle Management in Value Engineering

2011 ◽  
Vol 63-64 ◽  
pp. 251-254
Author(s):  
Wen Tsann Lin ◽  
Shen Tsu Wang ◽  
Meng Hua Li ◽  
Jiung Ming Huang
Keyword(s):  
Life Cycle ◽  
Product Life Cycle ◽  
Manufacturing System ◽  
Life Cycle Management ◽  
Intelligent Manufacturing ◽  
Value Engineering ◽  
Product Life ◽  
Product Life Cycle Management ◽  
Intelligent Manufacturing System ◽  
Weighted Values

This study first introduced product life cycle management procedures for designing expert questionnaire, and employed the Delphi method to investigate managerial functions of an intelligent manufacturing system in order to demonstrate performance of preliminary research results. Following that, the intelligent manufacturing management system was constructed, and weighted values of management functions were collected. The management function performance was evaluated through value analysis in order to determine whether system functions meet corporate goals. All functions were obtained using the hierarchic analysis method in value engineering analysis. The rational function weights were guaranteed through hierarchy consistency, and compared with the labor costs of operating such system functions to analyze whether the functions were in a suitable domain. After a two-phase investigation, based on expert comments and application functions, production control based on an intelligent manufacturing system can reduce personnel and time costs, thus, effectively increasing corporate competitive power.

An EDM Multi-Agent Collaborative Manufacturing System Based on Petri Net

2012 ◽  
Vol 457-458 ◽  
pp. 921-926
Author(s):  
Jin Zhi Zhao ◽  
Yuan Tao Liu ◽  
Hui Ying Zhao
Keyword(s):  
Petri Net ◽  
Manufacturing System ◽  
Intelligent Manufacturing ◽  
Agent Technology ◽  
Manufacturing Processes ◽  
Intelligent Manufacturing System ◽  
Collaborative Manufacturing ◽  
Model Based ◽  
Support Organizations ◽  
Multi Agent

A framework for building EDM collaborative manufacturing system using multi-agent technology to support organizations characterized by physically distributed, enterprise-wide, heterogeneous intelligent manufacturing system over Internet is proposed. According to the characteristics of agile EDM collaborative manufacturing system(AEDMCMS), the agent technology is combined with Petri net in order to analyze the model. Based on the basic Petri Net, the definition is extended and the Agent-oriented Petri net (APN) is proposed. AEDMCM is turned into the model of Petri Net which is suitable to the analysis and optimization of manufacturing processes.

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