Dependency analysis in constraint negotiation

Kusiak, Andrew; Wang, J.

doi:10.1109/21.400508

Cited by 61 publications

(54 citation statements)

References 10 publications

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“…Building dependency networks among design variables is regarded as an effective way to propagate design modifications and maintain information consistency. For example, Kusiak [7] proposed to use dependency analysis to resolve conflicted constraints. Park and Cutkosky [15] mentioned using dependencies at different abstraction levels to maintain information consistency.…”

Section: Dependency Network and Its Implementationmentioning

confidence: 99%

Knowledge-Based Reasoning in a Unified Feature Modeling Scheme

Chen

Thimm

et al. 2005

Computer-Aided Design and Applications

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Feature-based modeling is an accepted approach to include high-level geometric information in product models as well as to facilitate a parameterized and constraint-based product development process. Moreover, features are suitable as an intermediate layer between a product's knowledge model and its geometry model for effective and efficient information management. To achieve this, traditional feature technology must be extended to align with the approach of knowledge-based reasoning. In this paper, based on a previously proposed unified feature modeling scheme, feature definitions are extended to support knowledge-based reasoning. In addition, a communication mechanism between the knowledge-based system and the feature model is established. The methods to embed and use knowledge for information consistency control are described.Keywords: Unified feature; Knowledge-based reasoning; Feature-based modeling INTRODUCTIONHistorically, computer-aided tools, such as CAD, CAPP and CAM systems are developed to support the corresponding product lifecycle phases. Product geometry takes up a significant position in these systems. Feature technology is mainly used to provide high-level geometric representations to facilitate parameterized and constraint-based product geometric design process. However, traditional CAD systems usually assume that a designer has already finished the conceptual design as well as the concept-to-geometry mapping [17]. Therefore, only geometric modeling functions are provided in these CAD systems. Due to this limitation, some information, such as the design intent and the process patterns, is lost during the design process. Explicitly embedding knowledge-based reasoning processes within the traditional engineering systems can significantly enhance the systems' reusability, scalability and flexibility. Knowledge-oriented techniques can support more complex tasks with natural human-oriented intelligent processes. They are more acceptable by human-beings than dataoriented techniques. They can also represent and deal with inaccurate and incomplete information as well as rule-ofthumbs, which are usually difficult to be described mathematically. Due to the different natures between the knowledge information entities and the geometric entities, to interface the knowledge-based reasoning processes with the geometric modeling processes, an intermediate information layer is necessary. Feature-based technology can provide such a bridge. However, the current feature modeling technology has to be extended in two directions. First, feature definitions need to be extended to support knowledge-based reasoning processes. The purpose of this extension are checking and maintaining feature validity in the view of design intent. In other words, each feature model should be consistent to its specific knowledge bases. Second, the communication mechanism between the knowledge bases and the feature models must be established. This paper is intended to address the key issues for enabling knowledge-based reasoning in...

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Section: Dependency Network and Its Implementationmentioning

confidence: 99%

Knowledge-Based Reasoning in a Unified Feature Modeling Scheme

Chen

Thimm

et al. 2005

Computer-Aided Design and Applications

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“…Dependency networks provide a general solution. Kusiak and Wang (1995) used dependency relations to represent constraints on design variables. Four types of constraints are mentioned: equation, qualitative constraints, computer-based procedures, and influence rules.…”

Section: Persistent Representation For Non-geometric Associationsmentioning

confidence: 99%

Paradigm shift: unified and associative feature-based concurrent and collaborative engineering

Chen

Thimm

2008

J Intell Manuf

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With widely used concurrent and collaborative engineering technologies, the validity and consistency of product information become important. In order to establish the state of the art, this paper reviews emerging concurrent and collaborative engineering approaches and emphasizes on the integration of different application systems across product life cycle management (PLM) stages. It is revealed that checking product information validity is difficult for the current computer-aided systems because engineering intent is at best partially represented in product models. It is also not easy to maintain the consistency among related product models because information associations are not established. The purpose of this review is to identify and analyze research issues with respect to information integration and sharing for future concurrent and collaborative engineering. A new paradigm of research from the angle of feature unification and association for product modeling and manufacturing is subsequently proposed.Keywords Concurrent and collaborative engineering · Feature-based design and manufacturing · Product life cycle modeling · Information validity and consistency

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“…We can refine the fuzzy rule base by introducing new lingusitic variables modeling the linguistic dependencies between the variables and the objectives [1,2,4,11,15]. Namely, suppose we have the following piece of knowledge if .…”

Section: Refining the Fuzzy Rule Basementioning

confidence: 99%

Multiobjective linguistic optimization

Carlsson¹,

Fuller²

2000

Fuzzy Sets and Systems

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Generalizing our earlier results on optimization with linguistic variables [3,6,7] we introduce a novel statement of fuzzy multiobjective mathematical programming problems and provide a method for finding a fair solution to these problems. Suppose we are given a multiobjective mathematical programming problem in which the functional relationship between the decision variables and the objective functions is not completely known. Our knowledge-base consists of a block of fuzzy if-then rules, where the antecedent part of the rules contains some linguistic values of the decision variables, and the consequence part consists of a linguistic value of the objective functions. We suggest the use of Tsukamoto's fuzzy reasoning method to determine the crisp functional relationship between the decision variables and objective functions. We model the anding of the objective functions by a tnorm and solve the resulting (usually nonlinear) programming problem to find a fair optimal solution to the original fuzzy multiobjective problem.

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Dependency analysis in constraint negotiation

Cited by 61 publications

References 10 publications

Knowledge-Based Reasoning in a Unified Feature Modeling Scheme

Knowledge-Based Reasoning in a Unified Feature Modeling Scheme

Paradigm shift: unified and associative feature-based concurrent and collaborative engineering

Multiobjective linguistic optimization

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