Constraint capture and maintenance in engineering design

Abstract The Designers' Workbench is a system developed by the Advanced Knowledge Technologies Consortium to support designers in large organizations, such as Rolls-Royce, to ensure that the design is consistent with the specification for the particular design as well as with the company's design rule book(s). In the principal application discussed here, the evolving design is described using a jet engine ontology. Design rules are expressed as constraints over the domain ontology. Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench's knowledge base. This is an error-prone and time-consuming task. It is highly desirable to relieve the knowledge engineer of this task, so we have developed a system, ConEditor+, that enables domain experts themselves to capture and maintain these constraints. Further, we hypothesize that to appropriately apply, maintain, and reuse constraints, it is necessary to understand the underlying assumptions and context in which each constraint is applicable. We refer to them as “application conditions,” and these form a part of the rationale associated with the constraint. We propose a methodology to capture the application conditions associated with a constraint and demonstrate that an explicit representation (machine interpretable format) of application conditions (rationales) together with the corresponding constraints and the domain ontology can be used by a machine to support maintenance of constraints. Support for the maintenance of constraints includes detecting inconsistencies, subsumption, redundancy, fusion between constraints, and suggesting appropriate refinements. The proposed methodology provides immediate benefits to the designers, and hence, should encourage them to input the application conditions (rationales).

[1]  Ulrich Junker Conflict Detection for Arbitrary Constraint Propagation Algorithms , 2001 .

[2]  R. A. Adey,et al.  Knowledge Based Expert Systems in Engineering: Planning and Design , 1988 .

[3]  Becky L. Hooey,et al.  Requirements for a Design Rationale Capture Tool to Support NASA's Complex Systems , 2007 .

[4]  Ulrich Junker,et al.  The Logic of ILOG ( J ) Configurator : Combining Constraint Programming with a Description Logic , 2003 .

[5]  James Bowen,et al.  Design Rationale Management in Concurrent Engineering , 1992 .

[6]  William C. Regli,et al.  A Survey of Design Rationale Systems: Approaches, Representation, Capture and Retrieval , 2000, Engineering with Computers.

[7]  Alun Preece,et al.  Verifying expert systems: A logical framework and a practical tool , 1992 .

[8]  Henrik Eriksson,et al.  Custom-Tailored Development Tools for Knowledge-Based Systems , 1994 .

[9]  Deborah L. McGuinness,et al.  OWL Web ontology language overview , 2004 .

[10]  Christopher Tong,et al.  Artificial Intelligence in Engineering Design , 1992 .

[11]  Markus Stumptner,et al.  Consistency-based diagnosis of configuration knowledge bases , 1999, Artif. Intell..

[12]  Rob H. Bracewell,et al.  A TOOL FOR CAPTURING DESIGN RATIONALE , 2003 .

[13]  L.-C. Chen,et al.  Constraints modelling in product design , 2002 .

[14]  J. Goonetillake,et al.  Management of Evolving Constraints in a Computerised Engineering Design Environment , 2005 .

[15]  D. Sriram,et al.  The Representation and Use of Constraints in Structural Design , 1986 .

[16]  John M. Carroll,et al.  Design rationale: concepts, techniques, and use , 1996 .

[17]  Walton A. Perkins,et al.  Checking an Expert Systems Knowledge Base for Consistency and Completeness , 1985, IJCAI.

[18]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[19]  Alun Preece,et al.  An Expressive Constraint Language for Semantic Web Applications , 2001 .

[20]  Nick Bassiliades,et al.  CoLan: A Functional Constraint Language and its Implementation , 1995, Data Knowl. Eng..

[21]  David C. Brown,et al.  Rationale Support for Maintenance of Large Scale Systems , 2003 .

[22]  Du Zhang,et al.  PREPARE: A Toll for Knowledge Base Verification , 1994, IEEE Trans. Knowl. Data Eng..

[23]  Alun D. Preece,et al.  Verification and validation of knowledge-based systems with formal specifications , 1995, The Knowledge Engineering Review.

[24]  Bob J. Wielinga,et al.  Configuration-Design Problem Solving , 1997, IEEE Expert.

[25]  Mysore Ramaswamy,et al.  Knowledge Base Decomposition to Facilitate Verification , 2000, Inf. Syst. Res..

[26]  Neli P. Zlatareva A refinement framework to support validation and maintenance of knowledge-based systems , 1998 .

[27]  R. T. Evans Usability testing and research , 2002 .

[28]  Rob H. Bracewell,et al.  DRed and Design Folders: A Way of Capturing, Storing and Passing On Knowledge Generated During Design Projects , 2004, DAC 2004.

[29]  Li Lin,et al.  Implementation of knowledge maintenance modules in an expert system for fault diagnosis of chemical process operation , 2005, Expert Syst. Appl..

[30]  Mark A. Musen,et al.  The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility , 2000, EKAW.

[31]  F. Harary A graph theoretic approach to matrix inversion by partitioning , 1962 .

[32]  Alun D. Preece,et al.  Extending SWRL to Express Fully-Quantified Constraints , 2004, RuleML.

[33]  Dana Chisnell,et al.  Handbook of Usability Testing , 2009 .

[34]  Edward H. Shortliffe,et al.  An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System , 1982, AI Mag..

[35]  James Bowen,et al.  A constraint programming language for Life-Cycle Engineering , 1990, Artif. Intell. Eng..

[36]  Jeffrey Rubin,et al.  Handbook of Usability Testing: How to Plan, Design, and Conduct Effective Tests , 1994 .

[37]  Michael J. Maher,et al.  Constraint Hierarchies and Logic Programming , 1989, ICLP.

[38]  Edward H. Shortliffe,et al.  An approach to verifying completeness and consistency in a rule-expert system , 1989 .

[39]  David G. Ullman,et al.  Design rationale: Concepts, techniques, and use , 1997 .

[40]  Virginia E. Barker,et al.  Expert systems for configuration at Digital: XCON and beyond , 1989, Commun. ACM.

[41]  Steve Culley,et al.  Knowledge management in engineering design: personalization and codification , 2004 .

[42]  Derek H. Sleeman,et al.  Acquisition and maintenance of constraints in engineering design , 2005, K-CAP '05.

[43]  D. Sriram,et al.  Applications of Artificial Intelligence in Engineering Problems , 1986 .

[44]  Richard C. Hicks,et al.  Knowledge base management systems-tools for creating verified intelligent systems , 2003, Knowl. Based Syst..

[45]  Tal Streeter The art of the Japanese kite , 1974 .

[46]  Allen Ginsberg Knowledge-Base Reduction: A New Approach to Checking knowledge Bases for Inconsistency and Redundancy , 1988, AAAI.

[47]  Frank van Harmelen,et al.  Maintenance of KBS's by Domain Experts: The Holy Grail in Practice , 2000, IEA/AIE.

[48]  Peter M. D. Gray,et al.  Capturing Quantified Constraints in FOL, Through Interaction with a Relationship Graph , 2006, EKAW.

[49]  D. V. Steward On an Approach to Techniques for the Analysis of the Structure of Large Systems of Equations , 1962 .

[50]  Elliot Soloway,et al.  Assessing the Maintainability of XCON-in-RIME: Coping with the Problems of a VERY Large Rule-Base , 1987, AAAI.

[51]  David Serrano,et al.  Tools and techniques for conceptual design , 1992 .

[52]  Suraj Ajit,et al.  Capture and maintenance of constraints in engineering design , 2009 .