Improved knowledge management through first-order logic in engineering design ontologies (original) (raw)

FIDOE: A Framework for Intelligent Distributed Ontologies in Engineering

Volume 3: 28th Computers and Information in Engineering Conference, Parts A and B, 2008

This paper presents FIDOE, a Framework for Intelligent Distributed Ontologies in Engineering. FIDOE consists of a suite of logic rules and templates for interactively developing relationships between properties of linked ontologies. The logical rules embedded in FIDOE automatically operate on various discipline-specific ontologies to systematically identify influences, direct and indirect, of proposed design modifications on other aspects of the design through common domain concepts. Once potential influences are identified, FIDOE enables the user to precisely define the domain relationships, using predefined templates, between the identified domain concepts that enumerate influence types. This tool, thus, provides a pervasive, real time awareness of the implications of design changes during the design process in a distributed environment.

A Methodology for Creating Ontologies for Engineering Design (modified version DETC2005

kp.man.dtu.dk

This paper describes a methodology for developing ontologies for engineering design. The methodology combines a number of methods from social science and computer science, together with taxonomies developed in the field of engineering design. The methodology is based upon empirical research and hence, focuses upon understanding a user´s domain models as opposed to extracting an ontology from documentation. A case study is used throughout the paper focusing upon the use of an ontology for searching, indexing and retrieving engineering knowledge. An ontology for indexing design knowledge can assist the users to formulate their queries when searching for engineering design knowledge. The root concepts of the ontology were elicited from engineering designers during an empirical research study. These formed individual taxonomies within the ontology and were validated through indexing a set of ninety-two documents. Relationships between concepts are extracted as the ontology is populated with instances. The identified root concepts were found to be complete and sufficient for the purpose of indexing. A thesaurus and an automatic classification are being developed as a result of this evaluation. The methodology employed during the test case is presented in this paper. There are six separate stages, which are presented together with the research methods employed for each stage and the evaluation of each stage. The main contribution of this research is the development of a methodology to allow researchers and industry to create ontologies for their particular purpose and to develop a thesaurus for the terms within the ontology. of a taxonomy, for example, species would be the root concept for a taxonomy about species. As the ontology developed during this research project consists of several taxonomies and their relations, it is referred to as an integrated taxonomy (EDIT Engineering Design Integrated Taxonomy). As the integrated taxonomy is populated with instances the relationships between concepts (or multiple concepts) are captured and the ontology emerges.

A methodology for creating ontologies for engineering design

Journal of computing and Information …, 2007

The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original document and are linked to publications on ResearchGate, letting you access and read them immediately.

From Concepts to Design Ontologies

The research on engineering knowledge systems is continually evolving. Knowledge is conveyed through the thought processes of engineers. In order to provide adequate support for engineering design the thought processes must be understood. The aim of this paper is to discuss how to transform conceptual knowledge to design ontologies. We suggest a procedure termed Cartesian reasoning to explicate some intuitive steps in engineering thinking and to put them under scrutiny.

Ontologies for supporting engineering analysis models

2005

Abstract In this paper we lay the foundations for exchanging, adapting, and interoperating engineering analysis models (EAMs). Our primary foundation is based upon the concept that engineering analysis models are knowledge-based abstractions of physical systems, and therefore knowledge sharing is the key to exchanging, adapting, and interoperating EAMs within or across organizations. To enable robust knowledge sharing, we propose a formal set of ontologies for classifying analysis modeling knowledge.

Ontologies for Supporting Engineering Design Optimization

Volume 1: 32nd Design Automation Conference, Parts A and B, 2006

This paper presents an optimization ontology and its implementation into a prototype computational knowledge-based tool dubbed ONTOP (ontology for optimization). Salient feature of ONTOP include a knowledge base that incorporates both standardized optimization terminology, formal method definitions, and often unrecorded optimization details, such as any idealizations and assumptions that may be made when creating an optimization model, as well as the model developer's rationale and justification behind these idealizations and assumptions. ONTOP was developed using Protégé, a Java-based, free open-source ontology development environment created by Stanford University. Two engineering design optimization case studies are presented. The first case study consists of the optimization of a structural beam element and demonstrates ONTOP's ability to address the variations in an optimal solution that may arise when different techniques and approaches are used. A second case study, a more complex design problem that deals with the optimization of an impeller of a pediatric left ventricular heart assist device, demonstrates the wealth of knowledge ONTOP is able to capture. Together, these test beds help illustrate the potential value of an ontology in representing application-specific knowledge while facilitating both the sharing and exchanging of this knowledge in engineering design optimization. Downloaded From: http://computingengineering.asmedigitalcollection.asme.org/ on 05/14/2014 Terms of Use: http://asme.org/terms Transactions of the ASME Downloaded From: http://computingengineering.asmedigitalcollection.asme.org/ on 05/14/2014 Terms of Use: http://asme.org/terms

Interoperability of disparate engineering domain ontologies using basic formal ontology

Journal of Engineering Design

As engineering applications require management of ever larger volumes of data, ontologies offer the potential to capture, manage, and augment data with the capability for automated reasoning and semantic querying. Unfortunately, considerable barriers hinder wider deployment of ontologies in engineering. Key among these is lack of a shared top-level ontology to unify and organize disparate aspects of the field and coordinate co-development of orthogonal ontologies. As a result, many engineering ontologies are limited to their scope, and functionally difficult to extend or interoperate with other engineering ontologies. This paper demonstrates how the use of a top-level ontology, specifically the Basic Formal Ontology (BFO), greatly facilitates interoperability of multiple engineering-related ontologies. We constructed a system of formal linked ontologies by re-engineering legacy ontologies to be conformant with BFO and developing new BFO-conformant ontologies to capture knowledge in the engineering design, enterprise, human factors, manufacturing, and application domain of additive manufacturing. The resulting Integrated Framework for Additively Manufactured Products (IFAMP), including the body knowledge instantiated on its basis, serve as the basis for a proposed Design with Additive Manufacturing Method (DAMM), which we believe can support the design of innovative products with semantically enhanced ideation tools and enhanced access to application domain knowledge. The method and its facilitation through the ontological framework are demonstrated using a case study in medicine.

Design Process Modeling: Towards an Ontology of Engineering Design Activities

2008

An ontology of engineering design activities, called the Design Activity Ontology (DAO), is developed in this research. The DAO models 82 information flows and 25 design activities. These activities cover phases of the design process from conceptual phase through detail design phase. The ontology provides a formalized and structured vocabulary of design activities for consistency and exchange of design process models. The DAO enables design processes to be modeled, analyzed and optimized. The DAO is constructed using information flows identified in current design literature, commonly accepted engineering design textbooks, and an existing activity ontology. Specifically, the DAO is an extension and refinement of the ontology proposed by Sim and Duffy. The DAO addresses several shortcomings of the Sim and Duffy ontology including: (1) lack of computational representation, (2) inability to construct process models from defined design activities, (3) redundant and semantically equivalent information flows, (4) complex information flows, and (5) inconsistent classification. These shortcomings are identified through Design Structure Matrix (DSM) modeling and analysis, and certain protocols for the analysis of the individual information flows. A total of 112 information flows and 26 activities from the Sim and Duffy ontology are reduced to 82 and 25 respectively. The DAO is implemented in the Protégé using the Web Ontology Language (OWL) and Description Logic (DL). The implemented DAO is analyzed using DL's subsumption property through the Fact++ reasoner. Finally, the DAO is exercised through two demonstration examples: (1) the design of a trash truck and (2) the design of an automotive tail light installation fixture. Results from the example support the completeness of the ontology; ability to formulate design processes; and identify "dead-end" information flows, information flows required in design but not generated and critical information flows. iii DEDICATION Dedicated to my loving parents, Radha P. Kumar (Mom) and C.R. Prasanna Kumar (Dad); and my adorable sister, Pooja. I would also like to dedicate this piece of work to my special friends, who have stood beside me, always; and have taken all my tantrums gleefully.