Abstract

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term.

Highlights

  • Within the aerospace industry, the use of Knowledge-based engineering (KBE) methods and technologies has played a major role in automating routine and mundane design activities in view of supporting the cost-effective and timely development of a product

  • Graphical user interfaces that bridge the gap between KBE knowledge, Computer Aided Design (CAD) system and product designers are of high importance as presented in this study. This will ensure that end-users can directly interact with the ontology knowledge base and CAD system through a developed GUI that connects to all KBE components as presented in the primitive shapes KBE system case study

  • This paper has reported an ontology-based methodological framework for developing platform-independent KBE systems

Read more

Summary

Introduction

The use of Knowledge-based engineering (KBE) methods and technologies has played a major role in automating routine and mundane design activities in view of supporting the cost-effective and timely development of a product Developing these knowledge enabled KBE systems usually requires considerable effort in capturing, formalising and codifying knowledge. The focus of this study is to investigate approaches for developing KBE systems that are platform independent, well structured and offers high level of knowledge reuse For this purpose, ontology-based approaches for modelling the design parameters and design rules for KBE systems are employed. Particular attention is given to exploiting application programming interfaces (APIs) as a means of a communication and integration medium between KBE software components

Literature review and research scope
Research methodology
Justification of KBE framework components
Framework development
KBE system knowledge capture
An overview of the adopted ontology method
Ontology model construct of KBE system
Model-driven transformations and specifications
PIM technology selection and implementation
Architecture of platform-independent KBE system
Modelling of KBE design parameters and design rules
Integration of PIM KBE knowledge with CAD system
Validation and benefits
Not Generic
Semantic technologist 70
Discussions
Findings
Conclusions and future work
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call