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Supporting Knowledge Re-Use with Effective Searches of Related Engineering Documents - A Comparison of Search Engine and Natural Language Processing-Based Algorithms

Part of: Knowledge-based Engineering

Published online by Cambridge University Press:  26 July 2019

Ivar Örn Arnarsson ,
Otto Frost ,
Emil Gustavsson ,
Daniel Stenholm ,
Mats Jirstrand  and
Johan Malmqvist
Ivar Örn Arnarsson*
Affiliation:
Chalmers University of Technology;
Otto Frost
Affiliation:
Fraunhofer-Chalmers Centre
Emil Gustavsson
Affiliation:
Fraunhofer-Chalmers Centre
Daniel Stenholm
Affiliation:
Chalmers University of Technology;
Mats Jirstrand
Affiliation:
Fraunhofer-Chalmers Centre
Johan Malmqvist
Affiliation:
Chalmers University of Technology;
*
Contact: Arnarsson, Ivar Örn, Volvo Trucks / Chalmers, Product Development, Sweden, varo@chalmers.se

Abstract

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Product development companies are collecting data in form of Engineering Change Requests for logged design issues and Design Guidelines to accumulate best practices. These documents are rich in unstructured data (e.g., free text) and previous research has pointed out that product developers find current it systems lacking capabilities to accurately retrieve relevant documents with unstructured data. In this research we compare the performance of Search Engine & Natural Language Processing algorithms in order to find fast related documents from two databases with Engineering Change Request and Design Guideline documents. The aim is to turn hours of manual documents searching into seconds by utilizing such algorithms to effectively search for related engineering documents and rank them in order of significance. Domain knowledge experts evaluated the results and it shows that the models applied managed to find relevant documents with up to 90% accuracy of the cases tested. But accuracy varies based on selected algorithm and length of query.

Keywords

Natural Language ProcessingSemantic data processingMachine learningKnowledge management
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 2597 - 2606
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

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