Simulation based knowledge elicitation:effect of visual representation and model parameters

Abstract

Since much knowledge is tacit, eliciting knowledge is a common bottleneck during the development of knowledge-based systems. Visual interactive simulation (VIS) has been proposed as a means for eliciting experts’ decision-making by getting them to interact with a visual simulation of the real system in which they work. In order to explore the effectiveness and efficiency of VIS based knowledge elicitation, an experiment has been carried out with decision-makers in a Ford Motor Company engine assembly plant. The model properties under investigation were the level of visual representation (2-dimensional, 2½-dimensional and 3-dimensional) and the model parameter settings (unadjusted and adjusted to represent more uncommon and extreme situations). The conclusion from the experiment is that using a 2-dimensional representation with adjusted parameter settings provides the better simulation-based means for eliciting knowledge, at least for the case modelled.

Publication DOI: https://doi.org/10.1016/j.eswa.2012.01.170
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications,39, 9, (2012) DOI: http://dx.doi.org/10.1016/j.eswa.2012.01.170
Uncontrolled Keywords: automobile industry,discrete-event simulation,knowledge-based systems,knowledge elicitation,visual fidelity,visual interactive simulation,Artificial Intelligence,Computer Science Applications,Engineering(all)
Publication ISSN: 1873-6793
Last Modified: 26 Mar 2024 08:08
Date Deposited: 11 Mar 2019 18:02
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2012-07
Published Online Date: 2012-03-02
Authors: Robinson, Stewart
Lee, Ernie
Edwards, John (ORCID Profile 0000-0003-3979-017X)

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