Design concept evaluation based on rough number and information entropy theory

Abstract

Concept evaluation at the early phase of product development plays a crucial role in new product development. It determines the direction of the subsequent design activities. However, the evaluation information at this stage mainly comes from experts' judgments, which is subjective and imprecise. How to manage the subjectivity to reduce the evaluation bias is a big challenge in design concept evaluation. This paper proposes a comprehensive evaluation method which combines information entropy theory and rough number. Rough number is first presented to aggregate individual judgments and priorities and to manipulate the vagueness under a group decision-making environment. A rough number based information entropy method is proposed to determine the relative weights of evaluation criteria. The composite performance values based on rough number are then calculated to rank the candidate design concepts. The results from a practical case study on the concept evaluation of an industrial robot design show that the integrated evaluation model can effectively strengthen the objectivity across the decision-making processes.

Publication DOI: https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.257
Divisions: College of Engineering & Physical Sciences > Adaptive communications networks research group
Additional Information: -© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Event Title: 2015 Smart World Congress
Event Type: Other
Event Dates: 2015-08-10 - 2015-08-14
Uncontrolled Keywords: composite performance value,design concept evaluation,information entropy,rough number,subjectivity,Computer Networks and Communications,Computer Science Applications,Computer Vision and Pattern Recognition,Signal Processing,Health Informatics
ISBN: 978-1-4673-7211-4
Last Modified: 29 Oct 2024 18:46
Date Deposited: 23 Sep 2016 07:14
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2016-07-21
Accepted Date: 2015-08-01
Authors: Hu, Jie
Zhu, Guoniu
Qi, Jin
Peng, Yinghong
Peng, Xiaohong (ORCID Profile 0000-0002-0608-233X)

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