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A Robust Multivariate Statistical Procedure for Evaluation and Selection of Industrial Robots

A Robust Multivariate Statistical Procedure for Evaluation and Selection of Industrial Robots Industrial robots are increasingly used by many manufacturingfirms. The number of robot manufacturers has also increased, with manyof these firms now offering a wide range of robots. A potential user isthus faced with many options in both performance and cost. Proposes adecision model for the robot selection problem using both a robustifiedMahalanobis distance analysis, i.e. a multivariate distance measure, andprincipalcomponents analysis. Unlike most other models for robotselection, this model takes into consideration the fact that a robotsperformance, as specified by the manufacturer, is often unobtainable inreality. The robots selected by the proposed model become candidates forfactory testing to verify manufacturers specifications. Tests theproposed model on a real data set and presents an example. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Operations & Production Management Emerald Publishing

A Robust Multivariate Statistical Procedure for Evaluation and Selection of Industrial Robots

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0144-3577
DOI
10.1108/01443579210009023
Publisher site
See Article on Publisher Site

Abstract

Industrial robots are increasingly used by many manufacturingfirms. The number of robot manufacturers has also increased, with manyof these firms now offering a wide range of robots. A potential user isthus faced with many options in both performance and cost. Proposes adecision model for the robot selection problem using both a robustifiedMahalanobis distance analysis, i.e. a multivariate distance measure, andprincipalcomponents analysis. Unlike most other models for robotselection, this model takes into consideration the fact that a robotsperformance, as specified by the manufacturer, is often unobtainable inreality. The robots selected by the proposed model become candidates forfactory testing to verify manufacturers specifications. Tests theproposed model on a real data set and presents an example.

Journal

International Journal of Operations & Production ManagementEmerald Publishing

Published: Feb 1, 1992

References