Title: An integrated model for robot selection in robotic cells under uncertain situations

Authors: Rodrigo Merino; Ahmad Sarfaraz; Kouroush Jenab; Alireza Kabirian

Addresses: Department of Manufacturing Systems Engineering and Management, California State University, 18111 Nordhoff Street, Northridge, CA 91330-8332, USA ' Department of Manufacturing Systems Engineering and Management, California State University, 18111 Nordhoff Street, Northridge, CA 91330-8332, USA ' Society of Reliability Engineering-Ottawa, 812-761 Bay Street, Toronto, Ontario, Canada ' Department of Manufacturing Systems Engineering and Management, California State University, 18111 Nordhoff Street, Northridge, CA 91330-8332, USA

Abstract: Robots have become an extremely important part of society today; therefore, optimal selection of a robot is more important than ever. Companies, decision-makers and experts have experimented with several methodologies for selecting the proper robot to meet their needs and make an overall good business decision. This paper applies fuzzy AHP with QFD to compensate for the vagueness and imprecision of the data to provide the best ranking and customer needs for the weights given for the options to make an optimal selection for a robot. The case study discusses how this is an important aspect of a production environment and how it can provide great benefits with proper implementation.

Keywords: fuzzy AHP; FAHP; analytical hierarchy process; QFD; quality function deployment; production environments; robot selection; integrated modelling; robotic cells; uncertainty; fuzzy logic; robot ranking; customer needs; industrial robots.

DOI: 10.1504/IJLSM.2015.068427

International Journal of Logistics Systems and Management, 2015 Vol.20 No.3, pp.395 - 410

Received: 12 Sep 2013
Accepted: 14 Dec 2013
Published online: 15 Apr 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article