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Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory
Authors
Bojan Babić
Zoran Miljković
+3 more
Milica Petrović
Najdan Vuković
Nebojša Čović
Publication date
1 January 2011
Publisher
Niš : Faculty of Mechanical Engineering
Abstract
Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems
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Machinery - Repository of the Faculty of Mechanical Engineering, University of Belgrade
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oai:machinery.mas.bg.ac.rs:123...
Last time updated on 06/03/2023
machinery
See this paper in CORE
Go to the repository landing page
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oai:machinery.mas.bg.ac.rs:123...
Last time updated on 04/03/2023