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Digital Library

of the European Council for Modelling and Simulation

 

Title:

Intelligent Computer-Automated Crane Design Using An Online Crane Prototyping Tool

Authors:

Ibrahim A. Hameed, Robin T. Bye, Ottar L. Osen, Birger Skogeng Pedersen, Hans Georg Schaathun

Published in:

 

 

(2016).ECMS 2016 Proceedings edited by: Thorsen Claus, Frank Herrmann, Michael Manitz, Oliver Rose, European Council for Modeling and Simulation. doi:10.7148/2016

 

 

ISBN: 978-0-9932440-2-5

 

30th European Conference on Modelling and Simulation,

Regensburg Germany, May 31st – June 3rd, 2016

 

Citation format:

Ibrahim A. Hameed, Robin T. Bye, Ottar L. Osen, Birger Skogeng Pedersen, Hans Georg Schaathun (2016). Intelligent Computer-Automated Crane Design Using An Online Crane Prototyping Tool, ECMS 2016 Proceedings edited by: Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose  European Council for Modeling and Simulation. doi:10.7148/2016-0564

DOI:

http://dx.doi.org/10.7148/2016-0564

Abstract:

In an accompanying paper submitted concurrently to this conference, we present our first complete version of a generic and modular software framework for intelligent computer-automated product design. The framework has been implemented with a client-server software architecture that automates the design of offshore cranes. The framework was demonstrated by means of a case study where we used a genetic algorithm (GA) to optimise the crane design of a real and delivered knuckleboom crane. For the chosen objective function, the optimised crane design outperformed the real crane. In this paper, we augment our aforementioned case study by implementing a new crane optimisation client in Matlab that uses a GA both for optimising a set of objective functions and for multi-objective optimisation. Communicating with an online crane prototyping tool, the optimisation client and its GA are able to optimise crane designs with respect to two selected design criteria: the maximum safe working load and the total crane weight. Our work demonstrates the modularity of the software framework as well as the viability of our approach for intelligent computer-automated design, whilst the results are valuable for informing future directions of our research.

 

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