Commenced in January 2007
Paper Count: 31105
Introductory Design Optimisation of a Machine Tool using a Virtual Machine Concept
Abstract:Designing modern machine tools is a complex task. A simulation tool to aid the design work, a virtual machine, has therefore been developed in earlier work. The virtual machine considers the interaction between the mechanics of the machine (including structural flexibility) and the control system. This paper exemplifies the usefulness of the virtual machine as a tool for product development. An optimisation study is conducted aiming at improving the existing design of a machine tool regarding weight and manufacturing accuracy at maintained manufacturing speed. The problem can be categorised as constrained multidisciplinary multiobjective multivariable optimisation. Parameters of the control and geometric quantities of the machine are used as design variables. This results in a mix of continuous and discrete variables and an optimisation approach using a genetic algorithm is therefore deployed. The accuracy objective is evaluated according to international standards. The complete systems model shows nondeterministic behaviour. A strategy to handle this based on statistical analysis is suggested. The weight of the main moving parts is reduced by more than 30 per cent and the manufacturing accuracy is improvement by more than 60 per cent compared to the original design, with no reduction in manufacturing speed. It is also shown that interaction effects exist between the mechanics and the control, i.e. this improvement would most likely not been possible with a conventional sequential design approach within the same time, cost and general resource frame. This indicates the potential of the virtual machine concept for contributing to improved efficiency of both complex products and the development process for such products. Companies incorporating such advanced simulation tools in their product development could thus improve its own competitiveness as well as contribute to improved resource efficiency of society at large.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058839Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1653
 Thomke S.H., Experimentation matters: unlocking the potential of new technologies for innovation,: Harvard Business School Press, Boston, 2003.
 Jönsson A., Wall J. & Broman G., "A virtual machine concept for realtime simulation of machine tool dynamics", International Journal of Machine Tools & Manufacture 45(7-8), 2005, pp.795-801.
 Van Brussel H., Sas P., Németh I., De Fonseca P. & Van den Braembussche P., "Towards a mechatronic compiler". IEEE/ASME Transactions on Mechatronics 6(1), 2001, pp. 90-105.
 Dierssen S., "Systemkopplung zur komponentenorientierten Simulation digitaler Produkte", VDI-Fortschrittberichte, 20(358), VDI-Verlag GmbH, D├╝sseldorf, 2002.
 Kreusch K., Verifikation numerischer Steuerungen an virtuellen Werkzeugmaschinen, Berichte aus der Steuerungs- und Regelungstechnik, Shaker Verlag, Aachen, 2002.
 Altintas Y., Brecher C., Weck M. & Witt S., "Virtual machine tool", Annals of CIRP 54(2), 2005, pp. 651-674.
 Andersson J., "A survey of multiobjective optimization in engineering design", Technical report LiTH-IKP-R-1097, Department of Mechanical Engineering, Linköping University, Linköping, 2000.
 Ehrgott M. & Gandibleux X., "A survey and annotated bibliography of multiobjective combinatorial optimization", OR Spektrum 22(4), 2000, pp. 425-460.
 Schu├½ller G.I., "Computational stochastic mechanics - recent advances", Computers and Structures 79(22-25), 2001, pp. 2225-2234.
 Moens D. & Vandepitte D., "A survey of non-probabilistic uncertainty treatment in finite element analysis", Computer Methods in Applied Mechanics and Engineering 194(12-16), 2005, pp.1527-1555.
 Summers D.A., Waterjetting technology, Spon Press, London, 1995.
 Wall J., Englund T. & Berghuvud A., "Identification and modelling of structural dynamics characteristics of a water jet cutting machine", in: Proceedings of the International Modal Analysis Conference - IMAC, Dearborn, 26-29 January, 2004, pp. 138-147.
 Rosenkrantz W.A., Introduction to probability and statistics for scientists and engineers, McGraw-Hill, New York, 1997.
 ISO 230-4:2005, "Test code for machine tools - Part 4: Circular tests for numerically controlled machine tools".
 Gen M. & Cheng R., Genetic algorithms & engineering optimization, John Wiley & Sons, New York, 2000.
 Coello Coello C.A., "Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art". Computer Methods in Applied Mechanics and Engineering 191(11-12), 2002, pp. 1245-1287.