{"title":"Introductory Design Optimisation of a Machine Tool using a Virtual Machine Concept","authors":"Johan Wall, Johan Fredin, Anders J\u00f6nsson, G\u00f6ran Broman","volume":59,"journal":"International Journal of Industrial and Manufacturing Engineering","pagesStart":2235,"pagesEnd":2241,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/3285","abstract":"Designing modern machine tools is a complex task. A\r\nsimulation tool to aid the design work, a virtual machine, has\r\ntherefore been developed in earlier work. The virtual machine\r\nconsiders the interaction between the mechanics of the machine\r\n(including structural flexibility) and the control system. This paper\r\nexemplifies the usefulness of the virtual machine as a tool for product\r\ndevelopment. An optimisation study is conducted aiming at\r\nimproving the existing design of a machine tool regarding weight and\r\nmanufacturing accuracy at maintained manufacturing speed. The\r\nproblem can be categorised as constrained multidisciplinary multiobjective\r\nmultivariable optimisation. Parameters of the control and\r\ngeometric quantities of the machine are used as design variables. This\r\nresults in a mix of continuous and discrete variables and an\r\noptimisation approach using a genetic algorithm is therefore\r\ndeployed. The accuracy objective is evaluated according to\r\ninternational standards. The complete systems model shows nondeterministic\r\nbehaviour. A strategy to handle this based on statistical\r\nanalysis is suggested. The weight of the main moving parts is reduced\r\nby more than 30 per cent and the manufacturing accuracy is\r\nimprovement by more than 60 per cent compared to the original\r\ndesign, with no reduction in manufacturing speed. It is also shown\r\nthat interaction effects exist between the mechanics and the control,\r\ni.e. this improvement would most likely not been possible with a\r\nconventional sequential design approach within the same time, cost\r\nand general resource frame. This indicates the potential of the virtual\r\nmachine concept for contributing to improved efficiency of both\r\ncomplex products and the development process for such products.\r\nCompanies incorporating such advanced simulation tools in their\r\nproduct development could thus improve its own competitiveness as\r\nwell as contribute to improved resource efficiency of society at large.","references":"[1] Thomke S.H., Experimentation matters: unlocking the potential of new\r\ntechnologies for innovation,: Harvard Business School Press, Boston,\r\n2003.\r\n[2] J\u00f6nsson A., Wall J. & Broman G., \"A virtual machine concept for realtime\r\nsimulation of machine tool dynamics\", International Journal of\r\nMachine Tools & Manufacture 45(7-8), 2005, pp.795-801.\r\n[3] Van Brussel H., Sas P., N\u00e9meth I., De Fonseca P. & Van den\r\nBraembussche P., \"Towards a mechatronic compiler\". IEEE\/ASME\r\nTransactions on Mechatronics 6(1), 2001, pp. 90-105.\r\n[4] Dierssen S., \"Systemkopplung zur komponentenorientierten Simulation\r\ndigitaler Produkte\", VDI-Fortschrittberichte, 20(358), VDI-Verlag\r\nGmbH, D\u251c\u255dsseldorf, 2002.\r\n[5] Kreusch K., Verifikation numerischer Steuerungen an virtuellen\r\nWerkzeugmaschinen, Berichte aus der Steuerungs- und\r\nRegelungstechnik, Shaker Verlag, Aachen, 2002.\r\n[6] Altintas Y., Brecher C., Weck M. & Witt S., \"Virtual machine tool\",\r\nAnnals of CIRP 54(2), 2005, pp. 651-674.\r\n[7] Andersson J., \"A survey of multiobjective optimization in engineering\r\ndesign\", Technical report LiTH-IKP-R-1097, Department of Mechanical\r\nEngineering, Link\u00f6ping University, Link\u00f6ping, 2000.\r\n[8] Ehrgott M. & Gandibleux X., \"A survey and annotated bibliography of\r\nmultiobjective combinatorial optimization\", OR Spektrum 22(4), 2000,\r\npp. 425-460.\r\n[9] Schu\u251c\u00bdller G.I., \"Computational stochastic mechanics - recent advances\",\r\nComputers and Structures 79(22-25), 2001, pp. 2225-2234.\r\n[10] Moens D. & Vandepitte D., \"A survey of non-probabilistic uncertainty\r\ntreatment in finite element analysis\", Computer Methods in Applied\r\nMechanics and Engineering 194(12-16), 2005, pp.1527-1555.\r\n[11] Summers D.A., Waterjetting technology, Spon Press, London, 1995.\r\n[12] Wall J., Englund T. & Berghuvud A., \"Identification and modelling of\r\nstructural dynamics characteristics of a water jet cutting machine\", in:\r\nProceedings of the International Modal Analysis Conference - IMAC,\r\nDearborn, 26-29 January, 2004, pp. 138-147.\r\n[13] Rosenkrantz W.A., Introduction to probability and statistics for\r\nscientists and engineers, McGraw-Hill, New York, 1997.\r\n[14] ISO 230-4:2005, \"Test code for machine tools - Part 4: Circular tests for\r\nnumerically controlled machine tools\".\r\n[15] Gen M. & Cheng R., Genetic algorithms & engineering optimization,\r\nJohn Wiley & Sons, New York, 2000.\r\n[16] Coello Coello C.A., \"Theoretical and numerical constraint-handling\r\ntechniques used with evolutionary algorithms: a survey of the state of\r\nthe art\". Computer Methods in Applied Mechanics and Engineering\r\n191(11-12), 2002, pp. 1245-1287.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 59, 2011"}