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Keywords: frames, optimisation, FEM, genetic algorithm.

Summary

This paper presents a discussion on the optimisation of the dimensions of the ribs of a milling machine tool frame from the point of view of mass minimization. The paper presents a method where the genetic algorithm serves as a mechanism of searching optimal dimensions of ribs see Michalewicz [1] and Goldberg [2].

The static stiffness of machine tool frames is one of the most important features deciding the accuracy of machined workpiece. If the stiffness is to low, the geometrical errors of workpiece increase. Each machine tool consists of several movable frames. Movements of the frames may be realized with accelerations much higher than gravity acceleration. As a result we observe an increase in the forces and some additional displacements. The decrease in such displacements may be obtained by a reduction of the driven masses.

For a geometrical description of the ribs 36 parameters were used and 10 parameters affecting the thickness of the local walls (indirectly the height of the ribs).

We have applied the genetic algorithm method as an optimization procedure using ANSYS and AGAS software simultaneously. This makes it possible to choose the method of optimization, define the range of parameters and visualize the results as tables or plots.

The necessary condition for process optimization is to define the evaluation function. The evaluation function makes possible to evaluate each variant of rib dimensions. The evaluation function has been defined as the quotient of the mass of the optimized model and the static stiffness coefficient in each axes.

Before starting the optimization of the rib dimensions, a state of reference was defined. We calculated the mass of the columns and the displacements of the spindle in the x, y and z directions, assuming that all walls of the column are completely filled up, without ribs.

The optimization was performed from the point of view of mass minimization and stiffness coefficient maximization. We are confident that in spite of many simplifications,the results obtained show that the method of optimization using the genetic algorithm and the finite element method is a promising approach and should be further developed.

References

1: Z. Michalewicz, "Genetic Algorithm + Data of Structure = Evolution Software", WNT, Warsaw, 2003 (in polish).
2: D.E. Goldberg, "Genetic Algorithms and their applications", WNT, Warsaw, 2003 (in polish).

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 87 PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON THE APPLICATION OF ARTIFICIAL INTELLIGENCE TO CIVIL, STRUCTURAL AND ENVIRONMENTAL ENGINEERING Edited by: B.H.V. Topping Paper 13 Optimisation of Frames of a Milling Machine Tool using Genetic Algorithms and the Finite Element Method P. Wilk and J. Kosmol Department of Machine Technology, Silesian University of Technology, Gliwice, Poland doi:10.4203/ccp.87.13 purchase the full-text of this paper Full Bibliographic Reference for this paper P. Wilk, J. Kosmol, "Optimisation of Frames of a Milling Machine Tool using Genetic Algorithms and the Finite Element Method", in B.H.V. Topping, (Editor), "Proceedings of the Ninth International Conference on the Application of Artificial Intelligence to Civil, Structural and Environmental Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 13, 2007. doi:10.4203/ccp.87.13 Keywords: frames, optimisation, FEM, genetic algorithm. Summary This paper presents a discussion on the optimisation of the dimensions of the ribs of a milling machine tool frame from the point of view of mass minimization. The paper presents a method where the genetic algorithm serves as a mechanism of searching optimal dimensions of ribs see Michalewicz [1] and Goldberg [2]. The static stiffness of machine tool frames is one of the most important features deciding the accuracy of machined workpiece. If the stiffness is to low, the geometrical errors of workpiece increase. Each machine tool consists of several movable frames. Movements of the frames may be realized with accelerations much higher than gravity acceleration. As a result we observe an increase in the forces and some additional displacements. The decrease in such displacements may be obtained by a reduction of the driven masses. For a geometrical description of the ribs 36 parameters were used and 10 parameters affecting the thickness of the local walls (indirectly the height of the ribs). We have applied the genetic algorithm method as an optimization procedure using ANSYS and AGAS software simultaneously. This makes it possible to choose the method of optimization, define the range of parameters and visualize the results as tables or plots. The necessary condition for process optimization is to define the evaluation function. The evaluation function makes possible to evaluate each variant of rib dimensions. The evaluation function has been defined as the quotient of the mass of the optimized model and the static stiffness coefficient in each axes. Before starting the optimization of the rib dimensions, a state of reference was defined. We calculated the mass of the columns and the displacements of the spindle in the x, y and z directions, assuming that all walls of the column are completely filled up, without ribs. The optimization was performed from the point of view of mass minimization and stiffness coefficient maximization. We are confident that in spite of many simplifications,the results obtained show that the method of optimization using the genetic algorithm and the finite element method is a promising approach and should be further developed. References 1 Z. Michalewicz, "Genetic Algorithm + Data of Structure = Evolution Software", WNT, Warsaw, 2003 (in polish). 2 D.E. Goldberg, "Genetic Algorithms and their applications", WNT, Warsaw, 2003 (in polish). purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £62 +P&P)
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