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On the selection and assessment of input variables for the characteristic diagram based correction of thermo-elastic deformations in machine tools

Ihlenfeldt S., Naumann C., Putz M.

Journal of Machine Engineering

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2018

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Vol. 18, No. 4

25--38

EN

It is a well-known problem of milling machines, that waste heat from motors, friction effects on guides and most importantly the milling process itself greatly affect positioning accuracy and thus production quality. An economic and energy-efficient method of correcting this thermo-elastic positioning error is to gather sensor data from the machine tool and the process and to use that information to predict and correct the resulting tool center point displacement using high dimensional characteristic diagrams. On the one hand, the selection of which and how many input variables to use in the characteristic diagrams is critical to their performance. On the other hand, however, there are often a great number of possible variable combinations available and testing them all is practically impossible. This paper will discuss the suitability of many different input variable types and present a new method of input variable selection which will be compared to existing methods and demonstrated on measurements performed on a machine tool.

2

Efficient quantification of free and forced convection via the decoupling of thermo-mechanical and thermo-fluidic simulations of machine tools

Glaenzel J., Ihlenfeldt S., Naumann C., Putz M.

Journal of Machine Engineering

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2018

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Vol. 18, No. 2

41--53

EN

Thermo-elastic deformations represent one of the main reasons for positioning errors in machine tools. Investigations of the thermo-mechanical behaviour of machine tools, especially during the design phase, rely mainly on thermo-elastic simulations. These require the knowledge of heat sources and sinks and assumptions on the heat dissipation via convection, conduction and radiation. Forced convection such as that caused by moving assemblies has both a large influence on the heat dissipation to the surrounding air. The most accurate way of taking convection into account is via computational fluid dynamics (CFD) simulations. These simulations compute heat transfer coefficients for every finite element on the machine tool surface, which can then be used as boundary conditions for accurate thermo-mechanical simulations. Transient thermo-mechanical simulations with moving assemblies thus require a CFD simulation during each time step, which is very time-consuming. This paper presents an alternative by using characteristic diagrams to interpolate the CFD simulations. The new method uses precomputed thermal coefficients of a small number of load cases as support points to estimate the convection of all relevant load cases (i.e. ambient conditions). It will be explained and demonstrated on a machine tool column.

3

Optimized grid structures for the characteristic diagram based estimation of thermo-elastic tool center point displacements in machine tools

Putz M., Ihlenfeldt S., Naumann C., Glänzel J.

Journal of Machine Engineering

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2017

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Vol. 17, No. 3

36--50

EN

It is a well-known problem of milling machines, that waste heat from motors, friction effects on guides and also the milling process itself greatly affect the positioning accuracy and thus the production quality. An economic and energy-efficient method of correcting this thermo-elastic positioning error is to gather sensor data from the machine tool and the process and to use that information to predict and correct the resulting tool center point displacement using high dimensional characteristic diagrams. The size of these characteristic diagrams depends on the number of input variables (sensors) and the fineness of the discretization of the grid. While the number of sensors can usually not be reduced without affecting the quality of the prediction, it is often possible to minimize the size of characteristic diagrams through the use of adaptive grid refinement. This ensures that the finest grid sections correspond with the load cases that have the largest local gradients. Through such adaptive refinement, it is possible to reduce storage capacity and computation time without significant loss of precision. The aim of this article is to examine, test and compare different methods of adaptive grid refinement. For this, simulation data from a machine tool is used.

4

Implementation and demonstration of characteristic diagram as well as structure model based correction of thermo-elastic tool center point displacements

Putz M., Ihlenfeldt S., Kauschinger B., Naumann C., Thiem X., Riedel M.

Journal of Machine Engineering

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2016

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Vol. 16, No. 3

88--101

EN

In milling machines, waste heat from motors, friction effects on guides and most importantly the milling process itself greatly affect positioning accuracy and thus production quality. Therefore, active cooling and lead time are used to reach thermal stability. A cheaper and more energy-efficient approach is to gather sensor data from the machine tool to predict and correct the resulting tool center point displacement. Two such approaches are the characteristic diagram based and the structure model based correction algorithms which are briefly introduced in this paper. Both principles have never been directly compared on the same demonstration machine, under the equal environmental conditions and with the same measurement setup. The paper accomplishes this comparison ona hexapod kinematics examined in a thermal chamber,where the effectiveness of both approaches is measured and the strengths and weaknesses of both are pointed out.