Part Program Dependent Loss Forecast for Estimating the Thermal Impact on Machine Tools

Wenkler, Eric; Hellmich, Arvid; Schroeder, Steffen; Ihlenfeldt, Steffen

doi:10.17973/mmsj.2021_7_2021054

Cited by 4 publications

(5 citation statements)

References 5 publications

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“…FEM-based sensitivity analysis is used to determine the optimal positions for temperature sensors as the basis of simulation-based characteristics, and smoothed grid regression is used in research work as an extended calculation methodology for characteristic diagrams [31]. It has been shown that a 40-80% reduction in the mean thermally induced error can be achieved through the application of simulation-based characteristics [32][33][34] and even more, when the characteristics can be updated with information regarding the current load case [35][36][37].…”

Section: Characteristic Diagram-based Correctionmentioning

confidence: 99%

“…It includes partial models for power loss, thermal coupling coefficients, and thermo-elastic displacement and approaches for calculating the axis correction values. A modular strategy for correcting structure models in the context of machine tools has been developed through fundamental research and is undergoing validation on numerous machine components and structures [36,[40][41][42][43]. The modules can be divided into three areas: data acquisition, modeling, and correction, whereby each area is calculated in its own time domain (control real time and thermal real time) that can be calculated decoupled from each other (control internal and control external).…”

Section: Structure Model-based Correctionmentioning

confidence: 99%

See 1 more Smart Citation

Correction of Thermal Errors in Machine Tools by a Hybrid Model Approach

Friedrich,

Geist,

Yaqoob

et al. 2024

Applied Sciences

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Thermally induced position errors are one of the main error sources on the workpiece caused by the behavior of the machine tool. In today’s industrial environment, the correction of thermal errors is usually based on simple regression approaches, where the characteristic diagrams for correction are generated experimentally. The performance of these approaches is only valid for the corresponding load regimes, which often results in insufficient correction quality in practical applications. Consequently, there is only a limited benefit or even a deterioration in machine behavior if the correction characteristic is based on an inapplicable load case compared to the initial experiment. Simulation-generated characteristic diagrams using finite element models solve this disadvantage, but do not answer the question about the choice of the right characteristic matching the current load situation, and, in addition, calculate very slowly. Structural model-based correction using reduced models, on the other hand, calculates quickly, but requires a high modeling effort for accurate correction. The approach, presented in this contribution, combines simulation-generated characteristic diagrams and a structural model-based decision algorithm for a new hybrid model in order to select the appropriate characteristic diagram for the present load situation in the control system. This paper presents the simulative characteristic diagram generation by a finite element model validated by experiments in a climate chamber and a validated structural model including the concept for the decision algorithm.

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Section: Characteristic Diagram-based Correctionmentioning

confidence: 99%

Section: Structure Model-based Correctionmentioning

confidence: 99%

Correction of Thermal Errors in Machine Tools by a Hybrid Model Approach

Friedrich,

Geist,

Yaqoob

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The uncooled thermal steady state can either be determined by simulation, which allows a forecast, or be measured with a deactivated cooling system. The ability to forecast such losses and apply them to thermal FE models was shown in previews research [18,19] and is especially interesting for low batch manufacturing, where the measurement of the thermal steady state would cause to high costs.…”

Section: Thermal Feed-forward Controlmentioning

confidence: 99%

“…Therefore, it is important to apply a realistic thermal load scenario to compare the cooling strategies under realistic conditions. Such conditions can be obtained by defining a typical manufacturing task and perform a power loss forecast [18]. For this purpose, a typical aerospace component was designed, which are usually large, light and machining-intensive, with removal rates above 80 %.…”

Section: Thermal Load Scenariomentioning

confidence: 99%

Application and evaluation of classic and demand oriented cooling strategies in context of machine tools

Wenkler

Steiert²,

Ihlenfeldt³

et al. 2023

Preprint

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Energy consumption is an important factor in the operation of machine tools Recent studies showed that in average 1/5 of the machine tools total energy demand is caused by internal cooling systems. The continually rising performance of machine tools together with the importance of thermal stability, reasons the requirement for demand oriented cooling approaches, which could significantly reduce the energy consumption for internal machine cooling. This study applied classic and demand oriented cooling strategies on a machine tool frame, which is one of the most complex machine tool components from a thermal point of view. The demand oriented cooling is based on volume flow control and can either be configured close to the environmental temperature or close to the thermal steady state, which can be obtained by loss forecast in combination with an FE-Model or measurement. The impact of the strategies on the thermal reaction as well as the energy consumption is compared, showing a significant reduction of energy demand without significant impairment of the thermal stability.

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“…Finally, the developed Beckhoff-VNC (based on a VNC library provided by Beckhoff) is executed which processes the axis g-code and outputs a csv-file with the single time dependent positions of each axis for further processing. More details to the control design are given in (Wenkler et al, 2021).…”

Section: Machine Motion Determinationmentioning

confidence: 99%

Process concatenation to reduce thermal changes in machine tools

Hellmich¹,

Selch²,

Wenkler³

et al. 2022

IJMMS

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Thermal effects in machine tools are responsible for a significant amount of produced scrap. Therefore, various approaches have been investigated and applied on machine tools to reduce thermal changes during manufacturing. Most of them target the machine tool and its operational state and can therefore just react to the thermal changes caused by the process. This paper shows how thermal changes can be reduced already in the manufacturing planning stage. With the use of a virtual numerical control (VNC) and loss models, power losses can be estimated, enabling the concatenation of processes to achieve minimal jumps in power loss from one process to another.

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Part Program Dependent Loss Forecast for Estimating the Thermal Impact on Machine Tools

Cited by 4 publications

References 5 publications

Correction of Thermal Errors in Machine Tools by a Hybrid Model Approach

Correction of Thermal Errors in Machine Tools by a Hybrid Model Approach

Application and evaluation of classic and demand oriented cooling strategies in context of machine tools

Process concatenation to reduce thermal changes in machine tools

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