Thermal Positioning Error Modeling of Servo Axis Based on Empirical Modeling Method

In order to investigate the thermal effect of a servo axis’ positioning error on the accuracy of machine tools, an empirical modeling method was proposed, which considers both the geometric and thermal positioning error. Through the analysis of the characteristics of the positioning error curves, the initial geometric positioning error was modeled with polynomial fitting, while the thermal positioning error was built with an empirical modeling method. Empirical modeling maps the relationship between the temperature points and thermal error directly, where the multi-collinearity among the temperature variables exists. Therefore, fuzzy clustering combined with principal component regression (PCR) is applied to the thermal error modeling. The PCR model can preserve information from raw variables and eliminate the effect of multi-collinearity on the error model to a certain degree. The advantages of this modeling method are its high-precision and strong robustness. Experiments were conducted on a three-axis machine tool. A criterion was also proposed to select the temperature-sensitivity points. The fitting accuracy of the comprehensive error modeling could reach about 89%, and the prediction accuracy could reach about 86%. The proposed modeling method was proven to be effective and accurate enough to predict the positioning error at any time during the machine tool operation.

Selbstlernender Biegeprozess*/Self-learning bending process

Es wird eine Methode zur adaptiven Rückfederungskompensation von Blechbiegeprozessen im Folgeverbund vorgestellt. Die Methode ist von der Grundstruktur bauteilunabhängig und kann – auf Basis dieser Struktur – einfach für andere Bauteile und / oder Prozessbedingungen angepasst werden. Die Umsetzung der Methode erfolgt für ein Demonstrationswerkzeug, das über eine unabhängig von der Pressenbewegung steuerbare Biegeachse sowie ein integriertes Messsystem verfügt.   A method for the adaptive springback compensation in bending processes of sheet metal parts is presented. The method has a structure, which is independent of the part to be bent and can be adapted easily to different parts and process conditions. The implementation of the compensation and correction method is carried out on a demonstration tool, which features an additional independently controllable servo axis as well as an integrated measuring system.

Process-Controlled Forming Using an Intelligent Tool on a Servo Press

With regard to the climate change as well as the shortage and increase in price of natural resources, efficient resource management becomes more and more important, also for production processes. More than half of the sheet metal used in the automotive industry is wasted. Considering the amount of energy and the added value associated to the discards, enormous savings are possible. The approach of this research work is to avoid waste during a forming process by means of a continuous process monitoring and a self-learning intelligent tool interacting with the servo press. The flexibility of the servo press, which is so far used to optimize the single press stroke, only, shall be exerted to respond on altering material properties of blank sheets and the thereby changing forming behaviour. The sample process includes a two-tiered bending process, in which a conventional punch performs the pre-bending in the first step and an independent servo axis the compensation-bending in the second step. If an inadmissible bending angle is measured after the second step, the servo press stops automatically and the additional servo axis performs a teaching-stroke to adjust the compensation angle. After that, the continuous process starts again. This paper presents the springback compensation strategy which uses flexible correction algorithms based on data of the on-line process monitoring as well as data of the previous bending steps. Finite Element Analyses are carried out to validate the strategy.

A Multi-Axis Deep Drawing Servo Press With Non-Overconstrained Architecture

Servo actuated presses can provide maximum pressing force at any slide position in the same manner that hydraulic presses do, while offering several benefits in terms of precision, energy conversion efficiency and simplicity due to their lack of hydraulic circuitry and oil. Several press builders have developed electric-spindle actuated presses; however, issues relating to multi-axis architecture have been neglected. The present study proposes an innovative method of avoiding overconstrained architecture by implementing a kinematic mechanism that connects multiple servo axes to one slide. Servo axis design is developed by creating a dynamic model of a kinematic chain composed of a servo-motor, gearbox reducer and ball screw transmission. A study of a biaxial industrial servo press prototype with non-overconstrained architecture, currently under construction, is presented as proof of concept. It is shown that such a non-overconstrained multi-axis press can be constructed from commercially available components, achieving high energy efficiency at high load with relatively simple construction.

Analysis of a Position Control Extension on the Model of a Servo-Screw-Press

Currently, the achievable feedback control performance for servo-screw-presses is limited by its elastic structure. A possible approach to compensate this limitation is the extension of the velocity controller. This structural extension has the potential to improve the controller performance significantly due to a better damping of low frequencies. In this paper, the extension of the control structure by a state space feedback in the velocity control loop is examined. Considering that, the velocity control extension is investigated at a test rig which consists of a servo axis and a two mass system. Furthermore, a simulation model for the test rig is designed. The results of the simulated and experimentally obtained results of the test rig are presented and evaluated in order to make a prediction for the transferability to the simplified model of the servo-screw-press.

Control-Oriented Modeling Requirements of a Direct-Drive Machine Tool Axis

The high performance demands on commercial computer numerical control (CNC) machine tools have led to the widespread adoption of direct-drive servo axes. In industrial machines, where the workpiece is manipulated by the axis, the plant dynamics seen by the control system may vary widely between different workpieces. These changing plant dynamics have been observed to lead to limit-cycle behavior for a given controller. In such a situation, conventional modeling approximations used by practitioners may fail to predict the onset of instability for these axes. This work demonstrates the failure of conventional modeling approximations to predict the observed instability in an industrial CNC servo axis and investigates the model fidelity required to replicate the observations. This represents an important consideration when designing model-based controllers for direct-drive axes in CNC machines.