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US-12619216-B2 - Automatic process control in a gear processing machine

US12619216B2US 12619216 B2US12619216 B2US 12619216B2US-12619216-B2

Abstract

A method for monitoring a machining process in which tooth flanks of pre-toothed workpieces ( 23 ) are machined with a finishing machine ( 1 ) is disclosed. As part of the method, a plurality of measurement values are recorded while a finishing tool ( 16 ) is in machining engagement with a workpiece. Among them are values of a power indicator which indicates a current power consumption of the tool spindle during the machining of the tooth flanks of the workpiece. A normalization operation is applied to at least some of the measurement values or to values of a quantity derived from the measurement values in order to obtain normalized values. The normalization operation depends on at least one of the following parameters: geometrical parameters of the finishing tool, in particular its outside diameter, geometrical parameters of the workpiece and setting parameters of the finishing machine, in particular radial infeed and axial feed.

Inventors

  • Christian Dietz

Assignees

  • REISHAUER AG

Dates

Publication Date
20260505
Application Date
20200904
Priority Date
20190913

Claims (20)

  1. 1 . A method for monitoring a machining process in which tooth flanks of pre-toothed workpieces are machined with a finishing machine, the finishing machine having a tool spindle for driving a finishing tool to rotate about a tool axis and at least one workpiece spindle for driving a pre-toothed workpiece to rotation, the method comprising: detecting a plurality of measurement values, the measurement values being values of a power indicator which indicates a current power consumption of the tool spindle while the finishing tool is in machining engagement with a workpiece; applying a normalization operation to the measurement values or to values of a quantity derived from the measurement values to obtain normalized values, the normalization operation depending on one or more process parameters, the normalization operation causing the normalized values to have a reduced dependency on the process parameters, the process parameters being selected from geometric parameters of the finishing tool, geometric parameters of the workpiece and setting parameters of the finishing machine, the normalization operation being based on a model of process force or process power describing an expected dependence of the measurement values on the process parameters; analyzing the normalized values to detect impermissible process deviations; and removing a workpiece for which an impermissible process deviation has been determined.
  2. 2 . The method according to claim 1 , wherein the normalization operation is performed in real time while the finishing tool is in machining engagement with the workpiece.
  3. 3 . The method according to claim 2 , wherein the normalized values are analyzed in real time to detect the impermissible process deviations.
  4. 4 . The method according to claim 1 , comprising: recalculating the normalization operation when at least one of the process parameters has changed, using the model of process force or process power.
  5. 5 . The method according to claim 1 , comprising: calculating at least one characteristic parameter of the machining process from the measurement values or values derived from them.
  6. 6 . The method according to claim 5 , wherein the at least one characteristic parameter correlates with a predefined machining error of the workpiece.
  7. 7 . The method according to claim 6 , comprising: performing a gear measurement for selected workpieces to determine at least one gear measurement value per workpiece which characterizes the predefined machining error; and determining correlation parameters that characterize a correlation of the at least one characteristic parameter with the at least one gear measurement value.
  8. 8 . The method according to claim 6 , wherein the calculation of the at least one characteristic parameter comprises a spectral analysis of measurement values or values derived therefrom to obtain a plurality of spectral components.
  9. 9 . The method according to claim 8 , wherein the machining process is a generating process in which the finishing tool and the workpiece are in rolling engagement, and wherein the at least one characteristic parameter comprises at least one of the following variables: a cumulative pitch indicator, wherein the cumulative pitch indicator is calculated from a spectral component at a rotation frequency of the workpiece spindle and correlates with a cumulative pitch error or concentricity error of the workpiece; a wear indicator, wherein the wear indicator is calculated from a low-frequency spectral component and correlates with a degree of wear of the finishing tool; and a profile shape indicator, wherein the profile shape indicator is calculated from a spectral component at a tooth mesh frequency and correlates with a profile shape deviation of the workpiece.
  10. 10 . The method according to claim 6 , comprising: storing a data set in a database, wherein the data set comprises a unique identifier of the workpiece, at least one process parameter and the at least one characteristic parameter.
  11. 11 . A method for monitoring a machining process in which tooth flanks of pre-toothed workpieces are machined with a finishing machine, the finishing machine having a tool spindle for driving a finishing tool to rotate about a tool axis and at least one workpiece spindle for driving a pre-toothed workpiece to rotation, the method comprising: detecting a plurality of measurement values, the measurement values being values of a power indicator which indicates a current power consumption of the tool spindle while the finishing tool is in machining engagement with a workpiece; applying a normalization operation to the measurement values or to values of a quantity derived from the measurement values to obtain normalized values, the normalization operation depending on one or more process parameters, the normalization operation causing the normalized values to have a reduced dependency on the process parameters, the process parameters being selected from geometric parameters of the finishing tool, geometric parameters of the workpiece and setting parameters of the finishing machine, the normalization operation being based on a model of process force or process power describing an expected dependence of the measurement values on the process parameters; calculating at least one characteristic parameter of the machining process from the normalized values, the at least one characteristic parameter correlating with a predefined machining error of the workpiece; performing an analysis of values of the at least one characteristic parameter for a plurality of workpieces to determine a process deviation; changing the machining process to reduce the process deviation.
  12. 12 . The method according to claim 11 , wherein the analysis is performed by a trained machine learning algorithm.
  13. 13 . The method according to claim 11 , wherein the analysis comprises: correlating values of the at least one characteristic parameter for a plurality of workpieces with another parameter of the machining process.
  14. 14 . The method according to claim 6 , comprising: graphical outputting of values of the at least one characteristic parameter or values derived therefrom for a plurality of workpieces.
  15. 15 . The method according to claim 1 , wherein the recalculation of the normalization operation comprises a compensation with respect to a variable dimension of the finishing tool.
  16. 16 . A finishing machine for the machining of tooth flanks of pre- toothed workpieces, comprising: a tool spindle for driving a finishing tool about a tool axis to rotate; at least one workpiece spindle for driving a pre-toothed workpiece to rotate; a machine control device comprising a control computer and a plurality of axis modules for controlling a process of machining the workpiece with the finishing tool; and software which, when executed on one or more processors, causes the one or more processors to carry out a method comprising: detecting device for detecting a plurality of measurement values while the finishing tool is in machining engagement with a workpiece, the detected measurement values being values of a power indicator which indicates a current power consumption of the tool spindle; applying a normalization operation to at least part of the measurement values or to values of a quantity derived from the measurement values to obtain normalized values, the normalization operation depending on one or more process parameters, the normalization operation causing the normalized values to have a reduced dependency on the process parameters, the process parameters being selected from geometric parameters of the finishing tool, geometric parameters of the workpiece and setting parameters of the finishing machine, the normalization operation being based on a model of process force or process power describing an expected dependence of the measurement values on the process parameters; analyzing the normalized values in order to detect impermissible process deviations; and removing a workpiece for which an impermissible process deviation has been determined.
  17. 17 . The finishing machine according to 16 , wherein the normalization operation is performed in real time while the finishing tool is in machining engagement with the workpiece.
  18. 18 . The finishing machine according to claim 16 , wherein the normalized values are analyzed in real time in order to detect the impermissible process deviations.
  19. 19 . The finishing machine according to claim 16 , wherein the method comprises: recalculating the normalization operation when at least one of the process parameters has changed, using the model of process force or process power.
  20. 20 . The finishing machine according to claim 16 , wherein the method comprises: calculating at least one characteristic parameter of the machining process from the measurement values or values derived therefrom, wherein the at least one characteristic parameter correlates with a predefined machining error of the workpiece.

Description

CROSS REFERENCE TO RELATED APPLICATIONS This application is a National Stage of International Application No. PCT/EP2020/074828 filed on Sep. 4, 2020, claiming priority based on Swiss Patent Application No. 01158/19 filed on Sep. 13, 2019. TECHNICAL FIELD The present invention relates to a method for monitoring a machine for finishing gears, in particular a machine for carrying out a generating process. The invention further relates to a finishing machine configured to carry out such a method, a computer program for carrying out such a method and a computer-readable medium comprising such a computer program. STATE OF THE ART Hard fine machining (hard finishing) of pre-machined gears is a very demanding method, where even the slightest deviation from the process specifications can result in the machined workpieces being considered scrap (“NIO parts”, where NIO means “not in order”). This problem can be illustrated particularly well by the example of continuous generating grinding, but also applies equally to other generating finishing methods such as single flank generating grinding, gear honing or hard skiving. To a lesser extent, similar problems also arise for non-generating methods such as discontinuous or continuous profile grinding. In continuous generating grinding, a pre-machined gear blank is machined in rolling engagement with a worm-shaped profiled grinding wheel (grinding worm). Generating grinding is a very demanding, generating machining method, which is based on a large number of synchronized, high-precision individual movements and is influenced by many boundary conditions. Information on the fundamentals of continuous generating grinding can be found, for example, in the book by H. Schriefer et al., “Continuous Generating Gear Grinding”, published by Reishauer AG, Wallisellen 2010, ISBN 978-3-033-02535-6, in Chapter 2.3 (“Basic Methods of Generating Grinding”), pages 121 to 129. Theoretically, the tooth flank shape in continuous generating grinding is determined solely by the dressed profile shape of the grinding worm and the setting data of the machine. In practice, however, deviations from the ideal condition occur in automated production, which can have a decisive influence on the grinding results. Traditionally, the quality of gears produced by the generating grinding method is only assessed after the end of the machining process by gear measurements outside the machine (“offline”) using a large number of measured variables. There are various standards that prescribe how the gears are to be measured and how it is to be checked whether the measurement results are within or outside a tolerance specification. A summary of such gear measurements can be found, for example, in the aforementioned book by Schriefer et al. in Chapter 3 (“Quality Assurance in Continuous Generating Gear Grinding”) on pages 155 to 200. It is known from the state of the art to make corrections on the machine based on gear measurements in order to eliminate detected machining errors. In the above-mentioned book by Schriefer et al., this is discussed in Chapter 6.10 (“Analysing and Eliminating Gear Tooth Deviations”) on pages 542 to 551. Since, for reasons of time and cost, only random checks are usually carried out during gear inspection, machining errors are often detected very late. This can lead to the fact that, under certain circumstances, considerable parts of a production lot have to be discarded as NIO parts. It is therefore desirable to detect machining errors as early as possible “online” during machining, ideally before a machining error reaches such a degree that workpieces have to be rejected as NIO parts. For this purpose, it is desirable to provide an automated process monitoring system which makes it possible to detect undesirable process deviations, to obtain indications of possible machining errors and to change the machine settings in a targeted manner so that these machining errors are avoided or at least reduced. Ideally, process monitoring should also allow conclusions to be drawn about process deviations retrospectively if machining errors are only detected later, e.g. during EOL testing (EOL=End of Line). Until now, suitable strategies for automated process monitoring in gear machining are only rudimentarily known from the state of the art. For example, it is known from DE 10 2014 015 587 A1 to monitor parameters on a gear machine and to carry out a gear check whenever certain measured machine parameters deviate from nominal values. The company presentation “NORDMANN Tool Monitoring”, version dated 5 Oct. 2017, accessed on 25 Feb. 2019 from https://www.nordmann.eu/pdf/praesentation/Nordmann_presentation_ENG.pdf, describes various measures for tool monitoring on general metal-cutting machining tools (page 3). The presentation shows examples of applications in various metal-cutting processes, including in brief a few examples of processes relevant to gear machining, in particular hobbing (pages 4