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EP-4420830-B1 - IN-LINE CHARACTERIZATION OF DETERIORATION OF A CUTTING TOOL BASED ON THERMOELECTRIC MEASUREMENT

EP4420830B1EP 4420830 B1EP4420830 B1EP 4420830B1EP-4420830-B1

Inventors

  • Welm, Markus
  • Tröber, Philipp
  • Schrepfer, Agnes

Dates

Publication Date
20260506
Application Date
20230223

Claims (15)

  1. A detection module (100) for characterising a deterioration of a cutting tool (10), the detection module (100) comprising: an electric sensor (102) configured for measuring an electric parameter of an electric current flowing between a die (18) of the cutting tool and a material blank (20) during a cutting process for cutting the material blank (20) by the cutting tool (10) using the die (18); a measuring unit (104) configured for determining a first time evolution of a first electric parameter measured by the electric sensor (102); and the detection module characterized in that it further comprises: a detection unit (106) configured for detecting a type of deterioration of the die (18) of the cutting tool (100) based on the first time evolution and on one or more reference time evolutions.
  2. The detection module of claim 1, wherein the measuring unit (104) is further configured for determining, before determining the first time evolution, the one or more reference time evolutions for one or more corresponding reference electric parameters of corresponding reference electric currents measured by the electric sensor (102) during respective one or more cutting processes for cutting a respective material blank (20) by the cutting tool (10) using the die (18); and wherein the detection unit (106) is configured for detecting said type of deterioration of the die (18) of the cutting tool (10) based on a comparison of the first time evolution with the at least one reference time evolution.
  3. The detection module of claim 1 or 2, wherein the detection unit (106) is configured for detecting said type of deterioration of the die (18) based on time derivatives of the first time evolution and of the one or more reference time evolutions.
  4. The detection module of claim 3, wherein the detection unit (106) is configured for determining that said type of deterioration corresponds to an abrasive deterioration of the die (18) if the time derivative of the first time evolution has greater absolute value than a time derivative of the one or more reference time evolutions; and/or wherein the detection unit (106) is preferably configured for determining that said type of deterioration corresponds to a breakout deterioration of the die (18) if the time derivative of the first time evolution has smaller absolute value than a time derivative of the one or more reference time evolutions.
  5. The detection module of any of the preceding claims, wherein the detection unit (106) is configured for detecting said type of deterioration of the die (18) based on absolute values of the first time evolution and of the one or more reference time evolutions;
  6. The detection module of claim 5, wherein the detection unit (106) is configured for determining that said type of deterioration corresponds to an adhesive deterioration of the die (18) if an absolute value of the first time evolution has a greater maximum than an absolute value of the one or more reference time evolutions.
  7. The detection module of any of the preceding claims, wherein the detection unit (106) is configured for determining that said type of deterioration corresponds to a deterioration causing a shifting of a burnish zone limit in a workpiece manufactured by the cutting tool if a time position at which an absolute value of the first time evolution is maximal differs from a time position at which an absolute value of the one or more reference time evolutions is maximal.
  8. The detection module of any of the preceding claims, wherein the detection unit (106) comprises a machine learning algorithm trained on a training data set, preferably comprising the one or more reference time evolutions, for detecting said type of deterioration of the die (18) of the cutting tool (10) based on the first time evolution.
  9. A cutting tool (10) comprising: a die (18) for manufacturing a workpiece by cutting a material blank (20), a blank electrical contact (103) adjacent to a material blank (20), when the material blank (20) is being cut by the cutting tool (10), and a detection module (100) according to any of the preceding claims, wherein the electric sensor (102) of the detection module (100) is electrically connected between the die (18) and the blank electrical contact (103), wherein the electric sensor (102) is configured for measuring an electric parameter of an electric current flowing between the die (18) and the blank electrical contact (103), when the material blank (20) is being cut by the cutting tool (10); and wherein the detection module (10) is configured for detecting a type of deterioration of the die (18).
  10. A method (200) of determining a deterioration of a cutting tool (10), the method comprising: measuring (206) a first electric parameter of a first electric current flowing between a die (18) of the cutting tool (10) and a material blank (20) being cut by the cutting tool during a cutting process; determining (208) a first time evolution of the first electric parameter; and the method characterized in that it further comprises the step of detecting (210) a type of deterioration of the die (18) of the cutting tool (10) based on the first time evolution and on one or more reference time evolutions.
  11. The method of claim 10, further comprising, before measuring (206) the first electric parameter: measuring (202) a reference electric parameter for each of one or more reference electric currents flowing between the die (18) of the cutting tool (10) and a material blank (20) being cut by the cutting tool in a corresponding reference cutting process; determining (204) a reference time evolution for each of the reference electric parameters; and wherein the type of deterioration of the die (18) of the cutting tool (10) is detected (210) based on the first time evolution and on one or more reference time evolutions by comparing the first time evolution with the at least one reference time evolution.
  12. The method of any claim 10 or 11, wherein said type of deterioration is detected based on time derivatives of the first time evolution and of the one or more reference time evolutions; wherein said type of deterioration is preferably determined to correspond to an abrasive deterioration of the die (18) if the time derivative of the first time evolution has greater absolute value than a time derivative of the one or more reference time evolutions; and/or wherein said type of deterioration is preferably determined to correspond to a breakout deterioration of the die (18) if the time derivative of the first time evolution has a smaller absolute value than a time derivative of the one or more reference time evolutions.
  13. The method of any of claims 10 to 12, wherein said type of deterioration is detected based on absolute values of the first time evolution and of the one or more reference time evolutions; wherein said type of deterioration preferably is determined to correspond to an adhesive deterioration of the die (18) if an absolute value of the first time evolution has a greater maximum than an absolute value of the one or more reference time evolutions.
  14. The method of any of claims 10 to 13, wherein said type of deterioration is determined to correspond to a deterioration causing a shifting of a burnish zone limit in a workpiece manufactured by the cutting tool if a time position at which an absolute value of the first time evolution is maximal differs from a time position at which an absolute value of the one or more reference time evolutions is maximal.
  15. The method of any of claims 10 to 14, wherein the detecting (210) said type of deterioration comprises using a machine learning algorithm trained for detecting said type of deterioration of the die of the cutting tool based on the first time evolution, wherein the machine learning algorithm is trained using a training data set comprising a plurality of said reference time evolutions associated with respective ground truth values.

Description

FIELD OF THE INVENTION The present invention is in the field of cutting tools. In particular, the invention refers to a detection module and a method for characterising a deterioration or wear of a cutting tool and to a corresponding cutting tool. BACKGROUND OF THE INVENTION Cutting processes are of widespread use in the industry and their relevance tends to increase presently due to their suitability for the mass production of workpieces, in particular metallic workpieces, in a cost-efficient manner, for example of steel, titanium, magnesium or aluminum. One of the most common techniques for cutting a workpiece is shearing, also known as die cutting, where a material blank is cut by a press using a movable part of a die, a so-called punch, or a moving blade against a fixed part of the die or a fixed blade. Thereby, the material blank is cut according to a pattern determined by the die to form a workpiece with a desired shape. Current processes for ensuring quality requirements in a cutting process are typically based on a posteriori testing of the cutting tool and/or the workpieces cut therewith. Existing possibilities for in-line supervision in real time are very limited and highly demanding, requiring for example the use of complex optical monitoring systems. Therefore, most current quality monitoring systems focus on detecting a deterioration of the cutting tool by detecting an increase in a number of defective workpieces after production. Severe deterioration may be preventively countered by carrying out maintenance and reparation tasks on the cutting tool well before a state critical for given quality requirements is reached, this preventive serving of the cutting tool resulting in increased production costs. Therefore, there is room for technical improvement in the field of detection of deterioration of a cutting tool. WO 2022/049719 A1 discloses a cutting tool comprising a determination unit configured for determining a state of the blades of the cutting tool based on a voltage waveform when using the blades for a cutting process. However, this determination unit is not able to discriminate between different types of deterioration of the cutting tool. Techniques for detecting a state of excessive deterioration or near-failure state in a drilling tool based on electrical measurements are known from US 4 694 686 A and US 4 786 220 A. A technique for detecting deterioration in a similar drilling tool based on electrical measurements is described in JP S56 39852 A. However, none of the techniques described in these documents comprises detecting a type of the deterioration suffered by a tool based on an electrical measurement. SUMMARY OF THE INVENTION The present invention aims at providing a solution to the previously mentioned disadvantages of the prior art by providing a device and a method allowing to reliably detect and characterise a deterioration or wear of a cutting tool in-line and in real time. A solution to this problem is provided by a detection module according to claim 1, by a cutting tool according to claim 9 and by a method according to claim 10. Preferred embodiments of the invention are defined in the dependent claims. A first aspect of the invention refers to a detection module for characterising a deterioration of a cutting tool. A cutting tool may refer herein to a shearing tool, a punch tool and/or a stamping tool, which may in any case be configured as a press. The detection module may be configured for characterising a deterioration of a part of a cutting tool, in particular of a punch tool or die of the cutting tool. Cutting may refer herein to cutting processes in general, including deformation and mass separation, aimed at cutting one or more workpieces from a material blank. The detection module may be hardware-based and/or software-based. For example, the detection module may be or may comprise a processing unit or an executable code executable by a dedicated processing unit or by a general propose processing unit, for example by a computer. "Characterising" as used herein for the detection module according to the invention, may refer to the association of measured data to a predefined category. In this sense, "characterising" may further involve generating computer-readable information and/or human-readable information encoding the predefined category to which the measured data has been assigned. In other words, characterising a deterioration of a cutting tool by the detection module according to the invention may comprise generating an output including information about the presence and type of deterioration of the cutting tool. The detection module comprises an electric sensor, a measuring unit, and a detection unit. The electric sensor is configured for measuring an electric parameter of an electric current flowing between a die of the cutting tool and a material blank during a cutting process for cutting the material blank by the cutting tool using the die. The die refer