Cross-process precision monitoring system and cross-process precision monitoring method

Abstract

The present invention provides a cross-process precision monitoring system and a cross-process precision monitoring method. The process precision monitoring system includes an electrochemical machining device, an electrical discharge machining device, a storage unit, and a processing unit. The electrochemical machining device is used to first perform an electrochemical machining process on a workpiece. The electrical discharge machining device is used to subsequently perform an electrical discharge machining process on the workpiece. The processing unit is used to execute a linear regression model to estimate a first removal area of ​​the workpiece. The processing unit is used to execute an electrical discharge machining precision prediction model to estimate a second removal area of ​​the workpiece. The processing unit adjusts at least one of a discharge voltage and a discharge current based on the first removal area and the second removal area.

Description

Technical Field

[0001] The present invention relates to a monitoring system, and in particular to a cross-process precision monitoring system and a cross-process precision monitoring method. Background Art

[0002] Existing electrochemical machining (ECM) and electrical discharge machining (EDM) processes rely on offline measurement to monitor process accuracy, resulting in generally low process efficiency. Furthermore, during the inter-process manufacturing process of a workpiece, the accuracy cannot be monitored immediately, often leading to significant process errors. Summary of the Invention

[0003] The present invention is directed to a process accuracy monitoring system and a process accuracy monitoring method. When an electrochemical machining process is performed on a workpiece by an electrochemical machining device, the processing quality parameters of the workpiece can be estimated in real time. When an electric discharge machining process is performed on a workpiece by an electric discharge machining device, the processing quality parameters of the workpiece can also be estimated in real time.

[0004] According to an embodiment of the present invention, a process accuracy monitoring system includes an electrochemical machining apparatus, a storage unit, and a processing unit. The electrochemical machining apparatus is configured to perform an electrochemical machining process on a workpiece. The storage unit is configured to store a linear regression model. The processing unit is coupled to the electrochemical machining apparatus and the storage unit. The processing unit is configured to detect an operating voltage and an operating current of the electrochemical machining apparatus during the electrochemical machining process and execute the linear regression model. The processing unit inputs the operating voltage and operating current into the linear regression model, so that the linear regression model estimates machining quality parameters of the workpiece.

[0005] According to an embodiment of the present invention, the process accuracy monitoring method of the present invention includes the following steps: performing an electrochemical machining process on a workpiece through an electrochemical machining device; detecting the working voltage and working current of the electrochemical machining device during the electrochemical machining process through a processing unit; executing a linear regression model through the processing unit; and inputting the working voltage and working current into the linear regression model through the processing unit, so that the linear regression model estimates the processing quality parameters of the workpiece.

[0006] According to an embodiment of the present invention, the process accuracy monitoring system of the present invention includes an electrochemical machining device, an electrical discharge machining device, a storage unit, and a processing unit. The electrochemical machining device is used to first perform an electrochemical machining process on the workpiece. The electrical discharge machining device is used to subsequently perform an electrical discharge machining process on the workpiece. The storage unit is used to store a linear regression model and an electrical discharge machining accuracy prediction model. The processing unit couples the electrochemical machining device, the electrical discharge machining device, and the storage unit. The processing unit is used to detect the operating voltage and operating current of the electrochemical machining device during the electrochemical machining process, and execute the linear regression model to estimate the first removal area of ​​the workpiece. The processing unit is used to detect the discharge voltage and discharge current of the electrical discharge machining device during the electrical discharge machining process, and execute the electrical discharge machining accuracy prediction model to estimate the second removal area of ​​the workpiece. The processing unit adjusts at least one of the discharge voltage and the discharge current according to the first removal area and the second removal area.

[0007] According to an embodiment of the present invention, the process accuracy monitoring method of the present invention includes the following steps: first performing an electrochemical machining process on a workpiece through an electrochemical machining device; detecting the operating voltage and the operating current of the electrochemical machining device during the electrochemical machining process through a processing unit, and executing a linear regression model to estimate a first removal area of ​​the workpiece; continuously performing an electric discharge machining process on the workpiece through an electric discharge machining device; detecting the discharge voltage and the discharge current of the electric discharge machining device during the electric discharge machining process through the processing unit, and executing an electric discharge machining accuracy prediction model to estimate a second removal area of ​​the workpiece; and adjusting at least one of the discharge voltage and the discharge current according to the first removal area and the second removal area through the processing unit.

[0008] Based on the above, the process accuracy monitoring system and process accuracy monitoring method of the present invention can monitor the operating voltage and operating current of the electrochemical machining equipment during the electrochemical machining process in real time, thereby instantly estimating the machining quality parameters of the workpiece and dynamically adjusting the feed rate setting of the electrochemical machining equipment during the electrochemical machining process of the workpiece. Furthermore, the process accuracy monitoring system and process accuracy monitoring method of the present invention can monitor the discharge voltage and discharge current of the electric discharge machining equipment during the electric discharge machining process in real time, thereby instantly estimating the electric discharge machining results of the workpiece and dynamically adjusting the process settings of the electric discharge machining equipment.

[0009] In order to make the above features and advantages of the present invention more clearly understood, embodiments are given below with reference to the accompanying drawings for detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 is a circuit diagram of an electrochemical machining process accuracy monitoring system according to an embodiment of the present invention;

[0011] Figure 2A is a schematic diagram of an electrochemical machining apparatus according to an embodiment of the present invention;

[0012] Figure 2B is a schematic diagram of a workpiece according to an embodiment of the present invention;

[0013] Figure 3 is a flow chart of establishing a linear regression model according to an embodiment of the present invention;

[0014] Figure 4 is a flow chart of a method for monitoring electrochemical machining process accuracy according to one embodiment of the present invention;

[0015] Figure 5 is a schematic diagram of processing quality parameters according to an embodiment of the present invention;

[0016] Figure 6 is a circuit diagram of a cross-process accuracy monitoring system according to an embodiment of the present invention;

[0017] Figure 7 is a schematic diagram of an electrical discharge machining apparatus according to an embodiment of the present invention;

[0018] Figure 8 is a flow chart of establishing an electric discharge machining accuracy prediction model according to an embodiment of the present invention;

[0019] Figure 9 is a flow chart of a method for monitoring cross-process accuracy according to an embodiment of the present invention;

[0020] Figure 10 is a flow chart of a method for monitoring cross-process accuracy according to another embodiment of the present invention.

[0021] Description of Reference Numerals

[0022] 100, 600: process accuracy monitoring system;

[0023] 110, 610: processing unit;

[0024] 120, 620: storage unit;

[0025] 121, 621: linear regression model;

[0026] 130, 630: Electrochemical processing equipment;

[0027] 131: cathode;

[0028] 132: anode;

[0029] 133: electrode tool;

[0030] 134: insulating layer;

[0031] 140, 650: processed parts;

[0032] 141, 651: workpiece material removal area;

[0033] 141-1 to 141-6: Removed layers;

[0034] 142: electrolyte;

[0035] 143: electrolyte flow direction;

[0036] 501, 502, 503: curves;

[0037] 622: EDM precision prediction model;

[0038] 640: electrical discharge machining equipment;

[0039] 641: spindle;

[0040] 642: machining electrode;

[0041] 643: platform;

[0042] D1, D2, D3, D4: direction;

[0043] S310~S330, S410~S440, S810~S830, S910~S950, S1010~S1080: steps. DETAILED DESCRIPTION

[0044] Reference will now be made in detail to exemplary embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals are used in the drawings and the description to refer to the same or like parts.

[0045] Figure 1 FIG. 1 is a circuit diagram of an electrochemical machining process accuracy monitoring system according to an embodiment of the present invention. Figure 1The process accuracy monitoring system 100 includes a processing unit 110, a storage unit 120, and an electrochemical machining (ECM) device 130. The processing unit 110 is coupled to the storage unit 120 and the ECM device 130. The storage unit 120 is used to store a linear regression model 121. In this embodiment, the ECM device 130 can be used to perform an ECM process on a workpiece, and the processing unit 110 can instantly obtain the operating voltage and operating current of the ECM device 130 during the ECM process. The processing unit 110 can execute the linear regression model 121 to effectively estimate the current processing quality parameters based on the current operating voltage and the current operating current, and can dynamically adjust the current processing quality parameters based on the current processing quality parameters to effectively monitor and maintain the process accuracy of the ECM process performed on the workpiece.

[0046] In this embodiment, the processing unit 110 may include a central processing unit (CPU), a microprocessor control unit (MCU), a field programmable gate array (FPGA), or other processing circuits or control chips with data processing functions, but the present invention is not limited thereto. In this embodiment, the storage unit 120 may be a memory, wherein the memory may be, for example, a non-volatile memory such as a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a volatile memory such as a random access memory (RAM), a hard disk drive (HDD), a semiconductor memory, or the like. The storage unit 120 may be used to store the algorithm of the linear regression model 121, as well as the parameters, analysis software, control instructions, and related algorithms and programs mentioned in various embodiments of the present invention, and may be read and executed by the processing unit 110.

[0047] Figure 2A FIG. 1 is a schematic diagram of an electrochemical machining apparatus according to an embodiment of the present invention. Figure 2B Schematic diagram of a workpiece according to an embodiment of the present invention. Figures 1 to 2BThe electrochemical machining apparatus 130 may include a cathode 131, an anode 132, an electrode tool 133, and an insulating layer 134 formed on the outer layer of the electrode tool 133. In this embodiment, the electrochemical machining apparatus 130 may couple, install, or set the cathode 131 on the electrode tool 133, and couple, install, or set the anode 132 on the workpiece 140. The electrochemical machining apparatus 130 may apply a working voltage and a working current to the cathode 131 and the anode 132 so that the electrode tool 133 may perform an electrochemical machining process on the workpiece 140. As the electrolyte 142 adjacent to the electrode tool 133 reacts with the workpiece 140, a workpiece material removal zone 141 may be formed on the workpiece 140, and the removed material in the workpiece material removal zone 141 may be removed along the electrolyte 142 along the electrolyte flow direction 143.

[0048] like Figure 2B As shown, the workpiece 140 is in the workpiece material removal area 141, and the electrode tool 133 of the electrochemical machining device 130 can, for example, extend into the workpiece 140 along the direction D4 to remove the material of the workpiece 140 in the workpiece material removal area 141. The workpiece 140 can be placed horizontally to be parallel to the plane formed by extending along the direction D1 and the direction D2, wherein the direction D1 and the direction D2 can be horizontal directions respectively, and the direction D3 can be a vertical direction (the direction D4 is opposite to the direction D3). It is worth noting that the processing quality parameters described in the various embodiments of the present invention can be as follows Figure 2B The illustrated removal areas include a plurality of removal layers 141-1 to 141-6 of the workpiece 140, and the number of removal layers is not limited to Figure 2B shown.

[0049] Figure 3 FIG1 is a flow chart of establishing a linear regression model according to an embodiment of the present invention. Figures 1 to 3 , the process accuracy monitoring system 100 can perform the following steps S310 to S330 to pre-establish the linear regression model 121. In step S310, the process accuracy monitoring system 100 can pre-electrochemically process the same multiple reference workpieces according to multiple original working voltages and multiple original working currents through the electrochemical processing equipment 130. In this regard, the multiple original working voltages are the same voltage value, and the multiple original working currents are different current values, but the present invention is not limited to this. As shown in Table 1 below, the electrochemical processing equipment 130 can pre-evaluate process tests 1 to 5 (reference workpieces 1 to 5) according to different feed rates. In this regard, in process tests 1 to 5, the electrochemical processing equipment 130 can adjust the feed rate accordingly by changing the working current (fixed working voltage).

[0050]

[0051] Table 1

[0052] In step S320, the processing unit 110 may obtain a plurality of original processing parameters of a plurality of reference workpieces. In this embodiment, as shown in Table 2 below, the plurality of original processing parameters may correspond to a plurality of removed layers (e.g., Figure 2B The multiple removal areas of the multiple removal layers 141 - 1 to 141 - 6 are shown.

[0053]

[0054] Table 2

[0055] In step S330, the processing unit 110 may establish a linear regression model 121 based on the multiple original operating voltages, the multiple original operating currents, and the multiple original processing quality parameters. In this embodiment, the processing unit 110 may perform at least one of a heat map analysis and a scatter plot matrix (Pair plot) based on the multiple original operating voltages, the multiple original operating currents, and the multiple original processing quality parameters (removed area) in Table 1 above to evaluate the analysis characteristics of the multiple original operating voltages, the multiple original operating currents, and the multiple original processing quality parameters in Table 2 above. When the analysis characteristic is a linear analysis characteristic, the processing unit 110 may choose to establish a linear regression model 121. In this regard, in other embodiments, if the analysis characteristic is a type of analysis characteristic, the processing unit 110 may choose to establish a model of its corresponding type, without being limited to the linear regression model 121. In this embodiment, the processing unit 110 may establish a linear regression model 121 that conforms to the description of the following formula (1), and is suitable for finding the response variable (Y) and the explanatory variables (X1, X2, ..., X n In the following formula (1), the aforementioned multiple original working voltages and multiple original working currents are expressed by parameters X1, X2, ..., X n The estimated removal area output by the linear regression model 121 can be represented by the parameter Y. The parameter i is the total number of samples (n is a positive integer), the parameter p is the number of features, and β0, ..., β p are multiple parameters to be estimated.

[0056] Y i =β0+β1X i1 +…+β p X ip +ε,i=1,2,…,n…Formula (1)

[0057] Figure 4 FIG. 4 is a flow chart of a method for monitoring electrochemical machining process accuracy according to an embodiment of the present invention. Figure 5 FIG is a schematic diagram of processing quality parameters according to an embodiment of the present invention. Figure 1 、 Figure 2A 、 Figure 2B 、 Figure 4 as well as Figure 5 , the process accuracy monitoring system 100 may perform the following steps S410 to S440 to perform process accuracy monitoring. In step S410, the process accuracy monitoring system 100 may perform an electrochemical machining process on the workpiece 140 through the electrochemical machining equipment 130. In step S420, the processing unit 110 of the process accuracy monitoring system 100 may detect the operating voltage and the operating current of the electrochemical machining equipment 130 during the electrochemical machining process. In step S430, the processing unit 110 of the process accuracy monitoring system 100 may execute the linear regression model 121. In step S440, the processing unit 110 of the process accuracy monitoring system 100 may input the operating voltage and the operating current into the linear regression model 121, so that the linear regression model 121 estimates the processing quality parameters of the workpiece 140.

[0058] In this embodiment, the linear regression model 121 may vary with time (eg, from time t0 to time t6), and the output may be as follows: Figure 5 The unit of the horizontal axis of the curve 501 is time (seconds), and the unit of the vertical axis is square millimeters (mm 2 ). Curve 501 is a result estimated by the linear regression model 121 that the removal area generated in the workpiece material removal zone 141 changes with time (e.g., from time t0 to time t6) when the electrochemical machining apparatus 130 performs an electrochemical machining process on the workpiece 140. Alternatively, the linear regression model 121 may estimate the removal area corresponding to different removal layers (e.g., Figure 2B The multiple removal areas of the multiple removal layers 141-1 to 141-6 are shown, and the output is as follows Figure 5 The unit of the horizontal axis corresponding to the curves 502 and 530 may be the number of layers, and the unit of the vertical axis may be square millimeters (mm). 2). Curve 502 represents the result estimated by the linear regression model 121 of the removal areas (e.g., layers 1 to 6) corresponding to the multiple removal layers 141-1 to 141-6 in the workpiece material removal zone 141 when the electrochemical machining equipment 130 performs an electrochemical machining process on the workpiece 140. It is worth noting that curve 503 represents the result of the actual (experimental) removal areas (e.g., layers 1 to 6) corresponding to the multiple removal layers 141-1 to 141-6 in the workpiece material removal zone 141 when the electrochemical machining equipment 130 performs an electrochemical machining process on the workpiece 140. In this regard, the mean absolute error (MAE) between the estimated removal areas of the removal layers 141-1 to 141-6 and the actual (experimental) removal areas is less than three percent (3%). Therefore, the process accuracy monitoring system 100 can provide highly accurate and real-time processing quality parameters of the workpiece 140 and can effectively monitor the process accuracy of the electrochemical machining process. Furthermore, the processing unit 110 can dynamically adjust the feed rate setting during the ECM process on the workpiece 140 based on the machining quality parameters at the current point in the ECM process. Alternatively, the processing unit 110 can further operate an electrical discharge machining (EDM) device based on the machining quality parameters to perform a subsequent EDM process on the workpiece. In one embodiment, the ECM device 130 can perform a rapid hole enlargement process on the workpiece 140, while the EDM device can further perform fine machining on the workpiece 140.

[0059] Figure 61 is a circuit diagram of a cross-process accuracy monitoring system according to an embodiment of the present invention. The process accuracy monitoring system 600 includes a processing unit 610, a storage unit 620, an electrochemical machining apparatus 630, and an electrical discharge machining apparatus 640. The processing unit 610 is coupled to the storage unit 620 and the electrochemical machining apparatus 630. The storage unit 620 is used to store a linear regression model 621 and an electrical discharge machining accuracy prediction model 622. In this embodiment, the electrochemical machining apparatus 630 can be used to first perform an electrochemical machining process on a workpiece, and the processing unit 610 can immediately obtain the operating voltage and operating current of the electrochemical machining apparatus 630 during the electrochemical machining process. The processing unit 610 can execute the linear regression model 621 to effectively estimate the first removal area based on the operating voltage and operating current. Subsequently, the electrical discharge machining apparatus 640 can be used to subsequently perform an electrical discharge machining process on the workpiece, and the processing unit 610 can immediately obtain the discharge voltage and discharge current of the electrochemical machining apparatus 630 during the electrochemical machining process. The processing unit 610 can execute the EDM accuracy prediction model 622 to effectively estimate the second removal area based on the discharge voltage and discharge current. It is worth noting that the first removal area refers to the area of ​​a removed layer of the workpiece, for example, after undergoing an electrochemical machining process, and the second removal area can be based on the increased removal area of ​​the same removed layer, but the present invention is not limited to this. Therefore, the process accuracy monitoring system 600 of the present invention can effectively monitor process accuracy across processes and can dynamically adjust the process time, number of EDM processes, etc. of the EDM equipment 640.

[0060] It is worth noting that the specific implementation and technical features of the processing unit 610, the storage unit 620 and the electrochemical processing equipment 630 of this embodiment can be referred to above. Figures 1 to 5 The description of the embodiment can provide sufficient teachings, suggestions and implementation instructions, so no further details are given here. In addition, the process accuracy monitoring system 600 can perform the above Figure 3 In the embodiment, steps S310 to S330 are used to pre-establish a linear regression model 621. At least a portion of the process accuracy monitoring system 600 of this embodiment can be implemented using the related technical description of the process accuracy monitoring system 100 described above.

[0061] Figure 7 Schematic diagram of an electrical discharge machining device according to an embodiment of the present invention. Figure 6 as well as Figure 7 The EDM equipment 640 may include a spindle 641 and a tool-electrode 642 disposed on the spindle 641, so as to perform EDM on a workpiece 650 placed on a platform 643 through the tool-electrode 642. The workpiece 650 may be, for example, Figure 2B shown Figure 2A as well as Figure 2B The workpiece 140 is shown after electrochemical machining. In this embodiment, the processing unit 610 may include a sensing unit, and the sensing unit may sense the discharge voltage and discharge current of the EDM device 640 during online machining. The processing unit 610 may analyze the discharge voltage and discharge current to extract multiple reference characteristic parameters, and the processing unit 610 may input the multiple reference characteristic parameters into the EDM accuracy prediction model 622, so that the EDM accuracy prediction model 622 can estimate the (increased) removal area of ​​the workpiece material removal zone 651 of the workpiece 650 after EDM.

[0062] Figure 8 FIG1 is a flow chart of establishing an EDM precision prediction model according to an embodiment of the present invention. Figure 6 as well as Figure 8 , the process accuracy monitoring system 600 may perform the following steps S810 to S830 to pre-establish the EDM accuracy prediction model 622. In step S810, the process accuracy monitoring system 600 may pre-process a plurality of reference workpieces with the EDM device 640, and pre-detect a plurality of reference discharge voltages and a plurality of reference discharge currents of the EDM device 640 during the EDM process on the plurality of reference workpieces through the processing unit 610. Each of the plurality of reference workpieces may be similar to Figure 7 In step S820, the processing unit 610 may analyze the plurality of reference discharge voltages and the plurality of reference discharge currents to extract a plurality of reference characteristic parameters. In step S830, the processing unit 610 may select at least a portion of each of the plurality of reference characteristic parameters based on the workpiece types of the plurality of reference workpieces for use in establishing the discharge machining accuracy prediction model 622.

[0063] In this embodiment, each of the multiple groups of reference characteristic parameters may include spark frequency, open circuit ratio, short circuit ratio, average short circuit time, short circuit time standard deviation, average short circuit current, short circuit current standard deviation, average delay time, delay time standard deviation, average peak discharge current, peak current standard deviation, average discharge time, discharge time standard deviation, average discharge energy, and discharge energy standard deviation.

[0064] Among the aforementioned reference characteristic parameters, the average delay time and short-circuit ratio are derived from the discharge voltage signal. The average delay time is defined as the time difference from the point at which a sufficient open-circuit voltage is established to the point at which the voltage pulse crosses the gap between the electrode and the workpiece, initiating discharge current. The short-circuit ratio is defined as the number of short-circuit pulses (SCPs) divided by the number of discharge pulses. A short-circuit pulse is defined as a period of time during which the open-circuit voltage remains below a specified voltage threshold within a discharge pulse cycle.

[0065] Among the reference characteristic parameters mentioned above, discharge frequency, average discharge peak current, and average discharge time are established from the discharge current signal. Discharge frequency is defined as the number of times a current peak value exceeds a minimum threshold peak value within a pulse, indicating the occurrence of a current spark. Discharge frequency is defined as the total number of sparks occurring during a sampling period. Average discharge peak current is defined as the average of all peak currents during the sampling period. Peak current is the maximum current value reaching the workpiece through the electrode during a pulse.

[0066] Among the above-mentioned processing characteristics, the average short circuit time, open circuit ratio, average discharge energy and average short circuit current are jointly established based on the discharge current signal and the discharge voltage signal. The average short circuit time is related to the short circuit duration, and the short circuit duration is defined as when multiple consecutive short circuits occur during a discharge pulse period (more than two consecutive pulses are required). The short circuit duration is the time difference between the first short circuit peak and the last short circuit pulse peak during the multiple consecutive short circuits. The open circuit ratio is defined as the number of open circuits divided by the total number of discharge pulses during the sampling period. When the voltage peak ends within a certain pulse time and does not rise with the current peak, it is called an open circuit. If an open circuit occurs, it means that a voltage peak (Ignition Voltage) fails to induce a subsequent current peak (Discharge Current), and this voltage peak is an invalid pulse. The average discharge energy is mainly used to maintain the stability of the EDM process to ensure the machining quality. The discharge energy € of the i-th discharge is given by the following formula (1), where tei is the discharge duration, Ui is the discharge voltage, and Ipi is the discharge peak current. This formula assumes that the discharge voltage remains unchanged during the discharge process.

[0067]

[0068] In addition, according to the aforementioned disclosure, the calculation method of the standard deviation values ​​of the short-circuit time standard deviation, the short-circuit current standard deviation, the delay time standard deviation, the peak current standard deviation, the discharge time standard deviation, and the discharge energy standard deviation, as well as other parameters, are well known to those skilled in the art in the technical field to which the present invention belongs, and thus will not be described in detail here.

[0069] In this embodiment, the processing unit 610 can train a neural network (NN) model (or other types of known machine learning models) using at least a portion of the above-mentioned multiple sets of reference feature parameters, and can also use a regression analysis method (such as the partial least squares (PLS) method) to establish an EDM accuracy prediction model 622. In this regard, the processing unit 610 can select at least a portion of the above-mentioned multiple sets of reference feature parameters according to the workpiece types of these reference workpieces to establish the EDM accuracy prediction model 622. In other words, the processing unit 610 can select certain specific reference feature parameters according to the workpiece type of the reference workpiece to establish a corresponding prediction model to provide an effective and accurate process accuracy prediction function for the EDM process.

[0070] Figure 9 FIG. 1 is a flow chart of a method for monitoring cross-process accuracy according to an embodiment of the present invention. Figure 6 as well as Figure 9 The process accuracy monitoring system 600 can perform the following steps S910 to S950 to monitor the process accuracy. In step S910, the process accuracy monitoring system 600 can monitor the workpiece (such as Figure 2B or Figure 7 The workpiece 140, 650 is first subjected to an electrochemical machining process. In step S920, the processing unit 610 can detect the operating voltage and operating current of the electrochemical machining device 630 during the electrochemical machining process, and execute the linear regression model 621 to estimate the first removal area of ​​the workpiece. It is worth noting that the method for estimating the first removal area of ​​the workpiece can refer to the above Figure 4The description of the embodiment is omitted for brevity. In step S930, the process accuracy monitoring system 600 can perform an EDM process on the workpiece through the EDM equipment 640. In step S940, the processing unit 610 can detect the discharge voltage and discharge current of the EDM equipment 640 during the EDM process, and execute the EDM accuracy prediction model 622 to estimate the second removal area of ​​the workpiece. In step S950, the processing unit 610 can adjust at least one of the discharge voltage and the discharge current according to the first removal area and the second removal area. Therefore, the process accuracy monitoring system 600 of this embodiment can effectively estimate the overall removal area of ​​the workpiece after the electrochemical machining process and the EDM process, and can dynamically adjust the discharge voltage and discharge current in the EDM process according to the predicted removal area, so that the workpiece as the final product can meet the expected specifications.

[0071] Figure 10 FIG. 1 is a flow chart of a method for monitoring cross-process accuracy according to another embodiment of the present invention. Figure 6 as well as Figure 10 The process accuracy monitoring system 600 may execute the following steps S1010 to S1080 to perform process accuracy monitoring.

[0072] In step S1010, the processing unit 610 can obtain the working voltage and working current of the electrochemical processing equipment 630. In step S1020, the processing unit 610 can estimate the working voltage of the workpiece (such as Figure 2B or Figure 7The first removal area formed on the workpiece 140, 650). In step S1030, the processing unit 610 can adjust the process settings of the EDM equipment 640, such as the feed rate setting of the EDM equipment 640. In other words, the process accuracy monitoring system 600 can dynamically adjust the process parameters of the EDM process based on the results of the workpiece after the EDM process to effectively compensate for the process errors of the EDM process. In step S1040, the processing unit 610 can obtain the discharge voltage and discharge current of the EDM equipment 640. In step S1050, the processing unit 610 can estimate the second removal area formed on the workpiece. In other words, the process accuracy monitoring system 600 can effectively monitor the process accuracy of the EDM process. In step S1060, the processing unit 610 can calculate the volume of the workpiece after processing. To this end, the processing unit 610 can calculate the volume of the workpiece after processing based on the aforementioned first removal area, the second removal area, and a preset unit thickness (a preset or known thickness of the removed layer). In step S1070, processing unit 610 determines whether the post-processing volume is within a predetermined volume threshold. If not, processing unit 610 re-executes step S1030 to adjust the process settings of EDM equipment 640 and perform the EDM process on the workpiece again. If so, processing unit 610 concludes the estimation in step S1080 and outputs information such as the estimated process specifications or accuracy of the final finished workpiece.

[0073] In summary, the process accuracy monitoring system and process accuracy monitoring method of the present invention can provide effective cross-process accuracy monitoring for the electrochemical machining process performed by the electrochemical machining equipment and the discharge machining process performed by the discharge machining equipment, respectively. In addition, the process accuracy monitoring system and process accuracy monitoring method of the present invention can also feedback the processing quality parameters of the electrochemical machining process to control the feed rate setting of the electrochemical machining equipment to effectively maintain the process accuracy. In addition, the process accuracy monitoring system and process accuracy monitoring method of the present invention can also dynamically adjust the process setting of the discharge machining equipment according to the results of the electrochemical machining process to effectively integrate the process effects across processes, and can compensate for the process error of the electrochemical machining process through the discharge machining process.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A process accuracy monitoring system, characterized in that: include: Electrochemical machining equipment, used to perform electrochemical machining on workpieces; Discharge machining equipment, used to continuously perform discharge machining process on the workpiece; A storage unit for storing a linear regression model and an electric discharge machining accuracy prediction model; as well as a processing unit coupled to the electrochemical machining device, the electrical discharge machining device, and the storage unit, wherein the processing unit is configured to detect the operating voltage and the operating current of the electrochemical machining device during the electrochemical machining process, and execute the linear regression model to estimate the first removal area of ​​the workpiece. The processing unit is used to detect the discharge voltage and discharge current of the discharge machining device during the discharge machining process, and execute the discharge machining accuracy prediction model to estimate the second removal area of ​​the workpiece. The processing unit adjusts at least one of the discharge voltage and the discharge current according to the first removal area and the second removal area.

2. The process accuracy monitoring system according to claim 1, characterized in that: The processing unit calculates a processed volume of the workpiece according to the first removed area and the second removed area, and evaluates whether to operate the electrical discharge machining device to perform the electrical discharge machining process on the workpiece again according to the processed volume.

3. The process accuracy monitoring system according to claim 1, characterized in that: The electrochemical machining equipment performs the electrochemical machining process on the same plurality of first reference workpieces according to a plurality of original working voltages and a plurality of original working currents in advance, so that the processing unit obtains a plurality of original machining quality parameters of the plurality of first reference workpieces. The processing unit establishes the linear regression model according to the multiple original working voltages, the multiple original working currents, and the multiple original processing quality parameters.

4. The process accuracy monitoring system according to claim 1, wherein: The EDM device performs the EDM process on a plurality of second reference workpieces in advance, and the processing unit detects in advance a plurality of reference discharge voltages and a plurality of reference discharge currents of the EDM device during the EDM process on the plurality of second reference workpieces. The processing unit analyzes the multiple reference discharge voltages and the multiple reference discharge currents to extract multiple sets of reference characteristic parameters, and the processing unit selects at least a portion of the multiple sets of reference characteristic parameters according to the workpiece types of the multiple second reference workpieces for establishing the discharge machining accuracy prediction model.

5. The process accuracy monitoring system according to claim 4, characterized in that: Each of the multiple groups of reference characteristic parameters includes discharge frequency, open circuit ratio, short circuit ratio, average short circuit time, short circuit time standard deviation, average short circuit current, short circuit current standard deviation, average delay time, delay time standard deviation, average discharge peak current, peak current standard deviation, average discharge time, discharge time standard deviation, average discharge energy and discharge energy standard deviation.

6. A process accuracy monitoring method, characterized in that: include: The workpiece is first subjected to an electrochemical machining process using electrochemical machining equipment; detecting, by a processing unit, an operating voltage and an operating current of the electrochemical machining device during the electrochemical machining process, and executing a linear regression model to estimate a first removal area of ​​the workpiece; Performing an electrical discharge machining process on the workpiece by means of an electrical discharge machining device; detecting, by the processing unit, a discharge voltage and a discharge current of the electrical discharge machining device during the electrical discharge machining process, and executing an electrical discharge machining accuracy prediction model to estimate a second removal area of ​​the workpiece; as well as At least one of the discharge voltage and the discharge current is adjusted by the processing unit according to the first removal area and the second removal area.

7. The process accuracy monitoring method according to claim 6, characterized in that: Also includes: calculating, by the processing unit, a volume of the workpiece after processing according to the first removed area and the second removed area; as well as The processing unit evaluates whether to operate the electrical discharge machining device to perform the electrical discharge machining process on the workpiece again according to the processed volume.

8. The process accuracy monitoring method according to claim 6, characterized in that: Also includes: The electrochemical machining process is performed on a plurality of identical first reference workpieces using the electrochemical machining equipment in advance according to a plurality of original working voltages and a plurality of original working currents, so that the processing unit obtains a plurality of original machining quality parameters of the plurality of first reference workpieces; as well as The linear regression model is established by the processing unit according to the multiple original working voltages, the multiple original working currents and the multiple original processing quality parameters.

9. The process accuracy monitoring method according to claim 6, wherein: Also includes: Performing the EDM process on a plurality of second reference workpieces in advance by the EDM device, and detecting in advance by the processing unit a plurality of reference discharge voltages and a plurality of reference discharge currents of the EDM device during the EDM process on the plurality of second reference workpieces; analyzing the plurality of reference discharge voltages and the plurality of reference discharge currents by the processing unit to extract a plurality of sets of reference characteristic parameters; as well as The processing unit selects at least a portion of each of the plurality of groups of reference feature parameters according to workpiece types of the plurality of second reference workpieces for establishing the electrical discharge machining accuracy prediction model.

10. The process accuracy monitoring method according to claim 9, characterized in that: Each of the multiple groups of reference characteristic parameters includes discharge frequency, open circuit ratio, short circuit ratio, average short circuit time, short circuit time standard deviation, average short circuit current, short circuit current standard deviation, average delay time, delay time standard deviation, average discharge peak current, peak current standard deviation, average discharge time, discharge time standard deviation, average discharge energy and discharge energy standard deviation.

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