JP3768410B2 - Press machine and method for deep drawing - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a deep drawing press machine and method for deep drawing a workpiece fixed by a die and a blank holder.
[0002]
[Background Art and Problems to be Solved by the Invention]
Conventionally, as a deep drawing method using a press machine, a blank (for example, a plate-like aluminum material) that is an object to be processed is fixed with a die of the press machine and a blank holder, and the blank holder has a wrinkle holding force. A technique is known in which a blank is formed into, for example, a cylindrical shape by lowering and raising the punch while being applied.
[0003]
When performing such deep drawing, it is necessary to increase the punching speed of the press machine in order to increase the productivity. However, if the punching speed is increased, the possibility of breakage of the workpiece increases. The problem that processing becomes difficult occurs.
[0004]
Therefore, in the conventional deep drawing, since the press working is performed within a speed range in which it is guaranteed that no breakage occurs, there is a limit in increasing the productivity.
[0005]
In addition, a method of deep drawing by varying the punch speed has been studied, but with this type of conventional method, the punch speed is avoided by avoiding the condition that the risk of fracture is theoretically high. Therefore, there is a problem that the calculation for the speed control becomes complicated and the productivity of the molded product cannot be improved.
[0006]
This invention is made | formed in view of such a subject, The objective is to provide the press machine and method for deep drawing which can improve productivity of a favorable molded article.
[0007]
[Means for Solving the Problems]
(1) In order to achieve the above object, the present invention provides:
In a deep drawing press machine that performs deep drawing by varying the punch speed of a workpiece fixed by a die and a blank holder,
Data on the ideal machining curve obtained by performing analysis to represent the relationship between the amount of workpiece to be drawn and the punch stroke, and the actual machining curve representing the relationship between the amount of workpiece to be drawn and the punch stroke And evaluation function data obtained from the evaluation function associated with the deviation between the ideal machining curve and the fuzzy control basic data including at least one item of the type of the workpiece and the machining condition associated with the type Means for storing each as a database;
Acquire the relationship between the amount of workpiece pull-in actually measured during actual machining and the punch stroke, and specify the basic data for fuzzy control that matches the above-mentioned items of the workpiece from the database. Real-time evaluation data associated with the deviation between the data of the ideal machining curve included and the actual measurement data is obtained, and based on the obtained real-time evaluation data and the evaluation function data contained in the identified basic data, Control means for feedback control of speed;
It is characterized by including.
[0008]
In addition, the deep drawing method of the present invention,
In the deep drawing method using a press machine that performs deep drawing by changing the punch speed of the workpiece fixed by the die and the blank holder,
Data on the ideal machining curve obtained by performing analysis to represent the relationship between the amount of workpiece to be drawn and the punch stroke, and the actual machining curve representing the relationship between the amount of workpiece to be drawn and the punch stroke And evaluation function data obtained from the evaluation function associated with the deviation between the ideal machining curve and the fuzzy control basic data including at least one item of the type of the workpiece and the machining condition associated with the type Remember each as a database,
Acquire the relationship between the amount of workpiece pull-in actually measured during actual machining and the punch stroke, and specify the basic data for fuzzy control that matches the item of the workpiece from the above database and include it in the identified basic data Real time evaluation data associated with the deviation between the ideal machining curve data and the actual measurement data is obtained, and the punch drawing speed is determined based on the obtained real time evaluation data and the evaluation function data included in the identified basic data. Is feedback-controlled.
[0009]
Furthermore, a program for deep drawing to which the present invention is applied is as follows:
Data on the ideal machining curve obtained by performing analysis to represent the relationship between the amount of workpiece to be drawn and the punch stroke, and the actual machining curve representing the relationship between the amount of workpiece to be drawn and the punch stroke And the evaluation function data obtained from the evaluation function associated with the deviation between the ideal machining curve and the fuzzy control basic data include at least one of the type of the workpiece and the machining condition associated with the type. Based on the data of the database constructed for each item, the press machine can be controlled by the computer so that the workpiece fixed by the die and blank holder can be deep drawn at variable punch speeds. A program that
Acquire the relationship between the amount of workpiece pull-in actually measured during actual machining and the punch stroke, and specify the basic data for fuzzy control that matches the item of the workpiece from the above database and include it in the identified basic data Real time evaluation data associated with the deviation between the ideal machining curve data and the actual measurement data is obtained, and the punch drawing speed is determined based on the obtained real time evaluation data and the evaluation function data included in the identified basic data. Control means for feedback control,
Is realized.
[0010]
The program is preferably stored in a computer-readable storage medium.
[0011]
Here, the type of the processing object is specified by, for example, the material and other type conditions.
[0012]
The processing conditions include, for example, the material thickness, size, processing temperature, lubricant, wrinkle holding force, tool shape, and other conditions.
[0013]
According to the present invention, basic data for fuzzy control is obtained in advance for each item of at least one of the types of processing objects and the processing conditions associated with the types, and stored as a database.
[0014]
The basic data for fuzzy control includes ideal machining curve data and evaluation function data.
[0015]
Here, the ideal machining curve is obtained by, for example, finite element analysis based on a predetermined setting condition (for example, invariable thickness, constant volume, etc.), and the relationship between the amount of the workpiece to be drawn and the punch stroke is correlated. To express.
[0016]
The measured machining curve is obtained by actual measurement and represents the association between the amount of the workpiece to be drawn and the punch stroke. For example, when the punch speed is a parameter and multiple actual machining curves are obtained while gradually increasing the parameter speed, the workpiece is processed before the machining of the workpiece is completed when the speed reaches a certain upper limit. Breakage occurs. In the present invention, an actual machining curve obtained using the speed at this time as a parameter may be used as the actual machining curve here.
[0017]
The evaluation function for fuzzy control is used as an evaluation function related to fracture, and is specifically obtained as a function associated with the deviation between the measured machining curve and the ideal machining curve. The evaluation function data is obtained as, for example, the minimum value and the maximum value of the evaluation function.
[0018]
In the present invention, when the workpiece is actually machined, the relationship between the drawing amount of the workpiece and the punch stroke is measured in real time using a sensor or the like, and this measurement data is acquired.
[0019]
Then, basic data for fuzzy control matching the item of the workpiece is specified from the database, and the punch speed is feedback controlled using the specified basic data for fuzzy control and the measured data.
[0020]
Specifically, real-time evaluation data associated with the deviation between the ideal machining curve data included in the identified basic data and the actually measured data is obtained in real time.
[0021]
Based on the obtained real-time evaluation data and the evaluation function included in the basic data for fuzzy control, feedback control of the punch drawing speed is performed.
[0022]
By adopting the above configuration, according to the present invention, when deep drawing a workpiece, the punch speed is feedback controlled to the optimum speed so as to increase the productivity without breaking the workpiece. Therefore, it is possible to realize deep drawing with improved productivity of a good molded product.
[0023]
In particular, according to the present invention, since the punch drawing speed can be feedback-controlled to the optimum speed in accordance with the processing conditions excluding the punch drawing speed described above associated with the type of the workpiece and the type, the operator's It is possible to realize deep drawing using a press machine that can increase the productivity of a good molded product without being affected by the skill level.
[0024]
(2) In the present invention,
The basic data for fuzzy control is
A database is created for each type of processing object and processing conditions.
The control means includes
The basic data for fuzzy control suitable for the type and processing conditions of the workpiece is specified from the database, and the punching speed of the punch is feedback controlled.
[0025]
In this way, by creating a database of fuzzy control basic data for each type of workpiece and machining conditions (excluding punch drawing speed), even if the type of workpiece is different, the machining conditions Even if they are different, the optimum fuzzy control basic data can be selected, and the punch drawing speed can be feedback controlled to the optimum speed according to the type and processing conditions.
[0026]
In particular, according to the present invention, it is possible to efficiently produce these products without impairing the quality when producing a variety of products in a small quantity.
[0027]
(3) In the present invention,
The feedback control is performed by fuzzy inference according to a fuzzy inference rule created based on the evaluation function data.
[0028]
As a feedback control method performed by such fuzzy inference, various methods can be adopted as necessary.
[0029]
For example, one such technique is
The evaluation function data is
First evaluation function data obtained from a first evaluation function representing a deviation between the measured machining curve and the ideal machining curve;
Second evaluation function data obtained from a second evaluation function obtained by differentiating the first evaluation function,
A method may be adopted in which the feedback control is performed by fuzzy inference according to a fuzzy inference rule created based on the first and second evaluation function data. Here, as the first and second evaluation function data, for example, the minimum value and the maximum value of the first and second evaluation functions may be used.
[0030]
Further, a method may be employed in which the feedback control is performed by fuzzy inference according to fuzzy inference rules created based on the first and second evaluation function data and a membership function using them.
[0031]
DETAILED DESCRIPTION OF THE INVENTION
Next, embodiments of the present invention will be described in detail with reference to the drawings.
[0032]
(1) Outline of press machine
FIG. 1 schematically shows a press machine for deep drawing according to the present embodiment. The press machine of the present embodiment forms a bottomed container using a blank 20 which is a workpiece to be formed in a plate shape. Specifically, the die 10 having a predetermined die hole 12 is used. And the punch 14.
[0033]
The blank 20 is held and fixed on the die 10 by a blank holder 30 with a desired wrinkle pressing force H.
[0034]
In this state, as shown in FIGS. 1 (A), (B), and (C), the punch 14 is lowered at a given drawing speed V, so that the blank 20 is cup-shaped along the shape of the die hole 12. Deep drawn to produce a cup-shaped molded product.
[0035]
At this time, if the drawing speed V of the punch 14 is low, the production efficiency of the molded product is low. For this reason, it is preferable to set the drawing speed V of the punch 14 as high as possible within a range in which the blank 20 does not break during processing.
[0036]
The feature of this embodiment is that the blank pull-in amount r and the punch stroke S are measured in real time during the actual processing of the blank 20, and the drawing speed V of the punch 14 is determined using a fuzzy inference method based on the measured values. It is in feedback control.
[0037]
In particular, in this embodiment, basic data for fuzzy control is created in advance for each type and processing condition of the blank 20 and stored in a database, and the type and processing conditions of the blank 20 to be actually processed are stored. In addition, an optimum fuzzy control basic data is read out, and a configuration is employed in which the punch drawing speed V is feedback-controlled so that deep drawing can be efficiently performed without causing breakage of the blank 20. .
[0038]
FIG. 3 shows a comparative example of the speed control characteristics of the press machine according to the present embodiment and the speed control characteristics of a press machine using a conventional method.
[0039]
In the same figure, the horizontal axis represents the degree of drawing of the blank 20 as a function of the pull-in amount r. Specifically, as shown in FIG. The ratio between the pull-in amount r of the blank 20 and the radius Rp of the punch 14 is ΔDR^*= R / Rp and its value is described.
[0040]
The vertical axis is ΔDR^*Represents the drawing speed V of the punch 14 corresponding to.
[0041]
In the figure, a region surrounded by an alternate long and short dash line indicated by 100 represents an area where there is a high risk of breakage of the blank 20 during drawing of the blank 20, and this is referred to as an analytical breakage limit area. .
[0042]
In the conventional method of keeping the punch drawing speed V constant, the punch speed V is set as indicated by 110a in the figure so as to avoid the fracture limit area 100 in the analysis. That is, the punch speed V is set to an upper limit value that avoids the limit area 100, and consideration is given to increasing the production efficiency of the workpiece.
[0043]
When the punch speed V is set to a value equal to or higher than the upper limit value 110a, for example, a value as indicated by 110b in the drawing, the blank 20 being processed is broken at the location indicated by a cross mark in the drawing. Will occur.
[0044]
On the other hand, when the punch speed feedback control using the fuzzy inference method of the present embodiment is performed, the punch drawing speed V is indicated by 120 in the figure under the same processing conditions for the same blank 20. In addition, even when the punch speed V takes a value within the analytical break limit area 100, the blank 20 can be satisfactorily drawn and formed without actually breaking. It was confirmed.
[0045]
As described above, according to the method of the present embodiment, the punch speed V will be described later even in the analytical fracture limit area 100 that has been unavoidably avoided in order to avoid the fracture of the blank 20 during the drawing process. It has been confirmed that the blank 20 can be produced efficiently and satisfactorily without causing breakage by performing variable feedback control using a fuzzy inference method. Therefore, according to the present embodiment, press working is performed. Production efficiency can be increased while maintaining the quality of the product.
[0046]
In particular, in the method of the present embodiment, even in the case of performing multi-product small-volume production of press-processed products, by using basic data for fuzzy control suitable for the type and processing conditions of the blank 20 to be used, this multi-product small-volume production Can be realized with high production efficiency while maintaining quality.
[0047]
(2) Principle for fuzzy control of this embodiment
Hereinafter, the principle for fuzzy control of the present embodiment will be described.
[0048]
First, a method for obtaining basic data for fuzzy control for each type and processing condition of the processing target while changing the type and processing conditions of the blank 20 that is the processing target, and explaining this as a database will be described. A method for actually processing and forming a workpiece will be described.
[0049]
(Database construction)
For each type of blank 20 that is a workpiece, the blank 20 is subjected to drawing control under the processing conditions, and fuzzy control basic data is generated using the data obtained at this time and a finite element analysis technique. Such generation of basic data for fuzzy control is repeatedly performed by changing the type and processing conditions of the blank 20, and this is made into a database.
[0050]
1st stage
First, it is assumed that the thickness and volume of the target type blank 20 are constant. The parameter ΔDR with respect to the inflow amount r from the flange end of the blank 20 during deep drawing.^*The ideal machining curve 200 shown in FIG. 5A is obtained using a finite element analysis (FEN) method with the punch stroke S as a variable.
[0051]
Where ΔDR^*4A, the inflow amount (retraction amount) r from the flange end of the blank 20 is set to the radius R of the punch 14 as shown in FIG._PThis is a non-dimensional parameter.
[0052]
Second stage
Next, as shown in FIG. 4B, the blank 20 is actually press-drawn at a constant punch speed V, and ΔDR at this time^*And an actually measured machining curve 210 representing an association between the stroke stroke S and the punch stroke S. This measured machining curve 210 shows ΔDR when deep drawing is performed with a constant punch speed V.^*And actual measurement data representing the relationship between the punch stroke S and the punch stroke S. A plurality of actual machining curves 210 are obtained using the speed V as a parameter.
[0053]
The higher the punch speed V, the further away from the ideal machining curve 200, the measured machining curve is represented by 210a, 210b, 210c, 210d.
[0054]
In FIG. 4B, 270 represents an area where the blank 20 has a high risk of breaking when the blank 20 is drawn. Accordingly, when the measured processing curve 210 is obtained by gradually increasing the speed V, which is the parameter, using the punch speed V as a parameter, when the drawing speed V reaches a certain upper limit value, before the processing is completed. Breakage occurs in the blank 20. The measured machining curve 210 obtained using the velocity V at this time as a parameter is used as an measured machining curve 230 for obtaining the first evaluation function φ as shown in FIG.
[0055]
Third stage
As shown in FIG. 5A, a deviation φ between the ideal machining curve 200 obtained in the first stage and the actual machining curve 230 obtained in the second stage is used as a first evaluation function indicating the risk of fracture. Calculate as φ.
[0056]
Then, when the minimum value of the evaluation function φ is obtained as φa and the punch stroke S is increased in accordance with the measured machining curve 230, the evaluation function φ at the position of the breakage occurrence point 272 where the breakage occurs in the blank 20 is represented by φb Asking.
[0057]
In the present embodiment, φa and φb obtained from the first evaluation function φ are defined as first evaluation function data.
[0058]
Then, based on the first evaluation function data φa and φb obtained in this way, the input side membership function μφ for evaluating the risk of fracture shown in FIGS. 5C and 6A is generated. The fracture function described later is evaluated using this membership function μφ.
[0059]
4th stage
Further, in order to improve the reliability of the evaluation, the differential value φ ′ of the first evaluation function φ obtained in the third stage is obtained as a second evaluation function, and the minimum value φ of the differential value φ ′ is further obtained. 'A and the maximum value φ'b are obtained and defined as second evaluation function data.
[0060]
Then, based on the second evaluation function data φ′a and φ′b obtained in this way, the input side membership function for evaluating the risk of fracture shown in FIGS. 5C and 6B. μφ ′ is generated and used to evaluate the fracture.
[0061]
The degree of risk increases as the evaluation function φ increases, and the degree of risk becomes maximum when it coincides with φb. On the other hand, when the value coincides with φa, the degree of risk is minimized.
[0062]
Further, the differential component φ ′ of φ represents whether the punching speed during processing changes in a direction in which the risk of fracture is high (φb direction) or low (φa direction). When it coincides with φb ′, the degree of danger is maximum, and when it coincides with φa ′, the degree of danger is minimum.
[0063]
This evaluation is performed by performing a combination of the membership function shown in FIG. 6 (A) (or FIG. 5 (C)) and the membership function shown in FIG. 6 (B) (or FIG. 5 (C)). In this embodiment, the risk of breakage of the blank 20 during actual processing can be more accurately evaluated.
[0064]
In order to facilitate understanding, the membership functions are shown in FIGS. 5C, 6, 7A, and 8, respectively, but their contents are basically the same.
[0065]
5th stage
As described above, the ideal machining curve 200 obtained in the first to fourth stages, the first evaluation function φ, the first evaluation function data representing the minimum value φa and the maximum value φb, and the second evaluation function φ ′. , Second evaluation function data representing the minimum value φ′a and maximum value φ′b, and data for generating respective membership functions μφ and μφ ′ from the first and second evaluation function data, As basic data for fuzzy control, a database is created in association with the type and processing conditions of the blank 20 and stored in the storage means 40 shown in FIG.
[0066]
As described above, the processes of the first to fifth stages are repeatedly performed, and for each blank 20 of various materials, the processing conditions are changed to obtain basic data for fuzzy control. The database constructed based on the data is stored in the storage means 40 in advance.
[0067]
(Fuzzy inference rules)
Next, fuzzy inference rules for feeding back the drawing speed V of the punch 14 during actual machining using the basic data for fuzzy control associated with each type of blank 20 and machining conditions obtained as described above. explain.
[0068]
1st stage
The basic data for fuzzy control associated with the type of blank 20 to be actually processed and the processing conditions are read from the database stored in the storage means 40, and FIG. 7A (FIGS. 6A and 6B). A membership function μφ based on the first evaluation function and an input side membership function μφ ′ based on the second evaluation function are prepared.
[0069]
Second stage
When the blank 20 is actually drawn as shown in FIG. 1 according to the processing conditions, the punch stroke S and the pull-in amount r of the blank 20 shown in FIG. 4A are measured in real time.
[0070]
And the drawing amount r and the radius R of the punch 14_PAnd ΔDR^*= R / R_PAnd the calculated value ΔDR^*A deviation φ between the punch stroke S on the ideal machining curve 200 and the punch stroke S obtained by actual measurement is obtained as first real-time evaluation data.
[0071]
Further, a differential value φ ′ of the first real time evaluation data φ is obtained as second real time evaluation data.
[0072]
Third stage
FIG. 7B shows an If-then rule for estimating the variation ΔV of the punch drawing speed V from the real-time evaluation data φ and φ ′ obtained in this way.
[0073]
In FIG. 7B, if (φ, φ ′) on the left side represents the input condition of this fuzzy inference rule, and then then (ΔV) on the right side represents the output thereof. This is reflected in the output of the output control membership function in FIG.
[0074]
For example, it is assumed that the first and second real-time evaluation data obtained by actual measurement are φ and φ ′ as shown in FIG. In this case, the area of the input side membership function of the if-then rule shown in FIG. Specifically, as shown in FIG. 8, the input-side membership functions μφ, μφ ′ specified by the real-time evaluation data φ, φ ′ are 300-1, 300-2, 300-3, 300-4. The area of the triangle is A_φL, A_φS, A_φ'L, A_φ´SAsking.
[0075]
4th stage
Next, each partial fuzzy set (A_φL, A_φ'L, A_φS, A_φ´S) And is substituted into the membership function for determining the output value as shown in FIG. 9 according to the if-then rule.
[0076]
That is, the area of the input side membership function shown in FIG. 8 is substituted into the output side membership function shown in FIG. In FIG. 9, ΔV of the membership function for determining the output value_LL, ΔV_LS, ΔV_SL, ΔV_SSThe substituting areas are areas indicated by 400-1, 400-2, 400-3, and 400-4.
[0077]
The area of each of these regions 400-1, 400-2, 400-3, 400-4 is A_LL, A_LS, A_SL, A_SSIt is.
[0078]
Specifically, it is represented by the following formula.
A_LL= A_φL+ A_φ'L
A_LS= A_φL+ A_φ´S
A_SL= A_φS+ A_φ'L
A_SS= A_φS+ A_φ´S
[0079]
Next, a punch speed control value ΔV is obtained from the partial fuzzy set (areas of areas 400-1 to 400-4) assigned to the membership function for determining the output value by the center of gravity method.
[0080]
In the present embodiment, the area a and the center of gravity g of each of the areas 400-1 to 400-4 of the output value determining membership function shown in FIG. 9 are obtained, and the center of gravity position of the area 400 is feedback-controlled based on the following equation. It is obtained by calculation as a variable amount ΔV of the speed V.
[0081]
ΔV = Σa_ng_n/ Σa_n
(Σa_n= A_LL∪A_LS∪A_SL∪A_SS)
[0082]
A_nIs the area of the region obtained by arbitrarily dividing the partial fuzzy set of the membership function for determining the output value, g_nIndicates the center of gravity of the region.
[0083]
5th stage
ΔV thus obtained represents the amount of change for obtaining an optimum punch drawing speed V that does not cause breakage when the blank 20 is actually deep drawn.
[0084]
Therefore, by performing feedback control of the drawing speed of the punch 14 by the amount of change ΔV that is fuzzy inferred in real time in this way, as shown by 120 in FIG. 3, the efficiency is obtained at an optimum speed without causing breakage. Deep drawing can be performed well.
[0085]
In particular, even in the analytical fracture limit area 100 that could not be used in the conventional constant speed control of the punch speed, according to the present embodiment, the blank 20 can be deep-drawn without breaking. It becomes possible.
[0086]
As shown in FIGS. 6A and 6B described above, this is input using not only φ as real-time evaluation data indicating the risk of fracture during actual machining but also this differential value φ ′. This is because the side membership function is generated, the trend of the risk of fracture is also estimated, and the method of determining the feedback amount ΔV of the punch speed is adopted. Thereby, it is possible to realize the punch speed in the analytical fracture limit area 100 that cannot be achieved when the punch speed V is set to a fixed value, and it is possible to increase the productivity of the drawing process as compared with the conventional case.
[0087]
(3) Configuration block diagram of the main parts of the press machine
FIG. 2 shows a functional block diagram of a configuration for performing feedback control of the punch drawing speed V using the principle described above.
[0088]
The press machine according to the present embodiment includes a sensor group 60 that performs measurement at various portions, an actuator group 70 that drives the various portions, a control unit 50, and a storage unit 40.
[0089]
The sensor group 60 includes a punch stroke sensor 60a, a punch speed sensor 60b, a wrinkle pressing force sensor 60c, a pull-in amount sensor 60d, and other sensors.
[0090]
As shown in FIG. 4A, the punch stroke sensor 60a detects a stroke S that is the amount of movement of the punch 14 from the initial position, and the punch speed sensor 60b is a lowering and raising speed of the punch 14, especially an actual machining. The punch drawing speed V at the time is measured.
[0091]
The wrinkle pressing force sensor 60c measures the wrinkle pressing force H that holds the blank 20 between the blank holder 30 and the die 10, and the pull-in amount sensor 60d is a series of apertures shown in FIGS. In the processing step, the pulling amount r of how far the blank 20 is pulled by the drawing process of the punch 14 from the initial position before the processing shown in FIG. 1A is measured. Specifically, as shown in FIG. 4A, the pull-in amount r from the state before processing is measured in real time.
[0092]
The actuator group 70 includes a plurality of actuators that drive each part of the press machine. Specifically, the generation of the crease pressing force H by the blank holder 30, the raising and lowering of the punch 14, and the speed control associated therewith, It is configured to perform various other driving operations.
[0093]
As described above, the storage means 40 stores the basic data for fuzzy control created for each type and processing condition of the blank 20 that is the processing target in a database.
[0094]
The control means 50 reads the basic data for fuzzy control suitable for the type and processing conditions of the blank 20 from the database stored in the storage means 40 during the drawing process of the actual blank 20, and the read basic data for fuzzy control. Based on the punch stroke S measured in real time by the sensors 60a and 60d and the pull-in amount r of the blank 20, the aperture speed V of the punch 14 is feedback-controlled according to the fuzzy inference method described above.
[0095]
For this reason, the control means 50 of this Embodiment is comprised so that it may function as the basic data specific | specification means 52, the real time evaluation data calculating means 54, and the feedback control means 56. FIG.
[0096]
FIG. 10 shows an operation flowchart of the drawing apparatus of the present embodiment.
[0097]
As shown in FIG. 1, when the blank 20 is drawn by using the press machine according to the present embodiment, first, the operator first determines the type (for example, material) of the blank 20 to be processed before the processing. ) Is designated (ST10), and the processing conditions of the blank 20 are designated (ST11).
[0098]
Such type and processing condition input may be displayed as a selection screen on a display, for example, and the operator may select and perform this on the screen as appropriate.
[0099]
When the type and processing conditions of the blank 20 are input, the control unit 50 functions as the basic data specifying unit 52, and reads the basic data for fuzzy control suitable for these types and processing conditions from the database of the storage unit 40 (ST12). .
[0100]
When such a series of processing ends, the control means 50 starts the movement of the punch 14 for drawing (ST13), performs fuzzy inference processing (ST15), and feedback-controls the drawing speed V of the punch 14 (ST15). A series of processing of ST16) is repeated until it is determined in ST14 that the processing is finished.
[0101]
If it is determined that the processing is finished, the punch 14 is stopped (ST17), and then the punch is lifted and retracted (ST18), and when a predetermined reference position is returned, a series of drawing processing is finished.
[0102]
Here, a series of processing such as ST13, ST16, ST17 and the like is performed by the control means 50 functioning as the feedback control means 56 and driving the actuator group 70.
[0103]
FIG. 11 shows details of the fuzzy inference of ST15 described above.
[0104]
This series of processing is performed by the control unit 50 functioning as the real-time evaluation data calculation unit 54 and the feedback control unit 56.
[0105]
First, real-time measurement values of the punch stroke S and the blank 20 pull-in amount r are obtained from the sensors 60a and 60d (ST30), and the first and second real-time evaluation data φ are obtained from the deviation between the ideal machining curve 200 and the actual measurement data. , Φ ′ are calculated (ST31). Then, using the real-time evaluation data φ, φ ′ as input values of the input side membership functions μφ, μφ ′, the area A of the partial fuzzy set of the input side membership function_φL, A_φS, A_φ'L, A_φ´SIs obtained (ST32).
[0106]
Then, a determination process based on the if-then rule shown in FIG. 7B is performed (ST33), and the area (A of each partial fuzzy set of the input side membership function described above according to the determination rule)_φL, A_φ'L, A_φS, A_φ´S) Is substituted for the output side membership function as shown in FIG. 9 (ST34).
[0107]
Then, the center-of-gravity position G of the substitution area 400 of the output value determining membership function shown in FIG. 9 is specified, and the deviation ΔV between the center-of-gravity position G and the reference position is obtained as the punch speed change amount ΔV (ST35).
[0108]
In ST16 shown in FIG. 10, feedback control is performed so that the punch drawing speed V is changed by the change amount ΔV thus obtained.
(Verification of this embodiment)
[0109]
Next, the verification experiment of the result in the case of performing deep drawing by applying this embodiment was performed. Details will be described below.
[0110]
FIG. 12A shows an outline of the processing apparatus used in this experiment, and FIG. 12B shows dimensional data of the apparatus used in the experiment.
[0111]
Here, a cold-rolled steel sheet having a thickness of 0.7 mm was used as the blank 20.
[0112]
FIG. 13 shows the mechanical properties of this steel sheet.
[0113]
The aperture ratio representing the size of the blank 20 was 2.58. As the lubricant, a spray-type dry fluorine lubricant that is less affected by speed was applied.
[0114]
FIG. 3 shows actual measurement data when the punch drawing speed V is feedback-controlled using the fuzzy control method of the present embodiment under such experimental conditions. In the figure, 120 is actual measurement data at this time.
[0115]
The punch speed V that is feedback-controlled is low at the start of machining, and in the initial stage of machining, the speed increases rapidly to 130 mm / min, exceeding the condition of 150 mm / min that breaks at a constant speed from the middle stage to the latter stage, The drawing process was successful up to about 330 mm / min.
[0116]
FIG. 14 shows the distortion of the minimum plate thickness in the punch mold part of the deep-drawn container formed by experiment. As can be seen from the experimental results, the punch drawing speed is controlled by feedback control as in this embodiment, compared to the measured value when deep drawing is performed with the punch drawing speed being constant values of 150 mm / min and 125 mm / min. It was confirmed that when the variable speed control was performed, the distortion was greatly reduced.
[0117]
FIG. 15 shows the processing time when deep drawing is performed at a constant punch punch speed V of 125 mm / min, and the case where feedback control is performed using a fuzzy inference method and variable speed control is performed as in this embodiment. The comparison with the processing time is shown. From the figure, it was confirmed that the variable speed control of the present embodiment significantly shortened the machining time compared to the case of deep drawing with a constant speed machining time. Specifically, in this experiment, it was confirmed that the machining time could be shortened by 22%.
[0118]
As described above, it was confirmed that by using the system of the present embodiment, fuzzy adaptive control of the punching speed at the time of deep drawing can improve the product accuracy and shorten the processing time.
[0119]
In addition, this invention is not limited to the said embodiment, A various deformation | transformation implementation is possible within the range of the summary of this invention.
[0120]
For example, a blank holder wrinkle holding force H against a blank is added to one of the processing conditions, and a plurality of basic data for fuzzy control when this wrinkle holding force is changed is prepared in advance, and this is stored in a storage means as a database. You may comprise so that it may memorize | store.
[0121]
As a result, even when the punch drawing speed is controlled to be variable with respect to the same blank while changing the wrinkle pressing force, the value can be feedback controlled to a more optimal value.
[0122]
In the above embodiment, the case where the control means is formed as hardware has been described as an example. However, the present invention is not limited to this, and a general-purpose computer is used as the control means, and this computer functions as the control means. A program for functioning as a means such as basic data specifying means, real-time evaluation data calculating means, feedback control means, etc. is stored in a storage medium, and the computer is controlled based on this program. It may be configured to function as.
[0123]
In this case, the database stored in the storage means may be formed so as to be stored in the same storage means as the program, or may be formed so as to be stored in different storage means.
[Brief description of the drawings]
FIGS. 1A to 1C are schematic operation explanatory views of the main part of a press machine that performs a series of deep drawing.
FIG. 2 is a functional block diagram of a punch drawing speed control mechanism in the press machine according to the present embodiment.
FIG. 3 is an explanatory diagram showing a relationship between a flange end reduction rate and a punch speed.
FIG. 4A is an explanatory diagram of the blank pull-in amount during deep drawing, and FIG. 4B is an explanatory diagram of the relationship between the flange end reduction rate and the punch stroke.
FIG. 5A is an explanatory diagram showing a relationship between an ideal curve and an actually measured machining curve, and FIG. 5B is an explanatory diagram of a maximum value and a minimum value of an evaluation function.
FIG. 6 is an explanatory diagram of an input-side membership function.
FIG. 7A is an explanatory diagram of an input-side membership function, FIG. 7B is an explanatory diagram of an if-then rule for fuzzy inference, and FIG. 7C is an output diagram; It is explanatory drawing of a side membership function.
FIG. 8 is an explanatory diagram of an input side membership function for evaluating the risk of fracture when actual evaluation data is input.
FIG. 9 is an explanatory diagram of an output side membership function that evaluates the risk of fracture, with the area of the input side membership function substituted.
FIG. 10 is a flowchart showing an example of the operation of the press device according to the present embodiment.
FIG. 11 is an operational flowchart of fuzzy inference according to the present embodiment.
FIG. 12 is an explanatory diagram of a press machine used in the experiment and its dimensions.
FIG. 13 is an explanatory diagram of material characteristic values of a blank used in an experiment.
FIG. 14 is an explanatory diagram of an actual measurement value of a minimum thickness distortion at the time of deep drawing.
FIG. 15 is a comparative explanatory view of machining time when the punch speed is controlled at a variable speed and when controlled at a constant speed.
[Explanation of symbols]
10 die
14 Punch
20 blank
30 Blank holder
40 storage means
50 Control means
60 sensors
70 Actuators
200 Ideal processing curve
230 Actual machining curve

Claims (5)

In a deep drawing press machine that performs deep drawing by varying the punch speed of a workpiece fixed by a die and a blank holder,
Data on the ideal machining curve obtained by performing analysis to represent the relationship between the amount of workpiece to be drawn and the punch stroke, and the actual machining curve representing the relationship between the amount of workpiece to be drawn and the punch stroke and the evaluation function data to the associated deviation between the ideal working curve, and membership functions for the feedback control value determination of the stop speed punch obtained from the evaluation function data, and a fuzzy control basic data including and means for storing the types and database for each item of the associated processing conditions on the type of the object,
Acquire the relationship between the amount of workpiece pull-in actually measured at the time of actual machining and the punch stroke, and specify the basic data for fuzzy control that matches the above items of the workpiece from the above database, and for the specified fuzzy control Finds the real time evaluation data associated with the deviation between the ideal working curve data and the actual data contained in the basic data, and real time evaluation data obtained, the evaluation function data contained in the fuzzy control basic data identified and control means for feedback controlling the aperture speed of the punch based on the bets,
Including
The data of the evaluation function is
First evaluation function data obtained from a first evaluation function representing a deviation between the measured machining curve and the ideal machining curve;
Second evaluation function data obtained from a second evaluation function obtained by differentiating the first evaluation function,
Feedback control of the punch drawing speed is
Fuzzy inference rules created based on the first and second evaluation function data included in the identified basic data for fuzzy control, and a membership function using these, real-time evaluation data obtained, A press machine for deep drawing, which is performed by obtaining a feedback control value of the drawing speed of the punch by fuzzy inference based on an if-then rule associated with a membership function for determining the drawing speed output . In claim 1 ,
The press machine for deep drawing, wherein the ideal machining curve is obtained by finite element analysis based on predetermined setting conditions. In any one of Claims 1, 2.
  Means for inputting the type and type of the workpiece,
  The control means includes
  A press machine for deep drawing characterized by including means for specifying basic data for fuzzy control that matches the above-mentioned item of the processing object from the database from the type and type of the input processing object. In a control method of a press machine that deep-draws a workpiece to be processed fixed by a die and a blank holder by varying the punch speed,
Data on the ideal machining curve obtained by performing analysis to represent the relationship between the amount of workpiece to be drawn and the punch stroke, and the actual machining curve representing the relationship between the amount of workpiece to be drawn and the punch stroke and the evaluation function data to the associated deviation between the ideal working curve, and membership functions for the feedback control value determination of the stop speed punch obtained from the evaluation function data, and a fuzzy control basic data including , is stored as the type and database for each item of the associated processing conditions on the type of the object,
Acquire the relationship between the amount of workpiece pull-in actually measured during actual machining and the punch stroke,
Fuzzy control basic data conforming to the above items of the workpiece is identified from the database, and real-time evaluation is associated with the deviation between the ideal machining curve data included in the identified basic data for fuzzy control and the measured data for data, and real time evaluation data obtained, the aperture speed of the punch and feedback control on the basis of said evaluation function data contained in the fuzzy control basic data specified,
The data of the evaluation function is
First evaluation function data obtained from a first evaluation function representing a deviation between the measured machining curve and the ideal machining curve;
Second evaluation function data obtained from a second evaluation function obtained by differentiating the first evaluation function,
Feedback control of the punch drawing speed is
Fuzzy inference rules created based on the first and second evaluation function data included in the identified basic data for fuzzy control, and a membership function using these, real-time evaluation data obtained, A control method for a press machine, comprising: obtaining a feedback control value of a punching speed of the punch by fuzzy inference based on an if-then rule associated with a membership function for determining an output of a drawing speed . In claim 4 ,
The ideal working curve, a control method of a press machine, characterized in that it is determined by the finite element analysis based on a predetermined setting condition.

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