JP2019070916A - Cutting simulation method and device - Google Patents

Abstract

To provide a cutting simulation method and a device capable of following the variation of a cutting state during the feed amount per one blade of a tool, predicting the removing amount of a work material by canceling approximate error of a tool locus, and accelerating the processing time for calculation at the same time.SOLUTION: In a cutting simulation method and a device expressing a work material in a voxel model arranged with minute voxels, the shape of a tool cutting edge of a machine tool is expressed by a three-dimensional point group of minute intervals, specific index is given to each voxel corresponding to the arranged position in the voxel model, the index of the voxel superposing on lines connecting a tool central axis to the point group of the tool cutting edge is calculated for every minute rotation angle of the tool cutting edge to thereby determine interference, and to predict a removing amount of the work material using the resolution of minute time and minute spaces.SELECTED DRAWING: Figure 6

Description

  The present invention relates to a cutting simulation method and apparatus for cutting process in the field of machining.

  In order to improve the processing efficiency of cutting with a machine tool, it is important to grasp the processing situation and appropriately set the cutting conditions. Cutting power is mentioned as one index which grasps processing situation. The cutting force represents the machining state at that time, and is useful information for predicting the amount of deformation of the tool or the work material that affects the accuracy of the machined surface. Conventionally, researches for estimating cutting force have been conducted, and many cutting force models have been proposed so far, and in recent years, cutting force simulation with extremely high accuracy has become possible. However, such a cutting force model is a mathematical model created based on the geometrical relationship between the cutting edge of the tool and the work material, and if the processing form changes, a mathematical model corresponding to that must be created. In addition, there is a problem that considerable effort is required to simulate various processing situations. In addition, if the shape change of the workpiece during machining becomes complicated and the contact between the cutting edge of the tool and the workpiece becomes uneven, it is difficult to express with a mathematical model and it is difficult to predict the cutting force. There is also a problem.

  Also, for example, in a tool having a complicated cutting edge shape such as an end mill, in order to predict the cutting force at the time of processing, deformation, wear of the tool, in addition to basic processing conditions such as infeed, feed and cutting speed. Although it is necessary to create a cutting force model that takes into consideration all the factors related to cutting phenomena, such as the properties of the work material, the cutting phenomenon is a mechanical failure that is a continuous failure phenomenon under high strain rates. Because it is a very complex physical phenomenon, it is difficult to model taking into consideration all factors, and to formulate the cutting phenomenon approximately by focusing only on the dominant factors that have a large influence. The reality is that

A variety of cutting force models have been proposed to predict the cutting force of end milling, and average cutting force models (Average Rigid Force, Static Deflection Model), Instantaneous Cutting Force Model (Instantaneous Rigid Force Model), Instantaneous Cutting Force Model / Instantaneous Rigid Force, Static Deflection Model, Instantaneous Cutting Force Model with Tool Deformation (Instantaneous Force with Static Deflection Feedback Model), and Instantaneous Cutting Force Model / Dynamic Deformation Model Considering Chip Regeneration Effect It is mainly classified into five types of models such as (Regenerative Force, Dynamic Deflection Model).
Of the five types of cutting force models, in the instantaneous cutting force model, realistic cutting force can be calculated relatively easily from the amount of interference between the tool cutting edge and the work material. The instantaneous cutting force model takes into account the complex cutting mechanism by the end mill's twisting blade, and can calculate realistic cutting forces, and divides the end mill into micro thin plate elements along the tool rotation axis direction. Then, it is possible to calculate the cutting force of the whole tool by calculating the micro cutting force for each element and adding the micro cutting forces while considering the direction of the force.
Method to reproduce shape change of work material using solid kernel of 3D CAD, in order to calculate the amount of interference between tool cutting edge and work material, Z-Map model (2 dimensional array limited to Z axis data ) To estimate the amount of interference with the tool by estimating the surface shape of the workpiece from the tool axis direction), and a voxel model that expresses the three-dimensional shape of the workpiece as a set of small cubes (voxels) There have been proposed a method of estimating the amount of interference with a tool and a method of adding a distance attribute to the tool to a voxel model to perform high-accuracy estimation.

Among them, in the method of discretely simulating the cutting phenomenon using the voxel model (hereinafter referred to as “cutting simulation method”), the interference between the tool and the work material is detected to easily express the complicated machining shape. (See, for example, Patent Document 1 and Non-Patent Document 1).
The interference determination between the tool and the work material using the voxel model moves the tool center for each feed amount per tool edge as shown in FIG. 22, and the tool moves to a new position every time the tool moves to a new position. The existing voxels are searched to calculate the amount of interference between the tool and the work material. At this time, the voxel inside the tool area is determined by comparing the distance L of each voxel with respect to the tool central axis and the magnitude of the radius r of the sphere containing each voxel and the tool radius R.

  In the conventional cutting simulation method, the tool trajectory is approximated by a circular arc because analysis is performed for each feed amount per tool edge. Therefore, for example, the surface shape of the work material with a chipping residue (cusp) generated when using a ball end mill as a tool can not be correctly represented, and changes in the middle of the feed amount per tool edge There is a problem that it is difficult to take into account static deformation due to wear or bending of a tool, or dynamic deformation due to vibration or external stress.

  Moreover, in the conventional cutting simulation method, the speedup of the interference determination between the total amount of computer memory required to improve the simulation accuracy and the large number of voxels and the tool cutting edge is a major issue. In order to save the volume of data in voxel models, it is known to introduce an octree representation to reduce the consumption of computer memory. In this Oktoturi representation, the voxels that interfere with the tool are divided into eight equal divisions (Octotree: 8-tree) with each side bisected, and divided into voxels whose length of one side of the cube is 1⁄2 before division By repeating the process described above, a fine workpiece surface shape is expressed while suppressing the total number of voxels.

As shown in Fig. 23 (1), the interference judgment between voxels and the tool cutting edge by the Oktotsuri representation represents the work material as voxels of a large size, and the tool cutting edge and the interference from all voxels The voxels which have been determined are divided, and division is performed so that the length of one side is 1⁄2, as shown in FIG. The voxels interfering with the tool cutting edge are searched, and as shown in FIG. 23 (3), the length of one side is further divided into halves, the voxels are searched, and processing is repeated by repeating these processes. It is possible to express the surface shape of the work material and improve the accuracy (resolution) of cutting simulation.
However, in the cutting simulation method based on the Oktotli representation, in order to reduce the voxel size in stages, repeated processing of the interference determination is increased when expressing a finer workpiece surface shape, and interference with the tool cutting edge It is a problem that it is necessary to search for certain voxels in each layer, and it is difficult to accurately represent a large workpiece in terms of simulation processing time.

JP, 2016-162149, A

Shirase, K. et al., “Vocal representation of machining removed area for tool realization and tool motion control with reference to voxel information”, Proceedings of the Japan Society of Mechanical Engineers, Vol. 79, 808 (2013-12), pp. 47-56

  As described above, in the conventional cutting simulation method, the amount of interference between the tool cutting edge and the work material is calculated for each feed amount per tool edge, the actual cutting thickness is calculated, and the cutting force is estimated. There is. In this case, it is premised that the cutting state does not change between the feed amounts per tool edge. For this reason, there has been a problem that, when the cutting state changes during the feed amount, an approximation error of the tool trajectory occurs in actuality due to vibration or bending or deformation of the tool.

  In addition, interference judgment with the work material is performed with the tool used as a rotary body shape with the tool axis as the rotation axis, and the tool is limited to tools such as a square end mill that can be represented by a cylindrical shape or a ball end mill Because the tool trajectory is approximated by a circular arc, it has been difficult to correctly express the surface shape of the workpiece with the cusps.

  Furthermore, in the cutting simulation method based on the octoli representation, in order to reduce the voxel size in stages, there are many repetitive processes when expressing a finer workpiece surface shape, and voxels interfering with the tool cutting edge are made in each hierarchy It is difficult to express a large work material with high accuracy from the viewpoint of simulation processing time.

  In cutting, it is effective to evaluate the load applied to the tool cutting edge at the time of processing and the evaluation of the finished surface of the work material after processing. It is necessary to calculate the removal amount precisely. In addition, it is necessary to speed up the processing time involved in the calculation.

  In view of such circumstances, the present invention can follow changes in cutting conditions between feed amounts per tool edge, eliminate approximation errors of the tool trajectory, predict the removal amount of the work material, and simultaneously calculate It is an object of the present invention to provide a cutting simulation method and apparatus capable of achieving speeding up of the processing time involved. In addition, a cutting force adaptive control method and cutting force adaptive control system capable of following a change in cutting state between feed amounts per tool edge and predicting the cutting force or cutting torque of the tool with minute time and resolution of minute space Intended to provide.

  In order to solve the above problems, the cutting simulation method of the present invention is a cutting simulation method in which a material to be cut is represented by a voxel model in which minute voxels are arranged, and the shape of the tool cutting edge of the machine tool is three-dimensionally Expressed by the point group, gives a unique index to each voxel corresponding to the placement position in the voxel model, and connects the tool center axis and the point group of the tool edge for every minute rotation angle of the tool edge The index of voxels overlapping the group is calculated to perform interference determination, and the removal amount of the work material is predicted with the resolution of minute time and minute space.

In the method of the present invention, the conventional cutting simulation method for representing the work material in voxel shape is expanded to discretely represent the shape of the tool cutting edge with minutely spaced point groups, and for each feed amount per tool edge Analysis of each cutting edge of the cutting edge instead of the analysis of the tool edge, simulation of cutting phenomenon with resolution of minute time and minute space, and considering static deformation and dynamic deformation of the tool during cutting process Predict the amount of material removed.
According to the method of the present invention, the interference with the voxel is determined for each minute rotation angle of the tool cutting edge, and the removal amount of the work material is predicted with the minute time and the resolution of the minute space, It is possible to follow the change of the cutting state between the feed amounts of and eliminate the approximation error of the tool trajectory. In addition, a unique index is assigned to each voxel in correspondence with the arrangement position in the voxel model, and an index of voxels overlapping with a straight line group connecting the tool center axis and the point group of the tool edge is calculated to perform interference determination. By this, it is possible to speed up the processing time involved in the prediction calculation of the removal amount. The voxel index is a unique identifier assigned to each voxel in correspondence with the arrangement position in the voxel model.

  Here, the minute rotation angle of the tool cutting edge is a rotation angle at which the amount of movement of one of the straight lines connecting the tool center axis and the point cloud of the tool cutting edge is equal to or less than the diameter of the sphere circumscribing voxels of the voxel model. . The reason for setting the diameter equal to or less than the diameter of the sphere circumscribing the voxel is to set the rotation angle so as not to be a large moving amount such that the minute rotation angle skips one minute voxel. In other words, it is a rotation angle at which the amount of movement of the tip of the tool cutting edge is equal to or less than the distance of one side of the minimum voxel. The rotation angle is set so that the amount of movement of one group of straight lines is the length of one side of a voxel of a cube, the length of a diagonal of a cube or its constituting face, the radius of a circle inscribed in the voxel It is also good.

  In addition, the interference determination is performed by calculating an index of a voxel overlapping with a straight line group connecting the tool center axis and the point group of the tool cutting edge for each small thin plate element divided in the plane orthogonal to the rotation axis of the tool . The index of voxels is a unique identifier given to each voxel in correspondence with the arrangement position in the voxel model, and the tool center axis and the tool cutting are separated for each thin thin plate element divided by the plane orthogonal to the rotation axis of the tool. An index of voxels overlapping the straight line group connecting with the point group of the blade is calculated to determine the interference between the workpiece and the tool in the three-dimensional shape. By determining each of the thin thin plate elements divided in the plane orthogonal to the rotation axis of the tool, it is possible to determine the interference between the workpiece and the tool corresponding to the difference in the shape of the cutting edge of the tool in the axial direction.

  Then, the removal amount of the work material is calculated based on the number of voxels and the voxel size obtained by adding up the number of voxels of the index calculated by the interference determination in each thin thin plate element. By calculating the voxel index, it is possible to calculate the number of removed voxels, that is, the removal amount of the work material.

  The voxel model is represented by voxels of the smallest voxel size, that is, by expressing the voxel model with the voxel of the smallest size from the beginning, there is no repetitive process of interference determination as in the case of the Oktouri representation, and the removal amount is calculated The processing can be speeded up.

Also, the voxel model is represented by the first voxel of the first minimum voxel size, and the first voxel of the index calculated by the interference determination is further represented by the second voxel of the second minimum voxel size. Alternatively, each second voxel may be assigned a unique index corresponding to the arrangement position.
The cutting simulation may be performed using a voxel model which is obtained by dividing the voxel size into two layers and further dividing the first minimum voxel size voxel into a second minimum voxel size voxel. For example, due to computer and program limitations, it may be difficult to express in the minimum voxel size from the beginning. When a large size work material is represented by a small voxel size, for example, when a 1 m cube-shaped work material is represented by a 1 μm voxel size, the number of 10 ⁶ × 10 ⁶ × 10 ⁶ = 10 ¹⁸ An array of indices is required. In such a case, it can not be realized due to the restriction of the arrangement number of computers and programs, and in this case, the voxel size has to be divided into two layers, or three layers if necessary.

  When the tool shape is deformed statically or dynamically during cutting, it is preferable to change the three-dimensional point group representing the shape of the tool cutting edge according to the deformation. Even when the cutting state changes during the tool feed amount due to vibration or bending or deformation of the tool, the change in the cutting state can be followed, and the approximation error of the tool path can be eliminated.

  In the cutting simulation method of the present invention, it is preferable to further predict the cutting force or cutting torque of the tool based on the predicted removal amount of the work material for each minute rotation angle of the tool cutting edge. The cutting load (cutting force or cutting torque) during machining is predicted based on the predicted removal amount of the work material without using the cutting force sensor. Thereby, adaptive control can be performed by sequentially changing the cutting conditions according to the predicted cutting torque.

Next, the cutting force adaptive control method of the present invention will be described.
The cutting force adaptive control method of the present invention predicts the cutting force or cutting torque of the tool of the machine tool using the above-described cutting simulation method of the present invention, and according to the predicted cutting force or cutting torque, Change the machining command and regenerate the tool path.
According to the cutting force adaptive control method of the present invention, the cutting force of the tool is predicted in real time during cutting, and the cutting command for the machine tool is corrected based on the cutting torque calculated from the predicted cutting force. Adaptive control can be performed by sequentially outputting the obtained cutting command to the machine tool. Also, the corrected machining command can be fed back to regenerate the tool path of the machine tool. Here, the cutting command means a command for operating the target machine tool, such as a tool movement command, a tool feed speed, a tool feed stop command, a tool change command, and a spindle rotational speed.

  Further, according to the cutting force adaptive control method of the present invention, the cutting force or cutting torque of the tool of the machine tool is predicted using the above-described cutting simulation method of the present invention, and the machining force is controlled according to the predicted cutting force or cutting torque. It is also possible to increase or decrease at least one of the tool feed speed of the machine and the tool rotation speed.

Next, the cutting simulator device of the present invention will be described.
The cutting simulator device of the present invention comprises the following 1) to 4).
1) Work material data in which a material to be cut is represented by a voxel model in which minute voxels are arranged, and to which a specific index is assigned to each voxel corresponding to the arrangement position in the voxel model,
2) tool cutting edge shape data in which the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point group,
3) Using the material to be cut, tool edge shape data, and the position data of the material to be cut and the tool edge, the shape of the tool center axis and the tool edge for each minute rotation angle of the tool edge An interference determination unit that performs an interference determination by calculating an index of voxels that overlap with a straight line group connecting with a point group of dimensions;
4) A removal amount prediction unit that predicts the removal amount of the work material with the resolution of minute time and minute space based on the number of voxels and voxel size calculated by the interference determination unit.

  The cutting simulator program according to the present invention is a program that is configured by a computer and installed in the apparatus, and is a program for causing the computer to function as the interference determination unit in 3) and the removal amount prediction unit in 4). It is.

Here, the minute rotation angle is a rotation angle at which the amount of movement of one of the straight lines connecting the tool center axis and the three-dimensional point group of the shape of the tool cutting edge is equal to or less than the diameter of the sphere circumscribing voxels of the voxel model. is there. The interference determination unit calculates and determines an index of a voxel overlapping with a straight line group connecting the tool center axis and the point group for each small thin plate element divided in a plane orthogonal to the rotation axis of the tool. In the removal amount prediction unit, the removal amount of the work material is calculated based on the number of voxels obtained by adding up the number of voxels of the index calculated by the interference determination unit and the voxel size in each thin thin plate element.
The voxel model is preferably initially represented by voxels of the smallest voxel size. Also, the voxel model is represented by the first voxel of the first minimum voxel size, and the first voxel of the index calculated by the interference determination unit is further represented by the second voxel of the second minimum voxel size It is also possible to give each second voxel a unique index corresponding to the arrangement position.
Furthermore, when the tool shape is deformed statically or dynamically during cutting, it is preferable to change the three-dimensional point cloud of the shape of the tool cutting edge according to the deformation. Then, the removal amount prediction unit may further predict the cutting force or the cutting torque of the tool based on the predicted removal amount of the work material for each minute rotation angle of the tool cutting edge.

Next, the cutting force adaptive control system of the present invention will be described.
The cutting force adaptive control system according to the present invention has a tool path generation unit that generates a tool path of a machine tool in real time, is controlled by cutting parameters, and dynamically transmits a cutting command to the machine tool during cutting. The adaptive control system includes a sequential command unit that changes to and outputs sequentially, and includes the following (a) to (f): Regenerates the tool path according to the cutting parameters, and the cutting command is dynamic Change to

(A) Work material data in which the work material is represented by a voxel model in which minute voxels are arranged, and in which a unique index is assigned to each voxel corresponding to the arrangement position in the voxel model;
(B) tool cutting edge shape data in which the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point group;
(C) The shape of the tool center axis and the tool cutting edge for each minute rotation angle of the tool cutting edge using the material to be cut, the tool cutting edge shape data, and the position data of the cutting material and the tool cutting edge An interference determination unit that performs interference determination by calculating an index of voxels that overlap with a straight line group connecting a three-dimensional point group;
(D) a removal amount prediction unit that predicts the removal amount of the work material with a minute time and a minute space resolution based on the number of voxels and the voxel size calculated by the interference determination unit;
(E) a cutting force prediction unit that predicts the cutting force of the tool based on the predicted removal amount of the work material for each minute rotation angle of the tool cutting edge;
(F) A cutting parameter changing unit that dynamically changes a cutting parameter according to the cutting torque calculated from the predicted cutting force.

  About said (a)-(d), it is the same as that of description of the cutting simulator apparatus of the above-mentioned this invention, and it omits. The minute time with real-time capability is the time to end the processing of the instructed job when the computer is instructed to execute the job, and is several nanoseconds to several milliseconds. The cutting parameters are the tool rotational speed and the tool feed rate, and feedback the cutting load during cutting and increasing or decreasing the tool rotational speed or the tool feed rate, the cutting load predicted by simulation (cutting force) Alternatively, application control can be performed such as increasing or decreasing the speed according to the cutting torque). Further, it is possible to dynamically change the cutting parameters of the CNC (Computerized Numerical Control) device for a machine tool according to the predicted cutting force or cutting torque.

According to the cutting simulation method and apparatus of the present invention, it is possible to follow the change in the cutting state between the feed amount per tool edge, eliminate the approximation error of the tool trajectory, and predict the removal amount of the work material In addition, the removal amount is calculated discretely by expressing the material to be cut in small voxels from the beginning, so that it is possible to speed up the removal amount calculation processing time.
Further, according to the cutting force adaptive control method and the cutting force adaptive control system of the present invention, the cutting of the tool can be performed with the resolution of the minute time and the minute space, following the change of the cutting state between the feed amounts per tool edge. The effect is that the force or cutting torque can be predicted.

That is, according to the present invention, the removal amount can be finely calculated in a short time in cutting, and estimation of cutting force in cutting, estimation of finish surface shape in cutting, and deformation deformation of a tool are considered. Estimation can be performed with high accuracy.
In the cutting process, conventionally, trial cutting was actually performed to determine whether the processing conditions are good or bad. However, according to the present invention, simulation is performed in advance to estimate the finished surface shape with high accuracy, and the processing conditions are good. The ability to predict ill effects has the effect of increasing production efficiency.

Explanatory drawing about voxel removal for every minute rotation angle of a tool cutting edge Explanatory drawing about the voxel removal of the tool cutting edge for every micro thin plate element Explanatory drawing about the index of the material voxel model Explanatory drawing about the estimation method of the removal amount of material voxel model Explanatory drawing of the detection method of the voxel which has interfered with the tool edge Flow chart of the cutting serialization method of the first embodiment The figure which shows the processing shape in Example 3 Explanatory drawing about the minute thin plate element in the momentary cutting force model Image of workpieces in process of cutting process using voxel model Graph showing estimation result of cutting force in the middle process of cutting Comparison graph of measurement result and estimation result of cutting force (1) Comparison graph of measurement result and estimation result of cutting force (2) Functional block diagram of cutting simulation device Functional block diagram of cutting force adaptive control system Illustration of instantaneous cutting force model of ball end mill Illustration of instantaneous cutting force model of radius end mill An explanatory view of the attitude of the radius end mill being changed obliquely Explanatory drawing about the bending of the tool Illustration of calculation model of bending deformation of tool Processing flow of calculation of deformation Comparison figure of the processing shape measured by actual processing and the processing shape predicted Explanation of interference judgment between tool and work material using conventional voxel model Explanation of interference judgment between voxel and tool cutting edge by Oktoturi expression

  Hereinafter, an example of an embodiment of the present invention will be described in detail with reference to the drawings. In addition, the scope of the present invention is not limited to the following examples and illustrated examples, and many modifications and variations are possible.

The cutting simulation method of the present invention simulates the cutting phenomenon in minute time and minute spatial resolution by performing analysis not at every feed amount per tool edge but at every minute rotation angle of the tool cutting edge.
With reference to FIG. 1, voxel removal at every minute rotation angle of the tool cutting edge in the cutting simulation method of the present invention will be described. In the cutting simulation method of the present invention, a material model in which a three-dimensional shape of a work material is expressed by a voxel model in which minute voxels are arranged is calculated voxels to be removed at every minute rotation angle of a tool cutting edge . FIGS. 1 (1) to 1 (6) are schematic views when a cutting tool having two blades is viewed from the axial direction (Z direction), and shows voxels removed by minute rotation of a tool cutting edge. Here, the workpiece model in FIG. 1 indicates voxels in the XY plane. As shown in FIG. 1 (1), after the tool cutting edge is slightly rotated and interferes with one voxel and is cut away, as shown in FIG. 1 (2), the tool cutting edge is further slightly rotated and two voxels It interferes with cutting and removing. While the tool cutting edge is slightly rotated, the tool axis of the tool cutting edge moves in the X direction according to the tool feed speed. Therefore, by moving from the position of the tool axis in FIG. 1 (1) to the position of the tool axis in FIG. 1 (2), the distance between the tool cutting edge and the work material model is reduced, causing interference The amount is increasing. In addition, as shown in FIG. 1 (3), when the tool cutting edge is further slightly rotated, the distance between the tool cutting edge and the material model is further reduced, but the cutting edge tip interferes depending on the position of the tool cutting edge at that time. Then, the voxels that can be removed by cutting are different, and they are removed by interference with one voxel. Then, as shown in FIG. 1 (4), the tool cutting edge on the opposite side of 180 ° approaches the workpiece material model as it rotates slightly further as shown in FIG. 1 (4), and as shown in FIG. When the blade interferes with the two voxels and is cut away and further minutely rotated, as shown in FIG. 1 (6), the tool edge interferes with the three voxels and is cut away. As described above, according to the cutting simulation method of the present invention, the resolution of the minute time and the minute space is determined by performing the interference determination of the voxels of the workpiece material model for each minute rotation angle of the tool cutting edge to predict the removal amount. The voxels of the work material to be cut and removed by the interference of the tool cutting edge are calculated to predict the removal amount of the work material.

Further, in the cutting simulation method of the present invention, as shown in FIG. 2, the tool is divided into minute thin plate elements along the tool axis direction, and on the line segment connecting the tool center and the tool cutting edge for each minute thin plate element. The voxels present in the tool are determined to calculate the amount of interference between the tool and the work material.
Here, when the movement amount of the tool cutting edge is larger than the voxel size, there arises a problem that the voxel to be removed is skipped, so one movement amount is made smaller than the voxel size. The minute rotation angle of the tool cutting edge is set, for example, such that the moving amount of the circumferential portion of the tool cutting edge is equal to the length of one side of the voxel used for analysis.

In this case, the rotational speed of the tool axis is Smin ⁻¹ , the tool radius (the length from the tool rotation center to the cutting edge) is R mm, and the minimum voxel size used for the workpiece model is V mm. The processing time t _step sec of is _calculated from the following equation 1.
In the cutting simulation method of the present invention, the removal amount of the minimum voxel to be removed for each rotation angle of the tool cutting edge rotated at the processing time set based on the rotation speed of the tool axis and the tool radius and the minimum voxel size is estimated. Not only simulation analysis faithful to the path of the tool edge is possible, but also analysis of machining in which the shape of the tool edge is special or where the tool posture changes non-uniformly is possible. According to the cutting simulation method of the present invention, it is possible to follow the change in the cutting state by predicting the removal amount for each processing time set based on the rotation speed of the tool axis and the tool radius and the minimum voxel size. Therefore, the removal amount of the work material can be predicted.

For example, assuming that the rotational speed of the tool axis S = 2000 (min ⁻¹ ), the tool radius R = 3 mm, and the minimum voxel size V = 0.012 mm, the processing time t _step sec per analysis step and the rotational angle θ at that time are It becomes as follows.
Processing time t _step = V / (S × R × 2π) / 60
= 0.012 / (3 x 2000 x 2 pi) / 60 =
= 0.00006 / π = 0.0000191 (sec)
Rotation angle θ = 360 ° × _2000/60 × Processing time t _step
= 360 × 2000/60 × 0.0000191 = 0.229 °

As described above, in the conventional cutting simulation method using the voxel model, the total amount of computer memory required to improve the simulation accuracy and the speedup of the interference determination between a large number of voxels and the tool cutting edge Is a big problem. In addition, in the conventional cutting simulation method, the Octotry representation is introduced into the voxel model to reduce the memory consumption, but in the Octotlie representation, one voxel is divided into eight equal parts to form small voxels, which are divided into multiple layers. Since a fine shape is expressed by using the above, it is a problem to shorten the calculation time in order to express a large work material with high accuracy and to simulate a practical processing shape.
As shown in FIG. 3, in the cutting simulation method of the present invention, a voxel model is represented from the beginning with a minimum voxel of a minimum size from the beginning, and each minimum voxel is indexed and regularly aligned. This makes it possible to specify the voxel index from the position coordinates. For example, if the length of one side of the smallest voxel of the smallest size is V _L μm and n voxels are aligned in the x-axis direction, the index I of the voxel corresponding to the position of x _i μm, y _i μm Can be obtained from the following equation 2.

  When detecting a voxel interfering with the tool cutting edge, as shown in FIG. 4 (1), the tool cutting edge vector is divided by one side length of the minimum voxel, and the tool rotation center of the divided element The index of the interfering voxel is calculated from the coordinates of the position close to the above according to Equation 2 above. As shown in FIG. 4 (2), a voxel corresponding to an index obtained by each divided element can be detected as a voxel to be removed. This eliminates the need for repetitive processing for scanning all the minimum voxels of the workpiece material model to search for interfering voxels, thereby reducing the processing time.

However, when the material model is initially represented by the smallest voxels, there is a problem that the number of arrays of variables corresponding to the voxels becomes enormous. For example, in the case where a cube-shaped material having a side of 1 m is represented by voxels having a side length of 1 μm, 10 ¹⁸ arrays are required. However, in the case where the number of sequences that can be secured by one variable is limited to 10 ⁹ , it is impossible to represent a voxel model of a work material that requires 10 ¹⁸ sequences due to the restrictions of the computer program. It is possible.

Therefore, the above problem is addressed by expressing the material model with voxel sizes of two layers. For example, a voxel model of a work material can be expressed in an array of 10 ⁹ by expressing a cube-shaped work material having a side of 1 m with voxels (first voxels) having a side length of 1 mm. . Then, it is also possible to perform analysis by expressing the first voxel interfering with the tool cutting edge with a voxel (second voxel) having a side length of 1 μm.
In the detection of the voxel interfering with the tool cutting edge, as shown in FIG. 5, first, the first voxel interfering with the tool cutting edge vector is detected, and then the detected first voxel and the tool are detected. The point of intersection with the cutting edge vector is calculated. Then, the line segment connecting the calculated intersection points is divided by the length of one side of the second voxel, and the method shown in the above equation 2 is performed, the interference determination of the minimum voxel of the material model is performed, and the removal target is Detect voxels.
At that time, since only the position of the first voxel is offset, the target of removal is the same as the equation 2 by subtracting the coordinates of the origin of the first voxel from the position coordinates of each element obtained by dividing the tool cutting edge vector. Calculate the voxel index of Here, the length of one side of the first voxel and the second voxel can be set arbitrarily, and a value suitable for the size of the work material and the accuracy (resolution) of the simulation can be set. it can.

  FIG. 6 shows an example of the processing flow of the cutting simulation method. In the cutting simulation method, first, the material model is represented by the voxel model of the minimum voxel, and an index is given to each minimum voxel in correspondence with the arrangement position in the voxel model. In addition, the shape of the tool cutting edge is represented by a three-dimensional point group. The tool cutting edge is rotated by the rotation angle at which the movement amount of the tool cutting tip becomes the distance of one side of the minimum voxel. And as shown in FIG. 4 (2), the index of the minimum voxel which overlaps with the straight line which connects a tool central axis and a tool cutting edge is computed, and the removal amount of the minimum voxel of a material model is predicted. Since the tool moves at the feed speed while rotating, the rotation axis of the tool cutting edge is moved according to the feed speed. This is repeated until the end point of the tool path is reached.

  In order to confirm the effectiveness of the cutting simulation method of the present invention, the processing time was compared with that of the cutting simulation method in which interference determination is performed by using an Octoli expression using a tool path for actual processing. In the cutting simulation method of the present invention, the work material is set to the minimum voxel size from the beginning (hereinafter referred to as the index method), and on the other hand, in the cutting simulation method for performing interference determination by the Octoli representation, the initial voxel The size was set to 1 mm, and analysis was repeated until the voxel size reached the minimum (hereinafter referred to as the Octree method), and the processing times of the respective cutting simulations were compared.

In the index method, the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point cloud at minute intervals, the work material is set to the minimum voxel size from the beginning, and each voxel is assigned corresponding to the placement position in the voxel model. A unique index is given, and for each minute rotation angle of the tool cutting edge, an index of a voxel overlapping with a straight line group connecting the tool center axis and the point cloud of the shape of the tool cutting edge is calculated to perform interference determination.
On the other hand, in the Octree method, the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point group of minute intervals, the work material is initially set to the initial voxel size, and a unique index is not given to each voxel For each minute rotation angle of the cutting edge, the interference judgment of the voxel overlapping with the straight line group connecting the tool center axis and the point cloud of the shape of the cutting edge is performed, and each side of the voxel interfering with the cutting edge The process of dividing into 8 by 2 division and dividing into a voxel whose length of one side of the cube is 1/2 before division is repeated until the voxel size becomes the minimum voxel size.

  The conditions of the cutting simulation used for comparison are as follows. The cutting simulation is cutting with 3-axis control processing, and the tool used for cutting is a square end mill with a diameter of 5 mm, and a distance of 10 mm per 10 mm to a 10 × 10 × 10 mm cube work material It is a straight line processed only one pass. Moreover, the cutting direction was performed by the up-cut which a tool passes along the right side with respect to a cut material. Detailed cutting conditions are shown in Table 1 below.

  Octree method and index method in the case of initial voxel size 1 mm, minimum voxel size 250 μm, 125 μm, 62.5 μm, 31.25 μm, 15.625 μm, and 7.8125 μm from 2 layers to 7 layers The processing time of each was calculated. The calculation results are shown in Table 2 below. Here, the specification of the CPU of the computer used is Intel Xeon (registered trademark) 3.5 GHz (the number of logical processors: 8 cores).

According to the results of Table 2 above, the processing time of the Octree method was slightly faster than the analysis calculation of the index method up to the minimum voxel size of 15.625 μm of the 6 levels of the initial voxel size. At 8125 μm, the Octree method takes about three times longer processing time than the index method. If the number of layers is further increased and cutting simulation is performed with a small voxel size, it can be inferred that the difference in processing time becomes large. That is, as in the case where the initial voxel size is 1 mm and the minimum voxel size is 5 μm, if the number of divisions on one side is 200 (> 2 ⁷ = 128), comparison in 7 layers (= 1/2 ⁷ ) Since the index method is faster in processing time than the Octree method, the index method is advantageous because the processing time is longer than that of the Octree method.

In the cutting simulation method of the present invention, cutting simulation is performed using a voxel model consisting of voxels of a second minimum voxel size obtained by dividing voxel sizes into two layers and further dividing voxels of a first minimum voxel size. The relationship between accuracy (resolution) and calculation time will be described. Specifically, the result of performing simulation in 3-axis control processing using a tool path for actual processing is shown, and the relationship between accuracy (resolution) and calculation time of the cutting simulation method of the present invention will be described.
In the simulation in 3-axis control machining, the tools used for cutting are a square end mill (rough machining) and a ball end mill (finish machining) with a diameter of 4 mm, and the material shape before machining is 50 × 50. It is a rectangular solid of × 30 mm, and the processing shape is a dome shape (height of dome: 10 mm).

  The length of one side of the first voxel is 5 mm, and the length of one side of the second voxel is changed to 200 μm, 100 μm, and 50 μm, and serial calculation by one computer and parallel processing by two computers The processing time with the calculation was compared. The specification of the CPU of the used computer is Intel Xeon (registered trademark) 3.5 GHz (the number of logical processors: 8 cores). FIG. 7 shows a processed shape obtained when the length of one side of the second voxel is 100 μm. Table 3 below shows the total number of analysis steps, the processing time, and the processing time per analysis step when the length of one side (minimum voxel size) of the second voxel is changed.

  According to the results in Table 3 above, the processing time was shorter in parallel calculation than in serial calculation by a computer regardless of the length of one side of the second voxel. This is because, in the cutting simulation method of the present invention, the processing time per iteration of detecting the voxels that interfere with the tool cutting edge is longer than the overhead for parallel computing of the computer, and parallel computing of the computer is performed. Indicates that the processing time is short.

Further, according to the results of Table 1, when the length of one side of the second voxel (minimum voxel size) is 1⁄2, the total number of analysis steps is doubled. This is because the minute rotation angle of the tool cutting edge is determined such that the amount of movement of the cutting edge at the tool outer peripheral portion becomes equal to the length of one side of the second voxel. When the length (minimum voxel size) of one side of the second voxel is 1⁄2, the processing time per analysis step is doubled. This analysis is performed by dividing the tool cutting edge vector in the micro thin plate element of the tool by the length of one side of the second voxel when detecting the voxel in which the tool cutting edge interferes with the work material Therefore, when the length (minimum voxel size) of one side of the second voxel is 1⁄2, the number of divisions of the tool cutting edge vector is doubled.
That is, when the length (minimum voxel size) of one side of the second voxel is 1⁄2, the number of analysis steps is doubled, and the processing time per one analysis step is doubled. The time is quadrupled.

In the cutting force adaptive control method of the present invention, calculation of predicting the cutting force from the interference amount (actual cutting thickness) using the above-described cutting simulation method of the present invention for analysis of the interference amount of the tool cutting edge and the work material The conventional instantaneous cutting force model is used for. In the instantaneous cutting force model, as shown in FIG. 8, the micro cutting force is calculated for each thin plate element by dividing it into small thin plate elements along the tool axis z at the center of tool rotation. The micro-cutting forces are added while taking into consideration the direction of the force to determine the cutting force acting on the tool. It is assumed that the micro cutting force acts on the cutting edge of each thin plate element, and the processing in the plane (in the xy plane) perpendicular to the cutting edge is approximated in a two-dimensional cutting state. The tangential component dF _t , the radial component dF _r and the axial component dF _a of the cutting force acting on the respective thin plate elements are expressed by the following equations 3 to 5.

Here, K _te , K _re , K _ae , K _tc , K _rc and K _ac are cutting coefficients obtained from preliminary experiments, h (θ, z) is the actual cutting thickness in the tool radial direction, and dz is the tool It is the thickness of an axially divided thin sheet metal element. That is, if the actual cutting thickness h (θ, z) in the tool radial direction is obtained, the cutting force can be calculated. z of h (θ, z) represents the distance from the tip of the tool along the tool axis direction, that is, the tool position in the micro thin plate element. The θ of h (θ, z) represents the rotation angle of a straight line connecting the tip of the tool cutting edge and the tool axis. The tool shown in FIG. 8 is a square end mill having four blades, which can calculate the cutting force applied to each cutting blade and obtain the cutting torque applied to the entire tool.
The number of removal target voxels in the tool cutting edge vector in each thin thin plate element is calculated by the cutting simulation method of the present invention, but the interference amount in each axial direction (each axial component of actual cutting thickness) is the removal target Calculated from the product of the number of voxels and the length of one side of the voxel. The actual incision thickness h (θ, z) can be expressed by the following equation 6 using the x-direction component h _x , the y-direction component h _y , and the z-direction component h _z . Here, h _x , h _y and h _z are values in the x, y and z directions of the absolute coordinate system, respectively.

  In order to verify the effectiveness of the cutting force adaptive control method of the present invention, cutting experiments using a square end mill were performed, and measurement results of the cutting force were compared with simulation results. The cutting conditions and the cutting force simulation conditions are shown in Table 4 below. In the processing experiment, cutting was performed using a vertical machining center, and the cutting force during processing was measured using a quartz piezoelectric multi-component dynamometer (manufactured by Nippon Kistler; KISLER 9257B).

  The cutting coefficients determined in the preliminary experiment are shown in Table 5 below. FIG. 9 shows images of workpiece material models during processes A to D during cutting using the voxel model in the cutting force adaptive control method of the present invention, and FIG. 10 shows the estimation results of those cutting forces.

  The images A to D in FIGS. 9 and 10 and the estimation results of the cutting force show the relationship between the work material in the process of machining and the tool cutting edge vector, and it is not an analysis for each feed amount per tool edge, It shows that analysis is performed at every minute rotation angle of the tool cutting edge. Static deformation and dynamic deformation of the tool cutting edge during processing can also be considered.

FIGS. 11 and 12 are graphs showing measurement results and estimation results of cutting forces at tool feed speeds of 400 mm / min and 200 mm / min, respectively. FIG. 11 is a graph of measurement results and estimation results of cutting force at a tool feed speed of 400 mm / min. FIG. 12 is a graph of measurement results and estimation results of cutting force at a tool feed speed of 200 mm / min. In each graph, the x-direction component of the cutting force is divided into dF _x , the y-direction component is divided into dF _y , and the z-direction component is divided into dF _z . In each figure, F _x (Meas.), F _y (Meas.) And F _z (Meas.) Plotted with dotted lines are F _x (Esti.) And F _y (Measured results of cutting force plotted with solid lines) Esti.) And F _z (Esti.) Show the estimation results of the cutting force.
In each result, the waveforms of the measurement result and the estimation result were in good agreement. From this result, it can be confirmed that the prediction of the cutting force using the cutting force adaptive control method of the present invention is performed with high accuracy.

The cutting simulation device of the present invention will be described in detail. FIG. 13 shows an example of a functional block diagram of the cutting simulation device.
The cutting simulator device 1 includes an interference determination unit 14 for inputting work material data 11, tool cutting edge shape data 12, position data 13 of work material and tool cutting edge, and these data 11 to 13, and removal amount The prediction unit 15 is configured. Specifically, the cutting simulator device of the present invention is configured by a computer, data 11 to 13 are stored in the memory, and programs for causing the computer to function as the interference determination unit 14 and the removal amount prediction unit 15 are loaded.
The material to be cut 11 is data represented by a voxel model in which small voxels of the material to be cut are arranged, and a unique index is given to each voxel in correspondence with the arrangement position in the voxel model. The tool cutting edge shape data 12 is data in which the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point group. The interference determination unit 14 uses the data 11 to 13 and, for each minute rotation angle of the tool edge, an index of voxels overlapping with a straight line group connecting the tool center axis and the three-dimensional point group of the shape of the tool edge Calculate and perform interference determination. The removal amount prediction unit 15 predicts the removal amount of the work material with the resolution of the minute time and the minute space based on the number of voxels and the voxel size calculated by the interference determination unit 14. Thus, by accurately predicting the removal amount, it is possible to accurately reproduce the shape surface by the processing process.
Further, in the cutting simulation device of the present invention, as indicated by a dotted line in FIG. 13, the cutting force prediction unit 16 can be further provided, and the removal amount of voxels predicted by the removal amount prediction unit 15 can be The cutting force can also be estimated. As a result, the cutting force of the tool in the cutting process can be accurately predicted, and the rotational speed and feed rate of the tool can be adjusted so that the tool is not overloaded.

The cutting force adaptive control system of the present invention will be described in detail. FIG. 14 shows a functional block diagram of the cutting force adaptive control system of the present invention.
As shown in FIG. 14, the cutting force adaptive control system has a tool path generating unit that generates a tool path of a machine tool in real time, is controlled by a cutting process parameter, and performs cutting while cutting on the machine tool This system is provided with a sequential command unit that dynamically changes commands and outputs them one by one, and comprises the following (a) to (f): Regenerates the tool path according to cutting parameters and moves the cutting command To change

(A) Work material data in which the work material is represented by a voxel model in which minute voxels are arranged, and in which each voxel has a unique index corresponding to the arrangement position in the voxel model (b) tool of a machine tool Tool cutting edge shape data in which the shape of the cutting edge is represented by a three-dimensional point group (c) cutting material data, tool cutting edge shape data, and position data of the cutting material and the cutting edge Interference determination unit (d) Interference determination that performs interference determination by calculating, for each minute rotation angle of the cutting edge, an index of voxels that overlap the straight line group connecting the tool center axis and the three-dimensional point group of the shape of the tool cutting edge The removal amount prediction unit (e) predicts the removal amount of the work material with the resolution of minute time and minute space based on the number of voxels and the voxel size calculated in the unit (e) Based on the amount of material removed , Depending on the cutting torque calculated from the cutting force prediction unit for predicting the cutting force of the tool (f) the predicted cutting force, the cutting parameter changing section for dynamically changing the cutting parameters

When the cutting force adaptive control system inputs shape data (CAD data) of a product, a machining process is formulated based on the CAD data, and a tool path generation unit generates a tool path of the machine tool. The tool path generation unit corrects the tool path based on the cutting force prediction of the cutting force prediction unit. The sequential command unit sends command data such as the tool feed speed to the NC machine.
In the cutting parameter change unit, for example, when the cutting force or cutting torque exceeds a threshold at which continuous processing is determined to be dangerous, the tool feed rate is set to 0 (zero) to stop the tool, or the cutting force or cutting torque is If it is approximately 0 (zero), change the tool feed rate to the maximum value of the allowable range.
In addition, in the cutting process parameter changing unit, adaptive control can be performed according to the amount of tool deformation calculated from the cutting force. For example, when an error occurs in the machined surface of the work material due to the bending of the tool, the parameters of the amount of cutting and the tilt of the tool are changed and controlled so as to cancel the deformation amount of the tool bending, and the machined surface Errors can be reduced to obtain the intended processing surface.

The cutting force adaptive control system does not measure the cutting force acting on the tool of the NC machine, but expresses the work material by a voxel model in which minute voxels are arranged, and determines the interference in the cutting sequence device In this part, for each minute rotation angle of the tool cutting edge, the index of voxels overlapping the straight line group connecting the tool center axis and the three-dimensional point group of the shape of the tool cutting edge is calculated to perform interference determination, and removal amount prediction In the unit, the removal amount of the work material is predicted by the resolution of minute time and minute space based on the number of voxels and the voxel size calculated by the interference determination unit. Then, the cutting force prediction unit predicts the cutting force of the tool based on the predicted removal amount of the work material for each minute rotation angle of the tool cutting edge. The cutting processing parameter changing unit dynamically changes the cutting processing parameter according to the cutting torque calculated from the predicted cutting force, and performs adaptive control based on the cutting force prediction result.
In the cutting force adaptive control system, cutting is performed not by a command prepared in advance but by generating a tool path in real time and sequentially changing a command dynamically during processing.

In this embodiment, a cutting simulation method in the case of using a ball end mill as a tool will be described. FIG. 15 shows an instantaneous cutting force model of a ball end mill.
The ball end mill, as shown in FIG. 15 (1), differs from the square end mill in that the distance to the tip of the tool cutting edge differs depending on the position in the tool axial direction (see elements A and B). As shown in FIG. 15 (2), the tool is divided into micro thin plate elements along the tool axis, and the micro cutting force is calculated for each individual element. Then, the micro-cutting forces are added while taking into consideration the direction of the force, and the cutting force acting on the tool is determined. It is assumed that the micro cutting force acts on the cutting edge of each thin plate element, and processing in a plane perpendicular to the cutting edge is approximated in a two-dimensional cutting state.
In the case of a ball end mill, the tangential component dF _t , radial component dF _r and axial component dF _a of the cutting force acting on the cutting edge of each thin plate element are expressed by the following equations 7 to 9. Here, dS represents the length of the cutting edge along the spherical surface of the micro thin plate element, and db represents the thickness of the thin thin plate element divided in the tool axis direction. The θ of h (θ, z) represents the rotation angle of a straight line connecting the tip of the tool cutting edge and the tool axis.

Here, K _te , K _re , K _ae , K _tc , K _rc and K _ac are cutting coefficients obtained from preliminary experiments, h (θ, z) is the actual cutting thickness in the tool radial direction, and dz is the tool It is the thickness of an axially divided thin sheet metal element. Once the actual cutting thickness h (θ, z) in the tool radial direction is determined, the cutting force can be calculated. z of h (θ, z) represents the distance from the tip of the tool along the tool axis direction, that is, the tool position in the micro thin plate element.
The number of voxels to be removed in the tool cutting edge vector of each thin thin plate element is detected by the cutting simulation method of the present invention. The amount of interference in each axial direction (each axial component of the actual cut thickness) is calculated from the product of the number of voxels to be removed and the length of one side of the voxel. The actual incision thickness h (θ, z) can be expressed by the above-mentioned equation 6 using the x-direction component h _x , the y-direction component h _y and the z-direction component h _z .

In this embodiment, a cutting simulation method in the case of using a radius end mill as a tool will be described. In the case of a radius end mill, as shown in FIG. 16 (1), by applying the instantaneous cutting force model of the ball end mill to the corner of the cutting edge and applying the instantaneous cutting force model of the square end mill to the other cutting edges , Can predict the cutting force.
Also, in the case of a radius end mill, like the ball end mill and the square end mill, using the instantaneous cutting force model shown in FIG. 16 (2), for each minute thin plate element, the minute of each cutting edge (four in the case of the figure) For each rotation angle, the interference determination with the material model represented by the voxel model of the minimum voxel is performed, the removal amount of the minimum voxel is predicted, and the cutting force is estimated.
As shown in FIG. 16 (3), even when cutting by tilting the tool posture of the radius end mill, the shape of the tool cutting edge is a three-dimensional point group of the tool coordinate system (xa, ya, za) On the other hand, the voxel model of the work material is represented by the minimum voxel of the absolute coordinate system (x, y, z), and the coordinate systems are made to correspond to each other by using the inclination angle θ of the tool posture. For example, when the tool axis is inclined by an angle θ in the x-axis direction from the z-axis in the absolute coordinate system (x, y, z), the tool radius R is R · cos θ in the x-axis direction, in the y-axis direction In the R and z axis directions, interference determination between the tool tip and the voxel is performed as R sin θ.

In the present embodiment, it will be described that the cutting simulation method can be implemented even when the tool of the radius end mill is used obliquely.
As shown in FIG. 17, in the case where the radius end mill is inclined such that θ becomes 15 °, 30 °, 45 ° and 60 ° in the ZX plane, and the attitude of the radius end mill is changed, in the X direction When cutting the work material, the estimation accuracy of the cutting force for each small rotation angle of the cutting edge was confirmed. The estimation result is in good agreement with the measured cutting force waveform, and the present invention is a complex tool shape such as a radius end mill and the cutting is performed with the tool posture inclined at an angle. It has been confirmed that the cutting simulation method is useful.

The case where the shape of the tool cutting edge deforms statically or dynamically during cutting will be described.
In the cutting simulation method of the present invention, the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point group of minute intervals, and the tool central axis and the point group of the cutting edge are The index of voxels overlapping with the connecting straight line group is calculated to perform interference determination, and the removal amount of the work material is predicted.
Therefore, when the shape of the tool cutting edge is deformed statically or dynamically during cutting, the error due to the deformation is eliminated by changing the above three-dimensional point group according to the deformation, and the object is removed The removal amount of the cutting material can be predicted accurately.

  For example, when the cutting edge is deformed due to frictional heat during the cutting process, shape data after deformation of the cutting edge due to temperature is made into data beforehand, and the temperature of the cutting edge is measured by a temperature sensor, The temperature of the cutting edge is estimated from the cutting amount and cutting time of the work material, etc., and the change over time from the start of cutting is fed back to the three-dimensional point cloud of minute intervals regarding the cutting edge shape, and the shape is aged The change is reflected, the index of the voxel overlapping with the straight line group connecting the tool center axis and the point group of the cutting edge is calculated for every minute rotation angle of the tool cutting edge, the interference judgment is performed, and the removal amount of the work material Predict.

In addition to this, using a device that can measure the tool length and tool diameter during high-speed rotation of the tool, such as a tool position measurement device using a camera, measure the tool length and tool diameter during the cutting process and tool sway. Index of voxels that overlap with the straight line group connecting the tool center axis and the point cloud of the cutting edge for each minute rotation angle of the tool edge, reflecting the time-dependent change of length and tool diameter and the time variation of shaking of the tool It calculates and performs interference determination, and predicts the removal amount of the work material.
Every time the tool is attached to the machine tool, before the work on the work material, every time the work on the work material is finished, or every time the work of a certain number of work materials is processed, the tool length, the tool at each timing Measure the diameter, tool center position, etc. In that case, if the tool length, the tool diameter, and the tool center position are different than expected, the machining of the work material will be greatly affected. In the cutting simulation method of the present invention, the assumed three-dimensional point cloud of the tool cutting edge is different, which greatly affects the simulation result. In such a case, more accurate simulation can be performed by changing the position of the three-dimensional point cloud of the tool cutting edge according to the amount of deviation from the estimated value determined by measurement.

  Also, deformation of the tool cutting edge is also caused by bending of the tool that occurs during cutting. The bending of the tool means that the tool is elastically deformed by the machining force, and in the cutting process, the shape is deformed by the cutting force acting on the tool cutting edge. In cutting, the deformation of the central axis of the rotating tool is also applicable. The machining error affects not only the deformation due to the bending of the tool but also the displacement of the machine tool or the workpiece, but if the rigidity of the tool itself is smaller than the rigidity of the workpiece or the machine tool, the bending of the tool It is the main cause. In the end milling process, a fluctuation of the tool center axis occurs under the influence of the three cutting force components that fluctuate due to the intermittent cutting, so that a waveform processing error occurs with respect to the ideal shape of the processing surface.

  In end milling, the tool is bent by receiving a stress 23 in the direction opposite to the cutting direction 22 from a work material (not shown) with respect to the feeding direction (cutting direction 22) of the tool 21. As shown in FIG. 18, the deflection F of the tool is 16 times when the tool diameter D is 0.5 times, and 8 times when the tool length L (the protrusion length of the tool) is twice It is known. For this reason, generally, a tool with a thick and short shape is selected, but in complex shape processing, such a tool can not always be selected, and therefore, a processing error due to bending of the tool is small It exists. In the cutting simulation of the present invention, the error due to deformation is eliminated by changing the three-dimensional point group of the tool cutting edge according to the deformation of the tool at every minute rotation angle of the tool cutting edge, and the work material The amount of removal of can be accurately predicted.

About the bending deformation of the tool in end milling, as shown to FIG. 19 (1), the example calculated as a deformation of the cantilever which a distribution load concerning a tool acts on is demonstrated. Deformation amount in each micro sheet metal member, as shown in the figure, if load is applied to P ₁ to P ₃ to the tool deformation amount of v ₁ can be calculated by the following equation 10. In addition, as shown in FIG. 19 (2), the static deformation of the tool holder can be determined from the rigidity k experimentally obtained in the load displacement test and the horizontal component (radial component dF _r and tangent line of the cutting force generated during processing) It is calculated from the directional component dF _t ). In the following equation 10, a ₁ , a ₂ and a ₃ are the distances from the tool tip of the point at which the loads P ₁ , P ₂ and P ₃ act respectively, and b ₁ , b ₂ and b ₃ are the loads respectively It is the distance from the tool fulcrum of the point where P ₁ , P ₂ and P ₃ act. E is the Young's modulus of the material of the tool.

When considering the static deformation of the tool, the actual depth of cut changes depending on the amount of deformation of the tool and the tool holder. For this reason, the amount of deformation is obtained from the cutting force calculated ignoring these amounts of deformation, and the change in the actual cutting thickness accompanying this amount of deformation is fed back to recalculate the cutting force. The amount of deformation of the tool and the tool holder by repeatedly calculating until the cutting force becomes equal, taking into account the amount of deformation calculated from the actual cutting thickness in consideration of the amount of deformation and the amount of deformation obtained from the calculated cutting force. Can be determined. The processing flow of the iterative calculation is shown in FIG.
First, the amount of deformation is ignored to calculate the cutting force F, and the amount of deformation δ due to the cutting force F is calculated. Next, the cutting force F 'calculated by the actual cutting thickness in consideration of the deformation amount δ is calculated, and the deformation amount δ' obtained from the cutting force F 'is calculated. If the deformation amount δ is smaller than the deformation amount δ ′, the cutting force F is calculated excessively, so the cutting force F is reduced and recalculation is performed. On the contrary, when the deformation amount δ is larger than the deformation amount δ ′, the cutting force F is under-calculated, so the cutting force F is increased and re-calculated. The calculation is repeated until the deformation amount δ and the deformation amount δ ′ become substantially equal to determine the deformation amounts of the tool and the tool holder.

  The bending deformation of the tool in end milling is calculated as the deformation of the above-mentioned cantilever beam, and the cutting simulation method of the present invention predicts the removal amount of the voxel overlapping the three-dimensional point group of the tool cutting edge and cuts the cutting force. Calculate the amount of deformation due to the cutting force, and finally determine the amount of deformation of the cutting edge by the process of iterative calculation shown in the flow of FIG. 20, and change the three-dimensional point cloud of the cutting edge Estimate the amount of removal. The effectiveness of the cutting simulation method of the present invention was confirmed by comparing the processing shape predicted by simulation and the processing shape measured by actual processing. The cutting conditions and the cutting force simulation conditions are shown in Table 6 below.

  The comparison figure of the processing shape measured by FIG. 21 by actual processing and the processing shape estimated is shown. FIG. 21 (1) shows the measured processing shape, and FIG. 21 (2) shows the processing shape predicted by the cutting simulation method of the present invention. In the actual machining, the tool and the tool holder were deformed with respect to the cutting of 6.0 mm in the radial direction of the end mill tool, resulting in a processing error, and the measured shape of the cutting was a cut of 5.951 mm. The cutting shape predicted in the cutting simulation is predicted to be a 5.950 mm notch, and it was confirmed that the state of the processing error caused by the deformation due to the tool deflection can be expressed with high accuracy.

  The present invention is useful for a machine tool used in a cutting process and a machine tool that performs autonomous machining.

1 cutting simulation device 2 material model 3 tool axis 4 tool cutting edge 5 removed voxel 6 thin plate element 7 tool cutting edge tip 11 cutting material data 12 tool cutting edge shape data 13 position of cutting material and tool cutting edge Data 14 Interference determination unit 15 Removal amount prediction unit 16 Cutting force prediction unit 21 Tool 22 Cutting direction 23 Stress

Claims (14)

In a cutting simulation method for expressing a work material by a voxel model in which minute voxels are arranged,
Express the shape of the cutting edge of the machine tool with a three-dimensional point cloud with minute intervals,
Assigning a unique index to each voxel corresponding to the placement position in the voxel model,
For each minute rotation angle of the tool cutting edge, an index of voxels overlapping with a straight line group connecting a tool center axis and the point group is calculated to perform interference determination, and the resolution of the work material in minute time and resolution of minute space A cutting simulation method characterized by predicting a removal amount.   The cutting simulation method according to claim 1, wherein the minute rotation angle is a rotation angle at which an amount of movement of one of the straight line group is equal to or less than a diameter of a sphere circumscribing the voxel of the voxel model.   The interference determination is characterized by calculating and determining an index of voxels overlapping the straight line group connecting the tool center axis and the point group, for each thin thin plate element divided in the plane orthogonal to the rotation axis of the tool. The cutting simulation method according to claim 1 or 2.   The removal amount of the work material is calculated on the basis of the number of voxels obtained by adding the number of voxels of the index calculated by the interference determination in each of the thin thin plate elements and the voxel size. Cutting simulation method.   The said voxel model is represented by the voxel of the minimum voxel size, The cutting simulation method in any one of the Claims 1-4 characterized by the above-mentioned.   The voxel model is represented by a first voxel of a first minimum voxel size, and the first voxel of the index calculated by the interference determination is further represented by a second voxel of a second minimum voxel size The cutting simulation method according to any one of claims 1 to 4, wherein each second voxel is assigned a unique index corresponding to the arrangement position. When the shape of the tool cutting edge is deformed statically or dynamically during cutting,
The said point group is changed according to the said deformation | transformation, The cutting simulation method in any one of the Claims 1-6 characterized by the above-mentioned.   The cutting force or the cutting torque of the tool is further predicted on the basis of the predicted removal amount of the work material for each minute rotation angle of the tool cutting edge. Cutting simulation method described. A cutting simulation method according to claim 8 is used to predict the cutting force or cutting torque of a tool of a machine tool,
A cutting force adaptive control method comprising changing a machining command of the machine tool according to the predicted cutting force or cutting torque and regenerating a tool path. A cutting simulation method according to claim 8 is used to predict the cutting force or cutting torque of a tool of a machine tool,
A cutting force adaptive control method comprising: increasing or decreasing at least one of a tool feed speed and a tool rotation speed of the machine tool according to a predicted cutting force or cutting torque. Material to be cut is represented by a voxel model in which minute voxels are arranged, and material data to which a unique index is given to each voxel corresponding to the arrangement position in the voxel model,
Tool cutting edge shape data in which the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point group;
A tool center axis and the point group at every minute rotation angle of the tool cutting edge, using the work material data, the tool cutting edge shape data, and the position data of the work material and the tool cutting edge An interference determination unit that calculates an index of voxels overlapping with a straight line group connecting
A removal amount prediction unit that predicts the removal amount of the work material with a minute time and a minute space resolution based on the number of voxels and the voxel size calculated by the interference determination unit;
Cutting simulator device characterized by having.   The apparatus according to claim 11, further comprising a cutting force prediction unit that predicts the cutting force of the tool based on the predicted removal amount of the work material for each minute rotation angle of the tool cutting edge. Cutting simulator device. A cutting simulator device according to claim 11 or 12 is configured by a computer and is a program installed in the device,
A cutting simulator program for causing a computer to function as the interference determination unit and the removal amount prediction unit. It has a tool path generation unit that generates the tool path of the machine tool in real time, is controlled by cutting parameters, and sequentially changes the cutting command dynamically to the machine tool during cutting and sequentially outputs An adaptive control system having a control unit,
Material to be cut is represented by a voxel model in which minute voxels are arranged, and material data to which a unique index is given to each voxel corresponding to the arrangement position in the voxel model,
Tool cutting edge shape data in which the shape of the tool cutting edge of the machine tool is represented by a three-dimensional point group;
A tool center axis and the point group at every minute rotation angle of the tool cutting edge, using the work material data, the tool cutting edge shape data, and the position data of the work material and the tool cutting edge An interference determination unit that calculates an index of voxels overlapping with a straight line group connecting
A removal amount prediction unit that predicts the removal amount of the work material with a minute time and a minute space resolution based on the number of voxels and the voxel size calculated by the interference determination unit;
A cutting force prediction unit that predicts the cutting force of the tool based on the predicted removal amount of the work material for each minute rotation angle of the tool cutting edge;
A cutting parameter changing unit that dynamically changes the cutting parameters according to the cutting torque calculated from the predicted cutting force,
A cutting force adaptive control system comprising: regenerating the tool path according to the cutting parameters; and dynamically changing the cutting command.