An ultra-precision machining method

Abstract

The application discloses an ultra-precision machining method, which comprises the following steps: firstly, determining the total material removal amount according to a machining product and a blank, and performing rough machining on the blank to complete the material removal amount of the rough machining; after the rough machining, an existing machining error is used to establish an ultra-precision machining error prediction model, and the semi-finishing error is predicted; then, the influence of the semi-finishing error is considered, the ultra-precision machining error prediction model is re-established, and finally, the finishing process planning is performed. The ultra-precision machining method considers the influence of the semi-finishing error on the finishing, re-establishes the ultra-precision machining error prediction model, integrates and optimizes the process parameters of the semi-finishing and the finishing, and further improves the machining precision of the ultra-precision machining without reducing the machining efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of machining, in particular to a super-precision machining method. BACKGROUND

[0002] In the field of super-precision machining, in order to improve machining efficiency, the machining steps are divided into rough machining, semi-finish machining and finish machining, and the main process is as shown in Figure 1 It is generally believed that the final precision of the machined surface is determined by finish machining, so the process planning of semi-finish machining only considers machining efficiency, i.e. a large amount of material removal.

[0003] For process planning of finish machining, a machining precision prediction model is usually established by analyzing the influencing factors of surface quality in finish machining, and then the process parameters of finish machining, such as spindle speed and feed speed in super-precision turning, spindle speed, feed speed and cutting pitch in super-precision milling, are optimized to obtain products meeting the precision requirements. In existing super-precision machining error prediction models, only the tools used in finish machining, machining parameters and material properties of the workpiece are considered, and the process planning of finish machining only considers the influence of various process parameters in finish machining on machining precision on the premise that the surface obtained by semi-finish machining is a smooth surface. The existing technology ignores the fact that the machined surface of finish machining is left by semi-finish machining and also has surface roughness and shape error, and the error and the machining parameters of finish machining belong to the micron level and will also affect the machining quality of finish machining.

[0004] Therefore, how to change the current situation that the accumulation of semi-finish machining and finish machining errors affects the final machining precision in the super-precision machining process has become a problem to be solved by those skilled in the art. SUMMARY

[0005] The purpose of the present application is to provide a super-precision machining method to solve the problems existing in the prior art and improve machining precision.

[0006] To achieve the above purpose, the present application provides the following scheme: the present application provides a super-precision machining method, comprising the following steps:

[0007] Step one, determining the total material removal amount according to the machining product and the blank;

[0008] Step two, rough machining is performed to complete the material removal amount of rough machining;

[0009] Step three, using existing machining errors, establishing a super-precision machining error prediction model and predicting semi-finish machining errors;

[0010] Step four, considering the influence of semi-finish machining errors, re-establishing a super-precision machining error prediction model;

[0011] Step five, carry out the finishing process planning.

[0012] Preferably, in step one, according to the geometry of the blank, calculate the total material removal volume V all ; in step two, carry out the roughing process planning, complete the material removal volume V r .

[0013] In step three, the precision requirement of the product is R r , and the ultra-precision machining error prediction model R f =f1(T f ,M f ) is established using the existing machining error.

[0014]

[0015] Wherein, f f is the feed amount of finishing; r ε,f is the tool nose radius of the tool used for finishing.

[0016] Set R f R r , carry out the preliminary planning of the finishing process, and calculate the material removal volume Vf of finishing: V f =f2(T f ,M f ), wherein T f is the tool of finishing, and M f is the machining parameter of finishing.

[0017] Preferably, calculate the material removal volume V s of semi-finishing: V s =V all -V r -V f .

[0018] Preferably, carry out the semi-finishing process planning, and determine the tool T s and the machining parameter M s of semi-finishing.

[0019] Based on the existing ultra-precision machining quality and the ultra-precision machining error prediction model R f =f1(T f ,M f ), predict the error R s =f1(T s ,M s ) of semi-finishing.

[0020] Preferably, in step four, the semi-finished surface is discretized into i tool positions, and the instantaneous cutting thickness t of the finishing process based on the influence of semi-finished surface error is i and the calculation process is:

[0021]

[0022]

[0023]

[0024] wherein, Z s (i) is the residual height corresponding to the i-th tool position of semi-finishing; A s is the maximum residual height left by semi-finishing; r ε,s is the nose radius of the tool used in semi-finishing; f s is the feed rate of semi-finishing, which is equal to the period length between two tool tracks; w s is the cutting width of semi-finishing; t s is the nominal cutting depth of semi-finishing; Δl p is the horizontal distance between adjacent tool positions, i.e., the length of the discrete unit; t f (i) is the instantaneous cutting thickness of finishing at the i-th tool position:

[0025] t f (i) = Z s (i) + t o (Formula five).

[0026] Preferably, the super-precision finishing error prediction model R f = f(T f , M f , P m , R s )

[0027]

[0028] wherein, f f is the finishing feed rate; r ε,f is the nose radius of the tool used in finishing; r n,f is the cutting edge radius of the tool used in finishing; h Dmin is the minimum cutting thickness; H is the hardness of the material; E is the elastic modulus of the material; k1 represents the influence of the nose radius and the rake angle on the elastic rebound; k2 represents the influence of the minimum cutting thickness on the "size effect" generated in the cutting process; k3 represents the influence of plastic side flow; k4 is the proportional coefficient of semi-finishing error; ΔS sThe dynamic change interference area caused by the semi-finishing error in the finishing process is equal to the maximum cutting range of the tool at the i th tool position in the finishing process Z in the inner part s The sum of (i).

[0029] Preferably, in step five, according to the precision requirement of the processed product, R r And the re-established ultra-precision machining error prediction model in step five, the finishing process planning is carried out, and the finishing tool T f And the finishing parameter M f Meet the following conditions:

[0030]

[0031] Preferably, before step one, according to the processed product, the ultra-precision machining method is selected.

[0032] The present application has the following technical effects relative to the prior art: the ultra-precision machining method of the present application first determines the total material removal amount according to the processed product and the blank, and performs rough machining on the blank to complete the material removal amount of rough machining; after rough machining, an ultra-precision machining error prediction model is established using the existing machining error, and the semi-finishing error is predicted; then, considering the influence of the semi-finishing error, the ultra-precision machining error prediction model is re-established, and finally the finishing process planning is carried out. The ultra-precision machining method of the present application considers the influence of the semi-finishing error on the finishing, re-establishes the ultra-precision machining error prediction model, and integrates and optimizes the process parameters of semi-finishing and finishing, thereby further improving the machining precision of ultra-precision machining without reducing the machining efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0034] Figure 1 It is a flowchart of the ultra-precision machining method of the prior art;

[0035] Figure 2 It is a flowchart of the ultra-precision machining method of the present application;

[0036] Figure 3 It is a schematic diagram of the semi-finishing surface topography in embodiment one of the ultra-precision machining method of the present application;

[0037] Figure 4Fig. 1 is a schematic diagram of a machining interference area in an embodiment of the super-precision machining method of the present application;

[0038] Figure 5 Fig. 2 is a curve diagram of dynamic change of the machining interference area in an embodiment of the super-precision machining method of the present application;

[0039] Figure 6 Fig. 3 is a comparison diagram of experimental results and predicted results in an embodiment of the super-precision machining method of the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

[0041] The present application aims to provide a super-precision machining method to solve the problems in the prior art and improve machining precision.

[0042] In order to make the above objectives, characteristics and advantages of the present application more apparent, the present application will be described in further detail below with reference to the drawings and specific embodiments.

[0043] The present application provides a super-precision machining method, which comprises the following steps:

[0044] Step 1: determining the total material removal amount according to the machining product and the blank;

[0045] Step 2: performing rough machining to complete the material removal amount of rough machining;

[0046] Step 3: establishing a super-precision machining error prediction model using the existing machining error and predicting the semi-finish machining error;

[0047] Step 4: re-establishing a super-precision machining error prediction model considering the influence of the semi-finish machining error;

[0048] Step 5: performing finish machining process planning.

[0049] The super-precision machining method of the present application first determines the total material removal amount according to the machining product and the blank, and performs rough machining on the blank to complete the material removal amount of rough machining. After rough machining, a super-precision machining error prediction model is established using the existing machining error, and the semi-finish machining error is predicted. Then, a super-precision machining error prediction model is re-established based on the semi-finish machining error, and finally finish machining process planning is performed. The specific process is as shown in Fig. 1. Figure 2The application is shown in the drawings. The ultra-precision machining method of the application considers the influence of semi-finishing error on finishing, re-establishes an ultra-precision machining error prediction model, and integrates and optimizes the process parameters of semi-finishing and finishing, thereby improving the machining precision of ultra-precision machining.

[0050] The ultra-precision machining method of the application is further explained below through specific examples.

[0051] Example 1

[0052] The ultra-precision machining method of the embodiment comprises the following steps:

[0053] S1, selecting an ultra-precision machining method according to the machining product. For example, a product with rotational symmetry characteristics such as a spherical surface or a cylindrical surface can be machined by single-point diamond turning, and a non-rotational symmetry free-form surface and a microstructure array can be machined by milling.

[0054] S2, calculating the total material removal amount according to the geometric characteristics of the blank, and the removal volume is V all .

[0055] S3, rough machining process planning, which aims to establish the relative coordinate system of the machined workpiece and the ultra-precision machine tool, and at the same time complete the material removal amount of rough machining, and the removal volume is V r .

[0056] S4, finishing process planning

[0057] First, the precision requirement of the machining product is R r , and the existing machining error is used to establish an ultra-precision machining error prediction model R f =f1(T f ,M f ):

[0058]

[0059] Wherein, f f is the feed amount of finishing; r ε,f is the nose radius of the tool used for finishing;

[0060] Set R f R r , and perform preliminary finishing process planning and calculate the material volume removal amount of finishing, and the removal volume is Vf: V f =f2(T f ,M f ), wherein T f is the tool for finishing, and M f is the machining parameter of finishing.

[0061] Then, the material removal amount of semi-finishing is calculated, and the removal volume is V s : V s = V all -V r -V f .

[0062] Finally, the semi-finishing process planning is performed to determine the tool T s and machining parameters M s of semi-finishing;

[0063] Based on the existing ultra-precision machining quality and ultra-precision machining error prediction model R f =f1(T f ,M f ), the error R s =f1(T s ,M s ) of semi-finishing is predicted, including shape accuracy, surface roughness, and simulating the three-dimensional micro-topography pattern of the surface of semi-finishing.

[0064] It should be further pointed out that the semi-finishing process planning in the prior art needs to make the geometric characteristics of the blank as close as possible to the geometric characteristics of the required product while ensuring a large material removal volume V s , which will reduce the efficiency of ultra-precision machining. However, the present application optimizes the semi-finishing process parameters to improve the machining precision of ultra-precision machining without reducing the machining efficiency.

[0065] S5, considering the influence of semi-finishing error, re-establishing the ultra-precision machining error prediction model

[0066] Firstly, due to the existence of semi-finishing error, the surface of finishing is a non-smooth surface, which makes the cutting depth of finishing dynamically change, rather than being constant. The change of cutting depth will affect the micron-level material removal process, change the material removal mechanism, and thus affect the surface generation mechanism and surface quality. The semi-finishing surface topography is shown in Figure 3 , the semi-finishing surface is discretized into i tool points, and the instantaneous cutting thickness t i of finishing based on the influence of semi-finishing error is calculated as follows:

[0067]

[0068]

[0069]

[0070] Wherein, Z s (i) is the residual height corresponding to the i-th tool point of semi-finishing; A sthe maximum residual height left by semi-finishing; r ε,s the nose radius of the tool used in semi-finishing; f s the feed rate of semi-finishing, equal to the period length between two tool tracks; w s the cutting width of semi-finishing; t s the nominal cutting depth of semi-finishing (specifically, the nominal cutting depth used in the process of forming the semi-finishing topography in semi-finishing, see Figure 4 ) ; Δl p the horizontal distance between adjacent tool positions, i.e. the length of the discrete unit; t f (i) is the instantaneous cutting thickness at the i-th tool position:

[0071] t f (i) = Z s (i) + t o (Equation Five)

[0072] Based on the ultra-precision machining error prediction model R f = f1(T f , M f ) in S4, the influence of semi-finishing error and the dynamic change of instantaneous chip thickness is introduced, and the ultra-precision machining error prediction model R f = f(T f , M f , P m , R s ) is re-established, i.e. the ultra-precision machining error R f is expressed as a function of finishing parameters and tool, workpiece material properties and semi-finishing error:

[0073]

[0074] where f f is the finishing feed rate; r ε,f is the nose radius of the tool used in finishing; r n,f is the cutting edge radius of the tool used in finishing; h Dmin is the minimum cutting thickness; H is the hardness of the material; E is the elastic modulus of the material; k1 represents the influence of the nose radius and the rake angle on the elastic springback; k2 represents the influence of the minimum cutting thickness on the "size effect" generated in the cutting process; k3 represents the influence of plastic side flow; k4 is the proportional coefficient of semi-finishing error; ΔS s is the dynamic change interference area caused by semi-finishing error in the finishing process, equal to the sum of Z s (i) within the maximum cutting range at the i-th tool position in the finishing process, as shown in Figure 4 .

[0075] S6, according to the precision requirements of the processed product R r , and the re-established ultra-precision machining error prediction model R f in S5 f = f(T f , M m , P s , R f ) to carry out finish machining process planning and determine the finish machining tool T f and the finish machining parameters M s , which satisfy the following conditions:

[0076]

[0077] Example Two

[0078] The ultra-precision machining method of the present embodiment obtains semi-finish machining parameters:

[0079] Semi-finish machining feed amount f s = 180 μm

[0080] Semi-finish machining tool nose radius r ε,s = 2044 μm

[0081] Semi-finish machining cutting depth t s = 3 μm

[0082] Semi-finish machining theoretical residual height A s = 1.98 μm

[0083] The finish machining is an orthogonal cutting experiment, and the parameters are:

[0084] Finish machining nominal cutting depth t o = 3 μm

[0085] Finish machining tool nose radius r ε,s = 2044 μm

[0086] The material of the workpiece is RSA6061:

[0087] Hardness H = 1.585 GPa

[0088] Elastic modulus E = 88.203 GPa

[0089] After calculation, the dynamic change interference area ΔS s changes with the change of the tool position point, as shown in Figure 5 ;

[0090] Semi-finish machining error The comparison curve diagram with the experimental results is shown in Figure 6 .

[0091] The super-precision machining method of the application integrates and optimizes process parameters of semi-machining and finishing, and can improve machining precision of super-precision machining without affecting machining efficiency.

[0092] The principle and implementation mode of the application are described by using specific examples in the application, and the above examples are only used for helping to understand the method and core idea of the application; meanwhile, for the general technical personnel in the field, the specific implementation mode and application range will be changed according to the idea of the application. In conclusion, the content of the specification should not be understood as the limitation of the application.

Claims

1. A method for ultra-precision machining, characterized in that, Includes the following steps: Step 1: Determine the total amount of material to be removed based on the processed product and the blank; Step 2: Perform rough processing to remove the required amount of material. Step 3: Utilize existing machining errors to establish an ultra-precision machining error prediction model and predict semi-finishing errors; Step 4: Considering the impact of semi-finishing errors, re-establish the ultra-precision machining error prediction model; Step 5: Plan the finishing process; In step one, based on the geometric characteristics of the blank, the total material removal amount is calculated, and the removal volume is V. all ; In step two, the rough machining process is planned, and the material removal volume is determined, with a removal volume of V. r ; In step three, the required precision of the processed product is R. r Using existing machining errors, an ultra-precision machining error prediction model R is established. f =f1(T f M f ): Among them, f f For finishing feed rate; r ε,f The radius of the cutting edge radius of the tool used for finishing; Set R f <R r A preliminary plan for the finishing process is developed, and the material volume to be removed during finishing is calculated. The removal volume is V. f V f =f2(T f M f ), where T f For precision machining tools, M f These are the machining parameters for finishing. Calculate the material removal amount in the semi-finishing process, where the removal volume is V. s V s =V all -V r -V f ; Perform semi-finishing process planning and determine the tool T for semi-finishing. s and processing parameters M s ; Based on existing prediction models for ultra-precision machining quality and errors, R... f =f1(T f M f Predicting the semi-finishing error R s =f1(T s M s ); In step four, the semi-finished surface is discretized into i tool positions, and the instantaneous cutting thickness t during finishing is determined based on the influence of semi-finishing errors. i The calculation process is as follows: Among them, Z s (i) represents the residual height corresponding to the i-th tool position in the semi-finishing process; A s The maximum residual height left by semi-finishing; r ε,s The radius of the tool tip arc for semi-finishing; f s For semi-finishing, the feed rate is equal to the cycle length between two tool paths; w s The cutting width for semi-finishing; t s The nominal depth of cut for semi-finishing; Δl p t represents the horizontal distance between adjacent tool points, i.e., the length of the discrete element; f (i) represents the instantaneous cutting thickness during finishing at the i-th tool position: t f (i)=Z s (i)+t o (Formula 5) 2. The ultra-precision machining method according to claim 1, characterized in that: Re-establish the error prediction model R for ultra-precision machining f =f(T) f M f ,P m ,R s ) Among them, f f For finishing feed rate; r ε,f The radius of the tool tip arc used for finishing; r n,f The cutting edge radius of the tool used for finishing; h Dmin Minimum cutting thickness; H is the material hardness; E is the material's elastic modulus; k1 represents the influence of the tool tip radius and rake angle on elastic rebound; k2 represents the influence of the minimum cutting thickness on the "size effect" generated during the cutting process; k3 represents the influence of plastic lateral flow; k4 is the proportionality coefficient of semi-finishing error; ΔS s The interference area caused by the semi-finishing error during the finishing process is equal to the maximum cutting range of the tool at the i-th tool position during the finishing process. Z inside s The sum of (i).

3. The ultra-precision machining method according to claim 2, characterized in that: In step five, the precision requirement of the processed product is R. r In addition to the re-established ultra-precision machining error prediction model in step five, the finishing process planning is carried out, and the finishing tool T is determined. f and finishing parameters M f It meets the following conditions:

4. The ultra-precision machining method according to claim 1, characterized in that: Before proceeding to step one, select the ultra-precision machining method based on the product being processed.

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