CN117993116A - Reliability analysis method for machining allowance of mechanical part - Google Patents
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Abstract
The invention belongs to the technical field of machine part manufacturing, and discloses a machine part machining allowance reliability analysis method, which can judge the reliability of a part without sampling in a large amount in part detection, and can remarkably save a large amount of manpower and material resources by only setting a machining allowance target value range and a design tolerance in production.
Description
Technical Field
The invention belongs to the technical field of machine part manufacturing, and particularly relates to a machine part machining allowance reliability analysis method.
Background
In the production process of mechanical parts, the influence of the change of the machining allowance on the reliability of the mechanical parts is very huge, and in general, when the machining allowance of the parts is increased, the machining and production cost is increased, and when the machining allowance is reduced, the machining surface of the parts has defects which cannot be eliminated, so that the parts are not up to standard, and therefore, the reliability of the parts is detected in real time to judge the proper machining allowance, which is an important part in the machining process of the mechanical parts.
At present, a method for judging proper machining allowance by detecting the reliability of a part is to detect the part by using a mechanical part after production, if the reliability reaches the standard, the machining allowance is proper, and if the reliability does not reach the standard, the machining allowance needs to be adjusted.
However, in actual experience, the method consumes a great deal of manpower and material resources, and can detect the parts after the completion of processing a batch of parts, so that cost waste is caused.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the reliability analysis method for the machining allowance of the mechanical part, which can judge the reliability of the part only through the machining allowance target value range and the design tolerance set in the production without sampling in a large amount in the part detection, thereby obviously saving a large amount of manpower and material resources.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a machine part machining allowance reliability analysis method comprises the following steps:
Step S1: dividing the total machining allowance of the sample part into a plurality of working procedure machining allowances, and measuring the standard deviation of the sample part, the characteristic precision grade of any one working procedure and the surface roughness equivalent precision grade of the working procedure;
step S2: recording a machining allowance target value range and a design tolerance set during production of sample parts;
Step S3: obtaining recessive quality loss by using a field method and design tolerance;
step S4: defining a machining allowance influence factor based on the standard deviation of the sample part and a machining allowance target value range set during production of the sample part, and determining the machining allowance of the process through the characteristic precision grade of the measured process and the surface roughness equivalent precision grade of the process;
Step S5: establishing a numerical model based on the machining allowance influence factor, the machining allowance of the measured procedure and the recessive quality loss by using an asymmetric secondary quality loss function and a symmetric secondary index quality loss function;
Step S6: and obtaining inherent reliability by using the numerical model, and judging the reliability of the sample part.
Preferably, in step S3, the implicit quality loss is determined by a lower specification quality loss, a lower specification weight ratio, an upper specification quality loss, an upper specification weight ratio, specifically:
A＝ɑA1+βA2
Wherein: a is recessive mass loss, alpha is specification lower limit weight ratio, A 1 is specification lower limit mass loss, beta is specification upper limit weight ratio, and A 2 is specification upper limit mass loss.
Preferably, in step S4, the maximum value of the above-mentioned machining allowance target value range is an upper limit of the machining allowance target value, and the minimum value is a lower limit of the machining allowance target value.
Preferably, in step S4, the machining allowance influence factor is expressed as:
wherein: λ is the machining allowance influence factor, TU is the upper limit of the tolerance range, TL is the lower limit of the tolerance range, and σ is the standard deviation of the measured sample part.
Preferably, in step S5, the numerical model established using the asymmetric quadratic mass loss function is expressed as:
Wherein: r (t) is an intrinsic reliability.
Preferably, in step S5, the numerical model established using the symmetric quadratic exponential quality loss function is expressed as:
Compared with the prior art, the invention has the beneficial effects that:
1. Because the reliability of the part can be judged through the measured machining allowance target value range and the design tolerance, the invention does not need a large amount of manual sampling detection, and saves a large amount of manpower and material resources.
2. The invention can judge the reliability of the part by only detecting the characteristic precision grade of any procedure of the sample part, the determined machining allowance target value range and the design tolerance when detecting the sample part, and can adjust the machining allowance of the procedure when finding that the part is unqualified, and can detect the reliability of the part without waiting until the part is completely finished, thereby reducing the generation of waste products and lowering the production cost of enterprises.
3. The invention only needs to adjust the machining allowance of the process to ensure the quality of finished parts when the parts of any process are unqualified, thereby reducing the requirements on machine equipment and prolonging the service life of the equipment.
Drawings
FIG. 1 is a schematic diagram showing steps of a reliability analysis method for machining allowance of a mechanical part according to an embodiment of the present invention;
FIG. 2 is a schematic view of six sample pin elements according to an embodiment of the present invention;
FIG. 3 is a schematic view of a pin member length measurement according to an embodiment of the present invention;
FIG. 4 is a schematic view of a pin member diameter measurement according to an embodiment of the present invention;
FIG. 5 is a schematic view of the positions of three measurement points of a pin part according to an embodiment of the present invention;
FIG. 6 is a graph of the influence factor of the machining allowance in the rough machining according to the embodiment of the present invention;
FIG. 7 is a graph showing the variation of the process margin influence factor in the rough machining according to the embodiment of the invention;
FIG. 8 is a graph of a numerical model of an asymmetric quadratic mass loss function in rough machining according to an embodiment of the present invention;
FIG. 9 is a graph showing the variation rule of an asymmetric quadratic mass loss function numerical model in rough machining according to an embodiment of the present invention;
FIG. 10 is a graph showing a numerical model of a symmetric quadratic index mass loss function in rough machining according to an embodiment of the present invention;
FIG. 11 is a graph showing a change rule of a numerical model of a symmetric secondary index mass loss function in rough machining according to an embodiment of the present invention;
FIG. 12 is a graph of the influence factor of the machining allowance in the finishing according to the embodiment of the present invention;
FIG. 13 is a graph showing the variation of the process margin influence factor in the finishing process according to the embodiment of the present invention;
FIG. 14 is a graph showing a numerical model of an asymmetric quadratic mass loss function in finishing according to an embodiment of the present invention;
FIG. 15 is a graph showing the variation rule of the numerical model of the asymmetric quadratic mass loss function in the finishing according to the embodiment of the invention;
FIG. 16 is a graph showing a numerical model of a symmetric quadratic index mass loss function in finishing according to an embodiment of the present invention;
FIG. 17 is a graph showing the variation rule of a numerical model of a symmetric quadratic index mass loss function in finishing according to an embodiment of the present invention;
Detailed Description
In order to make the technical means, the creation characteristics, the achievement of the purposes and the effects of the present invention easy to understand, the following examples specifically describe a method for analyzing the reliability of machining allowance of mechanical parts according to the present invention with reference to the accompanying drawings, and it should be noted that the description of the embodiments is for aiding understanding of the present invention, but not limiting the present invention.
As shown in fig. 1, a method for analyzing reliability of machining allowance of a mechanical part in this embodiment includes the following steps:
s1, dividing the total machining allowance of a sample part into a plurality of working procedure machining allowances, and measuring standard deviation of the sample part, characteristic precision grade of any one working procedure and surface roughness equivalent precision grade of the working procedure.
Specifically, the total machining allowance of the sample part is divided into a plurality of working procedure machining allowances, which are the sum of the working procedure machining allowances Z i of each working procedure, namely:
wherein: z is the total machining allowance;
The process margin Z i of each process is the absolute value of the difference between the current process dimension B i and the previous process dimension B i-1, namely:
Zi＝|Bi-Bi-1| (2)
Wherein: b i is the current process size, and B i-1 is the previous process size.
S2, recording a machining allowance target value range and a design tolerance set during production of the sample part.
Specifically, the process dimensions are affected by the design tolerance, so that there are a maximum process margin Z imax and a minimum process margin Z imin, the minimum process margin Z imin is the absolute value of the difference between the minimum value of the current process dimension and the maximum value of the previous process dimension, and the maximum value of the previous process dimension is obtained by adding the dimensional tolerance to the minimum value of the previous process dimension, namely:
Zimin＝| Bimin-B(i-1)max|＝Bimin-B(i-1)min-TB(i-1) (3)
Wherein: b imin is the minimum value of the previous process dimension, B (i-1)max is the maximum value of the previous process dimension, B (i-1)min is the minimum value of the previous process dimension, and T B(i-1) is the dimensional tolerance of the previous process;
The maximum process machining allowance Z imax is the absolute value of the difference between the maximum value of the process dimension and the minimum value of the previous process dimension, and the maximum value of the process dimension is obtained by adding the dimensional tolerance to the minimum value of the process dimension, namely:
Zimax＝|Bimax-B(i-1)min|＝Bimin-B(i-1)min+TBi (4)
Wherein: b imax is the maximum value of the dimension of the process, and T Bi is the dimensional tolerance of the process;
By definition, the design tolerance is the difference between the maximum process margin and the minimum process margin. The formula for the tolerance of the machining allowance available according to formulas (3) and (4) is:
TZi＝Zimax-Zimin＝TBi+TB(i-1) (5)
The initial dimensions are centered in the tolerance specification, so the total tooling allowance can be expressed as:
wherein: t B0 is the initial dimensional tolerance.
S3, obtaining the recessive quality loss by using a field method and design tolerance.
Specifically, according to the field mouth quality view of the field mouth method, quality characteristic fluctuation of the product can occur in the specification limit, so that quality loss is generated, namely quality loss can be generated in the qualified product, namely, recessive quality loss is generated, and in order to study the influence of the working procedure machining allowance of the part on the reliability, the recessive quality loss is used for establishing the connection between the machining allowance and the reliability, and a normal distribution density function, a standard normal distribution density function and a distribution function are respectively adopted. The method comprises the following steps:
Normal distribution density function:
standard normal distribution density function:
Distribution function:
wherein: x is the machining allowance value, mu is the average value of the machining allowance, and sigma is the standard deviation.
S4, defining a machining allowance influence factor based on the standard deviation of the sample part and a machining allowance target value range set during production of the sample part, and determining the machining allowance of the process through the characteristic precision grade of the measured process and the surface roughness equivalent precision grade of the process.
Specifically, in general, surface defects and roughness of a part or a part blank to be processed, dimensional tolerance, position deviation, clamping error and other factors in the processing process are all main factors influencing machining allowance, and an existing machining allowance model is as follows:
Wherein: k L is a characteristic comprehensive dimension parameter coefficient, epsilon L is a positioning error generated by inaccurate positioning surface and misaligned reference of the ith procedure, epsilon F is a positioning error generated by inaccurate clamping element of the ith procedure, epsilon C is a clamping error of the ith procedure, ralpha (i-1) is the surface roughness of the ith-1 procedure, I s(i-1) is the surface defect depth of the ith-1 procedure, T B(i-1) is the dimension tolerance of the ith-1 procedure, and T p(i-1) is the position tolerance of the ith-1 procedure;
The epsilon L、∈F、∈C in the above formula is generally caused by clamping, and the clamping error is generally objectively influenced by human factors and mechanical factors, and objective factors are ignored, so that the epsilon L、∈F、∈C is 0, and the formula 7 can be changed into:
Wherein:
Wherein J i-1 is the characteristic precision grade of the ith-1 step, J a(i-1) is the equivalent precision grade of the surface roughness of the ith-1 step, and Z i is the machining allowance of the ith step.
S5, establishing a numerical model based on the machining allowance influence factor, the machining allowance of the measured process and the recessive quality loss by using the asymmetric secondary quality loss function and the symmetric secondary index quality loss function.
Specifically, a numerical model established based on an asymmetric quadratic mass loss function comprises the following specific steps:
By using the field method and the asymmetric secondary mass loss function, it can be seen that:
Where L (x) is a unit product mass loss, x is a processing margin value, D is a target value of processing margin, D L is a lower limit of a processing margin specification range, D U is an upper limit of the processing margin specification range, A 1 is a specification lower limit mass loss, A 2 is a specification upper limit mass loss, k 1 is a mass loss coefficient on the left side of the target value, and k 2 is a mass loss coefficient on the right side of the target value.
At this point k 1 and k 2 can be represented as:
estimating the expected quality cost based on a field method and probability theory:
wherein: e (L (x)) is the desired quality cost.
Order theThen:
Wherein: c is the average mass loss of a batch of products, including the mass loss resulting from reject products.
In order to estimate the quality loss of qualified products in a batch, the quality loss of qualified products borne by unqualified products should be transferred to the qualified products, and an expression is established:
Wherein: q is the qualification rate of the batch of products.
Defining C 0 as a loss of stealth quality, then the relationship between C 0 and C is:
Substituting 18 into 20, one can obtain:
wherein: sigma is the standard deviation and mu is the machining allowance average value.
In the actual production process, when the machining allowance is too large, the labor amount of machining is increased, the production efficiency is reduced, the consumption of materials, tools, electric power and the like is increased, and the cost is increased. However, the machining allowance is too small, so that the number of processes may be increased, various errors and surface defects of the previous process cannot be eliminated, even waste products are generated, and if the target value is located in the specification center, the following steps are performed:
Wherein: c p is a process capability index, T U is an upper limit of a tolerance range, T L is a lower limit of the tolerance range, and T Z is a tolerance range value.
The process capability index is also expressed as:
wherein: Δ T is half the tolerance range.
The above indicates the capability of meeting the tolerance of the specified machining allowance when producing a certain part, the ratio of the tolerance range value to 6 times of standard deviation is used for reflecting the degree that the process capability meets the technical requirement, and the smaller the standard deviation of the machining allowance is, the better the machining capability is, and the combination of the formula 22 and the formula 23 can be obtained:
ΔT＝3σCp (24)
DU-μ＝D+TU-μ＝ΔT＝3σCp (25)
DL-μ＝D-TL-μ＝-ΔT＝-3σCp (26)
Wherein: sigma is a standard deviation, mu is a machining allowance average value, T U is a tolerance range upper limit, T L is a tolerance range lower limit, D is a machining allowance target value, D L is a machining allowance specification range lower limit, and D U is a machining allowance specification range upper limit.
Substituting equations 24, 25 and 26 into equation 21 yields:
substituting equation 22 into equation 27 yields:
Wherein: a 1 is the specification lower limit mass loss, and a 2 is the specification upper limit mass loss.
According to step S4, the process margin influence factor is defined as:
wherein: t Zi is the design tolerance.
Combining equation 5, one can obtain:
Wherein T Bi is the dimensional tolerance of the previous process, and T B(i-1) is the dimensional tolerance of the previous process.
During machining, after the part is machined, the final part size is required to meet the design requirements and form a size chain. Therefore, the sum of the dimensional tolerances of the steps is equal to the dimensional tolerance of the final part, the dimensional tolerance of the previous step and the dimensional tolerance of the current step are necessarily related, the dimensional tolerance of the current step is omega times of the dimensional tolerance of the previous step, and the following formula is obtained according to the experience 0 < omega less than or equal to 1:
Substituting equation 11 into 31 yields:
wherein: lambda is the machining allowance influence factor.
Equation 28 may be changed from equation 32 above to:
At this time, the invisible quality loss of the product part is related to the machining allowance influence factor, and the machining allowance factor is related to the machining allowance of the working procedure.
At present, researchers propose that assuming that the number of parts in a batch is M, then the invisible mass loss of the parts in the batch is C 0 M, and the hidden mass loss of all the parts is transferred to the parts with larger mass loss, so that the number of parts with simulated failure in a batch of qualified parts can be obtained as follows:
Wherein: m s is the number of failed parts, A is the mass loss, and C 0 M is the invisible mass loss.
Equation 34 above shows that the number of simulated failed parts is minimal when the mass loss is greatest, but in actual production, manufacturers prefer to expand product tolerances to produce, so that while there is an upper specification mass loss, reworking repair can be performed to reduce the loss; however, when the product tolerance of the parts produced by the manufacturer is smaller than the design tolerance, the parts at this time are not compliant and are directly scrapped, which causes a large amount of lower limit mass loss of the specification, so in order to estimate the hidden mass loss of each product to be transferred to the product parts causing the mass loss, the invention defines:
A＝αA1+βA2 (35)
Wherein alpha is the weight ratio of the lower limit mass loss of the specification, and beta is the weight ratio of the upper limit mass loss of the specification.
The combination of equations 34 and 35 can be obtained:
Wherein: m s is the number of failed parts.
The existing intrinsic reliability numerical model is as follows:
wherein: r (t) is the inherent reliability and F (t) is the failure rate.
Substituting equation 36 into equation 37 yields:
substituting equation 33 into 38 yields:
at this time, the inherent reliability of the part is linked to the machining allowance factor, which is affected by the machining allowance of the process.
Specifically, a numerical model established based on a symmetric quadratic exponential quality loss function comprises the following specific steps:
the field method and the symmetrical secondary index mass loss function are utilized to know that:
Where L (x) is a unit product mass loss, x is a processing margin value, D is a target value of processing margin, D L is a lower limit of a processing margin specification range, D U is an upper limit of the processing margin specification range, A 1 is a specification lower limit mass loss, A 2 is a specification upper limit mass loss, k 1 is a mass loss coefficient on the left side of the target value, and k 2 is a mass loss coefficient on the right side of the target value.
At this point k 1 and k 2 can be represented as:
the step of establishing a numerical model based on the asymmetric secondary mass loss function is finally carried out, and the method comprises the following steps of:
s6, obtaining inherent reliability by utilizing a numerical model, and judging the reliability of the sample part.
As shown in fig. 2 to 17, a method for analyzing the reliability of machining allowance of a mechanical part according to the present embodiment will be described in detail with reference to the specific embodiment.
In this embodiment, the samples are selected, as shown in fig. 2, and are 6 pin elements, firstly, the outer circle sizes of the raw materials are measured by using vernier calipers at positions 30mm, 60mm and 90mm away from the end face, specifically as shown in fig. 5, and in the second step, the measurement results are ordered according to the sample serial numbers, specifically as shown in table 1:
as can be seen from table 1: the maximum value and the minimum value of the outer diameters of the 6 samples meet the specification requirements of parts.
In this embodiment, the final dimensional tolerance of the part is ± 0.40mm, so as to avoid the occurrence of false waste, in this case, two steps are performed in the same tolerance method, that is, the dimensional tolerance of the step is 1 times of the dimensional tolerance of the previous step, that is, ω=1 in the formula 32, the dimensional tolerance before rough machining in the first step is ± 0.40mm, and the dimensional tolerance of the pin part meeting the specification is ± 0.40mm after finishing the finish machining in the second step.
The method comprises the following steps of calculating related parameters of two processing procedures, and then analyzing and comparing the influence of the processing allowance on the reliability of the product by using the numerical model of the asymmetric secondary mass loss function and the symmetric secondary index mass loss function.
Calculating relevant parameters in the rough machining process:
Assuming that the processing adopts a grade treatment method, the basic idea is that the characteristic precision and the surface roughness grade of the process are smaller than those of the previous process by three grades; when the first process is rough machined, the corresponding characteristic precision grade of rough machining is 12, so that the depth of a surface defect layer of the previous process is 0.3mm, if the equivalent precision grade of the surface roughness of a blank is 10, the surface roughness of the previous process is 12.8um, in production, the position tolerance is generally 50% -60% of the dimensional tolerance value, in this case, 60% of the dimensional tolerance value of the blank is 0.8mm, and therefore, the position tolerance of the previous process is 0.48mm, and the specific parameter results are shown in table 2:
substituting the data of table 2 into equation 11 yields: z 1 = 1.5586mm.
At this time, according to equation 5, it is possible to obtain: t Z1 = 1.6mm.
Since the target value is located in the machining specification center, the margin tolerance of Z 1 is + -0.80 mm, and the target value of Z 1 is 1.5586mm-3.1586mm.
The process margin influence factor at this time is:
As can be obtained from equation 44, in order to make the machining allowance factor meaningful, that is, to minimize the machining allowance, the defect caused by the previous process is removed, where the value range of Z 1 obtained by the above equation is: 1.56mm-3.14mm.
As can be seen from equation 44, the machining allowance factor is related to the machining allowance and the standard deviation, and referring specifically to fig. 6 and 7, it can be seen that the larger the machining allowance, the larger the machining allowance influence factor, and the smaller the standard deviation, i.e., the better the reliability of the produced parts.
As can be seen from formulas 39 and 44, when the specification lower limit mass loss is 9, the specification upper limit mass loss is 3, the specification lower limit mass loss weight ratio is 0.9, and the specification upper limit mass loss weight ratio is 0.1, it is possible to obtain:
According to the formula 45, the numerical model established by the asymmetric secondary mass loss function is analyzed, and specific rules of the inherent reliability of the product are shown in fig. 8 and 9, and the larger the machining allowance, the better the reliability of the product in the design range is shown in fig. 9. And the smaller the standard deviation, the better the inherent reliability of the produced part. As can be seen from the two-dimensional change surface in fig. 8, when the product reliability is 0.95, the range of the machining allowance and the standard deviation is better selected, and the influence of the change of the machining allowance on the inherent reliability of the product can be analyzed.
As can be seen from the formula 43, the symmetric quadratic exponential quality loss function is analyzed, and referring to fig. 10 and 11, it can be seen that, if the product reliability is specified to satisfy 0.9, the machining allowance and standard deviation range are reduced compared with those of fig. 8, so that the implicit quality loss obtained by the quadratic exponential function is improved more accurately than that obtained by the asymmetric quadratic function, and the influence of the change of the machining allowance on the inherent reliability of the part is better analyzed.
Calculating relevant parameters in the finishing process:
When the second process is finished, the corresponding feature precision is 9, namely the depth of the surface defect layer of the previous process is 0.075mm, the processing adopts a grade treatment method, so that the surface roughness grade of the blank is 7, the surface roughness of the previous process is 1.6um, and the obtained data are listed in table 3:
The machining allowance of the second procedure is required to ensure that the dimensional tolerance of the final part meets the requirement, the defect left by rough machining of a blank is removed, and the data in table 3 are substituted into the data in table 11 to obtain the product: z 2 = 1.0862mm.
At this time, according to equation 5, it is possible to obtain: t Z2 = 1.0862m.
Since the target value is located in the machining specification center, the allowance tolerance Z 2 in the second process is + -0.80 mm, and the target value of Z 2 is 1.0862mm-2.6862mm.
The process margin influence factor at this time is:
As can be obtained from equation 46, to make the machining allowance factor meaningful, that is, to minimize the machining allowance, the defect caused by the previous process is removed, where the value range of Z 1 is: 1.10mm-2.68mm.
As can be seen from equation 46, the machining allowance factor is related to the machining allowance and the standard deviation, and referring specifically to fig. 12 and 13, it can be seen that the larger the machining allowance, the larger the machining allowance influence factor, and the smaller the standard deviation, i.e., the better the reliability of the produced parts.
As can be seen from formulas 39 and 46, when the specification lower limit mass loss is 9, the specification upper limit mass loss is 3, the specification lower limit mass loss weight ratio is 0.9, and the specification upper limit mass loss weight ratio is 0.1, it is possible to obtain:
As can be seen from the equation 47, the numerical model established by the asymmetric quadratic mass loss function is analyzed, and specific rules of the inherent reliability of the product can be obtained with reference to fig. 14 and 15, and in the finishing stage, the reliability is substantially unchanged with respect to the process margin and the rate of change of the standard deviation thereof although the process margin is reduced, which can explain the stability of the model to some extent. As can be seen by comparing fig. 14 with fig. 8, the range of rough machining stages corresponding to the finishing stage is reduced if the reliability of selection is 0.9. This is in fact in line with objective reality, as mentioned above, in the finishing stage, the process margin is not only to satisfy the removal of the defects of the previous stage, but also to ensure that the dimensions of the final produced part satisfy the design requirements, so that the area must be reduced.
From equation 47, it is known that the symmetric quadratic exponential quality loss function is analyzed, and specific rules of the inherent reliability of the product are shown in fig. 16 and 17, and specific results are similar to those of fig. 10 and 11.
The above embodiments are preferred embodiments of the present invention and are not intended to limit the scope of the present invention, and various modifications or variations which may be made by those skilled in the art without the inventive effort within the scope of the appended claims remain within the scope of this patent.
Claims (6)
1. The method for analyzing the reliability of the machining allowance of the mechanical part is characterized by comprising the following steps of:
Step S1: dividing the total machining allowance of the sample part into a plurality of working procedure machining allowances, and measuring standard deviation of the sample part, characteristic precision grade of any one working procedure and surface roughness equivalent precision grade of the working procedure;
step S2: recording a machining allowance target value range and a design tolerance set during production of sample parts;
Step S3: obtaining recessive quality loss by using a field method and design tolerance;
Step S4: defining a machining allowance influence factor based on the standard deviation of the sample part and a machining allowance target value range set during production of the sample part, and determining the machining allowance of the process through the characteristic precision grade of the measured process and the surface roughness equivalent precision grade of the process;
Step S5: establishing a numerical model based on the machining allowance influence factor, the machining allowance of the measured procedure and the recessive quality loss by using an asymmetric secondary quality loss function and a symmetric secondary index quality loss function;
Step S6: and obtaining inherent reliability by using the numerical model, and judging the reliability of the sample part.
2. The machine part machining allowance reliability analysis method according to claim 1, characterized in that:
In step S3, the implicit quality loss is determined by a lower specification quality loss, a lower specification weight ratio, an upper specification quality loss, and an upper specification weight ratio, specifically:
A＝ɑA1+βA2
Wherein: a is recessive mass loss, alpha is specification lower limit weight ratio, A 1 is specification lower limit mass loss, beta is specification upper limit weight ratio, and A 2 is specification upper limit mass loss.
3. The machine part machining allowance reliability analysis method according to claim 1, characterized in that:
In step S4, the maximum value of the above-mentioned machining allowance target value range is the upper limit of the machining allowance target value, and the minimum value is the lower limit of the machining allowance target value.
4. A machine part machining allowance reliability analysis method according to claim 1 or 3, characterized in that:
In step S4, the machining allowance influence factor is expressed as:
Wherein: lambda is the machining allowance influence factor, T U is the upper limit of the tolerance range, T L is the lower limit of the tolerance range, and sigma is the standard deviation of the measured sample part.
5. The machine part machining allowance reliability analysis method according to claim 1 or 2 or 4, characterized in that:
Wherein, in step S5, the numerical model established by using the asymmetric quadratic mass loss function is expressed as:
Wherein: r (t) is an intrinsic reliability.
6. The machine part machining allowance reliability analysis method according to claim 1 or 5, characterized in that:
Wherein, in step S5, the numerical model established by using the symmetric quadratic exponential quality loss function is expressed as:
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