Part size matching analysis method and device

Abstract

The invention discloses a part size matching analysis method and device. The part size matching analysis method comprises the steps that the part number and defect information of a target part are acquired; determining a target dimension chain and a matching tolerance thereof by using the whole vehicle model database according to the part number and the defect information; calculating a tolerance extreme value and a tolerance square root of the target dimension chain; the matching tolerance, the tolerance extreme value and the tolerance square root of the target dimension chain are evaluated, and when the tolerance extreme value and the tolerance square root are both larger than the matching tolerance, a matching tolerance defect is output; when the tolerance extreme value is smaller than the matching tolerance, the interference amount of the target dimension chain is evaluated, the positioning reference and the assembling reference of the target dimension chain are evaluated, when the interference amount of the target dimension chain is zero and the positioning reference and the assembling reference of the target dimension chain are consistent, part defects are output, and when the interference amount of the target dimension chain is larger than zero, part defects are output. And / or when the positioning reference and the assembly reference of the target dimension chain are inconsistent, outputting the structure defect.

Description

Technical Field

[0001] The present invention relates to the technical field of part size matching analysis in vehicle assembly, and in particular to a part size matching analysis method and device. Background Art

[0002] Quality is an important indicator for measuring the development of an enterprise. Quality management has risen to a strategic position that determines the development of an enterprise. Since the beginning of the 20th century, quality management has been increasingly valued by enterprises. The development stages of quality management have evolved from the initial quality inspection to the statistical quality management proposed by American mathematical statistician Shewhart, and then to the total quality management proposed by Feigenbaum. The development of quality has always kept pace with the times and focused on solving problems encountered in the production process. Changes in quality management concepts have driven the pace of quality development. The advent of the three-coordinate measuring machine in 1957 made it more efficient and convenient to quantify the size and status of products. The development of measurement technology has always been complementary to the development of quality management. From inspection to detection to process control and then to early prevention, measurement technology runs through the entire quality management process. Quality management is integrated into all stages of the enterprise's production and manufacturing process and is one of the indispensable indicators of products. Measurement technology is not only a tool for quantifying product status, but also provides solid data support for quality management.

[0003] In the whole vehicle size matching, there are many problems with long analysis cycles, slow optimization and incomplete optimization. Such problems affect various indicators of the whole vehicle. In the previous analysis of whole vehicle size matching problems, the use of traditional analysis methods (such as fishbone diagram, 5W2H, Toyota eight-step method, etc.) can only sort out the possible influencing factors of the problem, and it is necessary to measure the full size chain of the problem. Traditional analysis methods cannot accurately analyze the main influencing factors, and need to be based on full factor investigation. The quantitative process data collection volume is large and the cycle is long, and the efficiency is low. The application of measurement technology in quality problem analysis is not only reflected in the quantification of product status, but also in the quantification of the entire problem influencing factors and the CP and CPK monitoring in the product production process based on statistics. To a certain extent, the application of measurement technology reflects the quality and size management level of the enterprise.

[0004] Considering from the perspective of the quality cost curve and the normal distribution curve of product size, objectively speaking, it is allowed that some parts are unqualified. From the perspective of the size chain, size problems are accidental and random. Even if the sizes of all parts of the whole vehicle meet the design requirements, size matching problems will objectively exist. The quality control of the whole vehicle has prevention mechanisms for problems and means of dealing with problems after they occur. Summary of the invention

[0005] To solve at least one aspect of the above problems, the present invention provides a part size matching analysis method, comprising: obtaining a part number and defect information of a target part, wherein the part number is used to uniquely identify the part, and the defect information includes a defect value, a defect type, and a defect location; determining a target dimension chain and its matching tolerance according to the part number and the defect information using a vehicle model database, wherein the vehicle model database includes multiple dimension chains; calculating the tolerance extreme value and the tolerance square root of the target dimension chain; outputting a matching tolerance defect when both the tolerance extreme value and the tolerance square root are greater than the matching tolerance; when the tolerance extreme value is less than the matching tolerance, evaluating the interference amount of the target dimension chain, and evaluating the positioning datum and assembly datum of the target dimension chain; when the interference amount of the target dimension chain is zero, and the positioning datum and assembly datum of the target dimension chain are consistent, outputting a part defect; and when the interference amount of the target dimension chain is greater than zero, and / or the positioning datum and assembly datum of the target dimension chain are inconsistent, outputting a structural defect.

[0006] Preferably, when outputting part defects, the part deviation of the target dimension chain is calculated, and the defective part is determined according to the part deviation of the target dimension chain.

[0007] Preferably, the process parameters of the part are acquired, and a target optimized part is determined according to the process parameters of the defective part.

[0008] Preferably, the structural parameters of the defective part are acquired, and the target optimized part is determined according to the structural parameters of the defective part.

[0009] Preferably, the whole vehicle model database includes an over-positioning defect model and an under-positioning defect model, and when a structural defect is output, the corresponding defect model is determined according to the defect value.

[0010] On the other hand, a part size matching analysis device is provided, comprising: a receiving module, the receiving module is configured to receive input data, the input data includes a part number and defect information of a target part, the part number is used to uniquely identify the part, and the defect information includes a defect value, a defect type and a defect position; a query module, the query module includes a vehicle model database, the vehicle model database includes multiple dimension chains, the query module determines a target dimension chain and its matching tolerance according to the part number and the defect information; a calculation module, the calculation module is used to calculate the tolerance extreme value and the tolerance square root of the target dimension chain; a first evaluation module, the first evaluation module is used to evaluate the target dimension chain The matching tolerance, the tolerance extreme value and the tolerance square root of the chain, when the tolerance extreme value and the tolerance square root are both greater than the matching tolerance, a matching tolerance defect is output, and when the tolerance extreme value is less than the matching tolerance, a structural evaluation instruction is output; a second evaluation module, the second evaluation module evaluates the interference amount of the target dimension chain in response to the structural evaluation instruction, and evaluates the positioning datum and assembly datum of the target dimension chain, when the interference amount of the target dimension chain is zero, and the positioning datum and assembly datum of the target dimension chain are consistent, a part defect is output, and when the interference amount of the target dimension chain is greater than zero, and / or the positioning datum and assembly datum of the target dimension chain are inconsistent, a structural defect is output.

[0011] Preferably, it also includes a detection module, which calculates the part deviation in the target dimension chain in response to the received part defect, and determines the defective part according to the part deviation of the target dimension chain.

[0012] Preferably, it also includes an optimization target evaluation module, which obtains the process parameters of the defective part and determines the target optimized part according to the process parameters of the defective part.

[0013] Preferably, it also includes an optimization target evaluation module, which obtains the structural parameters of the defective part and determines the target optimized part according to the structural parameters of the defective part.

[0014] Preferably, the whole vehicle model database also includes an over-positioning defect model and an under-positioning defect model. When a structural defect is output, the corresponding defect model is determined according to the defect value.

[0015] The part size matching analysis method and device of the present invention have the following beneficial effects: based on the part structure, part tolerance, vehicle body matching tolerance requirements, etc., the part measurement results are analyzed to provide a basis for the whole vehicle size quality control, which is significantly more efficient and accurate than traditional analysis methods, and can quickly analyze and solve size problems that arise in the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to better understand the above and other purposes, features, advantages and functions of the present invention, reference may be made to the embodiments shown in the accompanying drawings. The same reference numerals in the accompanying drawings refer to the same components. It should be understood by those skilled in the art that the accompanying drawings are intended to schematically illustrate the preferred embodiments of the present invention and have no limiting effect on the scope of the present invention, and the components in the drawings are not drawn to scale.

[0017] Figure 1 A schematic diagram of the process of a part size matching analysis method according to an embodiment of the present invention is shown;

[0018] Figure 2 A structural block diagram of a device for analyzing part size matching according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0020] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0021] In order to at least partially solve one or more of the above problems and other potential problems, the embodiments of the present disclosure provide a part size matching analysis method, such as Figure 1 As shown, including:

[0022] Step S1, obtaining the part number and defect information of the target part, where the part number is used to uniquely identify the part, and the defect information includes the defect value, defect type, and defect location.

[0023] Specifically, the target part includes two directly related parts. For example, if there is a size defect in the gap between adjacent parts A and B, the target parts are parts A and B, the defect value is the defect state value obtained by measuring the gap between the two parts, the defect type is gap, and the defect position is the distance between adjacent endpoints of parts A and B in the vehicle coordinate system. Those skilled in the art can understand that the defect type also includes flatness, etc. The defect position also includes the preset surface of the target part, etc. The part number is used to uniquely identify the part in the vehicle model database.

[0024] Step S2, using the vehicle model database to determine the target dimension chain and its matching tolerance according to the part number and defect information, wherein the vehicle model database includes multiple dimension chains.

[0025] Specifically, the vehicle model database includes multiple vehicle model data units, and each vehicle model data unit includes all structural parameters of its corresponding vehicle model. Each vehicle model data unit includes all dimension chains belonging to the vehicle model, and each dimension chain includes at least two parts. The dimensions of the related parts in the dimension chain are arranged end to end in a certain order to form a closed dimension group. Each dimension chain includes the part number, part position information, part structure information, part tolerance, matching tolerance and dimension chain type of all parts that constitute the dimension chain. Dimension chain types include linear dimension chains, parallel dimension chains, etc. Those skilled in the art can understand that any part in the vehicle model can belong to different dimension chains.

[0026] According to the part number and defect of the target part, the query module from the vehicle database determines the target dimension chain according to the part number and defect information. Among them, the part number is used to query the dimension chain containing the part number, and the defect information is used to query the dimension chain type, so as to determine the target dimension chain. The target dimension chain includes the target part and related parts, and the number of related parts is greater than or equal to zero.

[0027] Step S3, calculating the tolerance extreme value and the tolerance square root of the target dimension chain.

[0028] Specifically, according to the queried target dimension chain, the manufacturing tolerances of the target part and the two related parts in the target dimension chain are obtained. For example, the target parts are part A and part B, and the related parts are part C and part D, and the corresponding manufacturing tolerances are a, b, c, and d, respectively. Then the tolerance extreme value PE m The sum of a, b, c, and d, the square root of the tolerance PE r for a 2 、b 2 、c 2 d 2 The square root of the sum,

[0029] PE m=a+b+c+d;

[0030] PE r =a 2 +b 2 +c 2 +d 2 .

[0031] Step S4, comparing the matching tolerance, tolerance extreme value and tolerance square root of the target dimension chain, and outputting a matching tolerance defect when both the tolerance extreme value and the tolerance square root are greater than the matching tolerance.

[0032] Specifically, the matching tolerance is the definition tolerance of the target dimension chain. The matching tolerance, tolerance extreme value and tolerance square root of the target dimension chain are compared. When the tolerance extreme value is greater than the matching tolerance and the tolerance square root is greater than the matching tolerance, it is judged that the matching tolerance setting is unreasonable and the matching tolerance of the target dimension chain needs to be redefined.

[0033] For example, the flatness requirement of part A and part B is ±1mm, and the manufacturing tolerance of part A is a=1.5mm, and the manufacturing tolerance of part B is b=0.5mm. The matching tolerance is defined as 1.5mm. When the matching tolerance is greater than 1.5mm, it is judged as a defect. The tolerance extreme value a+b=2mm, the square root of the tolerance The tolerance requirement of part A is 1.58 mm, which is greater than the matching tolerance of 1.5 mm. At this time, a matching tolerance defect is output. The solution to this problem is to redefine the tolerance requirement of part A in combination with the process flow of part A.

[0034] Step S5, when the tolerance extreme value is less than the matching tolerance, evaluate the interference amount of the target dimension chain, and evaluate the positioning datum and assembly datum of the target dimension chain. When the interference amount of the target dimension chain is zero, and the positioning datum and assembly datum of the target dimension chain are consistent, output the part defect. When the interference amount of the target dimension chain is greater than zero, and / or the positioning datum and assembly datum of the target dimension chain are inconsistent, output the structural defect.

[0035] Specifically, when the tolerance extreme value is less than the matching tolerance, whether there is interference between the target parts and related parts in the target dimension chain, and whether the positioning datum and assembly datum of each target part and each related part are unified are evaluated based on the part position information and part structure information of the target dimension chain.

[0036] For example, the left and right gaps between the glove box and the dashboard of a certain car company are inconsistent. The theoretical gap is 1.5mm, the symmetry requirement is 0.5mm, and the actual gaps are 2.1mm on the left and 0.9mm on the right. The target dimension chain includes target parts and related parts. The target parts include the dashboard and the glove box. The related parts include the front panel of the vehicle body, the sound insulation pad in the front compartment, the air conditioner, and the dashboard bracket. According to the evaluation of the part position information and part structure information in the target dimension chain, it can be determined that there are two interferences between the sound insulation pad and the air conditioner, with an interference amount of Amm. Because the air conditioner is installed on the dashboard bracket, this interference amount will cause deformation of part of the dashboard bracket, and this partial deformation will be released to the dashboard, affecting the matching state of the dashboard and the glove box. It is necessary to confirm the values ​​of the interference between the air conditioner and the sound insulation pad in the problem dimension chain. The interference amount Amm affects the deformation of the dashboard skeleton by Bmm, affects the dashboard by Cmm, and affects the glove box by Dmm. And A>B>C>D. The posture of the glove box is deflected.

[0037] Part structure information includes part positioning datum and part assembly datum. The positioning datum and assembly datum of the target dimension chain are compared to evaluate whether they are consistent. For example, if the positioning datum of the mounting hole diameter of part E is 5mm and the assembly datum is 4mm, the positioning datum and assembly datum are inconsistent. During the assembly process, the probability of exceeding the tolerance will increase due to shaking after part E is assembled through the mounting hole, or interference with related parts will occur.

[0038] If the tolerance extreme value is smaller than the matching tolerance, there is no interference, and the positioning reference and assembly reference are unified, it is judged that the target part or related parts have out-of-tolerance defects and the part defects are output.

[0039] When the tolerance extreme value is smaller than the matching tolerance, but there is interference, and / or the positioning datum and the assembly datum are not consistent, it is judged that the target part or related parts have structural problems and the structural defects are output.

[0040] Step S61, when outputting part defects, calculate the part deviation of the target dimension chain, and determine the defective part based on the part deviation of the target dimension chain.

[0041] Specifically, when the evaluation result is a part defect, the measurement data of the target part and the related parts are obtained, and the part deviation of each part is calculated based on the obtained measurement data. For example, the target parts are part A and part B, and the related parts are part C and part D. The measurement data includes the factory measurement data of multiple parts A, multiple parts B, multiple parts C, and multiple parts D. The part deviation of part A is the mean value of the out-of-tolerance parts (N, N≤M) among the multiple parts A (M). When the mean value of the out-of-tolerance of part A is greater than 0, part A is judged to be a defective part. An out-of-tolerance part is defined as a part whose measured size is greater than the manufacturing tolerance. The mean value of the out-of-tolerance is defined as the average value of the difference between the measured sizes of multiple out-of-tolerance parts and the maximum value of the manufacturing tolerance. Then:

[0042]

[0043] Among them, A j is the mean deviation of part A, is the measured size of the i-th part A, A z is the manufacturing tolerance of part A. Similarly, obtain the measurement data of parts B, C, and D and calculate the part deviation.

[0044] In some embodiments, the part deviations of various parts are compared, and the part with the largest part deviation value is determined as the target optimized part.

[0045] Step S71, obtaining the process parameters of the defective part, and determining the target optimized part according to the process parameters of the defective part.

[0046] Specifically, the numerical value of the process parameter is proportional to the difficulty of the manufacturing process. The vehicle model database includes the parts manufacturing process, and each manufacturing process corresponds to a process parameter. The process parameters of the defective parts are compared, and the defective part with the largest process parameter value is determined as the target optimization part.

[0047] In another embodiment, after step S61, step S72 is executed to obtain the structural parameters of the defective part and determine the target optimized part according to the structural parameters of the defective part.

[0048] Specifically, the size of the part, such as length, volume, etc., is determined according to the structural parameters of the part, and the target optimized part is determined according to the size of the part. For example, the defective part with the shortest length is selected as the target optimized part. Alternatively, in another embodiment, the defective part with the largest size is selected as the target defective part.

[0049] In another embodiment, after step 5, step S62 is executed, the vehicle model database includes an over-positioning defect model and an under-positioning defect model, and when a structural defect is output, the corresponding defect model is determined according to the defect value.

[0050] Specifically, the over-positioning defect model and under-positioning defect model in the vehicle model database are preset structural models for possible over-positioning or under-positioning of the dimension chain based on experience. They include the part structural parameters (position, size, connection relationship, positioning, etc.) of the dimension chain and the reference defect value. By comparing the defect value of the target part with the reference defect value, the structural model corresponding to the defect value can be determined.

[0051] For example, the gap between the trunk guard and the trunk lock guard is under-positioned. The dimension chain includes the rear panel of the vehicle body, the trunk seal, the trunk side guard, and the trunk lock guard. In the under-positioning defect model data, the trunk side guard is under-positioned, resulting in an unstable structure. There is a three-layer sheet metal overlap position on the rear panel of the vehicle body. The interference amount at this position is 0.9mm larger than that of the two-layer sheet metal position. The previous interference affects the posture of the subsequent parts, resulting in the deformation of the unstable trunk side guard due to lack of positioning, causing the gap between the trunk guard and the trunk lock guard to be wedge-shaped.

[0052] When the target parts are the trunk measuring surface and the trunk lock guard plate, and there is a gap defect between the target parts, the measured defect value is compared with the reference defect value corresponding to the above-mentioned under-positioning defect model to determine its corresponding defect model, wherein the reference defect value is a numerical range, and when the defect value of the target part belongs to the numerical range of the reference defect value, it is judged that the corresponding structural defect is the defect model corresponding to the reference defect value.

[0053] On the other hand, a part size matching analysis device is provided, including: a receiving module, the receiving module is configured to receive input data, the input data includes a part number and defect information of a target part, the part number is used to uniquely identify the part, and the defect information includes a defect value, a defect type and a defect position; a query module, the query module includes a vehicle model database, the vehicle model database includes multiple dimension chains, and the query module determines the target dimension chain and its matching tolerance according to the part number and the defect information; a calculation module, the calculation module is used to calculate the tolerance extreme value and the tolerance square root of the target dimension chain; a first evaluation module, the first evaluation module is used to evaluate the target dimension chain. The matching tolerance, tolerance extreme value and tolerance square root of the target dimension chain are outputted, when the tolerance extreme value and the tolerance square root are both greater than the matching tolerance, the matching tolerance defect is outputted, and when the tolerance extreme value is less than the matching tolerance, the structural evaluation instruction is outputted; the second evaluation module, the second evaluation module evaluates the interference amount of the target dimension chain in response to the structural evaluation instruction, and evaluates the positioning datum and assembly datum of the target dimension chain, when the interference amount of the target dimension chain is zero, and the positioning datum and assembly datum of the target dimension chain are consistent, the part defect is outputted, and when the interference amount of the target dimension chain is greater than zero, and / or the positioning datum and assembly datum of the target dimension chain are inconsistent, the structural defect is outputted.

[0054] Specifically, the receiving module is used to receive input data from the user, and the input data is used to provide a query basis for the target dimension chain and a judgment basis for the defect type.

[0055] The query module is connected to the receiving module to realize the reception of input data, that is, the query module queries the target dimension chain according to the part number and defect information of the received target part. The vehicle model database is configured to include multiple vehicle model data units, each vehicle model data unit includes all structural parameters of its corresponding vehicle model, each vehicle model data unit also includes all dimension chains belonging to the vehicle model, each dimension chain includes at least two parts, and the dimensions of each related part in the dimension chain are arranged end to end in a certain order to form a closed dimension group, and each dimension chain includes the part number, part position information, part structure information (including positioning reference, assembly reference, size, shape, etc.), part tolerance, matching tolerance and dimension chain type of all parts constituting the dimension chain. Dimension chain types include linear dimension chains, parallel dimension chains, etc. Those skilled in the art can understand that any part in the vehicle model can belong to different dimension chains. The query module queries the corresponding target dimension chain from the vehicle database according to the part number and defect of the target part.

[0056] The calculation module is connected to the query module. The calculation module obtains the target dimension chain from the vehicle model database through the query module. The calculation module obtains all data information of the target dimension chain, such as part numbers, part location information, part structure information, part tolerances, matching tolerances, and dimension chain types of all parts of the target dimension chain. The calculation module is used to calculate the obtained target dimension chain to determine the tolerance extreme value and tolerance square root of the target dimension chain.

[0057] The first evaluation module is connected to the calculation module to receive the tolerance extreme value and the tolerance square root of the target dimension chain. The first evaluation module receives the matching tolerance of the target dimension chain through the query module. The first evaluation module outputs the matching tolerance defect when the tolerance extreme value is greater than the matching tolerance and the tolerance square root is greater than the matching tolerance. Otherwise, the structural evaluation instruction is output. The structural evaluation instruction is used to control the second evaluation module to perform structural defect evaluation on the target dimension chain.

[0058] The second evaluation module is configured to receive a structural evaluation instruction and receive a target dimension chain through a query module to evaluate the positioning reference and assembly reference of the target dimension chain and the interference amount of the target dimension chain. The second evaluation module outputs a part defect or a structural defect according to the evaluation result.

[0059] In some embodiments, a detection module is further included, which calculates the part deviation in the target dimension chain in response to the received part defect, and determines the defective part according to the part deviation in the target dimension chain.

[0060] Specifically, the detection module is connected to the second evaluation module to receive the part defects output by the second evaluation module, and the detection module is used to connect to the product quality inspection system to obtain the measurement data of the parts leaving the factory. For example, the detection module obtains the target dimension chain through the query module, and obtains the measurement data through the product quality inspection system according to each part number in the target dimension chain to calculate the part deviation of the target dimension chain.

[0061] In some embodiments, it also includes an optimization target evaluation module, which obtains the process parameters of the defective part and determines the target optimized part according to the process parameters of the defective part. Specifically, the optimization target evaluation module is started in response to the received part defect, and the optimization target evaluation module is connected to the detection module to receive the defective part. The vehicle model database also includes the part manufacturing process, and the optimization target evaluation module includes a comparison table of the part manufacturing process and the process parameters. The optimization target evaluation module determines the corresponding process parameters according to the obtained part manufacturing process, and determines the target optimized part according to the value of the process parameters of the defective part, for example, the defective part with the largest process parameter is selected as the target optimized part.

[0062] In other embodiments, the optimization target evaluation module obtains the structural parameters of the defective part, and determines the target optimization part according to the structural parameters of the defective part. Specifically, the optimization target evaluation module receives the defective part through the detection module, and obtains the structural parameters of the defective part through the query module. The optimization target evaluation module determines the size of the part, such as length, volume, etc., according to the structural parameters of the part, and determines the target optimization part according to the size of the part. For example, the defective part with the shortest length is selected as the target optimization part. Or, in another embodiment, the defective part with the largest size is selected as the target defective part.

[0063] In some embodiments, the vehicle model database also includes an over-positioning defect model and an under-positioning defect model. When a structural defect is output, the corresponding defect model is determined according to the defect value.

[0064] Specifically, the over-positioning defect model and under-positioning defect model in the vehicle model database are preset structural defect models for over-positioning or under-positioning of the dimension chain based on experience, including the part structural parameters (position, size, connection relationship, positioning, etc.) of the dimension chain and the reference defect value. The query module receives the structural defects output by the second evaluation module, compares the defect value of the target dimension chain with the reference defect value, and can determine the structural defect model corresponding to the defect value.

[0065] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the present invention.

Claims

1. A part size matching analysis method, characterized in that: include: Obtaining a part number and defect information of a target part, wherein the part number is used to uniquely identify the part, and the defect information includes a defect value, a defect type, and a defect location; Determine a target dimension chain and its matching tolerance according to the part number and the defect information using a vehicle model database, wherein the vehicle model database includes a plurality of dimension chains; Calculating the tolerance extreme value and the tolerance square root of the target dimension chain; When the tolerance extreme value and the tolerance square root are both greater than the matching tolerance, a matching tolerance defect is output; When the tolerance extreme value is smaller than the matching tolerance, the interference amount of the target dimension chain is evaluated, and the positioning datum and assembly datum of the target dimension chain are evaluated. When the interference amount of the target dimension chain is zero, and the positioning datum and assembly datum of the target dimension chain are consistent, part defects are output. When the interference amount of the target dimension chain is greater than zero, and / or the positioning datum and assembly datum of the target dimension chain are inconsistent, structural defects are output.

2. The method according to claim 1, characterized in that When outputting part defects, the part deviation of the target dimension chain is calculated, and the defective part is determined according to the part deviation of the target dimension chain.

3. The method according to claim 2, characterized in that The process parameters of the part are obtained, and a target optimized part is determined according to the process parameters of the defective part.

4. The method according to claim 2, characterized in that: The structural parameters of the defective part are obtained, and the target optimized part is determined according to the structural parameters of the defective part.

5. The method according to claim 1, characterized in that The whole vehicle model database includes an over-positioning defect model and an under-positioning defect model. When a structural defect is output, the corresponding defect model is determined according to the defect value.

6. A part size matching analysis device, characterized in that: include: A receiving module, wherein the receiving module is configured to receive input data, wherein the input data includes a part number and defect information of a target part, wherein the part number is used to uniquely identify the part, and the defect information includes a defect value, a defect type, and a defect location; A query module, the query module includes a vehicle model database, the vehicle model database includes a plurality of dimension chains, and the query module determines a target dimension chain and its matching tolerance according to the part number and the defect information; A calculation module, the calculation module is used to calculate the tolerance extreme value and the tolerance square root of the target dimension chain; A first evaluation module, the first evaluation module is used to evaluate the matching tolerance, the tolerance extreme value and the tolerance square root of the target dimension chain, output a matching tolerance defect when the tolerance extreme value and the tolerance square root are both greater than the matching tolerance, and output a structural evaluation instruction when the tolerance extreme value is less than the matching tolerance; A second evaluation module, which evaluates the interference amount of the target dimension chain in response to the structural evaluation instruction, and evaluates the positioning datum and assembly datum of the target dimension chain. When the interference amount of the target dimension chain is zero, and the positioning datum and assembly datum of the target dimension chain are consistent, a part defect is output; when the interference amount of the target dimension chain is greater than zero, and / or the positioning datum and assembly datum of the target dimension chain are inconsistent, a structural defect is output.

7. The device according to claim 6, characterized in that It also includes a detection module, which calculates the part deviation in the target dimension chain in response to the received part defect, and determines the defective part according to the part deviation of the target dimension chain.

8. The device according to claim 7, characterized in that It also includes an optimization target evaluation module, which obtains the process parameters of the defective part and determines the target optimized part according to the process parameters of the defective part.

9. The device according to claim 7, characterized in that It also includes an optimization target evaluation module, which obtains structural parameters of the defective part and determines a target optimized part according to the structural parameters of the defective part.

10. The device according to claim 6, characterized in that The vehicle model database also includes an over-positioning defect model and an under-positioning defect model. When a structural defect is output, the corresponding defect model is determined according to the defect value.

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