CN101246369B - Vehicle element size quality control system and method - Google Patents
Vehicle element size quality control system and method Download PDFInfo
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- CN101246369B CN101246369B CN2008100347670A CN200810034767A CN101246369B CN 101246369 B CN101246369 B CN 101246369B CN 2008100347670 A CN2008100347670 A CN 2008100347670A CN 200810034767 A CN200810034767 A CN 200810034767A CN 101246369 B CN101246369 B CN 101246369B
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Abstract
The invention relates to a auto components dimension precision evaluation method for method comprising dividing components dimension quality supervising into lines side checking apparatus measuring control and off-line three coordinate measuring machine supervising. According to quality and control claim of product, the line side checking apparatus and off-line three coordinate measuring machine sample the product in different time and turn, detects the sample on detection apparatus or three coordinates checker and gather measuring data, analysis the measuring results and alarm in case of defect. The computer net device manages the defect components information found in data-handling procedure and provides to relative duty terminal. A plurality of terminals can be arranged in each zone in factory. The invention provides criterion for controlling and improving auto components dimension quality, is better than traditional method in efficiency and accuracy, and can efficiently evaluate, monitor and analysis the production chain state.
Description
Technical field
The invention belongs to auto parts and components workmanship control technology field, particularly relate to a kind of auto parts size quality control system and method, be used for quality assessment of auto parts fitted position and production quality control analysis.
Background technology
Automobile is the trunk industry and the pillar of Chinese manufacturing, Domestic Automotive Industry was finished 15,556 hundred million yuan of the output values in 2006, wherein auto parts and components are finished 5,200 hundred million yuan of the output values, and the proportion of parts industry in auto industry is about 35%～36%, and expectation in 2008 will be finished 720,000,000,000 yuan of the output values.The international competition of current auto manufacturing is fierce day by day, and the quality of product becomes the core competitiveness that enterprise is ready for the challenge, and automobile making and components supplying enterprise thereof all are devoted to improve self competitive power.1% accessory size manufacturing defect brings ill effect all might for the product final user, and even reduces the market competitiveness of automobile manufacturing enterprise.Therefore, the important component part of the size quality of automobile and parts thereof control becoming complete vehicle quality.
The control of quality and raising need a quality control system and a method accurately and efficiently.For auto parts, the dimensional accuracy of assembling is main assembling quality requirement, and at present domestic main auto parts and components manufacturing plant does not all have a system and method about size quality control, though the dimensional measurement of part has adopted equipment such as three-coordinate measuring machine to carry out, and still has the drawback that quality detection device is single, control method is backward, control system is unreasonable, work efficiency is lower.The auto parts manufacture process is the process that scale is produced in batches, and present most of part manufacturing enterprise can't accomplish that 100% detects, and the evaluation of size quality can only be adopted the method for the small sample sampling observation of off-line.Therefore, come accurately auto parts fitted position quality to be estimated by the sampling of standard and the analysis of measurement data, and, be target with " data-driven quality " according to size quality control 2mm engine request, excavate useful measurement data and carry out process analysis procedure analysis, have stronger Practical significance.
The control of auto parts size quality mainly is objectively the stability of manufacture process to be estimated.Patent CN1297146A points out that the dimensional stability in the car load manufacture process is a kind of random data fluctuation, the data of this random variation are the multivariate situations that a class has a plurality of parameters, characteristics in conjunction with body work adopt the EWMA method that measurement data is analyzed, set up the evaluation index of size fluctuation quality, for the quality control of car load manufacturing dimension and raising provide foundation.
Also has similar feature for the auto parts size of forming car load, but the control device of size quality and car load are different, accessory size quality control also comprises the other cubing measurement of line control except the three-coordinate measuring machine image data that is applicable to the overall dimensions of a car monitoring.Measure control procedure for cubing, have the metering mass property of successive value.According to auto parts size quality characteristics, needing more scientific methods comes the dimensional conditions of integral body is carried out effectively evaluating, lack the dimensional conditions that reflection auto parts and components that a rational system gears to actual circumstances are made at present, also do not find the pertinent literature report.
Summary of the invention
Technical matters to be solved
Technical matters to be solved by this invention provides a kind of vehicle element size quality control system and method, can provide the evaluation in instant and stage to part manufacturing dimension quality precision, and provide accessory size quality technological ability analysis result, for the control and the raising of the quality of production provides foundation.
Technical scheme
The technical solution adopted for the present invention to solve the technical problems is: a kind of vehicle element size quality control system is provided, comprise: the part assembly checking tool is connected with three-coordinate measuring machine, the other cubing of part line is connected with the portable type measuring instrument, the output of three-coordinate measuring machine and portable type measuring instrument is connected to the data analysis computing machine, and the data analysis computing machine connects enterprise computer network device and terminal output device.
A kind of vehicle element size method of quality control comprises the following steps:
(1) measurement data sampling: the dimensional data of part measures by the other cubing of line and three-coordinate measuring machine is gathered, and the data result of measuring is sent into central computer store and handle;
(2) measurement data analysis: other cubing measurement data of line and three-coordinate measuring machine measurement data are handled respectively,, adopted average-range chart analysis, obtain mean-range chart for the other cubing measurement data of line; For the three-coordinate measuring machine measurement data, adopt the following step:
(a) adopt the EWMA method to carry out the calculating of error separating, obtain trend data and fluctuation data;
(b) obtain trend analysis figure according to trend data; According to the quality assessment of fluctuating of fluctuation data;
(c) application data is separated later fluctuation data acquisition stages 6 σ value and dimension process merit rating;
(3) problem identification: according to mean-range chart, trend analysis figure, stages 6 σ value and dimension process merit rating carry out problem identification;
(4) principal component analysis (PCA): the main pattern that provides one group of part analysis data variation;
Correlation analysis: the similarity degree between the trend of measuring point measurement data is carried out analytical calculation, analyze the relevance of size between the part zones of different;
(5) reason is determined: binding data analysis and process knowledge model, determine reason;
(6) innovative approach: propose short-term measure, long-term measure and implement to follow the tracks of according to determined reason, the tracking mode that upgrades in time is inhibited until defective, and problem is resolved.
Under the situation of off-line measurement, the time of sampling and size are very important for the assessment of quality.The present invention is directed to measuring condition commonly used, proposed to be suitable for the method for sampling of subsupplier off-line measurement quality evaluation, require to sample according to different evaluations.
Described measurement sampling comprises determining of determining of sample size and sampling time, and the determining of sample size comprises: detect for the other cubing of line, carry out assay according to the measurement sample on the same day, sample number is generally 3～6; For off-line three dimension coordinate measurement machine testing, statistical sample is at least 15～18; For production line dimension process merit rating, the integral body of getting measurement data is as sample, i.e. all numbers that begin from volume production; The determining of sampling time comprises: sample every day at a fixed time; The other cubing of line is measured sampling and can be finished continuously, is 3～6 times/class, 1～2/class of off-line three-coordinate measuring machine sample frequency; The assembly relation of specific demand is sampled as irregular sampling, and guarantees assembly relation accurately.
Described measurement data analysis is measured the data that obtain to the other cubing of line and is passed through average-range chart analysis, whether measurement result is in the upper and lower control limit judges, exceeds the control line instant alarming; The The data EWMA method that the off-line three-coordinate measuring machine obtains is handled, and garbled data finds that " exceeding design tolerance ", " fluctuation is big ", " continuous in average one side " carry out instant alarming at 10.
Measure the data that obtain for the other cubing of line, the present invention adopts average-range chart analysis.This method is made up of figure, R figure, is most important, the most frequently used control chart for the metering mass property of successive value.For figure, measurement data x can think Normal Distribution or approximate Normal Distribution.For R figure, as long as population distribution is not too asymmetric, the distribution of R does not have big variation.In addition, the statistic of figure is an average, and the accidental fluctuation that is reflected on the x is at random, and by the mean effort of average, this accidental fluctuation obtains counteracting to a certain degree; Be reflected in unusual fluctuations on the x then often in same direction, it can not offset by the mean effort of average.Therefore figure detects unusual ability height.The remolding sensitivity x figure of R figure is less better.Specifically according to the following steps:
1) Sampling Estimation: estimate according to regulation sample drawn in " measuring sampling ", suppose to have extracted m sample, comprise n measured value in each sample, promptly carried out m time and measured, the number of each part of measuring is n.Usually m is not less than 25, and n gets 3～6.
A) the average μ of estimation procedure: the average of order sampling m sample originally is respectively
Then the best estimator of the μ of process is a grand mean
Promptly
B) standard deviation sigma of estimation procedure: can estimate according to the extreme difference of m sample.If x
1, x
2..., x
mFor capacity is the sample of n, this range R is greatest measurement x
MaxWith minimum measured value x
MinPoor, i.e. R=x
Max-x
Min, sample is taken from normal population, and the estimated value of σ can be demonstrate,proved and be
Then the mean range of sample is
The estimated value of σ
C) range R: range R is relevant with process standard difference σ, therefore can come the degree of variation of control procedure by R.
Similar above-mentioned, R figure center line promptly as can be known
σ
REstimated value be
2) determine control line
A) the figure control line is determined:
Can from the control chart coefficient table, check in;
B) R figure control line is determined:
3) generate control chart: average, the extreme difference of whole samples are distinguished described point in the drawings, if within control line, the average of declarative procedure is in state of a control, has generated to analyze and has used control chart; After deterministic process is in state of a control, can prolong the figure control limit, continue sampling measurement, calculate each sample respectively with R after described point in the drawings, generate the control control chart.
4) control chart utilization: distribution and development trend thereof according to each point among the figure judge whether there is abnormal factors in the part manufacture process.
When described EWMA method is carried out error separating to detecting data, measurement sample with every day is one group, from measuring for the first time, to one group of new data computation mean value of every day, with the trend data in the recursive operation acquisition data, the number S that introduces historical data is taken as 3～5, and weighting coefficient W gets 0.2～0.5, asks difference to obtain the high-frequency fluctuation data by raw data and trend data.
For the detection data that obtained by three-coordinate measuring machine, the present invention adopts EWMA (EWMA) method to carry out the calculating of error separating.This method is introduced estimation to current measurement data with the measurement data in past by the form of weighting, thereby weakens the influence of the random signal in the measurement data, and the main trend and the pure wave that obtain data variation move situation.Specifically according to the following steps:
A) packeting average: the measurement sample with every day is one group, from measuring for the first time, to one group of new data computation mean value of every day
B) recursion is calculated: the EWMA method has following recursive operation pattern and obtains trend term in the data:
Recursive operation is suitable for the increase of data finishing in time the mask work of data, has certain real-time.The acquisition of first data is according to the fundamental formular of EWMA
(0＜w＜1) obtains, and after this just calculates fast with recursion formula.
C) key parameter of EWMA: when carrying out EWMA calculating, have the parameter of two keys to provide, these two parameters are:
1. the number S of the historical data of Yin Ruing: among the present invention, S is taken as 3～5;
2. weighting coefficient w: among the present invention, the selection of weighting coefficient has bigger influence for the accuracy of handling, when w → 0, and weight coefficient (1-w) w
j→ w represents that all data have identical power, are equivalent to simple average.When w → 1, weight coefficient (1-w) w
jGrowth with j decays rapidly, and expression has only considered that nearest data are right
Influence.For the auto parts assembling, the present invention gets 0.2～0.5.
D) fluctuation is extracted: the value of the every bit in the trends calculated sequence has been represented the trend of data variation, and the present invention obtains the high-frequency fluctuation data of a point by the method for the difference of calculating raw data and trend data.This data have reflected that under not adjustment situation the deviation of tooling device and the deviation of part are to the influence of measurement data.
Data analysis of the present invention comprises:
A) stages 6 σ estimates: for a certain size fluctuation of part, the probability that drops between μ ± 3 σ is 99.73%, can think that 6 σ are exactly the scope of change in size, and all sizes all change in this scope.Stages 6 σ reflection be the intensity of removing resulting high-frequency fluctuation after the size sudden change that factor such as artificial adjustments causes in a period of time.High 6 σ explanation production status instability need take measures to control.Application data is separated later fluctuation item when carrying out stages 6 σ calculating.
In carrying out stages 6 σ evaluation, the present invention carries out according to following step:
1. according to the regulation of the sample size of front, and, determine the statistics capacity of sample in conjunction with the concrete time (as statistics monthly);
2. calculate 6 σ values of this measuring point.
B) part manufacturing process merit rating: the technological ability evaluation of accessory size is that the whole dimension control ability of part production line is assessed.The present invention is a foundation with the three-coordinate measuring machine measurement data of auto parts, and whole measurement data in inlet postpartum are carried out statistical study, obtains with 6 σ, C
p, C
PkDimension process indexes of capability evaluation for index.Specific as follows:
1. round individual measurement sequence as analytic target;
2. to 6 σ, C
p, C
PkThe calculating of sliding obtains dynamic change sequence and each measuring point C of 6 σ
p, C
Pk
Wherein
C
PkThe grading standard: (standard is done Corresponding Countermeasures to calculating the manufacture process Capability index in view of the above)
A++ level C
Pk〉=2.0 special excellent reductions of considering cost
A+ level 2.0＞C
Pk〉=1.67 excellently should keep it
A level 1.67＞C
Pk〉=1.33 intuitive ability power are good, in stable condition, but should promote to A+ level as possible
B level 1.33＞C
Pk〉=1.0 general states are general, and the manufacture process factor has variation that the bad danger of generation is promptly arranged slightly, should utilize various resources and method that it is promoted and be the A level
C level 1.0C
Pk〉=0.67 difference manufacture process is bad more, must promote its ability
D level 0.67＞C
PkUnacceptable its ability is too poor, should consider to rectify and improve again to manufacture and design process.
3. this sequence is carried out statistical study, determine 95% fiducial interval;
4. this fiducial interval has promptly reflected the size Control level that production line can reach;
The present invention is by analyzing online other cubing image data and three-coordinate measuring machine image data, control requirement in conjunction with " accumulation of process knowledge model " and part quality that car load vehicle body manufacturing dimension quality 2mm engineering proposes, with overproof, the fluctuation big and continuous 10 be principle in average one side, treated data are screened, and sort according to the sequence of importance that measuring technique is determined, specific as follows:
Defective is judged: record data screening for the other cubing of line, the result of calculation of this time sampling observation and the control line up and down of control chart are compared, if the result outside control line, judges that this measuring point is a defective; The data that record for three-coordinate measuring machine, with following principle data processed is screened:
1. overproof: measured value exceeds design tolerance;
2. fluctuation is big: 6 σ of measured value exceed 2 times of design tolerances;
3. continuous 10 in average one side: nearest 10 survey records all are greater than or less than sample average;
Meet above-mentioned among arbitrary principle, be judged as defective.
Beneficial effect
The present invention is significantly improved than classic method efficient and precision for the control and the raising of vehicle element size quality provide foundation, can carry out effective monitoring and analysis to the production line state.
The present invention can extract the fitted position quality information timely and effectively under the situation of auto parts off-line small sample dimensional measurement, accurately estimate.The evaluation index that provides can be estimated accessory size quality and dimension process ability.By estimating and analyzing, the evaluation that can be trial production stage part production line frock status level provides foundation.Because feedback that can be promptly and accurately can shorten the size quality problem effectively and solve the cycle, accelerates the supply of material speed of new parts.And at normal production period, can carry out effective monitoring, in time pinpoint the problems and deal with problems the production line state.
The present invention is directed to the offline inspection (the other cubing of line measures and three-coordinate measuring machine is measured) in the auto parts and components production run, set up small sample measurement-analysis-evaluation-case flow process, utilize mean-range chart and measurement data error separating technology, part manufacturing dimension quality precision is provided the evaluation in instant and stage, and provide accessory size quality technological ability evaluation index, for the control and the raising of the quality of production provides foundation, be significantly improved than traditional method precision.
The present invention also is applicable to the control and the analysis of size quality in the mechanical component product assembling process that other are produced in enormous quantities, small sample detects.
Description of drawings
Fig. 1 is that hardware system of the present invention connects block diagram.
---part assembly checking tool 2---three-coordinate measuring machine 3---existing other cubing 4---portable type measuring instrument 5---data analysis computing machine 6---terminal device 7---enterprise computer network device among the figure: 1
Fig. 2 is a size Control schematic flow sheet of the present invention.
Fig. 3-a is the average that the other cubing of part line is measured 25 groups of samples; Fig. 3-b is the extreme difference that the other cubing of part line is measured 25 groups of samples.
Fig. 4-a is the trend map that part three-coordinate measuring machine original measurement result plots; Fig. 4-b is the trend map of part three-coordinate measuring machine measurement result after the EWMA method is handled.
Fig. 5 obtains whole measurement data 6 σ result of calculations of sliding for certain auto parts three dimension coordinate measurement machine monitoring, and Fig. 5-a is the objects of statistics curve that obtains; Fig. 5-b is the objects of statistics distribution plan.
Fig. 6 exchanges report for utilizing the Intranet device to be distributed to relevant functional department defect information.
Embodiment
Below in conjunction with specific embodiment, further set forth the present invention.Should be understood that these embodiment only to be used to the present invention is described and be not used in and limit the scope of the invention.Should be understood that in addition those skilled in the art can do various changes and modification to the present invention after the content of having read the present invention's instruction, these equivalent form of values fall within the application's appended claims institute restricted portion equally.
Embodiment: 1. sampling: in this example, it is 5/time that the other cubing of the line of auto parts is measured sample frequency, and every day, each produced order of classes or grades at school set time sampling 4 times, the implementation Straight Run is produced, be to obtain 8 samples every day, get 25 samples, a certain measuring point dimensional measurements on the part is performed an analysis;
It is 2/day that the three-coordinate measuring machine of part is measured sample frequency, gets 45 day data, and totally 90 perform an analysis.
2. data analysis:
(1) the mean-range chart analysis of the other cubing measurement of line
1) generate the other cubing measurement report of line, as shown in table 1.
2) calculate sample average
For example to first sample
The rest may be inferred by analogy for it.
3) calculate range R: for example to the first sample R=1.1, the rest may be inferred by analogy for it.
4) calculate grand mean of sample and average sample extreme difference
5) calculate R figure and figure control line and mapping:
Owing to comprise in the control limit of figure
So if the variation of process is all out of control, then the result of calculation of control limit is just nonsensical.
For sample size n=5, from the control chart coefficient table, check in D
3=0, D
4=2.115,
R figure control line is
The extreme difference described point of 25 samples in R figure, shown in Fig. 3-b.Can find out that from R figure whole 25 points are all in control line, so the degree of variation of process is in state of a control.
For sample size n=5, from the control chart coefficient table, check in A
2=0.577,
The control line of figure is
The average described point of 25 samples in the drawings, shown in Fig. 3-a.As we can see from the figure, whole 25 points are all in control line, so the average of process is in state of a control.
6) conclusion: the size quality of this measuring point is in state of a control on the part.
(2) the three-coordinate measuring machine measurement data is analyzed
1) data separating
Carry out the calculating of error separating with EWMA (EWMA) method in the present embodiment, the measurement report that this method generates three-coordinate measuring machine carries out packeting average, recursion is calculated and fluctuation is extracted, wherein the number S of the historical data of Yin Ruing is 4, and weighting coefficient W is 0.2～0.4.A measuring point X the results are shown in Figure 4 on this part before and after Measurement and Data Processing, the trend map that Fig. 4-a plots for the original measurement result, and Fig. 4-b is the trend map after handling through the EWMA method.
2) stages 6 σ estimates
Data are got 30-60 totally 30 measurement data, calculate 6 σ that separate back fluctuation data, and obtaining stages 6 σ evaluation of estimate is 1.78.The size fluctuation that shows this point is in ± 0.89mm.
3) production-line technique ability index
1. auto parts carry out the example that the accessory size technological ability is estimated with 6 σ that slide.To the slide calculating of 6 σ of all measuring point datas since volume production, the value of getting its 95 hundredths has 45 days as objects of statistics, and therefore 90 objects of statistics are arranged.These 90 values are carried out statistical computation, obtain statistical distribution, its 95% fiducial interval is [0.75,3.75]; Show that this production line can be effectively be controlled at 0.75-3.75 with the fluctuation of size.
Fig. 5 is the whole measurement data of the part 6 σ result of calculations of sliding.Wherein Fig. 5-a is the objects of statistics curve that obtains, and Fig. 5-b is the objects of statistics distribution plan.
2. the C of each measuring point of part
p, C
PkResult of calculation, and with standard mentioned above relatively, make an appraisal.
3. defect information is handled
According to aforementioned principle measurement data is screened, generate defect information and exchange report, as shown in Figure 6, utilize the Intranet device to be distributed to relevant functional department.After the person liable carried out case study, the proposition measure was also followed the tracks of solution.
The present invention utilizes network equipment and the output of a plurality of terminal, dimensional defects information is passed to relevant departments, and provides correlation analysis and principal component analysis (PCA) instrument in each terminal, can help the person liable to analyze, the combined process knowledge model proposes solution, implements to follow the tracks of.
The present invention also is applicable to the control and the analysis of size quality in the mechanical component product assembling process that other are produced in enormous quantities, small sample detects.
Claims (3)
1. a vehicle element size precision evaluation method comprises the following steps:
(1) measurement data sampling: the dimensional data of part is measured collection by other cubing of line and three coordinate measuring machine, the data result of measuring is sent into central computer store and handle;
(2) measurement data analysis: other cubing measurement data of line and three coordinate measuring engine measurement data are handled respectively; For the other cubing measurement data of line, adopt average-range chart analysis, obtain mean-range chart; For the three coordinate measuring engine measurement data, adopt the following step:
(a) adopt the EWMA method to carry out the calculating of error separating, obtain trend data and fluctuation data;
(b) obtain trend analysis figure according to trend data; According to the fluctuation data quality evaluation that fluctuates;
(c) application data is separated later fluctuation data acquisition stages 6 σ value and the test and appraisal of dimension process ability;
(3) problem identification: according to mean-range chart, trend analysis figure, problem identification is carried out in stages 6 σ value and the test and appraisal of dimension process ability;
(4) principal component analysis (PCA): provide the main pattern that one group of parts is analyzed data variation;
Correlation analysis: the similarity degree between the trend of measuring point measurement data is carried out analytical calculation, analyze the relevance of size between the part zones of different;
(5) reason is determined: binding data analysis and process knowledge model, determine reason;
(6) innovative approach: propose short-term measure, long-term measure and implement to follow the tracks of according to determined reason, the tracking mode that upgrades in time is inhibited until defective, and problem is resolved.
2. a kind of vehicle element size precision evaluation method according to claim 1, it is characterized in that: described measurement data analysis is measured the data that obtain to the other cubing of line and is passed through average-range chart analysis, whether measurement result be in the upper and lower control limit judge, exceed the control line instant alarming; The The data EWMA method that the off-line three coordinate measuring machine obtains is handled, during data after Screening Treatment, if find one of following situation:
(1) measured value exceeds design tolerance;
(2) 6 σ of measured value exceed 2 times of design tolerances;
(3) nearest 10 survey records all are greater than or less than sample average;
Then carry out instant alarming.
3. a kind of vehicle element size precision evaluation method according to claim 1, it is characterized in that: when described EWMA method is carried out error separating to detecting data, to one group of new data computation mean value of every day, with the trend data in the recursive operation acquisition data, the number S that introduces historical data is taken as 3～5, weighting coefficient W gets 0.2～0.5, asks difference to obtain the high-frequency fluctuation data by raw data and trend data.
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| CN112346413A (en) * | 2020-09-24 | 2021-02-09 | 成都飞机工业（集团）有限责任公司 | Method for improving production quality of aviation structural part |
| CN113343361A (en) * | 2021-06-30 | 2021-09-03 | 东风汽车集团股份有限公司 | Intelligent monitoring method, device and equipment for vehicle body size and storage medium |
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| CN1297146A (en) * | 2000-12-28 | 2001-05-30 | 上海交通大学 | Data processing method for evaluating size and quality in making car body |
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