CN107256000A - Algorithm of the improved Domain Volume than weighing manufacturing process multivariate quality ability - Google Patents
Algorithm of the improved Domain Volume than weighing manufacturing process multivariate quality ability Download PDFInfo
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- CN107256000A CN107256000A CN201710395664.6A CN201710395664A CN107256000A CN 107256000 A CN107256000 A CN 107256000A CN 201710395664 A CN201710395664 A CN 201710395664A CN 107256000 A CN107256000 A CN 107256000A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/408—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
- G05B19/4083—Adapting programme, configuration
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/35—Nc in input of data, input till input file format
- G05B2219/35356—Data handling
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Abstract
Algorithm of the improved Domain Volume than weighing manufacturing process multivariate quality ability, collect the initial data of mass property in manufacturing process, carry out data prediction, on the basis of algorithm before, covariance matrix characterizes correlation between multivariate quality, the ratio between application specification amendment volume and process volume characterize procedure quality capacity factor, and the data recorded according to control figure are sentenced steady and whether anomaly occur, find out process exception source.Process of the present invention capacity factor condition is rigorous, decision state is accurate, algorithm complex is low, the time of processing is fast, parameter processing is more rigorous, the correlation between multivariate quality is combined again, then characterize process capability function preferably to tally with the actual situation, be that subsequent manufacturing processes diagnostic techniques has established preferable basis.
Description
Technical field
The present invention relates to Mechanical Product's Machining manufacturing process Quality Control Technology field, and in particular to improved Domain Volume
Than the algorithm for weighing manufacturing process multivariate quality ability.
Background technology
21 century, along with the development of global economic integration, the competition of international market, with time and cost
Equally, quality oneself turn into enterprise's survival and development main factors concerned.Extensively using domestic and international advanced quality method and matter
Amount technology is significant for Enhancing The Product Quality In Enterprises, raising product competitiveness.Good quality is inexpensive, efficient
Rate, low-loss, the guarantee of high yield are also to win customer loyalty for a long time, and enterprise obtains the foundation stone of sustainable development.Although in
The nearest focus of state's business circles seems to concentrate in terms of merger, capital management, the market expansion, diversification, but in fact, to appointing
He Yijia is manufactured for enterprise, the control of management, the production procedure of quality, is the mostly important " interior of enterprise development
One of work("." internal strength " how is perfected, thought, the ways and means of quality management is not only needed, with greater need for there is quality engineering skill
The support of art.How quality engineering technology is utilized, design and produce inexpensive, the short cycle, high-quality, high reliability production
Product, are derived from striving advantage unexpectedly, the problem of oneself turns into domestic and international vast theoretical research person and working people extensive concern.And carry
A high-quality technical way is exactly to carry out effective process monitoring.Because product quality is important in modern industry
Status, statistical Process Control (SPC) achieves very ten-strike in machinery, weaving, electronic product, auto lamp discrete manufacturing business,
And gradually permeated to the industry of the interval such as papermaking, oil refining, chemical industry, food and continuous manufacturing industry.Pass through the number to causing process exception
According to statistical analysis, and then the normal fluctuation and unusual fluctuations occurred in manufacturing process is made a distinction, can reached in exception
When just aobvious, the timely early warning before causing converted products unqualified, mountain this carry out guidance management operator and take correct solution in time
Certainly measure finds out abnormal cause, finally can accurately exclude abnormal factorses, therefore ensures that manufacturing process is in controlled shape all the time
State.So as to greatly reduce the generation of substandard product, it is ensured that production is smoothed out, and improves production efficiency.Based on above-mentioned need
Ask, the algorithm the invention provides improved Domain Volume than weighing manufacturing process multivariate quality ability.
The content of the invention
For the problem of quality control aspect is present between traditional vehicle, comparing weight the invention provides improved Domain Volume
Make the algorithm of process multivariate quality ability.
In order to solve the above problems, the present invention is achieved by the following technical solutions：
Step 1：The initial data of mass property in manufacturing process is collected, and necessary arrangement, simplification are carried out to the data
And calculate.
Step 2：Multivariate Quality Characteristics to critical process carry out process analysis procedure analysis；
Step 3：The data observed recorded in oneself control figure through finishing control limit, according to sentencing steady rule judgment mistake
Whether journey there is anomaly；
Step 4：According to recognition result, process exception source place is found out；
Step 5：Related personnel proposes and implemented improved measure for quality problems, solves process exception situation；
Step 6：After implementation is improved, dimension is continuous to carry out checking confirmation using control figure to procedure quality, and whether observe still has
It is abnormal, return and asked to (3) if having, manufacturing process is monitored if continuing with control figure without if.
Present invention has the advantages that：
1st, process capability coefficient condition is more rigorous, and decision state result is more accurate.
2nd, algorithm complex is low, and the time of processing is short, has obtained preferable result precision.
3rd, preferable basis has been established for subsequent manufacturing processes diagnostic techniques.
4th, the polynary characteristic between quality is considered, algorithm adaptability is stronger, more meets actual application.
5th, the more normative and reasonable of parameter factors processing, obtained value more meets the result of experience judgement.
Brief description of the drawings
The structure flow chart of Fig. 1 manufacture process controls and diagnostic techniques
Fig. 2 workshop data acquisition scheme figures of the present invention
The specification region of Fig. 3 two-dimensional process amendments and actual distribution example region figure
Embodiment
In order to solve the problem of quality control aspect between traditional vehicle is present, the present invention has been carried out in detail with reference to Fig. 1-Fig. 3
Illustrate, its specific implementation step is as follows：
Step 1：The initial data of mass property in manufacturing process is collected, and necessary arrangement, simplification are carried out to the data
And calculate.
Step 2：Multivariate Quality Characteristics to critical process carry out process analysis procedure analysis, and its specific calculating process is as follows：
In process of production, when Systematic Errors are not present in process, the quality characteristic value X of product meets normal distribution, X
∈ N (μ, σ2), wherein X is quality characteristic value, and μ is population mean, σ2It is population variance.When quality characteristic value Normal Distribution
When, its averageAlso Normal Distribution, wherein, n is sample size.According to the characteristic of normal distribution, then
P (σ of μ -3 σ ＜ X ＜ μ+3)=99.73%
That is, no matter what value μ and σ takes, and the probability that X falls between is 99.73%, that is to say, that fallen in this distribution
Outside probability there was only 0.27%.
Due to influenceing the polynary characteristic of quality, that should be carried out polynary characteristic than reassigning；
Proportion is calculated as follows：
Assuming that t ties up normal distribution Nt(μ, ∑), i.e. Xt~Nt(μ, ∑), wherein μ is population mean vector, and ∑ is covariance
Matrix, due to ∑t×tFor symmetrical matrix, therefore there is symmetrical matrix P so that
Wherein λ1, λ2..., λtFor the characteristic value of covariance matrix, it meets (λ1, λ2..., λt) ＞ 0, the i.e. polynary matter of t dimensions
The weight distribution of amount can be expressed as following formula：
Specification region for process amendment is a spheroid, and its volume calculation formula is：
Ui、LiThe bound of i-th yuan of quality factor respectively in control figure.
Complex process spheroid in actual distribution region under (1- α) confidence level is：
| ∑ | it is the covariance determinant of the multivariate quality factor.
If its correction factor is k；
ε=[(M1-μ1)2+(M2-μ2)2+…+(Mt-μt)2]1/2
Mi、μiRespectively specification figure and the mean location of real process, ε are that t ties up average difference.Another factor of influence is(Uj、Lj) be specification bound intersection point.
I.e.
In summary, process capability function is characterized as follows：
Here MCpThe C of unitary process can be analogized top, namely one be more than 1 numerical value mean process relative to rule
The fluctuation of lattice limit is smaller, means that fluctuation is larger less than 1.Equally, (1-k) measured Process Mean and desired value close to journey
Degree, larger (1-k) means Process Mean closer to desired value.
Step 3：The data observed recorded in oneself control figure through finishing control limit, according to sentencing steady rule judgment mistake
Whether journey there is anomaly, and it is described in detail below：
If process is in the control figure set up during non-statistical controlled process state with sample point and controls follow-up production
Journey, good control effect is not had not only, can be brought the forecast of mistake to enterprise on the contrary, be caused damage to enterprise.
Step 4：According to recognition result, process exception source place is found out；
Step 5：Related personnel proposes and implemented improved measure for quality problems, solves process exception situation；
Step 6：After implementation is improved, dimension is continuous to carry out checking confirmation using control figure to procedure quality, and whether observe still has
It is abnormal, return and asked to (3) if having, manufacturing process is monitored if continuing with control figure without if.
Claims (2)
1. algorithm of the improved Domain Volume than weighing manufacturing process multivariate quality ability, the present invention relates to Mechanical Product's Machining system
Make process quality control technical field, and in particular to calculation of the improved Domain Volume than weighing manufacturing process multivariate quality ability
Method, it is characterized in that, comprise the following steps：
Step 1：The initial data of mass property in manufacturing process is collected, and the data are carried out with necessary arrangement, simplifies and counts
Calculate
Step 2：Multivariate Quality Characteristics to critical process carry out process analysis procedure analysis；
Step 3：The data observed recorded in oneself control figure through finishing control limit, be according to steady rule judgment process is sentenced
No anomaly occur, it is described in detail below：
If process is in the control figure set up during non-statistical controlled process state with sample point and controls follow-up production process, no
Good control effect is not only had, the forecast of mistake can be brought to enterprise on the contrary, is caused damage to enterprise
Step 4：According to recognition result, process exception source place is found out；
Step 5：Related personnel proposes and implemented improved measure for quality problems, solves process exception situation； steps 6：
After implementation is improved, dimension is continuous to carry out checking confirmation using control figure to procedure quality, and whether still have exception, return and ask if having if observing
Extremely（3）, manufacturing process is monitored if continuing with control figure without if.
2. algorithm of the improved Domain Volume according to claim 1 than weighing manufacturing process multivariate quality ability, its
It is characterized in that the specific calculating process in step 2 described above is as follows：
Step 2：Multivariate Quality Characteristics to critical process carry out process analysis procedure analysis, and its specific calculating process is as follows：
In process of production, when Systematic Errors are not present in process, the quality characteristic value of productMeet normal distribution,, whereinIt is quality characteristic value,It is population mean,It is population variance, when quality characteristic value is obeyed
During normal distribution, its averageAlso Normal Distribution, wherein, n is sample size, according to the characteristic of normal distribution, then
I.e., no matterWithWhat value is taken,The probability fallen between is, that is to say, that fall in this distribution
Outside probability only have
Due to influenceing the polynary characteristic of quality, that should be carried out polynary characteristic than reassigning；
Proportion is calculated as follows：
Assuming thatTie up normal distribution, i.e.,, whereinIt is vectorial for population mean,For covariance
Matrix, due toFor symmetrical matrix, therefore there is symmetrical matrixSo that
WhereinFor the characteristic value of covariance matrix, it meets, i.e.,Tie up polynary matter
The weight distribution of amount can be expressed as following formula：
Specification region for process amendment is a spheroid, and its volume calculation formula is：
、Respectively in control figureThe bound of first quality factor
Complex process existsThe spheroid in actual distribution region is under confidence level：
For the covariance determinant of the multivariate quality factor
If its correction factor is；
、Respectively specification figure and the mean location of real process,Average difference is tieed up for t
Another factor of influence is,For the intersection point of specification bound
I.e.
In summary, process capability function is characterized as follows：
HereUnitary process can be analogized to, namely one be more than 1 numerical value mean process relative to specification
The fluctuation of limit is smaller, means that fluctuation is larger less than 1, equally,Measured Process Mean and desired value close to journey
Degree, it is largerMean Process Mean closer to desired value.
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Application publication date: 20171017 |