CN107256001A - The improved algorithm for weighing manufacturing process multivariate quality ability - Google Patents
The improved algorithm for weighing manufacturing process multivariate quality ability Download PDFInfo
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- CN107256001A CN107256001A CN201710396054.8A CN201710396054A CN107256001A CN 107256001 A CN107256001 A CN 107256001A CN 201710396054 A CN201710396054 A CN 201710396054A CN 107256001 A CN107256001 A CN 107256001A
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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
The improved algorithm for 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, confidential interval calculating is carried out to parameter, before the accuracy rate of this parameter is also integrated among algorithm, covariance matrix characterizes correlation between multivariate quality, mass property to critical process carries out process analysis procedure analysis, 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 measurement manufacture
The algorithm of 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 invention provides the algorithm of improved measurement manufacturing process multivariate quality ability.
The content of the invention
For the problem of quality control aspect is present between traditional vehicle, the invention provides improved measurement manufacturing process is polynary
The algorithm of quality capability.
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.
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
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. 2
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%.
The probability of misjudgement error is divided into two classes, and one is that slave mode is judged to runaway condition, and probability is P1, two be shape out of control
State is judged to slave mode, and probability is P2。
Sample X, when in slave mode.If it is distributed as normal distribution X ∈ N (μ, σ2)；Process is in runaway condition
When, its distribution is changed, and the distribution function after change is F (x).
The upper and lower control limit for remembering control figure is respectively U, L；
P1=2 (1- Φ (λ))
P2=F (U)-F (L)
Overall error probability is P1+P2
Above formula Φ (λ) is value of the distribution function of standardized normal distribution at point λ, and λ is actual parameter in control figure, this
Concrete condition can be determined specifically.
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：
Parameter error is | λi-μi|
Characterize process capability function as follows：
Due to the influence of the factors such as machine, equipment fault, σiCan not possibly be constant always, it is all need to be to σiCarry out confidence level
Calculate, only find such confidential interval, more could accurately withdraw deposit manufacturing process ability.
It is general to use sample standard deviation s as to σiEstimation, i.e.,
So its confidential interval isConfidence level is 1- α；
So having：
Only above formula CP' two formulas meet C simultaneouslyP' >=0.9973, then the potential ability of process is to meet to require.
If process meets CP' >=0.9973, is transferred to step 3 as shown in Figure 2, otherwise carries out quality improvement, until reaching it is process
Capability index, which is met, to be required.
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. the improved algorithm for weighing manufacturing process multivariate quality ability, the present invention relates to Mechanical Product's Machining manufacturing process quality
Control technology field, and in particular to the algorithm of improved measurement manufacturing process multivariate quality ability, it is characterized in that, including following step
Suddenly：
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. the algorithm of the improved measurement manufacturing process multivariate quality ability according to claim 1, it is characterized in that, the above
Specific calculating process in the step 2 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
The probability of misjudgement error is divided into two classes, and one is that slave mode is judged to runaway condition, and probability is, two be that runaway condition is sentenced
For slave mode, probability is
Sample, when in slave mode, if it is distributed as normal distribution；Process is in runaway condition
When, its distribution is changed, and the distribution function after change is
The upper and lower control of note control figure, which is limited, is respectively 、；
Overall error probability is
Above formulaFor standardized normal distribution distribution function in pointThe value at place,For actual parameter in control figure, this tool
Body situation can be determined specifically
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：
Parameter error is
Characterize process capability function as follows：
Due to the influence of the factors such as machine, equipment fault,Can not possibly be constant always, all need pairCarry out the meter of confidence level
Calculate, only find such confidential interval, more could accurately withdraw deposit manufacturing process ability
Typically use sample standard deviationAs rightEstimation, i.e.,
So its confidential interval is, confidence level is；
So having：
Only above formulaTwo formulas are met simultaneously, then the potential ability of process is to meet to require,
If process is met, step 3 is transferred to as shown in Figure 2, quality improvement is otherwise carried out, until reaching is
Process capability index, which is met, to be required.
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Application publication date: 20171017 |