CN105184413B - A kind of optimal ageing testing time evaluation method of product considering manufacturing quality deviation loss - Google Patents
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Abstract
A kind of optimal ageing testing time evaluation method of product considering manufacturing quality deviation loss, one, quantization signifying mass deviation Type-I type and Type-II type；Two, building mortality Type-I type manufacturing defect correlation factory yield loss cost model Y0；Three, the novel flaw size of quantization truncation is distributed s1(x)；Four, novel size feature distribution s is determined2(x)；Five, non-lethal Type-II type manufacturing defect correlation warranty charges model W is constructed0；Six, determine according toThe novel size feature distribution s of size increasing law3(x)；Seven, ageing cost model C is constructedbAnd the cost model W that fails in ageing duration bb；Eight, the novel flaw size of truncation is distributed s after quantifying aging test4(x)；Nine, determine according toThe novel size feature distribution s of size increasing law5(x)；Ten, warranty charges model W in guarantee period w is constructed1；11, quantify the increased ageing expense Δ of aging test1；12, quantization ageing test environment reduces mass deviation loss Δ2；13, objective function g (b) is established,It asksDetermine optimal burning-in period.
Description
Technical field
The present invention provides a kind of optimal ageing testing time evaluation methods of product for considering manufacturing quality deviation loss, belong to
In electronic product reliability test and administrative skill field.
Background technique
Electronic product is widely used in all trades and professions of national economy, and all types of industries and consumer products mostly have electronic die
Block.The quality of electronic product and technical level are the concentrated reflections of contemporary new and high technology, increasingly fierce with market competition,
Reliability level has become the common focus of attention of terminal user and manufacturing enterprise.The reliability test and pipe of electronic product
Important supplement of the reason technology as traditional quality management, more and more by the attention of vast electronic product manufacturing enterprise and become can
By the emphasis of property system engineering technology research.
During Electronic products manufacturing, dispatch from the factory after testing experiment, the product of batch production is in the initial stage rank come into operation
The number of faults and severity of Duan Fasheng is the key that customers' perception product quality superiority and inferiority and forms consumption trust.In electronics
Product early application stage, product gradually expose the morning caused by series of problems such as design defect, manufacturing defect, faults in material
Phase failure shows higher failure rate, and has rapid downward trend feature, and tub curve shape is presented in reliability level
Shape.After the adjustment of the early stage of certain time, product reliability level constantly approaches designed reliability target, infant mortality
Changing rule influences the failure rate of electronic product serviceability limit stage great.A large amount of engineering practices show the early stage event of product
Caused by barrier is mainly the potential manufacturing defect as caused by fabrication stage mass property deviation, these potential manufacturing defect are in tradition
Quality inspection link be not easy to detect, flow into consumer's hand in the form of " up-to-standard product " and cause using initial stage
Failure relevant to time, stress brings serious quality and reliability problem.Intrinsic uncertain decision in production process
The presence of manufacturing quality deviation, influences the stability of production process, so that the quality of manufacture product is difficult to ensure, and quality inspection ring
It is horizontal using the quality and reliability of perception that the careless omission of section is further degrading customer.As it can be seen that for the product for guaranteeing batch production
Reliability level considers that manufacturing process manufacturing quality deviation information rationally designs the rings such as certificate authenticity, the screening of production end
Section is to prevent product relatively high infant mortality occur to be crucial.
Ageing test (Burn-in testing) is to be commonly used to reject initial failure product in engineering, and it is reliable to improve system
The method of property.To reduce infant mortality, aging test is used to screen and reject have mass defect, wherein burning-in period
Length directly decides the efficiency of ageing test, and the determination of optimal burning-in period is effective pass for carrying out electronic product screening test
Key.At this stage, the research about best seasoned test period, in for example specific average remaining lifetime of different constraints, specifically
Task Reliability, specific failure rate under maximum seasoned test capability etc. limits, on the one hand pay close attention to the structure of cost model,
On the other hand the warranty policy type of product is paid close attention to.It is analyzed for eliminate fault features as the optimal ageing of ultimate aim
More the improvement based on aging test to the subsequent reliability achievement or benefit guaranteed to keep in good repair or repaired, prior art scheme are ignored
The prior informations such as the mass deviations of a large amount of fabrication stage preciousnesses are also unfavorable for the manufacture for helping Corporate Identity to cause initial failure
The Critical to quality in stage eliminates initial failure from the root.With people product reliability is required it is increasingly strict, such as
The manufacturing quality deviation loss for causing the higher infant mortality of product is incorporated seasoned test period by what to be optimized, and domination characterizes
Manufacturing quality deviation loss model reflects that underlying quality fluctuation influences, and becomes the new difficulty in seasoned test period optimization field
Topic.From the hidden loss of manufacturing process quality fluctuation, define manufacturing quality deviation loss causes this patent for quality fluctuation
Manufacturing defect to production cost bring extra charge, it include dispatch from the factory test failure device yields failure costs and
2 part of warranty charges of good devices under specific warranty policy.Meanwhile it selecting the size of flaw size to be used as and portraying manufacturing defect
Qualitative character, with time stress effect, it is believed that flaw size meets certain increasing law and makes non-lethal manufacture
Defect can develop into mortality defect with high costs.In turn, increased ageing cost after the addition by measuring aging test
It is lost with the mass deviation of reduction, from the analysis of the more comprehensive optimal burning-in period of economy point expansion, with fundamentally
Make up passively uses preceding adjustment and screening exposure defect that hazard rate is made to be reduced to normal shape in traditional sense by product
The deficiency of the post of state.Invalid characteristic towards product life cycels, customer determine the sensibility of initial failure
Carry out in traditional tub curve the importance of initial failure stage failure mechanism and the estimation of law study and optimal burning-in period and
Urgency.For this purpose, The present invention gives a kind of optimal ageing testing time estimations of product for considering manufacturing quality deviation loss
Method, for assessing the loss of manufacturing process mass deviation to the influence relationship of product optimal ageing testing time.
Summary of the invention
(1) purpose of the present invention: focusing mostly on for the optimizing research of traditional infant mortality in set warranty policy and most
The narrow sense of aging test time is optimized under small cost, existing method does not fully consider the system for causing the higher infant mortality of product
The influence for making mass deviation loss, so that the optimization of seasoned time cannot fundamentally refer to independently of the source cost of fabrication stage
The problem of leading the prioritization scheme reduced for infant mortality, the verifying of manufacturing process Quality Control And Reliability caused to disconnect, this
Invention provides a kind of new optimal burning-in period evaluation method of product --- and a kind of product for considering manufacturing quality deviation loss is most
Excellent ageing testing time evaluation method.It fully considers using the prevention in advance of defect and failure as visual angle and payes attention to manufacturing process
Mass deviation information is merged with the information of convectional reliability data, by domination characterize manufacturing quality deviation loss model this
New ageing criterion, on the one hand to reflect underlying quality fluctuation, on the other hand to support the optimal ageing testing time
The development of analysis.Different deflection effects based on manufacturing defect establish dependent deviation loss analysis model, and then are considering ageing
On the basis of influence of the addition of testing experiment to constructed mass loss model, the growth of flaw size is discussed to mistake
The regulating and controlling effect of cost and maintenance cost is imitated, and the optimization analysis of the burning-in period of cost control guiding is unfolded.The present invention is abundant
The deviation loss effect for paying attention to manufacturing process defect compensates for traditional infant mortality optimization and lacks to manufacture caused by underlying fluctuation
The vacancy of sunken preventative monitoring can promote objective cognition and assessment of the vast manufacturing enterprise to the optimal ageing testing time.
(2) technical solution:
The present invention is a kind of optimal ageing testing time evaluation method of product for considering manufacturing quality deviation loss, proposition
Basic assumption is as follows:
Assuming that 1 electronic device can not be repaired.
Assuming that 2 warranty policies are freely replacement guarantee in the guarantee period.
Assuming that the ageing environment of 3 devices is approximate with normal line environment consistent.
Assuming that 4 aging tests not will lead to other any new failure modes.
Assuming that the loss of brand brought by 5 device performance degenerations is not considered.
Assuming that the qualitative character of 6 electronic devices is flaw size, belong to prestige compact nature.
Assuming that when 7 manufacturing defect sizes are greater than x ° of a certain specific critical size, it is believed that component failure.
Assuming that negative binomial distribution is obeyed in the distribution of 8 per device defect concentrations.
Based on above-mentioned it is assumed that when being tested the invention proposes a kind of optimal ageing of the product for considering manufacturing quality deviation loss
Between evaluation method, its step are as follows:
The Type-I type of step 1 quantization signifying mass deviation and two class deflection effects of Type-II type manufacturing defect；
Step 2 constructs the relevant factory yields failure costs model Y of mortality Type-I type manufacturing defect0；
Step 3 quantifies the novel flaw size distribution s of truncation after factory testing1(x)；
Step 4 determine according toThe novel size feature distribution s of size increasing law2(x)；
Step 5 constructs the relevant warranty charges model W of non-lethal Type-II type manufacturing defect0；
Step 6 determine according toThe novel size feature distribution s of size increasing law3(x)；
Step 7 constructs the ageing cost model C under ageing effectbAnd the failure cost model W in ageing duration bb；
Step 8 quantifies the novel flaw size distribution s of truncation after aging test4(x)；
Step 9 determine according toThe novel size feature distribution s of size increasing law5(x)；
Step 10 building uses the warranty charges model W in guarantee period w1；
Step 11 quantifies increased ageing expense Δ under the plan of ageing testing experiment1；
The mass deviation loss Δ reduced under step 12 quantization ageing test environment2；
Step 13 establishes objective function g (b), considers from economical angle, passes through solutionIt determines optimal old
Refine the testing time.
Wherein, two classes of the Type-I type of quantization signifying mass deviation described in step 1 and Type-II type manufacturing defect
Deflection effect refers to when describing the qualitative character of manufacturing defect with size characteristic x, given to can lead to product failure and underproof
X ° of threshold value of manufacturing defect critical size, there are different deflection effects for the different manufacturing defect of size.Defect ruler if it exists
Very little x > x °, regards such defect as the large scale feature model defect of Type-I type, corresponding defect effect are as follows: influences device system
It is horizontal to make process yields；X≤x ° of flaw size if it exists regards such defect and lacks as the manufacture of the small size features of Type-II type
It falls into, corresponding defect effect are as follows: it is horizontal to influence device reliability；The cost angle of mass deviation, there are large scale feature mortality
The unit of defect is removed, and factory is caused to test relevant yields failure costs, and there are small size features non-lethals to lack
Sunken unit equally causes recessive cost, by flaw size growth and concentrate on the initial failure stage and show, bring spy
Determine the warranty charges under warranty policy.
Wherein, the relevant factory yields failure costs of the Type-I of building mortality described in step 2 type manufacturing defect
Model Y0Refer to based on set flaw size feature distribution s0(x) and because flaw size is excessive lead to device beyond x ° of critical size
The Probability p of part failure1=Pr (x > x ° | s0(x)), influenced by mortality defect effect, electronic device be judged to it is underproof go out
Factory's yields failure costs isHere, c0For the selling price of unit device, N refers to per-unit electronics
The manufacturing defect number that device includes.
Wherein, the novel flaw size of truncation is distributed s after quantization factory testing described in step 31(x) refer to due to going out
The test that factory examines eliminates the mortality defect beyond x ° of critical size, Initial Flaw Size feature distribution s0(x) become
Change, refines and be distributed s for the size of truncation1(x), flaw size size meets x1≤x°。
Wherein, determination described in step 4 according to size increasing law novel size characteristic
It is distributed s2(x) refer to that flaw size increasing law meets RULE-1: flaw size is with coefficient k1Ratio is in present defect size size
x1(x1~s1(x)) rate increases, that is, there is relationship: dx, t=k1x1, warranty duration w is given, the defect after accordingly increasing
Size x2For
Wherein, the relevant warranty charges model W of non-lethal Type-II type manufacturing defect constructed in step 50Refer to base
Exceed x ° of the critical size Probability p for leading to component failure in the increase because of non-lethal defect or reliability defect size2, by non-
Mortality flaw size increase influence, be using the warranty charges in the guarantee periodThis
In, c1For invalidation reports of the unit device in guarantee period w.
Wherein, the determination of step 6 according toThe novel size feature distribution s of size increasing law3
(x) refer to that flaw size increasing law meets RULE-2: flaw size is with coefficient k2Ratio is in present defect size size x1(x1
~s1(x)) rate of rise increases.There is relationship: dx/dt=k2x1, defect ruler in ageing duration b, after accordingly increasing
Very little x3For
Wherein, the ageing cost model C under ageing effect is constructed in step 7bAnd the failure cost model in ageing duration b
WbIt is to respectively refer to Cb=c2+c3* b,Wherein, c3For time correlation unit time ageing at
This, c4For invalidation reports of the unit device in ageing duration b.
Wherein, the novel flaw size of truncation is distributed s after quantization aging test in step 84It (x) is the survey through aging test
Examination eliminates the segmental defect sample that size in non-lethal defect increases and exceed x ° of critical size, ageing flaw size feature point
Cloth s3(x) it changes, refines and be distributed s for the size of truncation4(x), flaw size size meets x4≤x°。
Wherein, in step 9 according toSize increasing law obtains novel size feature distribution s5
(x)。
Wherein, constructed in step 10 using the warranty charges model W in guarantee period w1ForWherein, p4To be surpassed due to the increase of non-lethal defect or reliability defect size
X ° of the critical size probability for leading to component failure out, (1-p1)N(1-p3) be small size after aging test non-lethal defect
Number (1-p1)N(1-p3)。
Wherein, increased ageing expense Δ under aging test plan in step 111Include following two parts: fixed is old
Refine experimental enviroment setting up expenses c2, the aging test expense c of time correlation3* b, the ageing expense C as in ageing durationb, i.e.,
Δ1=Cb=c2+c3*b。
Wherein, the mass deviation loss Δ reduced under ageing environment in step 122It is by measuring unit under normal environment
The loss L of poor quality of device0=Y0+W0L is lost with the mass deviation based on per device under aging test plan1=Y0+W1+Wb
Between difference determined, i.e. Δ2=L0-L1。
Wherein, the objective function g (b) established in step 13 is g (b)=Δ2-Δ1.Theoretically, g (b) is to be greater than to be equal to
0, it is just meaningful to carry out ageing test.In concrete operations, with quadratic distribution f ()=Ax2+ Bx+C is to objective function g (b)
It is fitted, i.e. decomposition g (b) is g (b)=Ab2+ Bb+C, so that it is determined that Eco-power optimal burning-in period b out*And best g
(b*) analytic solutions.
(3) side of a kind of optimal ageing testing time estimation of product for considering manufacturing quality deviation loss of the present invention
Method, using steps are as follows:
Step 1 is based on set flaw size feature distribution s0(x), it determines and exceeds critical size because flaw size is excessive
The x ° of Probability p for leading to component failure1, calculation formula is as follows,
Here, initial flaw size feature distribution s0(x) expression formula is as follows,
Step 2 gives the selling price c of per device0, determine that electronic device is sentenced through electric performance test and functional test
For underproof factory yields failure costs
Here, N refers to the manufacturing defect number that per-unit electronics device includes, and can use the classical defect building-up effect that merged
The defect concentration distribution that negative binomial distribution defines is portrayed.That is,
Wherein, λ=α γ.α is the defect building-up effect factor, and value range is between 0.5 to 5, and α value is smaller, corresponding
Building-up effect it is bigger.Correspondingly, the desired value of N
Step 3 is measured by initial size distribution s0(x) the distribution s after truncation1(x) passing through's
New size characteristic after flaw size propagation process is distributed s2(x), there is following form,
Wherein, w is given warranty duration, and the size of truncation is distributed s1(x) there is following form:
Step 4 is based on set flaw size feature distribution s2(x), it determines and exceeds x ° of critical size because flaw size is excessive
Lead to the Probability p of component failure2, formula is as follows,
Step 5 gives invalidation reports c of the per device in guarantee period w1, determine using the warranty charges in the guarantee period
Step 6 measures the distribution s after truncation1(x) passing throughFlaw size propagation process after
New size characteristic degree be distributed s3(x), there is following form,
Step 7 is based on set flaw size feature distribution s3(x), it determines and exceeds x ° of critical size because flaw size is excessive
Lead to the Probability p of component failure3, Computing Principle is as follows,
Step 8 given time relevant unit time ageing cost c3And failure of the per device in ageing duration b at
This c4, determine the ageing expense C in ageing durationb=c2+c3* relevant failure expense in b and ageing duration
Step 9 measurement is distributed s by size3(x) the distribution s after truncation4(x) passing throughDefect
New size characteristic after size propagation process is distributed s5(x), there is following form,
Here, the distribution s of truncation4(x) distribution is as follows:
Step 10 is based on set flaw size feature distribution s5(x), due to non-lethal defect or reliability defect ruler
Very little increase leads to the Probability p of component failure beyond x ° of critical size4, calculating process is as follows,
IfExistI.e.There are contradictions.
IfExistS at this time5(x) there is following shape
Formula:
IfThen
IfThen
Step 11 is determined using the warranty charges in the guarantee period
Step 12 determines increased ageing expense Δ under ageing effect1=Cb=c2+c3* b and the loss of the mass deviation of reduction
For Δ2=(Y0+W)0-(Y0+W1+Wb)。
Step 13 quadratic fit g (b)=Δ2-Δ1, determine optimal burning-in period b*And best g (b*) analytic solutions.
(4) advantage and effect:
The present invention is a kind of method of optimal ageing testing time estimation of the product for considering manufacturing quality deviation loss, excellent
Point is:
I. manufacturing quality deviation loss proposed by the present invention, the hidden loss caused by the manufacturing process quality fluctuation,
The manufacturing defect as caused by quality fluctuation is highlighted to production cost bring extra charge, and the pact completely new as one
Beam criterion is applied to the optimization of ageing testing time.
Ii. the estimation for considering the optimal burning-in period of product of manufacturing quality deviation loss is sufficiently paid attention to leading to defect and event
Hinder the prior information of the fabrication stage occurred, manufacture fluctuation has been measured for the potential shadow of initial failure with the deflection effect of defect
It rings, realizes the ageing optimization based on production process prior information, can avoid the optimization of ageing testing time independently of the fabrication stage
Source cost, make up traditional ageing test optimization and ignore the deficiency to form the manufacturing quality deviation information of initial failure, can promote
Pay attention to the prevention and control of just carrying out initial failure from the fabrication stage into manufacturing enterprise, them is helped to get rid of a large amount of initial failure shapes
The embarrassment of ageing testing experiment post can only be passed through after.
Detailed description of the invention
Fig. 1 is four stage evolution process schematic diagrames of manufacturing defect size characteristic under ageing environment.
Fig. 2 is flaw size x in different burning-in period b next stage I- stage II3Evolutionary process.
Fig. 3 is that different flaw size increasing laws divide size characteristic in different burning-in period b next stage III- stage IV
The influence comparison diagram of cloth.
Fig. 4 is L under different defect building-up effects1And L0Variation characteristic figure.
Fig. 5 is the variation characteristic figure of ageing income g (b) under different warranty durations.
Fig. 6 is flow diagram of the present invention.
Symbol description is as follows in figure:
X, x1, x3, x4, x5Refer respectively to the size characteristic value of different phase manufacturing defect
FAT refers to the abbreviation of Factory Acceptance Test, i.e. factory inspection and acceptance is tested
B refers to that ageing tests lasting duration
W refers to the warranty duration of device
L1Refer to the manufacturing quality deviation loss under ageing effect
L0Refer to the manufacturing quality deviation loss under normal use environment
G (b) refers to established objective function, and characterization is ageing income
Specific embodiment
The present invention is described in further details below in conjunction with attached drawing and example.
The present invention is a kind of optimal ageing testing time evaluation method of product for considering manufacturing quality deviation loss, step
It is as follows:
Collect the related manufacture information and reliability information of certain model computer board.It is provided by computer board design and administrative staff
Computer board actual basic cost data are c0=850 (selling prices), c1=2000 (invalidation reports in the guarantee period), c2=
18 (aging test environmental preparation expenses), c4=60 (ageing invalidation reports)；By Reliability Engineer and maintenance technician's process pair
The analysis of computer board failure, the parameter for providing the negative binomial distribution of manufacturing defect sum N obedience is λ=3, the key of flaw size
X ° of threshold value=450, the mode of flaw size are x*=220, the growth of defect proportionality coefficient k under normal operating condition1=2.5E-
05/hour, and the growth of defect proportionality coefficient k under ageing environment2=0.01.These information are the optimal old of certain model computer board
The optimization of refining testing time provides basic data abundant.
See Fig. 6, a kind of optimal ageing testing time evaluation method of product for considering manufacturing quality deviation loss of the present invention should
Specific step is as follows for method:
Step 1, which is determined, exceeds x ° of the critical size Probability p for leading to component failure because flaw size is excessive1=Pr (x >
450|s0(x)).Based on given basic data,Number determines that the manufacture caused by manufacture deviation lacks
Four sunken stage flaw size feature evolution processes, as shown in Figure 1.Determine flaw size x, x1, x3, x4, x5Feature point
Cloth.Wherein, for different burning-in period b, flaw size x in I- stage, II stage3Evolutionary process and III- stage, IV stage
Fig. 2 and Fig. 3 are shown in the influence that interior difference flaw size increasing law is distributed size characteristic respectively.
Step 2 determines that electronic device is judged to underproof factory yields financial loss through electric performance test and functional test
With
Wherein
Step 3 measures new size characteristic distribution s2(x), there is following form,
Step 4 is determined because of the excessive Probability p for leading to component failure beyond x ° of critical size of flaw size2It is as follows:
ForThe case where,
ForThe case where,
Step 5 is determined using the warranty charges in the guarantee period
Step 6 measures new size characteristic degree distribution s3(x), there is following result:
Step 7 is determined because of the excessive Probability p for leading to component failure beyond x ° of critical size of flaw size3It is as follows:
ForThe case where,
ForThe case where,
Step 8 determines the ageing expense C in ageing durationbRelevant failure expense in=18+5*b and ageing duration
Step 9 measures new size characteristic distribution s5(x).Form is as follows,
ForThe case where,
ForSituation,
Step 10 determines that the increase of non-lethal flaw size leads to the Probability p of component failure beyond x ° of critical size4.Such as
Under,
IfThen
IfThen
Step 11 is determined using the warranty charges in the guarantee period
Step 12 determines the deviation loss L under ageing effect1And L0(as follows) discusses L under different defect building-up effects1With
L0Variation characteristic, determine influence relationship of the setting of defect building-up effect parameter to manufacturing quality deviation loss, see Fig. 4.After
And the mass deviation loss for obtaining reduction under ageing effect is Δ2=L0-L1, and determine increased ageing expense and Δ1=Cb=
18+5*b。
Step 13 quadratic fit objective function g (b)=Δ2-Δ1.Determine the change of ageing income g (b) under different warranty durations
Change feature, sees Fig. 5.Wherein, the quadratic fit process of objective function g (b) with the results are shown in Table 1.
The quadratic fit process and result of 1 objective function g (b) of table
In as can be seen from Table 1, g (b*) when warranty duration is i.e. 15 months w=15*30*24 hours, ageing income
Reach and is up to g (b*)=2051.86, while the ageing duration b of corresponding length rather moderate*=18.21, for this patent institute
The reliability test of certain the model computer board discussed has certain guidance and practice significance.In addition, in table 1, in optimal ageing
Duration b*=18.21 two sides, ageing income g (b*) show different variation characteristics.b*=18.21 left side, with ageing
The increase of duration, ageing income gradually increase, but in b*=18.21 right side, with the increase of ageing duration, ageing income is anti-
And it reduces.How enterprises are set for the acceptable warranty duration of product, when determining the burning-in period that enterprise can bear
It is long.Meanwhile the spy of the influence relationship by the setting in step 12 for defect building-up effect parameter to manufacturing quality deviation loss
It begs for, it can be seen that the effect of objective measure defect building-up effect is answered when mass deviation is lost and modeled, it is optimal with objective determination
Ageing length of testing speech.
Claims (10)
1. a kind of optimal ageing testing time evaluation method of product for considering manufacturing quality deviation loss, it is characterised in that: the party
Specific step is as follows for method:
The Type-I type of step 1 quantization signifying mass deviation and two class deflection effects of Type-II type manufacturing defect；
Step 2 constructs the relevant factory yields failure costs model Y of mortality Type-I type manufacturing defect0；
Step 3 quantifies the novel flaw size distribution s of truncation after factory testing1(x)；
Step 4 determine according toThe novel size feature distribution s of size increasing law2(x)；
Step 5 constructs the relevant warranty charges model W of non-lethal Type-II type manufacturing defect0；
Step 6 determine according toThe novel size feature distribution s of size increasing law3(x)；
Step 7 constructs the ageing cost model C under ageing effectbAnd the failure cost model W in ageing duration bb；
Step 8 quantifies the novel flaw size distribution s of truncation after aging test4(x)；
Step 9 determine according toThe novel size feature distribution s of size increasing law5(x)；
Step 10 building uses the warranty charges model W in guarantee period w1；
Step 11 quantifies increased ageing expense Δ under the plan of ageing testing experiment1；
The mass deviation loss Δ reduced under step 12 quantization ageing test environment2；
Step 13 establishes objective function g (b), considers from economical angle, passes through solutionDetermine that optimal ageing is surveyed
Try the time；
Wherein, two class deviations of the Type-I type of quantization signifying mass deviation described in step 1 and Type-II type manufacturing defect
Effect refers to that giving leads to product failure and underproof manufacture lacks when describing the qualitative character of manufacturing defect with size characteristic x
X ° of critical size threshold value is fallen into, there are different deflection effects for the different manufacturing defect of size；Flaw size x > if it exists
X °, regard such defect as the large scale feature model defect of Type-I type, corresponding defect effect are as follows: influence device manufacturing processes
Yields is horizontal；X≤x ° of flaw size if it exists regards such defect as the small size features manufacturing defect of Type-II type, corresponds to
Defect effect are as follows: it is horizontal to influence device reliability；The cost angle of mass deviation, there are the lists of large scale feature mortality defect
Member is removed, and factory is caused to test relevant yields failure costs, and there are the units of small size features non-lethal defect
Equally cause recessive cost, by flaw size growth and concentrate on the initial failure stage and show, bring specific guarantee plan
Warranty charges under slightly；
Wherein, the relevant factory yields failure costs model Y of the Type-I of building mortality described in step 2 type manufacturing defect0
Refer to based on set flaw size feature distribution s0(x) and because flaw size is excessive lead to device beyond x ° of critical size threshold value
Failure Probability p 1=Pr (x > x ° | s0(x)) it, is influenced by mortality defect effect, electronic device is judged to underproof factory
Yields failure costs isIn formula, c0For the selling price of unit device, N refers to per-unit electronics device
The manufacturing defect number that part includes；
Wherein, the novel flaw size of truncation is distributed s after quantization factory testing described in step 31(x) refer to since factory is examined
The test tested eliminates the mortality defect beyond x ° of critical size threshold value, Initial Flaw Size feature distribution s0(x) become
Change, refines and be distributed s for the size of truncation1(x), flaw size size meets x1≤x°；
Wherein, determination described in step 4 according toThe novel size feature distribution s of size increasing law2
(x) refer to that flaw size increasing law meets RULE1: flaw size is with coefficient k1Ratio is in present defect size size x1(x1~
s1(x)) rate increases, that is, there is relationship: dx/dt=k1x1, guarantee period w is given, the flaw size x after accordingly increasing2For
2. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: the relevant warranty charges model W of non-lethal Type-II type manufacturing defect constructed in step 50Refer to
Lead to the probability of component failure beyond x ° of critical size threshold value based on the increase because of non-lethal defect or reliability defect size
p2, influenced by the growth of non-lethal flaw size, be using the warranty charges in the guarantee periodIn formula, c1For invalidation reports of the unit device in guarantee period w.
3. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: in step 6 determine according toThe novel size feature distribution s of size increasing law3
(x) refer to that flaw size increasing law meets RULE2: flaw size is with coefficient k2Ratio is in present defect size size x1(x1~
s1(x)) rate of rise increases, that is, there is relationship: dx/dt=k2x1, flaw size in ageing duration b, after accordingly increasing
x3For
4. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: the ageing cost model C under ageing effect is constructed in step 7bAnd the failure expense mould in ageing duration b
Type WbIt is to respectively refer to Cb=c2+c3* b,Wherein, c3For the unit time ageing of time correlation
Cost, c4For invalidation reports of the unit device in ageing duration b.
5. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: quantify the novel flaw size distribution s of truncation after aging test in step 84It (x) is through aging test
Test eliminates the segmental defect sample that size in non-lethal defect increases and exceed x ° of critical size threshold value, ageing flaw size
Feature distribution s3(x) it changes, refines and be distributed s for the size of truncation4(x), flaw size size meets x4≤x°。
6. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: in step 9 according toSize increasing law obtains novel size feature distribution s5
(x)。
7. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 2
Method, it is characterised in that: constructed in step 10 using the warranty charges model W in guarantee period w1ForWherein, p4To be exceeded due to the increase of non-lethal defect or reliability defect size
X ° of critical size threshold value leads to the probability of component failure, (1-p1)N(1-p3) be aging test after small size non-lethal defect
Number (1-p1)N(1-p3)。
8. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: increased ageing expense Δ under aging test plan in step 111Include following two parts: fixed
Aging test environmental preparation expense c2, the aging test expense c of time correlation3* b, the ageing expense C as in ageing durationb,
That is Δ1=Cb=c2+c3*b。
9. a kind of product optimal ageing testing time estimation side for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: the mass deviation loss Δ reduced under ageing environment in step 122It is by measuring unit under normal environment
The loss L of poor quality of device0=Y0+W0L is lost with the mass deviation based on per device under aging test plan1=Y0+W1+Wb
Between difference determined, i.e. Δ2=L0-L1。
10. a kind of optimal ageing testing time estimation of product for considering manufacturing quality deviation loss according to claim 1
Method, it is characterised in that: the objective function g (b) established in step 13 is g (b)=Δ2-Δ1, theoretically, g (b) is to be greater than
Equal to 0, it is just meaningful to carry out ageing test；In concrete operations, with quadratic distribution f ()=Ax2+ Bx+C is to objective function g
(b) it is fitted, i.e. decomposition g (b) is g (b)=Ab2+ Bb+C, so that it is determined that Eco-power optimal burning-in period b out*And best g
(b*) analytic solutions.
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