CN103733041B - Managing device and management method - Google Patents

Abstract

The managing device (40) of the present invention obtains the measurement data group including the multiple characteristic values measured and obtain by the characteristic of the multiple measuring devices (11) workpiece to sending, and calculates the parameter of the measurement error expressed between multiple measuring devices based on this measurement data group.

Description

Managing device and management method

Technical field

The present invention relates to a kind of managing device that measurement error between measuring device used on production line is managed.

Background technology

In the past, production of articles line possesses there are the various characteristics to the workpiece as end article or intermediate to examine The inspection step looked into.This type of checks in step can use to measure the measuring device of characteristic.If the measured value that measuring device records falls In prescribed limit, then judging that goods are non-defective unit, if not falling within prescribed limit, then judging that goods are defective products.

Generally, measuring device is when measuring, longer to the process time of 1 workpiece, therefore can come with multiple measuring devices Carry out parallel processing.When using multiple measuring device to carry out parallel processing like this, the measurement error between measuring device will become asks Topic.Such as, when measuring 10 identical samples with 3 measuring devices, the measured value of each measuring device inequality sometimes.Measuring device Between this measurement error will give goods characteristic bring bigger discrete impact.It addition, measurement error is owing to meeting is because measuring The internal medium of device and the minor variations of external environment condition and increase, therefore have the tendency increased over.It is therefore desirable to early Measurement error between stage phase control survey device be corrected measuring device etc. processes.

About the supervision method of the measurement error between measuring device, there is one to carry out sense of vision by rectangular histogram and express each measurement The method of the measured value of device.Such as, if the rectangular histogram of only 1 measuring device deviates considerably from other measuring devices as (a) of Figure 13 Rectangular histogram, then can speculate that this measuring device there occurs that certain is abnormal.But in the production line of reality, do not limit and Figure 13 only occurs (a) as only 1 the visibly different situation of rectangular histogram, the most also as Figure 13 (b), the straight of each measuring device can occur Side schemes the most different situations.As the latter, only with the rectangular histogram of (b) observing Figure 13, it is to be difficult to judge to measure With presence or absence of measurement error between device.

It addition, when the rectangular histogram having 1 measuring device substantially occurs deviation as (a) of Figure 13, although it is able to confirm that Go out measurement error between measuring device with or without, but this simply just can confirm when rectangular histogram there occurs bigger deviation.Therefore, survey Measurement error between measuring device causes there occurs bigger economic loss.The reason of economic loss mentioned here is, measuring device Between measurement error increase caused by non-defective unit/defective products misjudgment.

Additionally, about the supervision method of the measurement error between measuring device, a kind of measured value to each measuring device The method that meansigma methods carries out confirming.Such as, if the rectangular histogram of only 1 measuring device (in figure shown in CH6) is relatively as (a) of Figure 14 The earth deviates the rectangular histogram of other measuring devices, then the meansigma methods of the measured value of measuring device CH6 just with the measurement of all measuring devices The average value " a " of value.Therefore can speculate that this measuring device there occurs that certain is abnormal.But in the production line of reality, do not limit Only 1 the visibly different situation of rectangular histogram as (a) of Figure 14 only occurs, the most also can occur each as Figure 14 (b) The situation that the rectangular histogram of measuring device is the most different.As the latter, only with the meansigma methods of measured value of each measuring device And the difference between the meansigma methods of the measured value of all measuring devices, is with presence or absence of the measurement error being difficult to judge between measuring device.

To this, ISO/TS16949 standard is to measuring systematic analysis (MSA；Measurement Systems Analysis) Specified.MSA is a kind of method managing certainty of measurement.As the typical example of MSA maneuver, surely there is following assessment method R& R(GRR).

[mathematical expression 1]

$\mathrm{GRR}=\frac{\sqrt{E{V}^2+A{V}^2}}{\sqrt{T{V}^2}}=\frac{\sqrt{E{V}^2+A{V}^2}}{\sqrt{P{V}^2+E{V}^2+A{V}^2}}$

Wherein, TV²It is the dispersion expressing measurement data entirety discrete case, PV²It is to express multiple goods (workpiece) are existed The dispersion of discrete case when measuring, EV has been carried out under identical conditions²It it is dispersion (the same survey expressing repeatedly discrete case The dispersion of measured value obtained by the same goods of measuring device repetitive measurement), AV²It is to express the measured value discrete case between measuring device Dispersion (every single measuring device same goods are taken multiple measurements obtained by the dispersion of meansigma methods).

And manage GRR according to following benchmark.

GRR is less than 10% qualified

GRR is 10～30% the most qualified

GRR is defective more than 30%.

It addition, patent documentation 1 discloses during a kind of mensuration at substrate size processes by asking for institute in mensuration system The random value (sum total random value) having measured value carrys out the scheme of evaluating and measuring system.Mensuration in patent documentation 1, to the system of mensuration The measurement result of result and standard test system makees linear regression respectively, then removes standard according to difference between the two The random value of mensuration system, thus evaluating and measuring system more accurately.

[prior art literature]

Patent documentation

Patent documentation 1: Japan's license bulletin " speciallyying permit No. 4272624 description ", announces on June 3rd, 2009.

Summary of the invention

[problem to be solved by this invention]

In the management having used GRR fixed for above-mentioned MSA, and in the technology that patent documentation 1 discloses, confession need to be got ready The sample analyzed the generally production stopping on production line are repeated sample and measure.It addition, the technology that patent documentation 1 discloses In also need to be measured by standard test system, the most bothersome.

The present invention is in order to solve above-mentioned problem and to research and develop, it is therefore intended that provide a kind of without stopping on production line Generally produce managing device, management method, program and record that the measurement error being easy to recognize between measuring device changes Medium.

[in order to solve the technical scheme of problem]

For solving the problems referred to above, the managing device management characteristic to workpiece on a production line of the present invention measures many Individual measuring device, it is characterised in that: the characteristic of the workpiece sent each is measured by the plurality of measuring device, and this management Device possesses: characteristic value obtaining section, obtains and is measured by the characteristic of the plurality of measuring device described workpiece to sending Obtained by multiple characteristic values；Operational part, the multiple characteristic values obtained according to described characteristic value obtaining section, calculate expression the plurality of The parameter of the measurement error between measuring device.

It addition, management method of the present invention is in order to manage the multiple measurements measured the characteristic of workpiece on a production line Device, it is characterised in that: the characteristic of the workpiece sent each is measured by the plurality of measuring device, and this management method bag Contain: characteristic value acquisition step, obtain and be measured by the characteristic of the plurality of measuring device described workpiece to sending Multiple characteristic values；Calculation step, according to the multiple characteristic values obtained in described characteristic value acquisition step, calculates expression described The parameter of the measurement error between multiple measuring devices.

It addition, the managing device of the present invention manages the multiple measuring devices measured the characteristic of workpiece on a production line, It is characterized in that: possess: characteristic value obtaining section, obtain the multiple characteristic values obtained by the plurality of measuring device；Operational part, The multiple characteristic values obtained according to described characteristic value obtaining section, calculate the ginseng of the measurement error expressed between the plurality of measuring device Number；Described operational part calculates the 1st value of the mutual relation expressed between the 1st standard deviation and the 2nd standard deviation and is used as described parameter, Wherein, described 1st standard deviation be multiple characteristic values of obtaining of described characteristic value obtaining section, between by the plurality of measuring device Measurement error standard deviation when taking 0, described 2nd standard deviation is the standard of multiple characteristic values that described characteristic value obtaining section obtains Difference.

It addition, management method of the present invention is in order to manage the multiple measurements measured the characteristic of workpiece on a production line Device, it is characterised in that: comprise: characteristic value acquisition step, obtain the multiple characteristic values obtained by the plurality of measuring device；Fortune Calculate step, according to the multiple characteristic values obtained in described characteristic value acquisition step, calculate between the plurality of measuring device of expression The parameter of measurement error, in described calculation step, calculate the mutual relation expressed between the 1st standard deviation and the 2nd standard deviation The 1st value be used as described parameter, wherein, described 1st standard deviation be in described characteristic value acquisition step obtain multiple characteristics Value, standard deviation time measurement error between by the plurality of measuring device takes 0, described 2nd standard deviation is described characteristic value The standard deviation of multiple characteristic values that obtaining section obtains.

[invention effect]

As it has been described above, the effect of the managing device of the present invention is, it is not necessary to stop generally producing on production line and just can hold The change of the measurement error recognized between measuring device of changing places.

Accompanying drawing explanation

Fig. 1 is the schematic configuration schematic diagram of the measuring device error management system of an embodiment of the present invention.

Fig. 2 is the number of units schematic diagram of the equipment that each step on production line shown in Fig. 1 is had.

Fig. 3 is the illustration of the information that data base shown in Fig. 1 is stored.

Fig. 4 is the illustration of the operation information that operation recording device of transit shown in Fig. 1 is stored.

Fig. 5 is the process chart of the measurement data obtaining section that managing device shown in Fig. 1 is possessed.

Fig. 6 is the schematic diagram of the most measured complete batch in timing statistics section.

Fig. 7 is the illustration of the information that the specification value storage part that managing device shown in Fig. 1 is possessed is stored.

Fig. 8 is the process chart of the operational part that managing device shown in Fig. 1 is possessed.

Fig. 9 is standard deviation TV and the scattergram of standard deviation PV '.

Figure 10 is the schematic diagram of a storage example of the storage part that managing device shown in Fig. 1 is possessed.

Figure 11 is the schematic diagram of the display example in the chart display process portion that managing device shown in Fig. 1 is possessed.

Figure 12 is the illustration of the chart being shown with operation content information.

Figure 13 is the diagram of histogrammic 2 kinds of examples of the measured value of each measuring device.

Figure 14 is the diagram of 2 kinds of examples of the rectangular histogram of the measured value of each measuring device and meansigma methods.

Detailed description of the invention

Hereinafter, an embodiment of the invention is described in detail in conjunction with accompanying drawing.Fig. 1 is the survey of an embodiment of the present invention The schematic configuration schematic diagram of measuring device error management system.

The measuring device error management system 1 of present embodiment possesses production line 10, measurement data collection device 20, data base 30, managing device 40, operation recording device of transit 50.

In present embodiment, production line 10 includes: the 1st～the 3rd production stage, in order to article of manufacture；Check step, right Various characteristics as the workpiece of intermediate or end article check.Fig. 2 is the number of units of the equipment that each step is had Schematic diagram.Here, in order to make the processing speed of each step generally remain constant, the 1st production stage～the 3rd production stage are gathered around respectively There are 8,3,1 production equipment, check that step has 3 measuring devices 11.In each step, multiple equipment or measuring device come real Execute parallel processing.That is, the multiple workpiece sent from the 2nd production stage are the allocated and are transmitted to 3 measuring devices 11, respectively survey The characteristic sending workpiece is measured by measuring device 11.The number of units of the measuring device 11 that inspection step is had is not limited to 3 Platform, as long as there being multiple stage.

The measurement data collection device 20 the most measured measurement data of multiple measuring devices 11 to checking that step is had It is collected, and the measurement data of collection is stored in data base 30.Fig. 3 is the illustration of the data that data base 30 is stored.For Each workpiece, measurement data collection device 20 as shown in Figure 3, arranges measurement data according to the sequential measuring date and time, And these measurement data are stored in data base 30.Measurement data comprises the following items corresponded to each other: work ID, in order to know Not this workpiece；Measuring device identification information, in order to identify the measuring device 11 that this workpiece implements inspection；The end article of this workpiece Machine numbering；Mission Number belonging to this workpiece；Characteristic value, namely corresponding with characteristic T1～this n kind characteristic of Tn survey Amount result；Date and time when measuring.

It addition, measurement data collection device 20 according to inputting the information come from not shown input unit, machine is numbered And Mission Number is stored in data base 30.That is, staff switch batch time, by input unit input machine number and Mission Number.Measurement data collection device 20 is when have received machine numbering and Mission Number, then to collected from then on Each measurement data all give the work ID of uniqueness, and generate measurement data, and measurement data be stored in data base 30.Measure number Work ID according to and the machine numbering and the Mission Number that are received are mutually corresponding.

Operation recording device of transit 50 is the device of storage operation information, comprises the letter that two categories below is mutually corresponding in operation information Breath: operation content information, it expresses the content of the operation that staff is carried out；Timing information, it is expressed this operation and is performed Date and time (regularly；Timing).Operation recording device of transit 50 stores operation letter according to the instruction that such as staff inputs Breath.Fig. 4 is the illustration of the operation information that operation recording device of transit 50 is stored.

Managing device 40 is the device being managed the measurement error checked between multiple measuring devices 11 that step is had. As it is shown in figure 1, managing device 40 possesses input unit 41, display part 42, obtains configuration part 43, measurement data obtaining section (characteristic value Obtaining section) 44, specification value storage part 45, operational part 46, data storage part 47, storage part 48, chart display process portion 49.

Input unit 41 accepts the various inputs from production line staff, and it is by inputting with points such as button, keyboard, mouses Position device, other entering apparatus are constituted.

Display part 42 is LCD(liquid crystal display), PDP(plasma display), organic EL The display units such as (electroluminescence: electroluminescent) display, it demonstrates literary composition according to the video data received The various information such as word, image.

Obtain configuration part 43, being set with reference to condition when measurement data obtaining section 44 is obtained measurement data group.Take Configuration part 43 according to being input to the information of input unit 41, statistics moment, timing statistics section are set.Set it addition, obtain Determine portion 43 have received from measurement data obtaining section 44 renewal instruct time, will from statistics the moment have passed through one statistics time Between moment after section, be set as the new statistics moment.

Measurement data obtaining section 44 obtains measurement data group from data base 30.Concrete place about measurement data obtaining section 44 Reason, illustrates below in conjunction with Fig. 5.Fig. 5 is the process chart of measurement data obtaining section 44.

First, measurement data obtaining section 44 judges when whether current time reaches the statistics obtained set by configuration part 43 Carve (S1).

If current time reaches statistics moment (being "Yes" at S1), then measurement data obtaining section 44 is special from data base 30 Make: the measurement data corresponding with the measurement date and time in the front a statistical time section from the statistics moment.Then, measure Data acquisition 44 according to measure date and time sequential, arrangement institute by specific go out measurement data, and determine whether measurement It is different that data exist on Mission Number from a measurement data thereafter.Arrange according to the sequential measuring date and time Time, last workpiece that the different measurement data on Mission Number is exactly batch is there is from latter measurement data.Therefore, survey Amount data acquisition 44 is different by determining whether that measurement data exists on Mission Number from a measurement data thereafter, Just can interpolate that whether there is the most measured complete batch in the front a statistical time section from the statistics moment.Thus, number is measured According to obtaining section 44 specific go out the N number of measurement data Mission Number (S2) mutually different from the Mission Number of latter measurement data.

Such as, as shown in Figure 6, in the front a statistical time section from the statistics moment, if Mission Number is " M2 ", " M3 " 2 batches the most measured complete, then by N specifically for 2, the most specific go out " M2 ", " M3 " these 2 Mission Numbers.

Then, measurement data obtaining section be respectively directed to the most specific go out each of N number of Mission Number, from data Storehouse reads the measurement data group being made up of all measurement data with this Mission Number, and the measurement data group that will read Output is to operational part 46(S3～S6).

Specific with step S2 go out the corresponding measurement data group of Mission Number be all exported to operational part 46(at S4 For "No") after, measurement data obtaining section 44 is just to obtaining configuration part 43 output renewal instruction.Thus, from statistics the moment through Moment after one timing statistics section is set to the new statistics moment (S7).

As described above, measurement data obtaining section 44 is for the most tested in the front a statistical time section from the statistics moment The batch measured, exports the measurement data group of each batch to operational part 46.

Specification value storage part 45 is in order to store specification value, and specification value comes district in order to the various characteristics measured for measuring device 11 Divide non-defective unit and defective products.Specification value storage part 45 stores the higher limit of specification value and at least one party of lower limit.Specification value stores Portion 45 stores the specification value set by each characteristic.Fig. 7 is the illustration of the information that specification value storage part 45 is stored.? This, specification value storage part is according to inputing to the information of input unit to store specification value.Therefore staff can be by defeated Enter portion 41 input specification value, set the specification value of various characteristic.

Operational part 46 uses the every a batch of measurement data group obtained from measurement data obtaining section 44, for each characteristic And calculate the parameter being readily susceptible to recognize 11 measurement error of measuring device respectively.That is, will survey obtained by same for repeated measurement goods The standard deviation of value is set to EV, and the standard deviation of the measured value by multiple goods measured under identical conditions (that is, expresses system The standard deviation of product discrete case) when being set to PV, operational part 64 calculates the PV ' meeting following formula, and uses according to measurement data group The PV' calculated calculates and expresses the parameter of discrete case between measuring device.

PV′²=PV²+EV²

About the concrete process of operational part 46, illustrate below in conjunction with Fig. 8.Fig. 8 is the handling process of operational part 46 Figure.

First, operational part 46, according to measurement data group, calculates statistic (S11) with regard to each characteristic.Specifically, computing Portion 46, with regard to each characteristic, all calculates meansigma methods and the standard deviation of the characteristic value that all measuring devices 11 record.Here, i-th is surveyed The characteristic value of the jth workpiece measured by measuring device is designated as xij.It addition, the individual number scale of the measuring device 11 that inspection step is had For a, and the number of the workpiece measured by ith measurement device 11 is designated as ni.Then, the characteristic value measured by all measuring devices 11 Meansigma methods ave(x) and standard deviation TV can be expressed by following mathematical expression.

[mathematical expression 2]

$\mathrm{ave}\left(x\right)\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}}{N_{\mathrm{total}}}$

[mathematical expression 3]

$\mathrm{TV}=\sqrt{\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}(\mathrm{ave}\left(x\right)-x_{\mathrm{ij}}{)}^2}{N_{\mathrm{total}}}}$

[mathematical expression 4]

$N_{\mathrm{total}}=\underset{i=1}{\overset{a}{\mathrm{\Σ}}}{n}_i$

Then, operational part 46, with regard to the various characteristics measured by ith measurement device 11, calculates spy according to following mathematical expression Meansigma methods ave(xi of property value) and standard deviation sigma (xi) (S12).

[mathematical expression 5]

$\mathrm{ave}\left(x_i\right)=\frac{\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}\left(x_{\mathrm{ij}}\right)}{n_i}$

[mathematical expression 6]

$\mathrm{\σ}\left(x_i\right)=\sqrt{\frac{\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}(\mathrm{ave}\left(x_i\right)-x_{\mathrm{ij}}{)}^2}{n_i}}$

Then, operational part 46 calculates discrete Magnification.If the standard deviation of the characteristic value between measuring device is AV, then according to discrete Additivity, formula TV²=PV²+EV²+AV²Set up.Due to PV '²=PV²+EV², then have TV²=PV '²+EV²。

Operational part 46 calculates PV ', AV according to following mathematical expression.

[mathematical expression 7]

$P{V}^{\′}=\sqrt{\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}(\mathrm{ave}\left(x_i\right)-x_{\mathrm{ij}}{)}^2}{N_{\mathrm{total}}}}$

[mathematical expression 8]

$\mathrm{AV}=\sqrt{\frac{\underset{i=1}{\overset{\mathrm{\α}}{\mathrm{\Σ}}}{n}_i(\mathrm{ave}\left(x\right)-\mathrm{ave}\left(x_i\right){)}^2}{N_{\mathrm{total}}}}$

PV ' can also pass through formula (TV²-AV²)^1/2Calculate.Alternatively, it is also possible to by averaging method/area method, discrete Other operation methods such as analysis calculate AV, PV ', TV.

Then, operational part 46 calculates discrete Magnification (S13) according to the following formula.

Discrete Magnification=TV/PV '

Discrete Magnification is that TV is divided by value obtained by PV '.If centrifugal pump 0(of the characteristic value between measuring device i.e. AV=0), The most discrete Magnification is 1.On the other hand, if the centrifugal pump of the characteristic value between measuring device has increased, discrete Magnification then becomes Value more than 1.That is, the concept expressed by discrete Magnification is:: standard deviation when there is measurement error between measuring device is measuring device Between when there is not the perfect condition of measurement error several times.

Then, the specification value (S14) of each characteristic of storage during operational part 46 reads specification value storage part 45.Then, computing Portion 46, based on the specification value read, calculates and improves fraction defective (S15).Improving fraction defective is to express current fraction defective and perfect condition Fraction defective between the value of difference.So-called perfect condition refers to that the measurement error between measuring device is 0.Current fraction defective energy according to The distribution situation of standard deviation TV calculates.On the other hand, if the measurement error between measuring device is 0, then AV=0, therefore measuring device Between measurement error be that fraction defective when 0 can calculate according to the distribution situation of standard deviation PV '.Fig. 9 is standard deviation TV and surveys The scattergram of the standard deviation PV ' when there is not measurement error between measuring device.Understand as shown in Figure 9, the less PV ' of standard deviation point In cloth, deviate from the fraction defective of specification value in being gradually reduced tendency.This means when improving fraction defective and being bigger, by surveying The corrections of measuring device etc. process and reduce the measurement error between measuring device, the most very likely reduce fraction defective.

Operational part 46 is for example with Microsoft Excel(registered trade mark) NORMDIST function calculate improvement bad Rate.NROMDIST(x, μ, σ, ture) expressed by function with regard to average value mu, the normal distribution of standard deviation sigma, calculate stochastic variable Become the probability of below x.

If setting upper limit specification value as d1, setting limit specification value is d2, if the characteristic value measured by all measuring devices 11 is flat Average is ave(x), then current fraction defective f(d1, d2, ave (x), TV) can be calculated by following formula.

F(d1, d2, ave (x), TV)=NORMDIST(d2, ave (x), TV, true)+(1-NORMDIST(d1, ave (x), TV, true))

Further, since this perfect condition that the measurement error between measuring device is 0 refers to AV=0, therefore during perfect condition Fraction defective f(d1, d2, ave (x), PV ') can be calculated by following formula.

F(d1, d2, ave (x), PV ')=NORMDIST(d2, ave (x), PV ', true)+(1-NORMDIST(d1, Ave (x), PV ', true))

Then, operational part 46 calculates according to the following formula and improves fraction defective.

Improve fraction defective=f(d1, d2, ave (x), TV)-f(d1, d2, ave (x), PV ')

If additionally, the distribution of characteristic value submits to the distribution beyond normal distribution, then operational part 46 can according to based on The cumulative distribution function of this distribution, calculates and improves fraction defective.

Like this, operational part 46 for each characteristic, all calculate the characteristic value that all measuring devices 11 record meansigma methods and Meansigma methods and standard deviation, the discrete Magnification of the characteristic value that standard deviation, every single measuring device 11 record, improve fraction defective.

The meansigma methods of the characteristic value that all measuring devices 11 that operational part 46 calculates for each characteristic record and standard deviation, The meansigma methods of the characteristic value that every single measuring device 11 records and standard deviation, discrete Magnification, improve fraction defective, by data storage part 47 are stored in storage part.Data storage part 47 is when being stored in, and the value these calculated and data below set up corresponding relation Being stored in storage part 48, these data are: in order to identify the data group ID becoming the measurement data group calculating object；Measurement data Machine numbering corresponding to Qun；Mission Number；Measure date and time.Here, data storage part 47 can be by measurement data group The measurement date and time of any one measurement data, as the measurement date and time of this measurement data group.Such as, data are deposited Portion can the survey of the measurement data that the measurement date and time of the measurement data that (the 1st) records, last (n-th) record by first The measurement date and time of the measurement data that amount date and time and the n-th/2 (if n odd number, then take (n+1)/2) record Either one, be set as the measurement date and time of this measurement data group.

Figure 10 is the diagrammatic illustration of the information that storage part 48 is stored.As shown in Figure 10, in each batch, all measuring devices The characteristic value that the meansigma methods of 11 characteristic values recorded and standard deviation (being denoted as " all " in Fig. 10), every single measuring device 11 record Meansigma methods and standard deviation, discrete Magnification, improve fraction defective and measure date and time all correspond to each other.It addition, In the drawings, " Ave " represents meansigma methods, and " Sd " represents standard deviation.

Chart display process portion 49 processes, thus demonstrates that in display part 42 timeliness expressing various parameters becomes The chart changed.When chart idsplay order is input into input unit 41, then chart display process portion 49 stores from storage part 48 Read each self-corresponding discrete Magnification of each characteristic in the middle of information, improve fraction defective, measurement date and time, and be made expression Discrete Magnification and improve the chart of Temporal changes of fraction defective.Specifically, be made transverse axis represent measure date and time and The longitudinal axis represents the chart of discrete Magnification and transverse axis represents measurement date and time and the longitudinal axis represents the chart improving fraction defective, And these charts are shown in display part 42.

It addition, chart display process portion 49 can also read each characteristic institute each in the middle of the information of storage part 48 storage The characteristic value that the meansigma methods of the self-corresponding characteristic value recorded by all measuring devices 11 and standard deviation, every single measuring device 11 record Meansigma methods and standard deviation and measure date and time, and be made the chart of the Temporal changes expressing each numerical value, and by these Chart shows in display part 42.

Figure 11 is the schematic diagram of a display example in chart display process portion 49.In fig. 11, (a) represents each characteristic The Temporal changes of discrete Magnification, (b) represents the Temporal changes improving fraction defective of each characteristic.It addition, (c) and (f) Respectively characteristic T1 being represented to the meansigma methods of each measuring device and the Temporal changes of standard deviation, (d) and (g) is respectively with regard to characteristic T2 And represent the meansigma methods of each measuring device and the Temporal changes of standard deviation, (e) and (h) represents each survey respectively with regard to characteristic T3 The meansigma methods of measuring device and the Temporal changes of standard deviation.

Chart display process portion 49 is also from operation recording device of transit 50 read operation information.Then, chart display process portion 49 In the display position of date and time shown in operation timing information, can demonstrate and this behaviour in each chart shown in Figure 11 Make the operation content information that timing information is corresponding.Figure 12 is the illustration of the chart being shown with operation content information.As shown in figure 12, Operation content information shows along time shaft, therefore by confirming discrete Magnification and to improve fraction defective be large change Operation content information shown on position, just can be readily appreciated discrete Magnification and improve the reason of changes of fraction defective.

As it has been described above, the managing device 40 of present embodiment is to the multiple measurements in order to measure characteristic on production line Device 11 is managed.On a production line, multiple workpiece are the allocated and are passed to multiple measuring device 11, and multiple measuring devices 11 are the most right The characteristic of the workpiece sent measures.Here, the measurement data obtaining section 44 of managing device 40 obtains measurement data group, This measurement data group comprises the multiple characteristics measured and obtain by the characteristic of multiple measuring devices 11 workpiece to sending Value.Further, operational part 46, based on the measurement data group obtained, calculates the parameter of the measurement error expressed between multiple measuring devices 11.

Like this, in the operation of production line, operational part 46 is according to by multiple measuring devices workpiece to sending Characteristic measure and multiple characteristic values of obtaining, calculate the parameter of the measurement error expressed between multiple measuring devices 11.Its knot Really, it is not necessary to stop generally producing on production line and be easy to recognize the measurement error between measuring device 11.

Budget portion 46 calculates expresses the 1st value of mutual relation between the 1st standard deviation (PV ') and the 2nd standard deviation (TV), and should 1st value is as described parameter.When 1st standard deviation is measurement data group, measurement error between by multiple measuring devices 11 is taken as 0 Standard deviation.2nd standard deviation is the standard deviation of this measurement data group.

Generally, it is to use standard deviation sigma to carry out step management at the scene of manufacture.Such as, step Capability index Cpk can lead to Crossing formula Cpk=(upper limit specification value-lower limit specification value)/6 σ express.The well-known part of 6 σ (six-sigma) is to fall (meansigma methods-6 σ)～(meansigma methods+6 σ) this extraneous probability is 3.4/1000000ths, and its slogan is " even if implementing 100 The operation of ten thousand times, the incidence rate of defective products is also suppressed in 3,4 times ".So, for staff, standard deviation is a kind of The parameter being very familiar to.Therefore staff has the highest consciousness to the decline degree of standard deviation.

And the GRR shown in [mathematical expression 1], its standard deviation showing that to express the dispersion corresponding to AV and EV, Ratio relative to the standard deviation in order to express all discrete case.But this is for the staff being familiar with standard deviation, It is difficult to the measurement error being visually known between measuring device.

Such as, if GRR is 30%, then staff learns that the standard deviation that the measurement error between measuring device is affected is 30%.Now, as long as the measurement error between staff may be misinterpreted as measuring device is adjusted to 0, just can be at utmost On current standard deviation is reduced to its 70%(100-30=70%).This is owing to staff takes for TV=PV+AV+ The reason of EV.That is, take for PV '/TV=1-AV/TV to calculate.It practice, the additivity of standard deviation is the most not Set up, but only set up discrete phase additivity, the most only TV²=PV²+AV²+EV²Set up.Therefore when GRR is 30%, actual On according to following mathematical expression 9 from the point of view of, if the measurement error between measuring device is adjusted to 0, the most current standard deviation maximum can reduce To its 0.954 times, but staff is but difficult to recognize this situation.

[mathematical expression 9]

$\frac{P{V}^{\′}}{\mathrm{TV}}=\sqrt{\frac{T{V}^2-A{V}^2}{T{V}^2}=\sqrt{1-\frac{A{V}^2}{T{V}^2}}}$

For staff, GRR be a kind of be difficult to recognize between measuring device the presence or absence of measurement error with The parameter of the relation between Current standards difference.Namely there is problems in that staff is difficult to recognize can be according to what of GRR Plant value and make how many standard deviations reduces.

And in present embodiment, staff will appreciate that between expression the 1st standard deviation (PV ') and the 2nd standard deviation (TV) 1st value of mutual relation.Here the 1st standard deviation is measurement data group, measurement error between by multiple measuring devices 11 takes 0 Time standard deviation.2nd standard deviation is the standard deviation of measurement data group.Here, the 2nd standard deviation (TV) is to obtain from multiple measuring devices 11 The standard deviation of the characteristic value obtained, its state is surrounded by the measurement error between measuring device 11 in being.Therefore by confirming the 1st value, just can Measurement error between being readily ascertained by compared to multiple measuring devices is taken as state when 0, and standard deviation there occurs how many change.

Specifically, the standard deviation of measured value obtained by same for repeated measurement goods is set to EV, and by multiple goods When the standard deviation of measured value is set to PV, operational part 64 calculates according to measurement data group and meets formula PV '²=PV²+EV²PV ', And use the PV' calculated to calculate the parameter of discrete case between expression measuring device.Then, chart display process portion 49 makes display Portion 42 display parameters.

Like this, in the operation of production line, operational part 46 is according to containing by multiple measuring devices sending The measurement data group of multiple characteristic values that is measured of the characteristic of workpiece, with meeting PV '²=PV²+EV²PV ' count Calculate parameter.That is, make measuring device with regard to same sample carry out standard deviation EV that repeated measurement obtains itself, be without operational part 46 Calculate.Accordingly, it is capable to use the characteristic value obtained in production line operation, demonstrate between the multiple measuring devices 11 of expression The parameter of discrete case.

Its result, it is not necessary to the measurement being easy to recognize between measuring device 11 that generally produces stopped on production line misses Difference.

Operational part 46 is by the most discrete for TV/PV' Magnification, as a parameter to calculate.As above, this discrete Magnification institute The concept expressed is:: standard deviation when there is measurement error between measuring device is to there is not the preferable shape of measurement error between measuring device During state several times.Therefore, staff, by observing discrete Magnification, just can be readily appreciated between measuring device the measurement existed Error causes standard deviation increases how many degree.

Although that in the above description, operational part 46 calculates is discrete Magnification TV/PV ' but it also may do not calculate from Dissipate Magnification TV/PV ', but calculate its inverse i.e. PV '/TV.Concept expressed by PV '/TV is:: there is not survey between measuring device When standard deviation when measuring the perfect condition of error is the current state that there is measurement error between measuring device several times.According to PV '/ TV, then staff is by confirming PV '/TV, just can be readily appreciated by the measurement error between measuring device is adjusted to 0 just Can make standard deviation reduces how many degree.

Additionally, operational part 46 is according to for judging that the good no characteristic value specification limit of workpiece calculates the 2nd value, and as Parameter.2nd value represents the mutual relation between two kinds of fraction defectives, and both fraction defectives are: the measurement error between multiple measuring devices 11 Fraction defective when taking 0, that draw according to measurement data group；And, the fraction defective drawn according to measurement data group.

Specifically, standard deviation is fallen the probability outside the normal distribution specification limit of TV by operational part 46, as standard deviation Fraction defective when being taken as TV calculates；Standard deviation is also fallen the probability outside the normal distribution specification limit of PV ' by operational part 46, makees The fraction defective being taken as during PV ' for standard deviation calculates.Then, calculate and improve fraction defective and be used as the 2nd value.Improving fraction defective is: The difference between fraction defective when fraction defective when standard deviation is taken as TV and standard deviation are taken as PV '.That is, improving fraction defective is: when Between front fraction defective and measuring device, measurement error is the difference between fraction defective during this perfect condition of 0.

Thus, staff, by confirming the 2nd value (improving fraction defective), just can be readily appreciated by by between measuring device Measurement error be adjusted to 0 that fraction defective just can be made to decline be how many.

It addition, operational part 46 calculates meansigma methods and the standard deviation of the characteristic value measured by all measuring devices, also calculate every list The meansigma methods of the characteristic value measured by individual measuring device and standard deviation.Further, chart display process portion 49 demonstrates and expresses each value The chart (seeing Figure 11) of Temporal changes.

Like this, it is possible to both shown discrete Magnification and improved fraction defective, the spy measured by every single measuring device is shown again The meansigma methods of property value and standard deviation, it is thus possible to carry out various analysis.

Such as, by confirming (a) of Figure 11, it is known that the discrete Magnification of characteristic T2 changes with high value state.Separately Outward, chart (d), (g) illustrate every single measuring device meansigma methods with regard to the measured value measured by characteristic T2 and the migration of standard deviation Situation, by confirming chart (d), (g), it is known that standard deviation each corresponding for measuring device a～c is roughly the same, but measuring device a institute Corresponding meansigma methods is relatively big both other.According to this phenomenon, the measuring device a corrector biasing when measurement characteristics T2 can be speculated Value probably occurs in that deviation.

It addition, by (a) that confirm Figure 11, it is known that the discrete Magnification of characteristic T3 changes with high value state.Figure Table (e), (h) illustrate every single measuring device meansigma methods with regard to the measured value measured by characteristic T3 and the migration situation of standard deviation, By confirming chart (e), (h), it is known that the meansigma methods corresponding to measuring device c is maximum, and the standard deviation corresponding to measuring device c is Minimum.It is said that in general, if meansigma methods is relatively big, standard deviation also can be bigger.It addition, also know that only standard deviation corresponding to measuring device c It is different from the timeliness transition of the standard deviation of other 2 measuring devices.According to this phenomenon, measuring device c can be estimated and there occurs certain Abnormal.For as loaded groove (load cell) by the contact characteristic measured of workpiece, if occur in that with The abnormal conditions of the improper contact of workpiece, the Temporal changes of standard deviation will be different from the tendency of the other.Therefore can push away Measure the generation of this type of exception.

Additionally, by (b) that confirm Figure 11, it is known that the improvement fraction defective of characteristic T3 is in only specific period (2011/3/28 To 2011/3/29,2011/4/4 to 20114/10) increase.Chart (e) illustrates every single measuring device and is surveyed with regard to characteristic T3 The meansigma methods of the measured value obtained and the migration situation of standard deviation, by confirming chart (e), it is known that the measurement of these 3 measuring devices is by mistake Difference has relatively big difference each other, and meansigma methods all there occurs decline in this specific period.According to this phenomenon, it can be appreciated that characteristic The distribution of T3 is just close to lower limit.Especially it is to be understood that relatively low characteristic T3 measured by measuring device b of meansigma methods causes bad Rate has increased and measuring device b needs to be corrected.

Chart display process portion 49, from operation information record carrier, specific goes out to represent that the operation of period is fixed in chart Time information, and in chart, above-mentioned specific go out operation timing information shown in timing show position accordingly, demonstrate with The operation content information that this operation timing information is corresponding.

Thus, just can easily speculate discrete Magnification according to operation content information and to improve the change of fraction defective former Cause.

In the above description, measurement data obtaining section 41 is the most tested in the front a statistical time section from the statistics moment The measurement data group of each batch measured, output is to operational part 46.But measurement data obtaining section 44 obtains the side of measurement data group Method is not limited to this.Such as, measurement data obtaining section 41 can also be in units of each batch, to from the statistics moment The measurement data recorded in front a statistical time section is grouped, and in units of each group, will belong to the measurement data of this group Group's output is to operational part 46.Or, measurement data obtaining section 44 can also be in the front a statistical time section from the statistics moment The all measurement data recorded are as 1 measurement data group, and output is to operational part 46.

Although illustrating not only to calculate discrete Magnification but also calculate the scheme improving fraction defective in above-mentioned, but only may be used without Calculate wherein certain side carry out the scheme shown.

The present invention is not limited to the respective embodiments described above, can carry out various change in the scope shown in claim, The embodiment being combined as in different embodiment the technical scheme that describes and obtain is also contained in the technology model of the present invention In enclosing.

It addition, each portion of the managing device 40 in the respective embodiments described above can be realized by below scheme: by CPU Arithmetic elements such as (central processing unit: central processing units) performs ROM(read only memory: read-only Memorizer) and RAM(random access memory: random access memory) etc. the program of storage in memory element, and right The communication units such as the output unit such as output unit, display or interface circuit such as keyboard are controlled.Therefore, possess and have these The computer of unit only needs have the record medium of said procedure to be read out and perform this program record, can be achieved with this enforcement The various functions of the line management device of mode and various process.It addition, by said procedure record is remembered at packaged type In recording medium, just can realize above-mentioned various functions and various process by arbitrary computer.

About this record medium, can be to supply microcomputer to carry out the not shown memorizer processed, such as, have the program of ROM etc. Media.Can also be the not shown program reading device arranged as external memory by insertion, just can be read Program medium.

No matter which kind of scheme, the program deposited preferably is accessed by microprocessor and performs.Additionally, it is preferred that below Cai Yonging Mode: read-out program is performed after being downloaded to the program storage area of microcomputer again.Here, for having carried out the program of this download Pre-deposit in the host device.

It addition, said procedure media are the record media that can separate with main frame, for instance that the band class such as tape and cartridge tape； The dish class including the CD such as magnetic plate and CD-ROM, MO, MD, DVD, CD-R such as including pliability dish and hard disk；IC-card (includes Storage card) etc. card class；Or include mask model ROM, EPROM(Erasable Programmable Read Only Memory: can EPROM), EEPROM(Electrically Erasable Programmable Read Only Memory: EEPROM), the semiconductor memory such as flash rom hold program in interior nature static Record medium etc..

If it addition, system has access to the communication networks such as the Internet, then preferably employ just as from downloaded program Hold to dynamic the record medium of program like that.

Additionally, the most as described above from downloaded program, then the most pre-for carrying out the program of this download First it is stored in host apparatus, or the program installed from other record media.

As it has been described above, the managing device of the present invention manages the multiple measurements measured the characteristic of workpiece on a production line Device, it is characterised in that: the characteristic of the workpiece sent each is measured by the plurality of measuring device, and this managing device tool Standby: characteristic value obtaining section, obtain and be measured by the characteristic of the plurality of measuring device described workpiece to sending Multiple characteristic values；Operational part, the multiple characteristic values obtained according to described characteristic value obtaining section, calculate the plurality of measuring device of expression Between the parameter of measurement error.

In such scheme, in production line operation, according to the characteristic by multiple measuring devices workpiece to sending The multiple characteristic values being measured, calculate the parameter of the measurement error expressed between multiple measuring devices.Its result, it is not necessary to stop Only the generally production on production line is easy to the measurement error recognizing between measuring device.

Additionally, the managing device of the present invention can also use below scheme: described operational part calculates expression the 1st standard deviation And the 1st value of the mutual relation between the 2nd standard deviation is used as described parameter, wherein, described 1st standard deviation is described characteristic value Multiple characteristic values that obtaining section obtains, standard deviation time measurement error between by the plurality of measuring device takes 0, described the 2 standard deviations are the standard deviations of multiple characteristic values that described characteristic value obtaining section obtains.

It addition, the managing device of the present invention manages the multiple measuring devices measured the characteristic of workpiece on a production line, It is characterized in that: possess: characteristic value obtaining section, obtain the multiple characteristic values obtained by the plurality of measuring device；Operational part, The multiple characteristic values obtained according to described characteristic value obtaining section, calculate the ginseng of the measurement error expressed between the plurality of measuring device Number；Described operational part calculates the 1st value of the mutual relation expressed between the 1st standard deviation and the 2nd standard deviation and is used as described parameter, Wherein, described 1st standard deviation be multiple characteristic values of obtaining of described characteristic value obtaining section, between by the plurality of measuring device Measurement error standard deviation when taking 0, described 2nd standard deviation is the standard of multiple characteristic values that described characteristic value obtaining section obtains Difference.

Generally, it is to use standard deviation sigma to carry out step management at the scene of manufacture, therefore for staff, marks Quasi-difference is a kind of parameter being very familiar to.So staff has the highest consciousness to the decline degree of standard deviation.

On the other hand, shown by above-mentioned GRR: in order to express the standard deviation of the dispersion corresponding to AV and EV, relatively Ratio in the standard deviation in order to express all dispersions.But this is for the staff being familiar with standard deviation, it is difficult to straight See ground and recognize the measurement error between measuring device.It is to say, for staff, GRR is that one is difficult to recognize survey The parameter of relation between presence or absence and the Current standards difference of measurement error between measuring device, therefore staff be difficult to recognize can basis It is how many which kind of value of GRR makes standard deviation reduce.

But by above-mentioned scheme, staff will be understood that and mutually closes between expression the 1st standard deviation and the 2nd standard deviation 1st value of system.1st standard deviation is the standard deviation that the measurement error between by multiple measuring devices is drawn when taking 0, the 2nd standard Difference is the standard deviation of multiple characteristic values that described characteristic value obtaining section obtains.Here, the 2nd standard deviation is to obtain from multiple measuring devices The standard deviation of characteristic value, and its state be in the measurement error that is surrounded by between measuring device.Therefore by confirming the 1st value, just can hold The measurement error between learning compared to multiple measuring devices of changing places is taken as state when 0, and standard deviation there occurs how many change.

Additionally, the managing device of the present invention can also use below scheme: be set with to judge that whether workpiece is The specification limit of the characteristic value of non-defective unit, and if characteristic value fall into described specification limit in be judged as in the case of workpiece is non-defective unit, Described operational part calculates the 2nd value be used as described parameter based on described specification limit, and wherein, described 2nd value expresses two kinds not Mutual relation between yield, the two fraction defective is: when the measurement error between by the plurality of measuring device takes 0, root The fraction defective drawn according to multiple characteristic values of described characteristic value obtaining section acquirement；And, take according to described characteristic value obtaining section Multiple characteristic values and the fraction defective that draws.

By such scheme, as long as staff confirms the 2nd value, it is easy to recognize by by the survey between measuring device It is how many that amount error transfer factor just can make fraction defective decline to 0.

Additionally, the managing device of the present invention can also use below scheme: will survey obtained by same for repeated measurement workpiece The standard deviation of value is set to EV, and when the standard deviation of the measured value of multiple workpiece measured under identical conditions is set to PV, Multiple characteristic values that described operational part obtains according to described characteristic value obtaining section, will meet formula PV '²=PV²+EV²PV ' work Calculate for described 1st standard deviation, and calculate described 2nd standard deviation TV, then using TV/PV ' or PV '/TV as described 1st value Calculate.

Below scheme can also be used: by being surveyed by i-th in the middle of multiple characteristic values of described characteristic value obtaining section acquirement The characteristic value of the jth workpiece that measuring device records is set to xij, and the number of the plurality of measuring device is set to a, also i-th is surveyed When the number of the workpiece that measuring device is measured is set to ni, described operational part is according to following mathematical expression

[mathematical expression 10]

$P{v}^{\′}=\sqrt{\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}(\mathrm{ave}\left(x_i\right)-x_{\mathrm{ij}}{)}^2}{N_{\mathrm{total}}}}$

[mathematical expression 11]

$\mathrm{TV}=\sqrt{\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}(\mathrm{ave}\left(x\right)-x_{\mathrm{ij}}{)}^2}{N_{\mathrm{total}}}}$

[mathematical expression 12]

$\mathrm{ave}\left(x\right)=\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}}{N_{\mathrm{total}}}$

[mathematical expression 13]

$\mathrm{ave}\left(x_i\right)=\frac{\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}\left(x_{\mathrm{ij}}\right)}{n_i}$

[mathematical expression 14]

$N_{\mathrm{total}}=\underset{i=1}{\overset{a}{\mathrm{\Σ}}}{n}_i$

Calculate PV' and TV.

Maybe can also use below scheme: in the middle of multiple characteristic values that described characteristic value obtaining section is obtained by i-th The characteristic value of the jth workpiece that measuring device records is set to xij, and the number of the plurality of measuring device is set to a, and by i-th When the number of the workpiece that measuring device is measured is set to ni, described operational part is according to following mathematical expression

[mathematical expression 15]

$\mathrm{TV}=\sqrt{\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}(\mathrm{ave}\left(x\right)-x_{\mathrm{ij}}{)}^2}{N_{\mathrm{total}}}}$

[mathematical expression 16]

$\mathrm{AV}=\sqrt{\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}{n}_i(\mathrm{ave}\left(x\right)-\mathrm{ave}\left(x_i\right){)}^2}{N_{\mathrm{total}}}}$

[mathematical expression 17]

$\mathrm{ave}\left(x\right)=\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}}{N_{\mathrm{total}}}$

[mathematical expression 18]

$\mathrm{ave}\left(x_i\right)=\frac{\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}\left(x_{\mathrm{ij}}\right)}{n_i}$

[mathematical expression 19]

$N_{\mathrm{total}}=\underset{i=1}{\overset{a}{\mathrm{\Σ}}}{n}_i$

[mathematical expression 20]

$P{V}^{\′}=\sqrt{T{V}^2-A{V}^2}$

Calculate PV ' and TV.

In such scheme, in production line operation, according to the characteristic by multiple measuring devices workpiece to sending The multiple characteristic values being measured, with meeting PV '²=PV²+EV²PV ' calculate parameter.That is, make measuring device the most same Sample carry out standard deviation EV that repeated measurement obtains itself, without calculating.Operate therefore, it is possible to use at production line During the characteristic value that obtains demonstrate and express the parameter of dispersion between multiple measuring devices.

It addition, as described above, for staff, GRR is that one is difficult to recognize between measuring device that measurement is by mistake The parameter of relation between presence or absence and the Current standards difference of difference, therefore staff be difficult to recognize can be according to which kind of value of GRR Standard deviation is made to reduce how many.

But in such scheme, TV/PV ' or PV '/TV is calculated as described parameter.The concept that TV/PV ' is expressed For:: Current standards difference when there is measurement error between measuring device is this perfect condition that there is not measurement error between measuring device Time several times.It addition, the concept expressed by PV '/TV is:: when there is not this perfect condition of measurement error between measuring device Standard deviation is several times of the current state that there is measurement error between measuring device.Therefore, staff by observe TV/PV ' or PV '/TV, just can be readily appreciated between measuring device the measurement error existed and cause standard deviation increases how many degree, maybe can hold Change places and recognize by the measurement error between measuring device being adjusted to 0 just can make standard deviation reduction how many degree.

Additionally, in the managing device of the present invention, described operational part preferably carries out following process (1) and (2): (1) will be anti- The standard deviation of measured value obtained by the same workpiece of repetition measurement amount is set to EV, and by the survey of multiple workpiece measured under identical conditions When the standard deviation of value is set to PV, the multiple characteristic values obtained according to described characteristic value obtaining section, calculate and meet formula PV '²= PV²+EV²PV ', and calculate standard deviation TV of multiple characteristic values that described characteristic value obtaining section obtains；(2) based on described specification Scope, calculates improving fraction defective as described 2nd value, and wherein, the described fraction defective that improves is, when standard deviation is taken as TV not The difference between fraction defective when yield and standard deviation are taken as PV '.

It addition, operational part with regard to the normal distribution of TV, standard deviation can also be fallen specification limit outside probability as standard Difference fraction defective when being taken as TV calculates, and the probability outside specification limit is fallen using standard deviation with regard to the normal distribution of PV ' as Fraction defective when standard deviation is taken as PV ' calculates.

By such scheme, staff improves fraction defective by confirmation, is easy to recognize by by measuring device Between measurement error be adjusted to 0 that fraction defective just can be made to decline be how many.

Additionally, the managing device of the present invention can also use below scheme: described operational part calculates described characteristic value and takes The meansigma methods of multiple characteristic values that the portion of obtaining obtains and standard deviation, and multiple characteristic values division that described characteristic value obtaining section is obtained Become the characteristic value measured by every single measuring device, and calculate meansigma methods and the standard of characteristic value measured by every single measuring device Difference.Thus, by confirming these meansigma methodss and standard deviation, various analysis just can be carried out.

Additionally, the managing device of the present invention can also use below scheme: described characteristic value obtaining section is with regard to each regulation Period obtain characteristic value；Described operational part calculates described parameter with regard to the period of each regulation.Thus, can easily verify that The Temporal changes of parameter.

Additionally, above-mentioned managing device can also be realized by computer.Now, computer is made to control dress as described The each portion put carrys out the control program of function and record has the computer-readable recording medium of this program to be also contained in this In the category of invention.

[industrial applicability]

The present invention can be used for the managing device being managed the measurement error between the multiple measuring devices arranged on production line.

[description of reference numerals]

1 measuring device error management system

10 production lines

11 measuring devices

20 measurement data collection devices

30 data bases

40 managing devices

41 input units

42 display parts

43 obtain configuration part

44 measurement data obtaining sections (characteristic value obtaining section)

45 specification value storage parts

46 operational parts

47 data storage parts

48 storage parts

49 chart display process portions

50 operation recording device of transits (storage device)

Claims (10)

1. a managing device, it manages the multiple measuring devices measured the characteristic of workpiece on a production line, this management dress Put and be characterised by:

The characteristic of the workpiece sent each is measured by the plurality of measuring device,

And this managing device possesses:

Characteristic value obtaining section, obtains and is measured by the characteristic of the plurality of measuring device described workpiece to sending Multiple characteristic values；

Operational part, the multiple characteristic values obtained according to described characteristic value obtaining section, calculate between the plurality of measuring device of expression The parameter of measurement error,

Described operational part calculates the 1st value of the mutual relation expressed between the 1st standard deviation and the 2nd standard deviation and is used as described ginseng Number, wherein, described 1st standard deviation be described characteristic value obtaining section obtain multiple characteristic values, when by the plurality of measuring device Between measurement error standard deviation when taking 0, described 2nd standard deviation is multiple characteristic values that described characteristic value obtaining section obtains Standard deviation.

Managing device the most according to claim 1, it is characterised in that:

Be set with to judge that whether workpiece is the specification limit of the characteristic value of non-defective unit, and if characteristic value fall into described specification model It is judged as in the case of workpiece is non-defective unit in enclosing,

Described operational part calculates the 2nd value be used as described parameter based on described specification limit, wherein, and described 2nd value expression two Planting the mutual relation between fraction defective, the two fraction defective is: the measurement error between by the plurality of measuring device takes 0 Time, the fraction defective drawn according to multiple characteristic values of described characteristic value obtaining section acquirement；Take according to described characteristic value obtaining section Multiple characteristic values and the fraction defective that draws.

Managing device the most according to claim 1, it is characterised in that:

The standard deviation of measured value obtained by same for repeated measurement workpiece is set to EV, and by measured multiple under identical conditions When the standard deviation of the measured value of workpiece is set to PV,

Multiple characteristic values that described operational part obtains according to described characteristic value obtaining section, will meet formula PV'²=PV²+EV²'s PV' calculates as described 1st standard deviation, and calculates described 2nd standard deviation TV, then using TV/PV' or PV'/TV as described 1st value calculates.

Managing device the most according to claim 3, it is characterised in that:

The spy of the jth workpiece recorded by ith measurement device in the middle of multiple characteristic values that described characteristic value obtaining section is obtained Property value is set to x_ij, and the number of the plurality of measuring device is set to a, the number of the workpiece also measured by ith measurement device is set to n_iTime,

Described operational part is according to following various

${\mathrm{PV}}^{\′}=\sqrt{\frac{\underset{i=1}{\overset{a}{\Σ}}\underset{j=1}{\overset{n_i}{\Σ}}{\left(ave\right(x_i)-x_{ij})}^2}{N_{total}}}$

$TV=\sqrt{\frac{\underset{i=1}{\overset{a}{\Σ}}\underset{j=1}{\overset{n_i}{\Σ}}{\left(ave\right(x)-x_{ij})}^2}{N_{total}}}$

$ave\left(x\right)=\frac{\underset{i=1}{\overset{a}{\Σ}}\underset{j=1}{\overset{n_i}{\Σ}}{x}_{ij}}{N_{total}}$

$ave\left(x_i\right)=\frac{\underset{j=1}{\overset{n_i}{\Σ}}\left(x_{ij}\right)}{n_i}$

$N_{total}=\underset{i=1}{\overset{a}{\Σ}}{n}_i$

Calculate PV' and TV.

Managing device the most according to claim 3, it is characterised in that:

The spy of the jth workpiece recorded by ith measurement device in the middle of multiple characteristic values that described characteristic value obtaining section is obtained Property value is set to x_ij, and the number of the plurality of measuring device is set to a, and the number of the workpiece measured by ith measurement device is set to n_iTime,

Described operational part is according to following various

$TV=\sqrt{\frac{\underset{i=1}{\overset{a}{\Σ}}\underset{j=1}{\overset{n_i}{\Σ}}{\left(ave\right(x_i)-x_{ij})}^2}{N_{total}}}$

$AV=\sqrt{\frac{\underset{i=1}{\overset{a}{\Σ}}{n}_i{\left(ave\right(x)-ave(x_i\left)\right)}^2}{N_{total}}}$

$\mathrm{ave}\left(x\right)=\frac{\underset{i=1}{\overset{a}{\mathrm{\Σ}}}\underset{j=1}{\overset{n_i}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}}{N_{\mathrm{total}}}$

$ave\left(x_i\right)=\frac{\underset{j=1}{\overset{n_i}{\Σ}}\left(x_{ij}\right)}{n_i}$

$N_{total}=\underset{i=1}{\overset{a}{\Σ}}{n}_i$

${\mathrm{PV}}^{\′}=\sqrt{{\mathrm{TV}}^2-{\mathrm{AV}}^2}$

Calculate PV' and TV.

Managing device the most according to claim 2, it is characterised in that:

Described operational part carries out following process (1) and (2):

(1) standard deviation of measured value obtained by same for repeated measurement workpiece is set to EV, and by measured under identical conditions When the standard deviation of the measured value of multiple workpiece is set to PV, the multiple characteristic values obtained according to described characteristic value obtaining section, calculate full Foot formula PV'²=PV²+EV²PV', and calculate standard deviation TV of multiple characteristic values that described characteristic value obtaining section obtains；

(2) based on described specification limit, calculate improving fraction defective as described 2nd value, wherein, described improve fraction defective It is, the difference between fraction defective when fraction defective when standard deviation is taken as TV and standard deviation are taken as PV'.

Managing device the most according to claim 6, it is characterised in that:

Described operational part using standard deviation, specification limit is fallen with regard to the normal distribution of TV outside probability as standard deviation be taken as TV time Fraction defective calculate, and the probability outside standard deviation being fallen specification limit with regard to the normal distribution of PV' is taken as standard deviation Fraction defective during PV' calculates.

Managing device the most according to claim 1, it is characterised in that:

Described operational part not only calculates described parameter, also calculates the meansigma methods of multiple characteristic values that described characteristic value obtaining section obtains And standard deviation, and multiple characteristic values that described characteristic value obtaining section obtains are divided into the characteristic measured by every single measuring device Value, and calculate meansigma methods and the standard deviation of characteristic value measured by every single measuring device.

Managing device the most according to claim 1, it is characterised in that:

Described characteristic value obtaining section obtains characteristic value with regard to the period of each regulation；

Described operational part calculates described parameter with regard to the period of each regulation.

10. a management method, it is in order to manage the multiple measuring devices measured the characteristic of workpiece on a production line, this pipe Reason method is characterised by:

The characteristic of the workpiece sent each is measured by the plurality of measuring device,

And this management method comprises:

Characteristic value acquisition step, obtains and is measured by the characteristic of the plurality of measuring device described workpiece to sending Multiple characteristic values；

Calculation step, according to the multiple characteristic values obtained in described characteristic value acquisition step, calculates the plurality of measurement of expression The parameter of the measurement error between device,

In described calculation step, the 1st value calculating the mutual relation expressed between the 1st standard deviation and the 2nd standard deviation is used as Described parameter, wherein, described 1st standard deviation be in described characteristic value acquisition step obtain multiple characteristic values, when by described Measurement error between multiple measuring devices takes standard deviation when 0, and described 2nd standard deviation is to obtain in described characteristic value acquisition step The standard deviation of multiple characteristic values.