CN102662832A - Evaluation method of production process data correction software - Google Patents
Evaluation method of production process data correction software Download PDFInfo
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- CN102662832A CN102662832A CN201210074830XA CN201210074830A CN102662832A CN 102662832 A CN102662832 A CN 102662832A CN 201210074830X A CN201210074830X A CN 201210074830XA CN 201210074830 A CN201210074830 A CN 201210074830A CN 102662832 A CN102662832 A CN 102662832A
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Abstract
The invention discloses an evaluation method of production process data correction software. The evaluation method includes the steps of firstly, establishing a production process model according to a specific production process; secondly, verifying correctness of the production process model, and performing a step 3 if the result is positive; thirdly, using the production process model to simulate the production process to obtain a simulation truth value; fourthly, importing an error to the simulation truth value to obtain a simulation measured value; fifthly, inputting the simulation measured value into the correction software for correction to obtain a corrected value; and sixthly, cycling the steps from three to five according to the number of simulation test so as to obtain corrected values of multiple simulation tests, and determining reliability of the correction software according to differences between the corrected values and the corresponding simulation truth value. By the evaluation method, correction capability of a production process balance module in the software to be evaluated can be accurately and comprehensively evaluated.
Description
Technical field
The present invention relates to a kind of evaluating method, particularly a kind of evaluating method of the degree of reliability of production process data correction software.
Background technology
Factory's manufacturing execution system (Manufacturing Execution System, MES) be develop rapidly in the world over nearly 10 years, towards the production management technology and the real time information system of shop layer.MES can provide a rapid reaction, flexible, the settings that becomes more meticulous for the user, helps enterprise to reduce the cost, deliver goods on schedule, improve the quality of product and improves service quality.
At present external esbablished corporation is used the MES system has become universal phenomenon, and domestic many enterprises also begin to adopt this technology to strengthen the core competitiveness of self gradually.Return information " tomography " problem of seeing between enterprise plan layer and the process control station, the characteristics of the traditional mode of production process that China's manufacturing industry adopts for many years are that " from top to bottom " produces according to plan.Briefly be from plan layer to the production control layer: enterprise formulates the production schedule-production schedule arrival production scene-tissue production-product according to situation such as order or markets and sends with charge free.The emphasis of enterprise management informatization construction also mostly is placed on plan layer, to carry out production planning management and general issued transaction.As ERP be exactly " position " in enterprise's upper strata plan layer, be used to integrate the existing resources of production of enterprise, work out a production plan.Production control layer in lower floor, the corporate boss will adopt automated production equipment, robotization detecting instrument, automatic material flow carrying storage facilities etc. to solve the concrete production bottleneck of producing (processing procedure), realizes the robotization control of production scene.
Because the variation of market environment and the continual renovation of modern production control theory; Can a manufacturing enterprise optimumly run; Key is to make " plan " and " production " close fit; Enterprise and workshop management personnel can grasp the variation of production scene in the shortest time, make judgement and counter-measure accurately fast, guarantee that the production schedule obtains rationally and fast revising.Though ERP and on-the-spot automated system have developed into very ripe degree, because the service object of ERP system is the upper strata of business administration, generally the management process to shop layer does not provide direct and detailed support.And the function of on-the-spot automated system mainly is the monitoring of field apparatus and technological parameter, and it can provide on-the-spot to managerial personnel and detect and statistics, but itself is not management system truly.
The core of process industry production executive system (MES) is to follow the tracks of exactly logistics and to the timely fast processing of the problem in the production management, is the support that offers precise data of other application systems in other modules of production executive system or the enterprise.Thereby the logistics data management of balance is the vital functional module of production executive system.Usually the data balancing module in the MES business software has been selected the strategy of adjustment of data technology and Expert Rules, like the Business.FLEX PKS of Honeywell
TM, the Plantelligence of ASPEN Tech and SMES of China Petrochemical Industry etc.The immesurable data in production scene push away gauge through soft-measuring technique and expert and then obtain; The outlier that obviously departs from historical data is rejected automatically through the appreciable error detection technique and is utilized associated redundant data to carry out correction calculation; Compare according to workman's experience amended record data merely with tradition, it is reliable relatively and complete to calculate the data that obtain through correction software.
But whether correct and complete according to the data result after this combined balance system strategy correction, whether enough near actual value, existing business software also can't be tested and assessed voluntarily.
Summary of the invention
The present invention adopts the assessment method based on emulation, and through setting up test and appraisal object equivalence model storehouse, simulation run obtains evaluating and testing needed true value, thereby objectively evaluates and tests the degree of reliability of adjustment of data software.
A kind of evaluating method of production process data correction software may further comprise the steps:
(1) sets up model, set up the production run model according to concrete production run;
(2) if correctness of the said production run model of checking is correct execution in step (3) then;
(3) analog simulation utilizes said production run model that production run is carried out flow process emulation, obtains the emulation true value;
(4) error is introduced, and the simulation result that in step (3), obtains is introduced error, and the simulation result that obtains with error is the simulated measurement value;
(5) trimming process is input to correction software with the simulation result of being with error and proofreaies and correct, and draws corrected value;
(6) evaluation and test correction software by predetermined emulation testing number of cycles step (3)～(5), obtains the corrected value of repeatedly emulation testing, confirms the degree of reliability of correction software according to the deviation between corrected value and the corresponding simulation true value.
In the step (1), can utilize prior art to combine concrete production run and device build production run model.
As preferably; Set up production run model Graphics Application aided modeling method in the step (1); Figure in the utilization VISIO mould is as descriptive model; Utilize Custom Attributes and the database linkage function of VISIO, set up, upgrade figure Custom Attributes and through open database interconnected with database in corresponding attribute list carry out synchronously.
Verification model correctness described in the step (2) may further comprise the steps:
A, in described production run model, import production data, comprise production run cycle initial value and produce instruction;
B, obtain simulation result through model emulation;
C, simulation result is imported correction software proofread and correct and obtain correcting result;
D, correcting result and simulation result are compared, when correcting result is identical with simulation result, execution in step (3).
Because the simulation result that utilizes model emulation to obtain can think not have error; So when utilizing correction software to carry out timing; Resulting correcting result should be identical with the simulation result before proofreading and correct, and think that said production run model meets the requirements this moment, then execution in step (3).
Otherwise the simulation result before resulting correcting result and the correction is inequality, thinks that then said production run model is wrong, needs adjustment or revises said production run model, until the requirement that meets correctness.
Step (3) comprising:
A, in said production run model, carry out data inputs, comprise production run cycle initial value and produce instruction;
B, call the production run model of being set up and carry out flow process emulation, obtaining simulation result is the emulation true value, and goes back to the deposit data storehouse.
In the emulation true value, introduce error in the step (4) at random, general artificial some known, controlled errors of adding are convenient to follow-up evaluation and test to correction software.
Extent of deviation between corrected value described in the step (6) and the emulation true value correctly detects the average level that the probability of appreciable error, average degree that the simulated measurement value departs from the emulation true value and corrected value depart from the emulation true value through correction software and confirms.
If correction software is reliable, then corrected value should be consistent with the emulation true value, promptly through the correction software error introduced of step (4) of having eliminated example.But be to have deviation between corrected value and the emulation true value sometimes, promptly do not have the error that complete removal process (4) is introduced through correction software, so, the deviation more greatly then correction software degree of reliability is poor more.
Described correction software correctly detects the probability of appreciable error:
Described simulated measurement value departs from the average degree of emulation true value:
Described corrected value departs from the average level of emulation true value:
The correction software level of corrections:
Wherein:
The number of the appreciable error that emulation produces is the number that has the variable of appreciable error in the simulated measurement value;
The number of proofreading and correct appreciable error is after proofreading and correct through correction software, the number of the variable that has appreciable error that is identified or proofreaies and correct;
Ns is the emulation testing number of times, i.e. the cycle index of step (3)～(5);
N is the node number in the said production run model, and node promptly possibly introduced equipment, instrument, jar of error etc. in actual production;
I is a sequence number of distinguishing corresponding variable with each node, all corresponding variable of each node;
K is the sequence number of number of corrections, i.e. the number of times sequence number of step (5) execution;
T
I, kIt is the emulation true value of i variable the k time;
M
I, kIt is the simulated measurement value of i variable the k time;
R
I, kIt is the corrected value of i variable the k time.
Wherein correctly to detect the probability OP value of appreciable error big more for correction software, and it is high more to explain that then correction software correctly detects the probability of appreciable error;
The simulated measurement value departs from the average degree IRR of emulation true value
1Be worth greatly more, system's average measurement error is big more, and corrected value departs from the average level IRR of emulation true value
2Be worth greatly more, the corrected value average error is big more, and correction software level of corrections RT value is big more, and the system compensation result is poor more.
The assessment method of production process data correction software of the present invention; At first, the true value that emulation produces is not done change, directly as input; Import correction software to be evaluated through real-time data base; The corrected value and the true value that obtain after the line balancing module balance of correction software to be evaluated, the treatment for correcting are compared analysis, if error proves then that in tolerance interval plant model conforms in the industrial process simulation model set up and the correction software to be evaluated, evaluating result is reliable.It is accurate that the model feedback modifiers system that data-driven can iteration be called by system when on the contrary, unreliable is revised up to model model.
Secondly; The emulation true value that emulation produces is added stochastic error and imported correction software to be evaluated; The corrected value and the emulation true value that obtain after the line balancing module Balance Treatment in the correction software to be evaluated are compared, and multiple evaluation index can present the processing power of system to stochastic error.
Once more, need according to plant model situation in the software and test and appraisal, formulate the test and appraisal scheme, select different side lines to add appreciable error, multiple evaluation index can present the processing power of system to appreciable error on the different side lines.
Beneficial effect of the present invention:
(1) the present invention can proofread and correct needs according to plant data, convenient and swiftly builds, revises the required factory's graphical model of test and appraisal, and can import corresponding emulated data according to production scheduling practical operation flow process.
(2) the present invention can provide each variable emulation true value data of the full MES of factory layer, measured value (automatic/artificially adjustable) to generate according to selected plant model and corresponding input.
(3) the present invention can provide and import the communication interface of commenting software database to be evaluated.
(4) can test and assess routine data alignment technique and multi-levels data alignment technique of the present invention.
(5) the present invention supports multiple data input module to be evaluated, comprises the software amount of pushing away balance, adjustment of data result etc., and does contrast and displaying.
The present invention can be widely used in the test and appraisal of flow process enterprise production executive system adjustment of data softwares such as petrochemical industry, and its meaning is to have obtained through model emulation the production data true value of full factory aspect.Thereby test and appraisal have been realized to factory level adjustment of data software and algorithm.
Description of drawings
Fig. 1 is a production process data correction software assessment method process flow diagram of the present invention;
Fig. 2 is emulation production models strategic process figure in the embodiment of the invention;
Fig. 3 is for respectively installing side line 7 order of classes or grades at school correcting result maximum error rate synoptic diagram in the embodiment of the invention during verification model correctness;
Fig. 4 is simulated measurement value and a corrected value error rate synoptic diagram in the embodiment of the invention.
Embodiment
Fig. 1 is a production process data correction software assessment method process flow diagram of the present invention, mainly comprises following step:
(1) graphical modeling utilizes graphical tools VISIO to set up the production run model according to concrete production run;
(2) whether the model of checking production run is correct, and at first, the initial value that is provided with in the production run instructs with producing; And import in the production run model of being set up, the production run model is according to production run initial value that imports and production instruction simulation emulation production run, and the generation simulation result; This analog simulation result is imported in the production executive system software to be evaluated; The production run balance module that the production executive system software transfer carries, the production run balance module carries out balance, correction to simulation result, obtains correcting result; The correcting result that the emulation true value and the production executive system software of the generation of production run model emulation are proofreaied and correct generation compares; If correcting result is consistent with the emulation true value or error within normal range, explain that the production run model of being set up is correct, can carry out follow-up test and appraisal step; If simulation result and correcting result are inconsistent or error is bigger; Explain that the production run model of being set up is incorrect, need call the data-driven model feedback system this moment, and the model feedback modifiers system that system iterative calls data-driven revises up to model correct to model;
(3) analog simulation utilizes the correct production run model that obtains that production run is carried out flow process emulation, obtains the emulation true value;
(4) error is introduced, and artificial some known, the controlled errors of adding of emulation true value with the production run model emulation of being set up produces obtain the simulated measurement value;
(5) trimming process, the simulated measurement value importing production executive system software with the band error lets production executive system that the simulated measurement value of band error is proofreaied and correct, and obtains correcting result;
(6) evaluation and test correction software; Emulation true value and correcting result are compared, and the utilization correction software correctly detects the average level that the probability of appreciable error, average degree that the simulated measurement value departs from the emulation true value and corrected value depart from the emulation true value balance, the calibration capability of production run balance module in the production executive system software is estimated.
Present embodiment is an example with the data correction system of the commercial MES software of domestic certain petrochemical field, verifies actual effect of the present invention.It is core that this system has formed with the MES integrated platform at present, go up with the ERP layer, descend and production operation optimal control layer integrated, the refinery one total solution and the application system of unified data access mechanism are provided." production scheduling " module mainly comprises the preparation of line balancing data, line balancing, three functions of scheduling daily paper in this system.Physical node amount and the physics produced after calibration function is prepared based on the line balancing data move relation; The uniform rules storehouse, algorithms library, plant model and the model solution device that utilize system to provide; Automatically accomplishing the corresponding topological model of node dynamically generates and node amount correction calculation; The scheduling level that reaches Petrochemical Enterprises is proofreaied and correct, and supports for production scheduling provides data; Aligning tool is provided, realizes producing and proofread and correct the inspection of moving relation and node amount between node,, improve and proofread and correct efficient, reduce calibration cycle through the man-machine interaction of line balancing process.
The present invention sets up parallel complete plant model outside software to be evaluated; Calculate the emulation true value; And on the emulation true value, do corresponding mathematics Error processing, obtain the simulated measurement value, let this data software corrective system the line balancing module to this part error can know, artificial controlled " simulated measurement value " carry out the adjustment of data computing of full factory and obtain correcting result; Correcting result and emulation true value are done corresponding comparison; Reflection calibration result directly perceived is in time initiatively found correction problem place, selects the olefin plant in this system to do the test and appraisal case here.
One, graphical modeling
Utilize graphical tools VISIO to set up the production run model according to concrete production run, emulation production models strategic process figure sees accompanying drawing 2;
Two, checking realistic model correctness
According to the condition of production of continuous three and half 7 order of classes or grades at school on November 25 to November 28 (this factory's order of classes or grades at school be set at 12 hours a class), select corresponding order of classes or grades at school production decision at emulation platform; According to dispatching record, scheduling actions (moving relation) is resolved to the split point coefficient import emulation platform; Set corresponding input: each order of classes or grades at school advances factory's amount, this class jar amount of paying.Set that the last order of classes or grades at school end of term jar that the emulation cycle begins is deposited, entry and exit factory, side line progressive schedule semi-invariant be the emulation initial value, is defined as the 0th order of classes or grades at school.Simulation calculation obtains each order of classes or grades at school device turnover side line output, jar receipts amount, (amount of movement is still for there being the breakpoint amount of movement of branch confluence here for jar on duty end of term amount, the amount of dispatching from the factory and all amount of movements; Subsequent module can be resolved these amount of movements, forms not the true amount of movement with minute confluence).
Above continuous 7 order of classes or grades at school emulation true value amounts are sent into each correlation module of this production executive system to be evaluated; Call storing process the emulation true value and the relation that moves are prepared to require to resolve according to software equilibrium criterion to be evaluated, re-use the line balancing module emulation true value is carried out correction calculation.
Fig. 3 is each device side line 7 order of classes or grades at school correcting result maximum error rate synoptic diagram.
Correction calculation is average error rate 7.75e as a result
-8, each installs side line 7 order of classes or grades at school correcting result and shows that maximum error rate is 1.59e
-6, deviation is very little, can ignore.So can get, it is consistent to have built the olefin plant model in emulation parallel model (yield model, annexation, split point coefficient) and the software to be evaluated.
Three, analog simulation
After the checking realistic model was correct, selected 25 day shift of November, simulation result carried out follow-up assessment.
Four, error is introduced
In emulation platform; Select simulation result on 25 day shift of November; Stochastic error to all device side line emulation true value addings 2%～5%; The stochastic error setting meets in the software material mobile module to be evaluated for the affirmation value of side line amount sets (having the error of standard productive rate ± 5% to allow for side line in the software material mobile module to be evaluated), obtains the simulated measurement value.
Five, trimming process
The simulated measurement value that obtains is sent into Software Production balance module to be evaluated, obtain correcting result.
Simulated measurement value and corrected value error rate are seen Fig. 4.
Test result, the average error of side line value drop to 1.568% from 3.717%, and wherein maximum error is " virtual the dispatching from the factory of 3# butadiene loss "; Simulated measurement value error rate 62.658%; Proofread and correct the back error rate and drop to 25.712%, error rate significantly descends, but fails obviously to eliminate.This be because, no matter be model or the emulation platform model in the software to be evaluated, all be for satisfying the virtual side line that the overall balance of turnover material is provided with for the definition of loss side line, the error of every other side line can all be accumulated on the loss side line at last.
Six, evaluation and test correction software
By predetermined emulation testing number of cycles step 3～five, obtain the corrected value of repeatedly emulation testing, confirm the degree of reliability of correction software according to the deviation between corrected value and the corresponding simulation true value.
The definition test index:
Correction software correctly detects the probability of appreciable error:
The simulated measurement value departs from the average degree of emulation true value:
Corrected value departs from the average level of emulation true value:
The correction software level of corrections:
Wherein:
The number of the appreciable error that emulation produces is the number that has the variable of appreciable error in the simulated measurement value;
The number of proofreading and correct appreciable error is after proofreading and correct through correction software, the number of the variable that has appreciable error that is identified or proofreaies and correct;
Ns: emulation testing number of times;
N: the node number in the said production run model;
I: the sequence number of the variable corresponding with each node difference;
K: the sequence number of number of corrections;
T
I, k: the emulation true value that i variable is the k time;
M
I, k: the simulated measurement value that i variable is the k time.
R
I, k: the corrected value that i variable is the k time.
Utilize emulation platform, on all side line variablees, choose 10%, 15%, 25% variable number, add 25%, 35%, 100% appreciable error respectively and test.The side line variable of this moment no longer all is independent side line, the concrete data of appearance such as the table 1 of the relevant side line of meeting.
Table 1 differentiation appreciable error balance result is (OP/IRR relatively
1/ IRR
2/ RT)
Above result shows that the appreciable error number was at 10% o'clock, and the side line of band appreciable error is that the probability of related side line is lower, and the equilibrium strategy of correction software still can be handled the appreciable error of side line preferably.Increase in appreciable error quantity, the appreciable error rate becomes under the big situation, and the possibility that side line becomes related side line becomes big, thereby causes the balance result along with the increase of the increase of appreciable error rate and appreciable error quantity worse and worse.Use multiple Evaluation Strategy in the production process data correction software assessment method of the present invention can assess out balance, the calibration capability of production run balance module in the software to be evaluated accurately, all sidedly to the test and appraisal of software correcting result to be evaluated.
Claims (9)
1. the evaluating method of a production process data correction software is characterized in that, may further comprise the steps:
(1) sets up model, set up the production run model according to concrete production run;
(2) if correctness of the said production run model of checking is correct execution in step (3) then;
(3) analog simulation utilizes said production run model that production run is carried out flow process emulation, obtains the emulation true value;
(4) error is introduced, and in the emulation true value, introduces error, obtains the simulated measurement value;
(5) trimming process is input to correction software with the simulated measurement value and proofreaies and correct, and draws corrected value;
(6) evaluation and test correction software by predetermined emulation testing number of cycles step (3)～(5), obtains the corrected value of repeatedly emulation testing, confirms the degree of reliability of correction software according to the deviation between corrected value and the corresponding simulation true value.
2. the evaluating method of production process data correction software according to claim 1; It is characterized in that; When setting up model in the described step (1); Figure in the utilization VISIO mould utilizes Custom Attributes and the database linkage function of VISIO as descriptive model, set up, the Custom Attributes of renewal figure and through open database interconnected with database in corresponding attribute list carry out synchronously.
3. the evaluating method of production process data correction software according to claim 1 is characterized in that, the verification model correctness described in the step (2) may further comprise the steps:
A, in described production run model, import production data, comprise production run cycle initial value and produce instruction;
B, obtain simulation result through model emulation;
C, simulation result is imported correction software proofread and correct and obtain correcting result;
D, correcting result and simulation result are compared, when correcting result is identical with simulation result, execution in step (3).
4. the evaluating method of production process data correction software according to claim 1 is characterized in that, said step (3) comprising:
A, in said production run model, carry out data inputs, comprise production run cycle initial value and produce instruction;
B, call the production run model of being set up and carry out flow process emulation, obtaining simulation result is the emulation true value, and goes back to the deposit data storehouse.
5. the evaluating method of production process data correction software according to claim 1 is characterized in that, in the emulation true value, introduces error in the step (4) at random.
6. the evaluating method of production process data correction software according to claim 1; It is characterized in that the extent of deviation between corrected value described in the step (6) and the emulation true value correctly detects the average level that the probability of appreciable error, average degree that the simulated measurement value departs from the emulation true value and corrected value depart from the emulation true value through correction software and confirms.
7. the evaluating method of production process data correction software according to claim 6 is characterized in that, described correction software correctly detects the probability of appreciable error:
The number of the appreciable error that emulation produces is the number that has the variable of appreciable error in the simulated measurement value;
The number of proofreading and correct appreciable error is after proofreading and correct through correction software, the number of the variable that has appreciable error that is identified or proofreaies and correct;
Ns is the emulation testing number of times.
8. the evaluating method of production process data correction software according to claim 7 is characterized in that, described simulated measurement value departs from the average degree of emulation true value:
Wherein:
Ns: emulation testing number of times;
N: the node number in the said production run model;
I: the sequence number of the variable corresponding with each node difference;
K: the sequence number of number of corrections;
T
I, k: the emulation true value that i variable is the k time;
M
I, k: the simulated measurement value that i variable is the k time.
9. the evaluating method of production process data correction software according to claim 8 is characterized in that, described corrected value departs from the average level of emulation true value:
Wherein:
Ns: emulation testing number of times;
N: the node number in the said production run model;
I: the sequence number of the variable corresponding with each node difference;
K: the sequence number of number of corrections;
T
I, k: the emulation true value that i variable is the k time;
R
I, k: the corrected value that i variable is the k time.
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| CN104077485A (en) * | 2014-06-30 | 2014-10-01 | 西安电子科技大学 | Model correctness evaluation method based on goodness of fit |
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| CN110196912A (en) * | 2019-04-15 | 2019-09-03 | 贵州电网有限责任公司 | A kind of power grid archives parallel model construction method based on trust regular network |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104718547A (en) * | 2013-10-11 | 2015-06-17 | 文化便利俱乐部株式会社 | Customer data analysis system |
| CN104077485A (en) * | 2014-06-30 | 2014-10-01 | 西安电子科技大学 | Model correctness evaluation method based on goodness of fit |
| CN110196912A (en) * | 2019-04-15 | 2019-09-03 | 贵州电网有限责任公司 | A kind of power grid archives parallel model construction method based on trust regular network |
| CN110196912B (en) * | 2019-04-15 | 2022-09-23 | 贵州电网有限责任公司 | Power grid archive parallel model construction method based on trust rule network |
| CN110426137A (en) * | 2019-08-12 | 2019-11-08 | 国网河南省电力公司新乡供电公司 | A kind of temperature checking method, device, system and computer readable storage medium |
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Application publication date: 20120912 |