WO2015037754A1 - Procédé d'inspection de qualité faisant appel à un système de contrôle de qualité intégré - Google Patents

Procédé d'inspection de qualité faisant appel à un système de contrôle de qualité intégré Download PDF

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Publication number
WO2015037754A1
WO2015037754A1 PCT/KR2013/008264 KR2013008264W WO2015037754A1 WO 2015037754 A1 WO2015037754 A1 WO 2015037754A1 KR 2013008264 W KR2013008264 W KR 2013008264W WO 2015037754 A1 WO2015037754 A1 WO 2015037754A1
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quality
management system
test
integrated
quality management
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PCT/KR2013/008264
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English (en)
Korean (ko)
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탁지훈
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(주) 네오위드넷
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Definitions

  • the present invention relates to a quality inspection method based on an integrated quality management system, and more specifically, to an integrated quality management system for improving the quality and consistency of observation data by applying a consistent quality standard for observation data collected at an observation point. Based on quality inspection methods.
  • the present invention is to solve the above problems, by applying a consistent quality standard for the observation data collected at the observation point only after the quality (QC) inspection to ensure the quality and consistency of the observation data only observation data above the appropriate quality standards It is to provide quality inspection method based on integrated quality management system to utilize.
  • the present invention performs statistical analysis activities by classifying the error rate and missing rate of the quality control results of the quality management results of the joint utilization center into various characteristics such as branch and institution, and use this to transfer the entire quality from the site quality stage to the final stage. This is to provide a quality inspection method based on the integrated quality management system to ensure the high quality of observation data through systematic quality improvement activities in the process.
  • the integrated quality management system has 10 steps (physical limit inspection, step inspection, internal consistency test, persistence test, climate range) A first step of determining whether an algorithm of a test, a central filter value test, a Cressman method, a Barnes method, a Madsen-Allerup method, an AMeDAS precipitation test) is an error; And the integrated quality management system includes the 10 steps (physical limit test, step test, internal consistency test, persistence test, climate range test, central filter value test, Cressman method, Barnes method, Madsen-Allerup method, AMeDAS precipitation test). Registering a QC flag value error if all errors exist in the second step; Characterized in that it comprises a.
  • the second step is an error in each step if the integrated quality management system is not all the error in step 10 Step 2-1 of determining whether one or more are present; And step 2-2 of the integrated quality management system registering the QC flag value as normal when one or more errors do not exist in each step. It characterized in that it further comprises.
  • the second step 2 when the integrated quality management system has one or more errors in each step, for each case Calculating a probability value for the QC flag value and determining whether to register the case as a case based on the calculated probability value; And a step 2-2 (b) of registering a QC flag when the integrated quality management system is able to make a normal determination and registers as a case. It characterized in that it further comprises.
  • the integrated quality management system-based quality inspection method if the integrated quality management system is determined to be normal after the step 2-2 (b), the QC flag value is normal. Registering as an error case, registering a QC flag value as an error case; It characterized in that it further comprises.
  • Quality inspection method based on integrated quality management system by applying a consistent quality standards for the observation data collected at the observation point is appropriate after the quality (QC) inspection to improve the quality and consistency of observation data It provides the effect to be used as observation data above the quality standard.
  • the quality inspection method based on the integrated quality management system according to another embodiment of the present invention, the error rate and the missing rate of the quality control results of the on-site quality management from the joint utilization center classified into various characteristics, such as branch, institution, etc. By conducting the analysis activities and using them, systematic quality improvement activities are carried out in the entire process from the site quality stage to the final stage, thereby providing the effect of securing high quality of observation data.
  • FIG. 1 is a view showing a quality inspection system based on integrated quality management according to an embodiment of the present invention.
  • FIG. 2 is a table for explaining the functions of the components constituting the integrated quality management based quality inspection system according to an embodiment of the present invention.
  • 3 is a flowchart showing a real-time quality inspection performed by an integrated quality management system.
  • FIG. 4 is a flowchart showing a quasi-real time quality inspection performed by an integrated quality management system.
  • FIG. 5 is a flow chart illustrating a non real-time quality inspection performed by an integrated quality management system.
  • Figure 6 is a view for explaining the improvement of the quality inspection process procedure performed by the integrated quality management system according to an embodiment of the present invention.
  • FIG. 7 is a view for explaining the applied QC flag by the integrated quality management system according to an embodiment of the present invention.
  • FIG. 8 is a view for explaining the value for the QC flag which is the result of inspection at each step as the quality inspection process by the integrated quality management system according to an embodiment of the present invention.
  • FIG. 9 is a view for explaining the mapping of the QC flag value for each step when all the 10-step quality algorithm in the QC Flag value definition on the integrated quality management system according to an embodiment of the present invention.
  • FIG. 10 is a flowchart illustrating an integrated quality management method according to the QC flag heuristic analysis performed by the integrated quality management system according to an embodiment of the present invention.
  • 11 is a reference diagram illustrating an example of calculating a probability value for each case.
  • the component when one component 'transmits' data or a signal to another component, the component may directly transmit the data or signal to another component, and through at least one other component. This means that data or signals can be transmitted to other components.
  • the integrated quality management-based quality inspection system is a joint utilization system manager terminal 10, joint utilization quality manager terminal 20, observation institution quality manager terminal 30, system user terminal 40 ), Observer quality officer terminal 50, collection / processing system 60, and integrated quality management system 70.
  • the integrated quality management system 70 is not limited to the terminals. It can be transformed into an object that can access.
  • the joint utilization system manager terminal 10 receives the request of the general user and selects and registers the joint utilization quality manager as the integrated quality management system 70.
  • the joint utilization quality manager terminal 20 sets a reference value for each step QC inspection, refers to the inquiry and statistical data, and performs non-real time QC through the integrated quality management system 70.
  • Observation agency quality manager terminal 30 may query the QC result data of the observer belonging to the integrated quality management system 70 and may request a correction for the wrong result.
  • the system user terminal 40 may query the currently requested items by the system administrator.
  • the collection / processing system 60 collects raw data from observation equipment, distributes raw data to the integrated quality management system 70 for QC inspection, and receives the QC result.
  • the joint utilization system manager terminal 10 registers the joint utilization quality manager as the integrated quality management system 70 (S1).
  • step S1 the joint utilization quality manager terminal 20 transmits the QC reference value automatic statistics generation request to the integrated quality management system 70 (S2).
  • the integrated quality management system 70 allows the joint utilization quality manager terminal 20 to query the QC reference value automatic statistics generation results (S3).
  • step S3 the joint utilization quality manager terminal 20 performs the setting for the QC reference value to the integrated quality management system 70 (S4).
  • step S4 the system user terminal 40 transmits a request for the authority of the observer quality manager / manager to the integrated quality management system 70 (S5).
  • the integrated quality management system 70 allows the system user terminal 40 to query the observation authority quality manager / manager authority request result (S6).
  • step S6 the collection / processing system 60 transmits the QC target data to the integrated quality management system 70 (S7).
  • step S7 the integrated quality management system 70 causes the QC result inquiry to the observer quality officer terminal 50 to be performed (S8).
  • step S8 the observer quality officer terminal 50 transmits a QC result correction request to the integrated quality management system 70 (S9).
  • the integrated quality management system 70 allows the observing agency quality manager terminal 30 to query the QC result modification request (S10). Accordingly, the observation agency quality manager terminal 30 approves the QC correction request to the integrated quality management system 70 (S11).
  • step S11 the joint utilization quality manager terminal 20 requests the non-real time QC to the integrated quality management system 70 (S12).
  • the integrated quality management system 70 transmits the QC result data to the collection / processing system 60 (S13).
  • the integrated quality management system 70 applies a consistent quality standard for observation data collected at an observation point and then checks the quality (QC) to improve the quality of the observation data and to ensure consistency. It is a system to utilize only observation data above the proper quality standard.
  • the integrated quality management system (70) classifies the error rate and missing rate of the quality control result of the joint utilization center into various characteristics such as branch and institution, and performs statistical analysis activities. It is a work process for integrated quality management system to secure high quality of weather observation data by systematic quality improvement activities throughout the entire process.
  • the integrated quality management system 70 has the following main functions. First, it performs the automatic and manual function of quality inspection by type and step. Second, it performs the basic quality test result value and detailed flag search function. Third, the quality monitoring performance status real-time monitoring function.
  • the integrated quality management system 70 performs real-time quality inspection, non-real time quality inspection, quasi-real time quality inspection by the quality inspection method corresponding to the first category.
  • the integrated quality control system 70 includes physical limit tests, step tests, internal consistency tests, persistence tests, climate range tests, central filter values tests, Cressman techniques, Barnes techniques as end quality management algorithms corresponding to the first category. , Madsen-Allerup technique, AMeDAS precipitation test.
  • the real-time quality inspection is a quality inspection method that is automatically performed every minute by the integrated quality management system 70 is performed according to the procedure as shown in FIG.
  • the integrated quality management system 70 does not perform quality inspection at the same time as the data is collected, but processes all the data at once, including delayed data after 24 hours, and the data after the deadline is 'uninspected'. And statistics about it.
  • the integrated quality management system 70 is a function that is performed when a quality manager needs to collectively check the past observation data by performing a quality inspection manually for a specific period or time range.
  • the quality inspection process performed by the integrated quality management system 70 is a main function of the above-mentioned real-time, non-real-time and quasi-real-time quality inspection methods, and includes ten kinds of quality inspection algorithms (physical limit inspection, step inspection, internal matching). It is key to improve the reliability of data quality by applying the procedures such as sex test, persistence test, climate range test, central filter value test, Cressman method, Barnes method, Madsen-Allerup method, AMeDAS precipitation test).
  • FIG. 6 is a view for explaining the improvement of the quality inspection process procedure performed by the integrated quality management system 70 according to an embodiment of the present invention.
  • the existing method applies 10 quality check (QC) algorithms to data, and n + 1 if the quality check algorithm is normal or suspected in step n (n is a natural number of 1 or more).
  • QC Algorithm for Steps Checks the quality of data and if there is an error, no QA algorithm for the step is performed.
  • n-1 step algorithm normal / suspicious flag
  • the quality inspection algorithm is a program that sets its own reference value and handles it as an error if it is out of the reference value and success if the value exists in the reference value.
  • the reference value is set based on weather phenomena that were considered impossible in the past. Therefore, the existing method is local, just like the current weather phenomenon, and if an unexpected value is actually observed, it may be regarded as an error of data, which may cause a huge problem in the weather phenomenon judgment. Therefore, even if the quality inspection was an error in step n, all the quality inspection algorithms after n + 1 were performed to check at different angles. We want to change the quality inspection process so that we can accurately determine weather events.
  • the integrated quality management system 70 attempts to change the currently applied quality inspection (QC) algorithm QC Flag, and the current quality inspection algorithm and the applied QC flag are as follows in FIG. 7.
  • the value for the QC flag which is the result of the inspection at each step is also changed as shown in FIG. 8.
  • the integrated quality control system 70 looks at the quality of weather data analysis and observation equipment error determination process through the QC flag.
  • the current system does not have a process for interpreting weather data quality or using QC flags to determine observational equipment errors. It is possible to estimate the correlation between QC flag, meteorological quality analysis and observation equipment during actual quality activities. Therefore, we propose a method of quality analysis and error reading through QC flag as a heuristic statistical method.
  • QC flag pattern analysis analyzes the convergence phenomenon of QC flag values by numerically mapping the QC flag and mapping the values to the case for each phenomenon as shown in FIG. 10, and indicates which case the QC flag value is hunting for. This function helps to make a proper judgment about.
  • the integrated quality management system 70 can check all stages (physical limit test, step test, internal consistency test, persistence test, climate range test, central filter value test, Cressman technique, Barnes technique, Madsen-Allerup technique, AMeDAS precipitation). It is determined whether the algorithm of the check) is an error (S21).
  • step (S21) the integrated quality control system 70 checks all stages (physical limit test, step test, internal consistency test, persistence test, climate range test, central filter value test, Cressman method, Barnes method, Madsen- If there is an error in the Allerup technique (AMeDAS precipitation test), the QC flag value error is registered (S22).
  • step S21 the integrated quality management system 70 determines whether at least one error exists in each step (S23), unless there is an error in every step (S23).
  • step S23 the integrated quality management system 70 registers the QC flag value as normal when one or more errors do not exist in each step (S24).
  • step (S24) integrated quality management system 70 calculates the probability value for the QC flag value for each case (S25).
  • step S25 the integrated quality management system 70 determines whether to register as a case based on the probability value calculated in step S25 (S26).
  • step S26 If it is determined that the normal determination is possible in step S26 and needs to be registered as a case, the integrated quality management system 70 registers the QC flag (S27).
  • step S26 the integrated quality management system 70 checks the measured value to determine whether it is normal or error (S28).
  • the integrated quality management system 70 registers the QC flag value as a normal case (S29).
  • the integrated quality management system 70 registers the QC flag value as an error case (S30).
  • mapping QC flag value registration registration for each case performed by the integrated quality management system 70 in detail, all the data whose QC flag is not normal after the quality inspection is inspected by the manager for equipment abnormalities or data abnormalities. Define and classify as case of, and map QC flag value to corresponding case of analysis. In particular, if the error or suspicion value on the QC flag is judged to be normal data after the final manager's judgment, the error rate is reduced by further subdividing the case.
  • the probability value for each case QC flag value is calculated. That is, when a specific QC flag value is generated, the probability that the QC flag value is included in each case is displayed to the calculation manager so that the meaning of the QC flag value can be determined.
  • the administrator can infer the meaning of the current QC flag value by looking at the probability value for each case corresponding to the QC flag value.
  • 11 is a reference diagram illustrating an example of calculating a probability value for each case.

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Abstract

La présente invention concerne un procédé d'inspection de qualité faisant appel à un système de contrôle de qualité intégré. Le procédé d'inspection de qualité selon la présente invention comprend les étapes suivantes : tout d'abord, le système de contrôle de qualité intégré détermine s'il existe une erreur dans un algorithme consistant en 10 étapes (vérification de limites physiques, vérification d'étapes, vérification de cohérence interne, essai de tenue dans le temps, vérification d'observations aberrantes temporelles, vérification de valeur de filtre médian, méthode de Cressman, méthode de Barnes, méthode de Madsen-Allerup et essai de précipitation AMeDAS); ensuite, le système de contrôle de qualité intégré enregistre une erreur dans une valeur de drapeau QC si une erreur est détectée dans chacune des 10 étapes (vérification de limites physiques, vérification d'étapes, vérification de cohérence interne, essai de tenue dans le temps, vérification d'observations aberrantes temporelles, vérification de valeur de filtre médian, méthode de Cressman, méthode de Barnes, méthode de Madsen-Allerup et essai de précipitation AMeDAS). Grâce à cette caractéristique, la présente invention offre l'avantage que, par application de normes de qualité cohérentes à des données d'observation rassemblées auprès de points d'observation, seules des données d'observation supérieures à une norme de qualité requise sont utilisées après un essai de contrôle de qualité (QC) de manière à améliorer la qualité des données d'observation et à assurer la cohérence des données d'observation. En outre, des activités d'analyse statistique sont effectuées à partir d'une étape de contrôle de qualité de site par classification de taux d'erreur et de taux d'absence de résultats de contrôle de qualité d'un centre d'utilisation commune en diverses propriétés telles que branches et organisations, et des activités d'amélioration de qualité systématique sont effectuées dans tout le processus, de l'étape de contrôle de qualité de site à l'étape finale, à l'aide des résultats des analyses statistiques, ce qui a pour effet d'assurer des données d'observation de haute qualité.
PCT/KR2013/008264 2013-09-11 2013-09-12 Procédé d'inspection de qualité faisant appel à un système de contrôle de qualité intégré WO2015037754A1 (fr)

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KR1020130109057A KR101623354B1 (ko) 2013-09-11 2013-09-11 통합 품질관리시스템 기반의 품질검사 방법

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KR101874085B1 (ko) * 2016-12-08 2018-08-02 에스케이테크엑스 주식회사 복합 판단을 통한 기상 센서의 이상 감지 장치, 그 방법 및 컴퓨터 프로그램이 기록된 기록매체
KR102580312B1 (ko) * 2018-04-30 2023-09-18 김기영 관측자료 품질검사 장치 및 이를 이용한 관측자료 품질검사 방법
KR102308243B1 (ko) * 2019-12-02 2021-09-30 사단법인 한국기술사업화진흥협회 영상 데이터 처리를 이용한 도로 기상정보 시스템

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JP3287889B2 (ja) * 1992-11-24 2002-06-04 トーヨーエイテック株式会社 品質管理装置
JP2001117625A (ja) * 1999-10-21 2001-04-27 Canon Inc 品質監視装置、品質監視方法および品質監視システム
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