WO2009087986A1 - Information providing system, information providing device, information providing method, and program - Google Patents

Information providing system, information providing device, information providing method, and program Download PDF

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Publication number
WO2009087986A1
WO2009087986A1 PCT/JP2009/050012 JP2009050012W WO2009087986A1 WO 2009087986 A1 WO2009087986 A1 WO 2009087986A1 JP 2009050012 W JP2009050012 W JP 2009050012W WO 2009087986 A1 WO2009087986 A1 WO 2009087986A1
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WIPO (PCT)
Prior art keywords
quality
frequency distribution
value
management rule
quality item
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PCT/JP2009/050012
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French (fr)
Japanese (ja)
Inventor
Tomohiro Igakura
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Nec Corporation
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Priority to JP2009548910A priority Critical patent/JPWO2009087986A1/en
Publication of WO2009087986A1 publication Critical patent/WO2009087986A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3466—Performance evaluation by tracing or monitoring
    • G06F11/3476—Data logging
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3447—Performance evaluation by modeling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
    • G06F2201/81—Threshold

Definitions

  • the present invention relates to a technique for providing information for testing and checking whether or not a start condition of a newly created management rule is appropriately set, and in particular, a threshold value for a specific quality condition that the management rule starts. It is related with the technique which can show a management rule maker the information for a management rule maker to judge whether the start condition is referring to the appropriate quality information with respect to the start condition which specified conditions by .
  • Management rules monitor the operating status and operating status of systems and devices to be managed, and when the conditions are met, that is, when the status assumed by the management rules occurs in the management symmetric system, the management rules The purpose is to automatically manage the system by performing the operation set in (1).
  • This management rule has a start condition. For example, “CPU load> 10”. This means that when the value of the quality item “CPU load” is 10 or more, the “operation” of this management rule is executed.
  • This management rule is created based on the knowledge of a person who is familiar with the operation of the system managed by the management rule.
  • Newly created management rules should be applied to the actual system after confirming that they will not work when they are not needed, and that they will work as intended when an expected situation occurs. . This is because a rule that does not operate as intended cannot correctly grasp the state of the system to be managed, and may cause a system abnormality. For this purpose, first, it is necessary to check whether the activation conditions of the created management rule are set appropriately.
  • the data when the event that the management rule is supposed to operate or the data that imitates it is entered into the management rule, and the operation result of the management rule It is possible to confirm whether a person performs the operation as expected and outputs the expected result.
  • the management rule test system as shown in FIG. 6 includes a test condition data storage unit 602, an expert system 623, an execution result output unit 622, and a display device 610.
  • the expert system 623 can be considered as a set of management rules.
  • the first problem is that it is not possible to confirm whether the quality item adopted as the start condition of the created management rule is optimal.
  • the operation is performed as expected on the quality information given the management rule, and it is confirmed whether the expected result is output.
  • the rule is improved such as changing the threshold value of the condition.
  • the management rule does not always work correctly. Because, depending on the quality item, even if the system is in a normal state, the value of the quality item may be temporarily deteriorated. Management rules do not work as intended. However, in the management rule operation test, there is a problem that even if it is known that the management rule does not operate correctly, it is not possible to know which quality item is not appropriate.
  • the second problem is that it is not possible to confirm whether there is a quality item that can be adopted instead of the quality item adopted as the activation condition of the created management rule.
  • the problem to be solved by the present invention is to solve the above-mentioned problem, and whether the quality information referred to as the activation condition of the created management rule is suitable for being referred to as the activation condition based on the threshold value.
  • the purpose is to generate and present information for verification to the creator.
  • a management rule test system that can find quality information suitable for analysis based on a threshold value and present it to the management rule creator, compared with the quality information that is referred to as the start condition of the created management rule.
  • the present invention for solving the above problems is an information providing system, wherein a storage unit stores a history of numerical values indicating operation quality of a device to be managed for each quality item, and a quality item from the storage unit.
  • Information collection means that collects numerical history every time, and creates a frequency distribution from the collected numerical history, and uses this frequency distribution to determine whether the quality item that is the starting condition of the management rule is appropriate
  • generating means for generating information for doing so.
  • the present invention for solving the above-mentioned problems is an information providing device, and information collecting means for collecting, for each quality item, a history of numerical values indicating the operation quality of the device to be managed, and the collected quality item Generation means for generating a frequency distribution from the history of numerical values and generating information for determining whether the quality item which is the start condition of the management rule is appropriate using the frequency distribution
  • information collecting means for collecting, for each quality item, a history of numerical values indicating the operation quality of the device to be managed
  • the collected quality item Generation means for generating a frequency distribution from the history of numerical values and generating information for determining whether the quality item which is the start condition of the management rule is appropriate using the frequency distribution
  • the present invention for solving the above-described problem is an information providing method, in which a numerical value history indicating the operation quality of a device to be managed is stored for each quality item, and a numerical value for each quality item is stored for each quality item.
  • An information collection step for collecting the history of data
  • a frequency distribution creation step for creating a frequency distribution from the collected history of numerical values
  • the present invention for solving the above-mentioned problem is a program, and the program includes an information collection unit that collects, for each quality item, a history of numerical values indicating the operation quality of a device to be managed. Generating means for generating a frequency distribution from the collected history of numerical values of the quality items, and generating information for determining whether the quality item which is the starting condition of the management rule is appropriate using the frequency distribution It is made to function as.
  • the present invention it is possible to present information for determining to the management rule creator whether or not the quality item referred to by the created management rule is appropriate for the purpose used for the condition determination by the threshold. it can.
  • Frequency distribution table search means 100, 200 Computer 101, 201 Start condition extraction means 102, 202 Quality item management table 103, 203 Correlation calculation means 104, 204 Frequency distribution analysis means 105, 205 Quality information acquisition means 106, 206 Frequency distribution graph creation means 110, 210 Management Rule input device 120, 220 Display 130, 230 Database 207 Correlation value table 208 Correlation value table search means 209 Frequency distribution table 2010 Frequency distribution table search means
  • FIG. 1 is a block diagram of a system according to the first embodiment of the present invention.
  • a computer central processing unit; processor; data processing unit
  • a management rule input unit 110 that operates by program control
  • a display unit 120 that operates by program control
  • a database Device 1 30 that stores data.
  • a computer (central processing unit; processor; data processing unit) 100 includes an activation condition extraction unit 101, a quality item management unit 102, a correlation calculation unit 103, a frequency distribution analysis unit 104, a quality information acquisition unit 105, and a frequency. And a distribution graph creation unit 106. Each of these components operates as follows.
  • the activation condition extraction unit 101 analyzes the quality item that is the activation condition of the management rule input by the management rule input device 110, and what kind of parameter is referred to by the quality item and the threshold value that is the condition Recognize if there is. When a plurality of inputs are made, one by one is taken out and a series of operations are performed.
  • the quality item management table 102 holds a list of quality information items that are the conditions of the management rule reported by the operating device (device to be managed).
  • the correlation calculation unit 103 compares the values of the quality information issued from the same device at the same time in the quality information that is the activation condition of the management rule and the other quality information, and the correlation value of the values Calculate For a device with a high value at one time and a high value, the correlation value is high when the other value is also high.
  • the frequency distribution analysis unit 104 determines whether the shape of the frequency distribution of the quality information has a specific feature or, specifically, a shape having a plurality of maximum values, and takes the maximum value and the minimum value of the frequency. The test value obtained from the interval between the values and the difference between the maximum value and the minimum value is calculated.
  • the quality information acquisition unit 105 acquires a past history of values indicating the quality of operation of a device to be managed from the database 200 of the database device 130.
  • the frequency distribution graph creation unit 106 creates a frequency distribution graph that is a graph of the value and the frequency of taking the value for each quality item.
  • the database device 130 has a database 200.
  • this database 200 history data in which quality information, which is an operation status of a device to be managed, is numerically recorded for each quality item is recorded.
  • the management rule input device 110 inputs the set management rule to the computer 100 (step A1 in FIG. 2).
  • the activation condition extraction unit 101 recognizes the name and threshold value of the quality item of the current activation condition from the management rule input in step A1 (step A2).
  • the quality information acquisition unit 105 acquires the past history of the quality information of the quality item extracted in step A2 from the database 130 (step A3 in FIG. 2).
  • the frequency distribution graph creation unit 106 creates a frequency distribution graph from the past history obtained in step A3 (step A4), and the display 120 together with the name of the quality item obtained by the activation condition extraction unit 101 in step A2. (Step A5).
  • the activation condition acquisition unit 105 refers to the quality item management table 102 and extracts a quality item that is reported by the system and is different from the quality item extracted in step A2 (step A6).
  • the quality information acquisition unit 105 acquires the past history of the quality information of the quality item extracted in step A6 from the database 130 and passes it to the correlation calculation unit 103 (step A7).
  • the correlation calculation unit 103 calculates a correlation value between the past history of the quality information extracted in step A7 and the past history of the quality information extracted in step A3 (step A8).
  • the correlation calculation unit 103 compares the correlation value calculated in step A8 with a predetermined threshold, and if the correlation value is larger, the quality information acquisition unit 105 stores the history of the quality information obtained in step A6 in the frequency distribution graph creation unit.
  • the instruction is sent to 106, the process proceeds to step A10, and if smaller, the process proceeds to step A15 (step A9).
  • the frequency distribution graph creation unit 106 calculates the frequency distribution of the quality information obtained in step A6 and passes it to the frequency distribution analysis unit 104 (step A10). . Then, the frequency distribution analysis unit 104 examines the degree of whether or not the shape of the frequency distribution has a plurality of maximum values, the interval between the maximum value and the minimum value of the frequency, and the difference between the maximum value and the minimum value. The test value obtained from (1) is calculated (step A11).
  • the frequency distribution analysis unit 104 compares the test value obtained in step A11 with a predetermined threshold value. If the test value is larger, the frequency distribution analysis unit 104 notifies the frequency distribution graph creation unit 106 to that effect and proceeds to step A13. If the value is smaller, the process proceeds to step A14 (step A12).
  • the frequency distribution graph creation unit 106 When it is determined in step A12 that the test value is larger than the threshold value, the frequency distribution graph creation unit 106 outputs the frequency distribution of the quality information obtained in step A10 and the name of the quality item obtained in step A6 to the display. (Step A13).
  • step A6 to step A13 are repeated for all quality items other than the quality item obtained in step A2 (step A14).
  • steps A3 to A14 are repeated for all quality items referred to in the management rule activation conditions obtained in step A2 (step A15). ).
  • the rule creator can determine whether the quality item adopted by the created rule is suitable for use in threshold judgment by looking at the frequency distribution graph displayed on the display device.
  • the second embodiment of the present invention is a computer (central processing unit; processor; data processing unit) 200 that operates by program control, a management rule input unit 210, a display unit 220, and a database.
  • the apparatus 230 is comprised.
  • a computer (central processing unit; processor; data processing unit) 200 includes an activation condition extraction unit 201, a quality item management unit 202, a correlation calculation unit 203, a frequency distribution analysis unit 204, a quality information acquisition unit 205, a condition An attached information acquisition unit 206 and a frequency distribution graph creation unit 207.
  • the activation condition extraction unit 201 analyzes the activation condition of the management rule and recognizes what kind of parameter the condition refers to and what threshold value is the condition.
  • the quality item management table 202 holds a list of quality information reported by devices in the system.
  • the correlation calculation unit 203 compares the values of both quality information issued from the same device at the same time for the two quality information, and calculates the correlation value of the values. At a time when one value is high and a high device, the correlation value is high when the other value is high.
  • the frequency distribution analysis unit 204 determines whether the shape of the frequency distribution of the quality information is a shape having a plurality of maximum values, the interval between the values at which the frequency maximum value and the minimum value are taken, and the difference between the maximum value and the minimum value Calculate the test value obtained from.
  • the quality information acquisition unit 205 acquires the past history of the quality information of the designated quality from the database 200.
  • the frequency distribution graph creation unit 206 calculates a frequency distribution, which is a graph of the value and the frequency of taking the value for the quality item.
  • the correlation value table 207 is a table that stores correlation values between quality items calculated by the correlation calculation unit 203.
  • the correlation value table calculation unit 208 searches the correlation value table 207 for a correlation value between two quality items.
  • the frequency distribution table 209 is a table for storing the frequency distribution created by the frequency distribution graph creating unit 206 and the test value calculated by the frequency distribution analyzing unit 204.
  • the frequency distribution search unit 2010 acquires the frequency distribution and the test value for the designated quality item from the frequency distribution table 209.
  • the currently set management rule is input from the management rule input device 210 to the computer 200 (step B1 in FIG. 4).
  • the activation condition extraction unit 201 recognizes one quality item and threshold value of the activation condition from the management rule input in step B1, and notifies the frequency distribution search unit 2010 via the correlation table search unit 208 (step). B2).
  • the frequency distribution search unit 2010 acquires the frequency distribution of the quality item obtained in step B2 from the frequency distribution table 209 (step B3).
  • the frequency distribution search unit 2010 displays the frequency distribution obtained in step B3 on the display device 220 together with the name of the quality item obtained in step B2 (step B4).
  • the correlation table search unit 208 extracts one quality item other than the quality item obtained in step B2 from the quality item management table 202 (step B5).
  • the correlation table search unit 208 acquires the correlation value between the quality item obtained in step B5 and the quality item obtained in step B2 from the correlation value table 207 (step B6).
  • the correlation table search unit 208 compares the correlation value calculated in step B6 with a prescribed threshold value. If the correlation value is large, the correlation table search unit 208 notifies the frequency distribution search unit 2010 to that effect and proceeds to step B8. B7).
  • the frequency distribution table search means 2010 acquires the test value of the frequency distribution of the quality information obtained in step B5 from the frequency distribution table 209 (step B8).
  • step B8 The test value obtained in step B8 is compared with a prescribed threshold value. If it is larger, the frequency distribution search unit 2010 is notified to that effect and proceeds to step B10. If smaller, the process proceeds to step B12 (step B9).
  • the frequency distribution search unit 2010 acquires the frequency distribution of the quality item obtained in step B5 from the frequency distribution table 209 (step B10), and displays the frequency distribution obtained here and the name of the quality item obtained in step B5. 220 is displayed (step B11).
  • Step B5 to Step B11 are repeated for all quality items other than the quality item obtained in Step B2 (Step B12).
  • step B2 the process is repeated from step B2 to step B12 (step B13).
  • the quality information acquisition unit 205 extracts all the quality items one by one from the quality item management table 202 (step B14), and acquires quality information for each quality item. (Step B15).
  • the frequency distribution graph creating unit 206 creates a frequency distribution graph from the quality information obtained in step B15 (step B16), and the frequency distribution analyzing unit 204 is based on the frequency distribution graph created by the frequency distribution graph creating unit 206 in step B16.
  • the test value is calculated (step B17).
  • the frequency distribution analysis unit 204 registers the frequency distribution graph obtained in step B16 and the test value obtained in step B17 as data corresponding to the quality item obtained in step B14 in the frequency distribution table 209 (step B18).
  • the quality information acquisition unit 205 extracts one quality item different from the quality item obtained in step B14 from the quality item management table 202 (step B19), and acquires the quality information of the quality item obtained here from the database 230 ( Step B20).
  • the quality information acquisition unit 205 passes the quality information obtained in step B15 and the quality information obtained in step B20 to the correlation calculation unit 203, and the correlation calculation unit 203 calculates a correlation value of the quality information (step B21). ).
  • the correlation calculation unit 203 registers the calculation result in the correlation value table 207 as data corresponding to the combination of the quality item obtained in step B14 and the quality item obtained in step B19 (step B22).
  • step B14 The quality item different from the quality item obtained in step B14 is taken out from the quality item management table 202 one by one, and step B19 to step B22 are performed once for all the quality items (step B23).
  • Step B14 to Step B23 are performed once for all quality items (Step B24).
  • a frequency distribution of quality items, a test value of the shape of the frequency distribution, and a correlation value between the quality items are calculated in advance, stored in a table, and the data is periodically transmitted.
  • the display item corresponding to the management rule is selected using the correlation value and the test value calculated in advance. Quality item candidates can be displayed at high speed.
  • the management rule test system includes a management rule creation terminal 500, a management rule test server 510, a management server 520, and a management target system 530.
  • the management rule creation terminal 500 is a PC and functions as a management rule registration device and a display device.
  • the management rule test server 510 is a PC and functions as the computer 100 in FIG.
  • the management server 520 is a PC, functions as the database 103 in FIG. 1, and periodically collects information from the network system to be managed.
  • the management target system 530 is a system composed of a plurality of devices, and includes a server A531, a server B532, and a server C533 in FIG.
  • the activation condition of the management rule is specified as “P_a> 10 & P_b> 5”. That is, the quality items referred to by the management rule activation condition in this example are P_a and P_b, the threshold value of P_a is 10, the threshold value of P_b is 5, and the value of P_a that is regularly reported is 10 or more. At the same time, when there is a device whose P_b value is 5 or more, this management rule operates on that device.
  • FIG. 7 is a graph for the server A of the network system to be managed, the vertical axis is the value of P_a, and the horizontal axis is time. A frequency distribution is created from this value.
  • the frequency distribution of P_a is, for example, as shown in FIG. In FIG. 8, the horizontal axis indicates the value of P_a, and the vertical axis indicates the number of times each value is reported for all devices that have acquired quality information, that is, server A, server B, and server C.
  • the frequency distribution of P_a is displayed on the test screen of the rule creation terminal.
  • the correlation values with P_b are 0.3, 0.7 with P_c, 0.2 with P_d, and 0.9 with P_e, respectively, and 0.7 is used as the threshold value, leaving P_c and P_e.
  • the test value of the shape of the frequency distribution is calculated for each.
  • the test value is the value obtained by normalizing the frequency distribution so that the sum is 1, and multiplying the normalized frequency by the number of divisions in the range with the value, that is, the number of bars in the bar graph. Is used to calculate the test value.
  • the difference between the maximum value (there are two) and the minimum value in this frequency distribution is calculated, and the product with each other is calculated.
  • P_c is 0.8
  • P_e is 0.3
  • the frequency distribution of P_c exceeding the threshold value 0.7 (FIG. 9) is displayed.
  • the frequency distribution of P_a corresponding to 10 or more, which is the threshold value of P_a is separately colored and displayed.
  • correlation values are calculated for P_a, P_c, P_d, and P_e, and a test value is calculated for P_d that exceeds the threshold value. In this case, the test value is not displayed because it does not exceed the threshold value.
  • the management rule creator uses this display, and for P_a, P_a often takes a value close to the threshold value compared to P_c, and distinguishes between abnormal and normal characters from the shape of the graph. In other words, it turns out that it is not suitable for use in threshold judgment, and it is judged that using P_c instead of P_a can more accurately distinguish between normal and abnormal, and P_a is changed to P_c. As a result, the activation condition of the management rule is changed to “P_c> 8 & P_b> 5”.
  • a frequency distribution is created from the history for the past two weeks, and a test value for the frequency distribution is obtained and stored in the HDD of the management rule test server.
  • the present invention can be applied to a purpose of creating a management rule for a system that automatically manages a system constituted by a computer or a plurality of computers connected by a network.
  • the management rule creator is presented with information for determining whether the quality item referred to by the created management rule is appropriate for the purpose used for the condition judgment based on the threshold. be able to.
  • the frequency distribution of the quality item value can be displayed from the past history for the quality item referenced by the management rule.
  • the quality item has a high correlation and the frequency distribution of the frequency distribution is divided into two distributions according to the threshold, that is, the frequency distribution of quality items having a distribution with multiple local maximum values is also displayed.
  • the management rule creator can see the characteristics of the quality item referred to by the created management rule. As a result, it is possible to determine whether or not the referenced quality item is appropriate.
  • the quality item referenced by the management rule has a high correlation
  • the frequency distribution of the quality item has a shape in which the frequency distribution is divided into two distributions depending on the threshold value, that is, a distribution with multiple local maximum values. Is also displayed together.
  • a high correlation with the quality item referenced by the tested control rule means that if a certain quality item exceeds a certain threshold value, the other quality item also exceeds the threshold value at the same time. This means that it can be expected to have a threshold value, which means that it can be used to determine the same situation.
  • the management rule is changed by changing the quality item referenced by the created management rule activation condition. Information for determining whether to operate more appropriately can be presented.

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Abstract

It is possible to solve the problem that a quality item to be referenced by a start condition is inappropriately selected when checking whether the start condition of a new management rule generated is appropriately set. Among quality items issued by a system, the one having a high correlation with a quality item referenced by the management rule start condition is displayed. The value frequency distribution has a plurality of maximum values, the interval of the values having the maximum values are apart from one another, and a difference between the frequency at the minimum values and the frequency at the maximum values is large. Thus, for the quality item referenced by the start condition of the management rule created by the creator, it is possible to present to the creator of the management rule whether any quality item which can be used as an alternative and is appropriate for judgment made by a threshold value exists.

Description

情報提供システム、情報提供装置、情報提供方法およびプログラムInformation providing system, information providing apparatus, information providing method, and program
　本発明は、新たに作成した管理ルールの起動条件が適切に設定されているかを試験して調べるための情報を提供するための技術に関し、特に管理ルールが起動する特定の品質条件に対して閾値による条件を特定した起動条件に対して、起動条件が適切な品質情報を参照しているか、管理ルール作成者が判断するための情報を、管理ルール作成者に対して提示することができる技術に関する。 The present invention relates to a technique for providing information for testing and checking whether or not a start condition of a newly created management rule is appropriately set, and in particular, a threshold value for a specific quality condition that the management rule starts. It is related with the technique which can show a management rule maker the information for a management rule maker to judge whether the start condition is referring to the appropriate quality information with respect to the start condition which specified conditions by .
　管理ルールとは、管理対象とするシステムや装置の稼働状態や動作状況を監視し、条件が満たされたとき、つまり、管理ルールが想定する状況が管理対称システムに発生したときに、その管理ルールに設定された動作を行うことで、システムの管理を自動的に行うことを目的にしたものである。 Management rules monitor the operating status and operating status of systems and devices to be managed, and when the conditions are met, that is, when the status assumed by the management rules occurs in the management symmetric system, the management rules The purpose is to automatically manage the system by performing the operation set in (1).
　この管理ルールは起動条件を持つ。たとえば「ＣＰＵ負荷＞１０」などというものである。これは、品質項目「ＣＰＵ負荷」の値が１０以上であるときにこの管理ルールの「動作」が実行されるというものである。この管理ルールは、管理ルールが管理の対象とするシステムの動作に精通した人が、その知識に基づいて、作成するものである。 This management rule has a start condition. For example, “CPU load> 10”. This means that when the value of the quality item “CPU load” is 10 or more, the “operation” of this management rule is executed. This management rule is created based on the knowledge of a person who is familiar with the operation of the system managed by the management rule.
　新たに作成された管理ルールは、不必要なときに動作するようなことがないよう、また、想定した状況が発生したときには、意図通りに動作するよう確認してから、実際のシステムに適用する。なぜなら、意図通りに動作しないルールでは、管理対象のシステムの状態を正しく把握することができず、システムの異常を引き起こすこともありうるからである。そのために、まず、作成された管理ルールの起動条件が適切に設定されているか確認することが必要となる。 Newly created management rules should be applied to the actual system after confirming that they will not work when they are not needed, and that they will work as intended when an expected situation occurs. . This is because a rule that does not operate as intended cannot correctly grasp the state of the system to be managed, and may cause a system abnormality. For this purpose, first, it is necessary to check whether the activation conditions of the created management rule are set appropriately.
　管理ルールの動作を確認するために、管理ルールが動作の対象と想定している事象が実際に発生したときのデータ、もしくはそれを模したデータを、管理ルールに入力し、管理ルールの動作結果を人が観察して、想定どおりの動作を行い、想定どおりの結果を出力しているか確認することができる。 In order to confirm the operation of the management rule, the data when the event that the management rule is supposed to operate or the data that imitates it is entered into the management rule, and the operation result of the management rule It is possible to confirm whether a person performs the operation as expected and outputs the expected result.
　一般的な管理ルール試験システムの一例が、特許文献１に記載されている。図６に示すような管理ルール試験システムは、試験条件データ保存部６０２、エキスパートシステム６２３、実行結果出力手段６２２、および表示装置６１０を含む。 An example of a general management rule test system is described in Patent Document 1. The management rule test system as shown in FIG. 6 includes a test condition data storage unit 602, an expert system 623, an execution result output unit 622, and a display device 610.
　エキスパートシステム６２３とは、管理ルールの集合と考えることができる。 The expert system 623 can be considered as a set of management rules.
　エキスパートシステムが管理対象と想定する装置、システムの過去の状況から得た状態情報、品質情報が、試験条件データ保存部に保存されており、試験時には、それぞれ、試験条件データ保存部からシステムの状態情報を得て、そのデータをエキスパートシステムに与え、その結果を表示機に表示することでエキスパートシステム、つまり管理ルールの良し悪しを判定する。
特開平８－２０２４３０号公報　（第２－４頁、図１） Equipment that is assumed to be managed by the expert system, status information obtained from the system's past status, and quality information are stored in the test condition data storage unit. The information is obtained, the data is given to the expert system, and the result is displayed on the display device to judge whether the expert system, that is, the management rule is good or bad.
JP-A-8-202430 (page 2-4, FIG. 1)
　第１の問題点は、作成された管理ルールの起動条件として採用した品質項目が最適なものか確認できないことである。 The first problem is that it is not possible to confirm whether the quality item adopted as the start condition of the created management rule is optimal.
　その理由は、既存の技術では、起動条件とした品質項目での判断でどの程度誤判定のしやすさを判断することができないためである。 The reason is that, with the existing technology, it is not possible to determine how easily misjudgment can be made by judging the quality item as the start condition.
　つまり、過去の品質情報による管理ルールの試験では、管理ルールが与えられた品質情報に対して想定どおりの動作を行い、想定どおりの結果を出力したかを確認する。 In other words, in the management rule test based on the past quality information, the operation is performed as expected on the quality information given the management rule, and it is confirmed whether the expected result is output.
　過去の品質情報による管理ルールの試験により、管理ルールが意図とは異なるものと判断された場合は条件の閾値を変更する等のルールの改善が行われる。 If the management rule is judged to be different from the intention by the management rule test based on past quality information, the rule is improved such as changing the threshold value of the condition.
　しかし、この試験で正しいと判断された場合でも、必ず管理ルールが正しく動作するとは限らない。なぜなら、品質項目によっては、システムが正常な状態であっても、品質項目の値が一時的に悪化することもあるため、適切でない品質項目の値が閾値を越えたことをもって起動条件とすると、管理ルールが意図通り動作しなくなる。しかし、管理ルールの動作試験では、管理ルールが正しく動作しないことはわかっても、どの品質項目が適切でないのかわからないという問題がある。 However, even if it is determined to be correct in this test, the management rule does not always work correctly. Because, depending on the quality item, even if the system is in a normal state, the value of the quality item may be temporarily deteriorated. Management rules do not work as intended. However, in the management rule operation test, there is a problem that even if it is known that the management rule does not operate correctly, it is not possible to know which quality item is not appropriate.
　第２の問題点は、作成された管理ルールの起動条件として採用した品質項目の代わりに採用可能な品質項目の有無が確認できないことである。 The second problem is that it is not possible to confirm whether there is a quality item that can be adopted instead of the quality item adopted as the activation condition of the created management rule.
　その理由は、システムが報告する品質項目は多種類に渡り、また、それらの品質は相互に関連があるため、ある異常が発生したときに複数の品質が悪化するが、その品質のいずれを見るべきかわからないためである。 The reason is that there are many kinds of quality items reported by the system, and those qualities are related to each other, so when a certain abnormality occurs, multiple qualities deteriorate. This is because we don't know what to do.
　つまり、ある異常が発生した場合に対処を行う管理ルールを作成しようとした場合、その異常により引き起こされる品質低下がどのようなものになるか検証し、それにあわせて参照する品質項目を選定し、異常と正常を分かつ閾値を決め、起動条件とする。しかし、一つの異常で悪化する品質項目は複数になりうる。さらに、品質項目によっては、品質情報(品質項目の値)が、正常時にも一時的に悪化するものがありうるため、不適切な品質項目を選択すると、異常と正常をうまく区別することができなくなる。そこで、異常時と正常時の振る舞いがなるべく異なるパラメータを利用することが必要となる。 In other words, if you try to create a management rule to deal with a certain abnormality, verify the quality degradation caused by the abnormality, select a quality item to refer to it, Abnormality and normality are divided and a threshold value is determined as an activation condition. However, there can be multiple quality items that deteriorate due to one abnormality. In addition, depending on the quality item, quality information (quality item value) may temporarily deteriorate even during normal operation, so selecting an inappropriate quality item makes it possible to distinguish abnormal from normal. Disappear. Therefore, it is necessary to use different parameters as much as possible for the behavior at the time of abnormality and normal.
　そこで、本発明が解決しようとする課題は、上記課題を解決することにあり、作成した管理ルールの起動条件として参照した品質情報が、閾値による起動条件として参照するのに適しているか、管理ルール作成者に対して検証するための情報を生成して提示することにある。 Therefore, the problem to be solved by the present invention is to solve the above-mentioned problem, and whether the quality information referred to as the activation condition of the created management rule is suitable for being referred to as the activation condition based on the threshold value. The purpose is to generate and present information for verification to the creator.
　また、作成した管理ルールの起動条件として参照した品質情報と比べ、より閾値により分析するのに適した品質情報を探し出し、管理ルール作成者に提示できる管理ルール試験システムを提供することにある。 Also, it is to provide a management rule test system that can find quality information suitable for analysis based on a threshold value and present it to the management rule creator, compared with the quality information that is referred to as the start condition of the created management rule.
　上記課題を解決するための本発明は、情報提供システムであって、管理対象である装置の動作品質を示す数値の履歴が品質項目毎に記憶されている記憶部と、前記記憶部から品質項目毎に数値の履歴を収集する情報収集手段と、前記収集した数値の履歴から頻度分布を作成し、この頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成手段とを有することを特徴とする。 The present invention for solving the above problems is an information providing system, wherein a storage unit stores a history of numerical values indicating operation quality of a device to be managed for each quality item, and a quality item from the storage unit. Information collection means that collects numerical history every time, and creates a frequency distribution from the collected numerical history, and uses this frequency distribution to determine whether the quality item that is the starting condition of the management rule is appropriate And generating means for generating information for doing so.
　また、上記課題を解決するための本発明は、情報提供装置であって、管理対象である装置の動作品質を示す数値の履歴を品質項目毎に収集する情報収集手段と、前記収集した品質項目の数値の履歴から頻度分布を生成し、この頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成手段とを有することを特徴とする。 Further, the present invention for solving the above-mentioned problems is an information providing device, and information collecting means for collecting, for each quality item, a history of numerical values indicating the operation quality of the device to be managed, and the collected quality item Generation means for generating a frequency distribution from the history of numerical values and generating information for determining whether the quality item which is the start condition of the management rule is appropriate using the frequency distribution And
　また、上記課題を解決するための本発明は、情報提供方法であって、管理対象である装置の動作品質を示す数値の履歴が品質項目毎に記憶されている記憶部から品質項目毎に数値の履歴を収集する情報収集ステップと、前記収集した数値の履歴から頻度分布を作成する頻度分布作成ステップと、前記作成された頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成ステップとを有することを特徴とする。 Further, the present invention for solving the above-described problem is an information providing method, in which a numerical value history indicating the operation quality of a device to be managed is stored for each quality item, and a numerical value for each quality item is stored for each quality item. An information collection step for collecting the history of data, a frequency distribution creation step for creating a frequency distribution from the collected history of numerical values, and a quality item that is a start condition of the management rule using the created frequency distribution is appropriate And a generation step of generating information for determining whether or not.
　また、上記課題を解決するための本発明は、プログラムであって、前記プログラムは情報処理装置を、管理対象である装置の動作品質を示す数値の履歴を品質項目毎に収集する情報収集手段と、前記収集した品質項目の数値の履歴から頻度分布を生成し、この頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成手段として機能させることを特徴とする。 Further, the present invention for solving the above-mentioned problem is a program, and the program includes an information collection unit that collects, for each quality item, a history of numerical values indicating the operation quality of a device to be managed. Generating means for generating a frequency distribution from the collected history of numerical values of the quality items, and generating information for determining whether the quality item which is the starting condition of the management rule is appropriate using the frequency distribution It is made to function as.
　本発明によると、作成した管理ルールが参照した品質項目が、閾値による条件判断に使用する目的に対して適切であるかどうか、管理ルール作成者に対して判断するための情報を提示することができる。 According to the present invention, it is possible to present information for determining to the management rule creator whether or not the quality item referred to by the created management rule is appropriate for the purpose used for the condition determination by the threshold. it can.
本発明の第１の発明を実施するための最良の形態の構成を示すブロック図である。[BRIEF DESCRIPTION OF THE DRAWINGS] It is a block diagram which shows the structure of the best form for implementing 1st invention of this invention. 第１の発明を実施するための最良の形態の動作を示す流れ図である。It is a flowchart which shows operation | movement of the best form for implementing 1st invention. 本発明の第２の発明を実施するための最良の形態の構成を示すプロック図である。It is a block diagram which shows the structure of the best form for implementing 2nd invention of this invention. 第２の発明を実施するための最良の形態の動作を示す流れ図である。It is a flowchart which shows operation | movement of the best form for implementing 2nd invention. 第２の発明を実施するための最良の形態の動作を示す流れ図である。It is a flowchart which shows operation | movement of the best form for implementing 2nd invention. 第２の発明を実施するための最良の形態の動作を示す流れ図である。It is a flowchart which shows operation | movement of the best form for implementing 2nd invention. 第１の発明を実施するための最良の形態の動作の具体例を示す図である。It is a figure which shows the specific example of operation | movement of the best form for implementing 1st invention. 本発明の動作の具体例における品質項目の値の履歴である。It is the history of the value of the quality item in the specific example of the operation of the present invention. 本発明の動作の具体例における品質項目の頻度分布である。It is frequency distribution of the quality item in the specific example of operation | movement of this invention. 本発明の動作の具体例における検定値の高い品質項目の頻度分布である。It is frequency distribution of a quality item with a high test value in the specific example of the operation of the present invention.
符号の説明Explanation of symbols
１００，２００　　コンピュータ
１０１，２０１　　起動条件取り出し手段
１０２，２０２　　品質項目管理テーブル
１０３，２０３　　相関計算手段
１０４，２０４　　頻度分布解析手段
１０５，２０５　　品質情報取得手段
１０６，２０６　　頻度分布グラフ作成手段
１１０，２１０　　管理ルール入力装置
１２０，２２０　　表示機
１３０，２３０　　データベース
２０７　　　　　　相関値テーブル
２０８　　　　　　相関値テーブル検索手段
２０９　　　　　　頻度分布テーブル
２０１０　　　　　頻度分布テーブル検索手段 100, 200 Computer 101, 201 Start condition extraction means 102, 202 Quality item management table 103, 203 Correlation calculation means 104, 204 Frequency distribution analysis means 105, 205 Quality information acquisition means 106, 206 Frequency distribution graph creation means 110, 210 Management Rule input device 120, 220 Display 130, 230 Database 207 Correlation value table 208 Correlation value table search means 209 Frequency distribution table 2010 Frequency distribution table search means
　次に、発明を実施するための最良の形態について図面を参照して詳細に説明する。 Next, the best mode for carrying out the invention will be described in detail with reference to the drawings.
　図1は、本発明の第1の実施の形態におけるシステムのブロック図である。 FIG. 1 is a block diagram of a system according to the first embodiment of the present invention.
　図１を参照すると、本発明の第１の実施の形態では、プログラム制御により動作するコンピュータ（中央処理装置；プロセッサ；データ処理装置）１００と、管理ルール入力装置１１０と、表示装置１２０と、データベース装置１3０とを有する。 Referring to FIG. 1, in the first embodiment of the present invention, a computer (central processing unit; processor; data processing unit) 100 that operates by program control, a management rule input unit 110, a display unit 120, and a database Device 1 30.
　コンピュータ（中央処理装置；プロセッサ；データ処理装置）１００は、起動条件取出部１０１と、品質項目管理部１０２と、相関計算部１０３と、頻度分布解析部１０４と、品質情報取得部１０５と、頻度分布グラフ作成部１０６とを有する。これらの各構成部は、以下のように動作する。 A computer (central processing unit; processor; data processing unit) 100 includes an activation condition extraction unit 101, a quality item management unit 102, a correlation calculation unit 103, a frequency distribution analysis unit 104, a quality information acquisition unit 105, and a frequency. And a distribution graph creation unit 106. Each of these components operates as follows.
　起動条件取出部１０１は、管理ルール入力装置１１０によって入力された管理ルールの起動条件となっている品質項目を解析し、この品質項目が参照しているパラメータの種類と、条件となる閾値が何であるか認識する。尚、複数入力された場合は、１つずつ取り出して一連の作業を行っていく。 The activation condition extraction unit 101 analyzes the quality item that is the activation condition of the management rule input by the management rule input device 110, and what kind of parameter is referred to by the quality item and the threshold value that is the condition Recognize if there is. When a plurality of inputs are made, one by one is taken out and a series of operations are performed.
　品質項目管理テーブル１０２は、動作中の機器（管理対象の機器）が報告してくる、管理ルールの条件となる品質情報の項目のリストを保有する。 The quality item management table 102 holds a list of quality information items that are the conditions of the management rule reported by the operating device (device to be managed).
　相関計算部１０３は、管理ルールの起動条件となっている品質情報とこれ以外の各品質情報とにおける、同じ時刻、同じ機器から発行された両品質情報の値を比較し、その値の相関値を計算する。片方の値が高い時刻、高い機器においては、もう片方の値も高くなるような場合、相関値が高いということになる。 The correlation calculation unit 103 compares the values of the quality information issued from the same device at the same time in the quality information that is the activation condition of the management rule and the other quality information, and the correlation value of the values Calculate For a device with a high value at one time and a high value, the correlation value is high when the other value is also high.
　頻度分布解析部１０４は、品質情報の頻度分布の形状が特異的な特徴を有するか、具体的には極大値を複数もつ形状であるかを判別し、頻度の極大値と極小値とを取る値の間隔および、極大値と極小値との差から得られる検定値を計算する。 The frequency distribution analysis unit 104 determines whether the shape of the frequency distribution of the quality information has a specific feature or, specifically, a shape having a plurality of maximum values, and takes the maximum value and the minimum value of the frequency. The test value obtained from the interval between the values and the difference between the maximum value and the minimum value is calculated.
　品質情報取得部１０５は、管理対象である機器の動作の品質を示す値の過去の履歴を、データベース装置１３０のデータベース２００から取得する。 The quality information acquisition unit 105 acquires a past history of values indicating the quality of operation of a device to be managed from the database 200 of the database device 130.
　頻度分布グラフ作成部１０６は、各品質項目について、値とその値をとる頻度とのグラフである、頻度分布グラフを作成する。 The frequency distribution graph creation unit 106 creates a frequency distribution graph that is a graph of the value and the frequency of taking the value for each quality item.
　データベース装置１３０は、データベース２００を有する。このデータベース２００には、管理対象の機器の動作状況である品質情報を数値で品質項目毎に時事記録した履歴データが記録されている。 The database device 130 has a database 200. In this database 200, history data in which quality information, which is an operation status of a device to be managed, is numerically recorded for each quality item is recorded.
　次に、図１及び図２のフローチャートを参照して本実施の形態の全体の動作について詳細に説明する。 Next, the overall operation of the present embodiment will be described in detail with reference to the flowcharts of FIGS.
　まず、試験動作が開始されると、管理ルール入力装置１１０は、設定されている管理ルールをコンピュータ１００に入力する（図２のステップＡ１）。 First, when the test operation is started, the management rule input device 110 inputs the set management rule to the computer 100 (step A1 in FIG. 2).
　起動条件取出部１０１は、ステップＡ１において入力された管理ルールから現在の起動条件の品質項目の名称及び閾値を認識する（ステップＡ２）。 The activation condition extraction unit 101 recognizes the name and threshold value of the quality item of the current activation condition from the management rule input in step A1 (step A2).
　品質情報取得部１０５は、ステップＡ２で取り出された品質項目の品質情報の過去履歴をデータベース１３０から取得する（図２のステップＡ３）。 The quality information acquisition unit 105 acquires the past history of the quality information of the quality item extracted in step A2 from the database 130 (step A3 in FIG. 2).
　頻度分布グラフ作成部１０６は、ステップＡ３で得た過去履歴から頻度分布のグラフを作成し（ステップＡ４）、ステップＡ２で起動条件取出部１０１が認識して得た品質項目の名称とともに表示機１２０に表示させる（ステップＡ５）。 The frequency distribution graph creation unit 106 creates a frequency distribution graph from the past history obtained in step A3 (step A4), and the display 120 together with the name of the quality item obtained by the activation condition extraction unit 101 in step A2. (Step A5).
　起動条件取得部１０５は、品質項目管理テーブル１０２を参照して、システムが報告してくる、ステップＡ２で取り出した品質項目とは異なる品質項目を取り出す(ステップＡ６)。 The activation condition acquisition unit 105 refers to the quality item management table 102 and extracts a quality item that is reported by the system and is different from the quality item extracted in step A2 (step A6).
　次に、品質情報取得部１０５は、ステップＡ６で取り出した品質項目の品質情報の過去履歴をデータベース１３０から取得して相関計算部１０３に渡す(ステップＡ７)。 Next, the quality information acquisition unit 105 acquires the past history of the quality information of the quality item extracted in step A6 from the database 130 and passes it to the correlation calculation unit 103 (step A7).
　相関計算部１０３は、ステップＡ７で取り出した品質情報の過去履歴と、ステップＡ３で取り出した品質情報の過去履歴との相関値を計算する（ステップＡ８）。 The correlation calculation unit 103 calculates a correlation value between the past history of the quality information extracted in step A7 and the past history of the quality information extracted in step A3 (step A8).
　相関計算部１０３は、ステップＡ８で計算した相関値を所定の閾値と比較し、相関値の方が大きい場合は品質情報取得部１０５にステップＡ６で得た品質情報の履歴を頻度分布グラフ作成部１０６に渡すように命令してステップＡ１０に進み、小さい場合はステップＡ１５に進む(ステップＡ９)。 The correlation calculation unit 103 compares the correlation value calculated in step A8 with a predetermined threshold, and if the correlation value is larger, the quality information acquisition unit 105 stores the history of the quality information obtained in step A6 in the frequency distribution graph creation unit. The instruction is sent to 106, the process proceeds to step A10, and if smaller, the process proceeds to step A15 (step A9).
　ステップＡ９において、相関値が所定の閾値より大きいと判定された場合、頻度分布グラフ作成部１０６はステップＡ６で得た品質情報の頻度分布を計算して頻度分布解析部１０４に渡す(ステップＡ１０)。そして、頻度分布解析部１０４はその頻度分布の形状が極大値を複数もつかどうかの度合いを調べるために、頻度の極大値と極小値を取る値の間隔、及び極大値と極小値との差から得られる検定値を計算する(ステップＡ１１)。 If it is determined in step A9 that the correlation value is greater than the predetermined threshold, the frequency distribution graph creation unit 106 calculates the frequency distribution of the quality information obtained in step A6 and passes it to the frequency distribution analysis unit 104 (step A10). . Then, the frequency distribution analysis unit 104 examines the degree of whether or not the shape of the frequency distribution has a plurality of maximum values, the interval between the maximum value and the minimum value of the frequency, and the difference between the maximum value and the minimum value. The test value obtained from (1) is calculated (step A11).
　頻度分布解析部１０４はステップＡ１１で得られた検定値と所定の閾値とを比較し、検定値の方が大きい場合はその旨を頻度分布グラフ作成部１０６に通知してステップＡ１３に進み、検定値の方が小さい場合はステップＡ１４に進む(ステップＡ１２)。 The frequency distribution analysis unit 104 compares the test value obtained in step A11 with a predetermined threshold value. If the test value is larger, the frequency distribution analysis unit 104 notifies the frequency distribution graph creation unit 106 to that effect and proceeds to step A13. If the value is smaller, the process proceeds to step A14 (step A12).
　ステップＡ１２で検定値が閾値より大きいと判定された場合、頻度分布グラフ作成部１０６はステップＡ１０で得た品質情報の頻度分布と、ステップＡ６で得た品質項目の名称とを表示機に出力する(ステップＡ１３)。 When it is determined in step A12 that the test value is larger than the threshold value, the frequency distribution graph creation unit 106 outputs the frequency distribution of the quality information obtained in step A10 and the name of the quality item obtained in step A6 to the display. (Step A13).
　ステップＡ１２で検定値が閾値より小さいと判定された場合、ステップＡ２で得た品質項目以外のすべての品質項目について、ステップＡ６からステップＡ１３を繰り返す(ステップＡ１４)。 If it is determined in step A12 that the test value is smaller than the threshold value, step A6 to step A13 are repeated for all quality items other than the quality item obtained in step A2 (step A14).
　ステップＡ９において、相関値が規定の閾値より小さいと判定された場合、ステップＡ２で得た管理ルールの起動条件で参照しているすべての品質項目について、ステップＡ３から、ステップＡ１４まで繰り返す(ステップＡ１５)。 If it is determined in step A9 that the correlation value is smaller than the prescribed threshold value, steps A3 to A14 are repeated for all quality items referred to in the management rule activation conditions obtained in step A2 (step A15). ).
　次に、本実施の形態の効果について説明する。 Next, the effect of this embodiment will be described.
　本実施の形態では、管理ポリシの起動条件が参照している品質項目の値の分布と相関を持ち、なおかつ、極大値が複数ある分布を持つ、他の品質項目を発見し、その頻度分布をグラフとして表示することで、管理ポリシの起動条件として採用した品質項目よりも閾値判定による条件判断に適切な品質項目の有無や程度をルール作成者に提示することができるように構成されている。 In the present embodiment, other quality items that have a correlation with the distribution of the quality item value referenced by the activation condition of the management policy and have a plurality of local maximum values are found, and the frequency distribution is determined. By displaying it as a graph, it is possible to present to the rule creator the presence / absence and level of a quality item that is more suitable for condition judgment by threshold judgment than the quality item adopted as the management policy activation condition.
　ルール作成者は表示機に表示された頻度分布グラフを見て、作成したルールが採用した品質項目が閾値判断に利用することに適しているかどうかを判断することができる。 The rule creator can determine whether the quality item adopted by the created rule is suitable for use in threshold judgment by looking at the frequency distribution graph displayed on the display device.
　さらに、その品質項目に代用してルールの起動条件判断に利用でき、なおかつ、閾値により異常と正常を分割しやすい、つまり、異常時にもかかわらず正常と判断する場合や正常時に異常と判断する場合を、より避けやすくする品質項目を採用することができる。 Furthermore, it can be used to determine the activation condition of a rule instead of the quality item, and it is easy to divide anomaly and normality by a threshold value, that is, when it is judged normal or abnormal even when it is abnormal Quality items that make it easier to avoid can be adopted.
　次に、本発明の第２の発明を実施するための最良の形態について図面を参照して詳細に説明する。尚、上記実施の形態と同様の構成についてはその詳細な説明を省略する。 Next, the best mode for carrying out the second invention of the present invention will be described in detail with reference to the drawings. The detailed description of the same configuration as that of the above embodiment is omitted.
　図３を参照すると、本発明の第２の実施の形態は、プログラム制御により動作するコンピュータ（中央処理装置；プロセッサ；データ処理装置）２００と、管理ルール入力装置２１０と、表示装置２２０と、データベース装置２３０とから構成されている。 Referring to FIG. 3, the second embodiment of the present invention is a computer (central processing unit; processor; data processing unit) 200 that operates by program control, a management rule input unit 210, a display unit 220, and a database. The apparatus 230 is comprised.
　コンピュータ（中央処理装置；プロセッサ；データ処理装置）２００は、起動条件取出部２０１と、品質項目管理部２０２と、相関計算部２０３と、頻度分布解析部２０４と、品質情報取得部２０５と、条件付き情報取得部２０６と、頻度分布グラフ作成部２０７とを有する。 A computer (central processing unit; processor; data processing unit) 200 includes an activation condition extraction unit 201, a quality item management unit 202, a correlation calculation unit 203, a frequency distribution analysis unit 204, a quality information acquisition unit 205, a condition An attached information acquisition unit 206 and a frequency distribution graph creation unit 207.
　これらの各構成部はそれぞれ以下のように動作する。 These components operate as follows.
　起動条件取出部２０１は、管理ルールの起動条件を解析し、条件が参照しているパラメータの種類と、条件となる閾値が何であるか認識する。 The activation condition extraction unit 201 analyzes the activation condition of the management rule and recognizes what kind of parameter the condition refers to and what threshold value is the condition.
　品質項目管理テーブル２０２は、システム中の機器が報告する品質情報のリストを保有する。 The quality item management table 202 holds a list of quality information reported by devices in the system.
　相関計算部２０３は、二つの品質情報について、同じ時刻、同じ機器から発行された両品質情報の値を比較し、その値の相関値を計算する。片方の値が高い時刻、高い機器においては、もう片方の値も高くなるような場合相関値が高くなる。 The correlation calculation unit 203 compares the values of both quality information issued from the same device at the same time for the two quality information, and calculates the correlation value of the values. At a time when one value is high and a high device, the correlation value is high when the other value is high.
　頻度分布解析部２０４は、品質情報の頻度分布の形状が極大値を複数もつ形状であるかを判別し、頻度の極大値と極小値を取る値の間隔および、極大値と極小値との差から得られる検定値を計算する。 The frequency distribution analysis unit 204 determines whether the shape of the frequency distribution of the quality information is a shape having a plurality of maximum values, the interval between the values at which the frequency maximum value and the minimum value are taken, and the difference between the maximum value and the minimum value Calculate the test value obtained from.
　品質情報取得部２０５は、指定された品質の品質情報の過去の履歴を、データベース２００から取得する。 The quality information acquisition unit 205 acquires the past history of the quality information of the designated quality from the database 200.
　頻度分布グラフ作成部２０６は、品質項目について、値とその値をとる頻度とのグラフである、頻度分布を計算する。 The frequency distribution graph creation unit 206 calculates a frequency distribution, which is a graph of the value and the frequency of taking the value for the quality item.
　相関値テーブル２０７は、相関計算部２０３により計算された各品質項目間の相関値を保存するテーブルである。 The correlation value table 207 is a table that stores correlation values between quality items calculated by the correlation calculation unit 203.
　相関値テーブル計算部２０８は、二つの品質項目間の相関値を相関値テーブル２０７から検索する。 The correlation value table calculation unit 208 searches the correlation value table 207 for a correlation value between two quality items.
　頻度分布テーブル２０９は、頻度分布グラフ作成部２０６で作成した頻度分布と、頻度分布解析部２０４で計算した検定値とを保存するテーブルである。 The frequency distribution table 209 is a table for storing the frequency distribution created by the frequency distribution graph creating unit 206 and the test value calculated by the frequency distribution analyzing unit 204.
　頻度分布検索部２０１０は、頻度分布テーブル２０９から、指定された品質項目に対する頻度分布と検定値を取得する。 The frequency distribution search unit 2010 acquires the frequency distribution and the test value for the designated quality item from the frequency distribution table 209.
　次に、図３および図４のフローチャートを参照して本実施の形態の全体の動作について詳細に説明する。 Next, the overall operation of the present embodiment will be described in detail with reference to the flowcharts of FIGS.
　まず、試験動作が開始すると、現在設定されている管理ルールを管理ルール入力装置２１０からコンピュータ２００に入力する（図４のステップＢ１）。 First, when the test operation starts, the currently set management rule is input from the management rule input device 210 to the computer 200 (step B1 in FIG. 4).
　次に、起動条件取出部２０１は、ステップＢ１において入力された管理ルールから起動条件の品質項目と閾値を一つ認識して相関テーブル検索部２０８を介して頻度分布検索部２０１０に通知する（ステップＢ２）。 Next, the activation condition extraction unit 201 recognizes one quality item and threshold value of the activation condition from the management rule input in step B1, and notifies the frequency distribution search unit 2010 via the correlation table search unit 208 (step). B2).
　ステップＢ２で得た品質項目の頻度分布を頻度分布検索部２０１０が頻度分布テーブル２０９から取得する（ステップＢ３）。 The frequency distribution search unit 2010 acquires the frequency distribution of the quality item obtained in step B2 from the frequency distribution table 209 (step B3).
　さらに、頻度分布検索部２０１０は、ステップＢ３で得た頻度分布をステップＢ２で得た品質項目の名称とともに表示機２２０に表示させる（ステップＢ４）。 Further, the frequency distribution search unit 2010 displays the frequency distribution obtained in step B3 on the display device 220 together with the name of the quality item obtained in step B2 (step B4).
　相関テーブル検索部２０８は、ステップＢ２で得た品質項目以外の品質項目を品質項目管理テーブル２０２から一つ取り出す(ステップＢ５)。 The correlation table search unit 208 extracts one quality item other than the quality item obtained in step B2 from the quality item management table 202 (step B5).
　相関テーブル検索部２０８は、ステップＢ５で得た品質項目とステップＢ２で得た品質項目の相関値を相関値テーブル２０７から取得する(ステップＢ６)。 The correlation table search unit 208 acquires the correlation value between the quality item obtained in step B5 and the quality item obtained in step B2 from the correlation value table 207 (step B6).
　相関テーブル検索部２０８は、ステップＢ６で計算した相関値を規定の閾値と比較し、大きい場合はその旨を頻度分布検索部２０１０に通知してステップＢ８に進み、小さい場合ステップＢ１２に進む(ステップＢ７)。 The correlation table search unit 208 compares the correlation value calculated in step B6 with a prescribed threshold value. If the correlation value is large, the correlation table search unit 208 notifies the frequency distribution search unit 2010 to that effect and proceeds to step B8. B7).
　頻度分布テーブル検索手段２０１０は、ステップＢ５で得た品質情報の頻度分布の検定値を、頻度分布テーブル２０９から取得する(ステップＢ８)。 The frequency distribution table search means 2010 acquires the test value of the frequency distribution of the quality information obtained in step B5 from the frequency distribution table 209 (step B8).
　ステップＢ８で得た検定値を規定の閾値と比較し、大きい場合はその旨を頻度分布検索部２０１０に通知してステップＢ１０に進み、小さい場合はステップＢ１２に進む(ステップＢ９)。 The test value obtained in step B8 is compared with a prescribed threshold value. If it is larger, the frequency distribution search unit 2010 is notified to that effect and proceeds to step B10. If smaller, the process proceeds to step B12 (step B9).
　頻度分布検索部２０１０は、ステップＢ５で得た品質項目の頻度分布を頻度分布テーブル２０９から取得し(ステップＢ１０)、ここで得た頻度分布と、ステップＢ５で得た品質項目の名称を表示機２２０に表示させる(ステップＢ１１)。 The frequency distribution search unit 2010 acquires the frequency distribution of the quality item obtained in step B5 from the frequency distribution table 209 (step B10), and displays the frequency distribution obtained here and the name of the quality item obtained in step B5. 220 is displayed (step B11).
　さらに、ステップＢ２で得た品質項目以外のすべての品質項目について、ステップＢ５からステップＢ１１を繰り返す(ステップＢ１２)。 Further, Step B5 to Step B11 are repeated for all quality items other than the quality item obtained in Step B2 (Step B12).
　さらに、ステップＢ２で得た管理ルールの起動条件で参照しているすべての品質項目について、ステップＢ２から、ステップＢ１２まで繰り返す(ステップＢ１３)。 Further, for all quality items referred to in the management rule activation condition obtained in step B2, the process is repeated from step B2 to step B12 (step B13).
　また、上記ステップＢ１からＢ１３までとは独立に、品質情報取得部２０５は品質項目管理テーブル２０２からすべての品質項目を一つずつ取り出し(ステップＢ１４)、それぞれの品質項目に対して品質情報を取得する（ステップＢ１５）。 Independent of steps B1 to B13, the quality information acquisition unit 205 extracts all the quality items one by one from the quality item management table 202 (step B14), and acquires quality information for each quality item. (Step B15).
　頻度分布グラフ作成手段２０６が、ステップＢ１５で得た品質情報から頻度分布グラフを作成し（ステップＢ１６）、頻度分布解析部２０４がステップＢ１６で頻度分布グラフ作成手段２０６が作成した頻度分布グラフに基づいて検定値を計算する（ステップＢ１７）。 The frequency distribution graph creating unit 206 creates a frequency distribution graph from the quality information obtained in step B15 (step B16), and the frequency distribution analyzing unit 204 is based on the frequency distribution graph created by the frequency distribution graph creating unit 206 in step B16. The test value is calculated (step B17).
　頻度分布解析部２０４は、ステップＢ１６で得た頻度分布グラフとステップＢ１７で得た検定値とをステップＢ１４で得た品質項目に対応するデータとして、頻度分布テーブル２０９に登録する(ステップＢ１８)。 The frequency distribution analysis unit 204 registers the frequency distribution graph obtained in step B16 and the test value obtained in step B17 as data corresponding to the quality item obtained in step B14 in the frequency distribution table 209 (step B18).
　品質情報取得部２０５は、品質項目管理テーブル２０２からステップＢ１４で得た品質項目とは異なる品質項目を一つ取り出し(ステップＢ１９)、ここで得た品質項目の品質情報をデータベース２３０から取得する(ステップＢ２０)。 The quality information acquisition unit 205 extracts one quality item different from the quality item obtained in step B14 from the quality item management table 202 (step B19), and acquires the quality information of the quality item obtained here from the database 230 ( Step B20).
　品質情報取得部２０５は、ステップＢ１５で得た品質情報と、ステップＢ２０で得た品質情報とを相関計算部２０３に渡し、相関計算部２０３はそれらの品質情報の相関値を計算する(ステップＢ２１)。相関計算部２０３は、この計算結果をステップＢ１４で得た品質項目と、ステップＢ１９で得た品質項目の組に対応するデータとして相関値テーブル２０７に登録する(ステップB22)。 The quality information acquisition unit 205 passes the quality information obtained in step B15 and the quality information obtained in step B20 to the correlation calculation unit 203, and the correlation calculation unit 203 calculates a correlation value of the quality information (step B21). ). The correlation calculation unit 203 registers the calculation result in the correlation value table 207 as data corresponding to the combination of the quality item obtained in step B14 and the quality item obtained in step B19 (step B22).
　品質項目管理テーブル２０２からステップＢ１４で得た品質項目とは異なる品質項目を1つずつ取り出し、品質項目すべてに対して一度ずつ、ステップＢ１９からステップＢ２２までを行う(ステップＢ２３)。 The quality item different from the quality item obtained in step B14 is taken out from the quality item management table 202 one by one, and step B19 to step B22 are performed once for all the quality items (step B23).
　さらに、すべての品質項目について一度ずつ、ステップＢ１４からステップＢ２３を行う(ステップＢ２４)。 Furthermore, Step B14 to Step B23 are performed once for all quality items (Step B24).
　次に、本発明を実施するための最良の形態の効果について説明する。 Next, the effect of the best mode for carrying out the present invention will be described.
　本発明を実施するための最良の形態では、品質項目の頻度分布と、頻度分布の形状の検定値と、品質項目間の相関値が予め、計算され、テーブルに保存され、またそのデータが定期的に更新され、管理ルール登録時には、その予め計算された相関値、検定値を用いて、管理ルールに対応する表示項目の選択が行われるように構成されているため、管理ルール登録時に、参照品質項目候補を高速に表示することができる。 In the best mode for carrying out the present invention, a frequency distribution of quality items, a test value of the shape of the frequency distribution, and a correlation value between the quality items are calculated in advance, stored in a table, and the data is periodically transmitted. When the management rule is registered, the display item corresponding to the management rule is selected using the correlation value and the test value calculated in advance. Quality item candidates can be displayed at high speed.
＜実施例＞
　次に、具体的な実施例を用いて本発明を詳細に説明する。 <Example>
Next, the present invention will be described in detail using specific examples.
　図５に示すように、本管理ルール試験システムは、管理ルール作成端末５００と、管理ルール試験サーバ５１０と管理サーバ５２０と管理対象システム５３０とを有する。 As shown in FIG. 5, the management rule test system includes a management rule creation terminal 500, a management rule test server 510, a management server 520, and a management target system 530.
　管理ルール作成端末５００はＰＣであり管理ルール登録装置、表示機として機能する。 The management rule creation terminal 500 is a PC and functions as a management rule registration device and a display device.
　管理ルール試験サーバ５１０はＰＣであり、図１におけるコンピュータ１００として機能する。 The management rule test server 510 is a PC and functions as the computer 100 in FIG.
　管理サーバ５２０はＰＣであり、図１におけるデータベース１０３として機能し、管理対象となるネットワークシステムから定期的に情報を収集している。 The management server 520 is a PC, functions as the database 103 in FIG. 1, and periodically collects information from the network system to be managed.
　管理対象システム５３０は複数の機器から構成されるシステムであり、図5ではサーバＡ５３１、サーバＢ５３２、サーバＣ５３３を有する。 The management target system 530 is a system composed of a plurality of devices, and includes a server A531, a server B532, and a server C533 in FIG.
　例えば、管理ルールの起動条件は「Ｐ_ａ＞１０ ＆ Ｐ_ｂ＞５」などと指定されるとする。つまり、この例における管理ルールの起動条件が参照する品質項目は、Ｐ_ａとＰ_ｂとであり、Ｐ_ａの閾値は１０、Ｐ_ｂの閾値は５となり、定期的に報告されるＰ_ａの値が１０以上となり、同時にＰ_ｂの値が５以上になる機器があった場合、この管理ルールが、その機器に対して動作する。 For example, it is assumed that the activation condition of the management rule is specified as “P_a> 10 & P_b> 5”. That is, the quality items referred to by the management rule activation condition in this example are P_a and P_b, the threshold value of P_a is 10, the threshold value of P_b is 5, and the value of P_a that is regularly reported is 10 or more. At the same time, when there is a device whose P_b value is 5 or more, this management rule operates on that device.
　この管理ルールを本発明の管理ルール試験システムの管理ルール作成端末５００に登録すると、Ｐ_ａ、Ｐ_ｂの二つの品質項目を取り出す。 When this management rule is registered in the management rule creation terminal 500 of the management rule test system of the present invention, two quality items P_a and P_b are extracted.
　まず、Ｐ_ａの品質情報の過去履歴を取得する。図７のようにシステム中に存在する機器ごとに、時間ごとに変動するＰ_ａの値が取得される。図７では管理対象のネットワークシステムのサーバＡについてのグラフであり、縦軸がＰ_ａの値であり、横軸が時間となっている。この値から頻度分布を作成する。Ｐ_ａの頻度分布はたとえば、図８のようになる。この図８では横軸がＰ_ａの値、縦軸が品質情報を取得したすべての機器、つまり、サーバＡ、サーバＢ、サーバＣすべてについて、時刻における各値を報告した回数となる。 First, the past history of quality information of P_a is acquired. As shown in FIG. 7, for each device present in the system, the value of P_a that varies with time is acquired. FIG. 7 is a graph for the server A of the network system to be managed, the vertical axis is the value of P_a, and the horizontal axis is time. A frequency distribution is created from this value. The frequency distribution of P_a is, for example, as shown in FIG. In FIG. 8, the horizontal axis indicates the value of P_a, and the vertical axis indicates the number of times each value is reported for all devices that have acquired quality information, that is, server A, server B, and server C.
　ルール作成端末のテスト画面にはこのＰ_ａの頻度分布が表示される。 The frequency distribution of P_a is displayed on the test screen of the rule creation terminal.
　次に、Ｐ_ａ以外の品質項目Ｐ_ｂ、Ｐ_ｃ、Ｐ_ｄ、Ｐ_ｅについて、Ｐ_ａとの相関値を計算する。 Next, a correlation value with P_a is calculated for quality items P_b, P_c, P_d, and P_e other than P_a.
　それぞれ、Ｐ_ｂとの相関値は０．３、Ｐ_ｃとは０．７、Ｐ_ｄとは０．２、Ｐ_ｅとは０．９となり、閾値として０．７を採用し、Ｐ_ｃ、Ｐ_ｅが残る。それぞれについて頻度分布の形状の検定値を計算する。ここで、検定値は、頻度分布を総和が1になるように正規化し、さらにその正規化した頻度と、値をもつ範囲の分割数、つまり棒グラフの棒の数との積をとり、その値をとって検定値の計算に使用する。この頻度分布中の極大値(二つある)と極小値との差を計算し、互いとの積をとる。 The correlation values with P_b are 0.3, 0.7 with P_c, 0.2 with P_d, and 0.9 with P_e, respectively, and 0.7 is used as the threshold value, leaving P_c and P_e. The test value of the shape of the frequency distribution is calculated for each. Here, the test value is the value obtained by normalizing the frequency distribution so that the sum is 1, and multiplying the normalized frequency by the number of divisions in the range with the value, that is, the number of bars in the bar graph. Is used to calculate the test value. The difference between the maximum value (there are two) and the minimum value in this frequency distribution is calculated, and the product with each other is calculated.
　Ｐ_ｃは０．８、Ｐ_ｅは０．３で、閾値である０．７を超えたＰ_ｃの頻度分布(図９)を表示する。また、このとき、補助のため、Ｐ_ａの閾値である１０以上に対応するＰ_ａの頻度分布を別個に着色して表示する。 P_c is 0.8, P_e is 0.3, and the frequency distribution of P_c exceeding the threshold value 0.7 (FIG. 9) is displayed. At this time, for assistance, the frequency distribution of P_a corresponding to 10 or more, which is the threshold value of P_a, is separately colored and displayed.
　同様にＰ_ｂについても、Ｐ_ａ、Ｐ_ｃ、Ｐ_ｄ、Ｐ_ｅについて相関値を計算し、閾値を超えたＰ_ｄについて検定値を計算し、この場合、検定値が閾値を超えなかったので表示しない。 Similarly, for P_b, correlation values are calculated for P_a, P_c, P_d, and P_e, and a test value is calculated for P_d that exceeds the threshold value. In this case, the test value is not displayed because it does not exceed the threshold value.
　管理ルール作成者はこの表示を利用して、Ｐ_ａについては、Ｐ_ａはＰ_ｃに比べて、その値が閾値近傍の値をとることが多く、また、グラフの形状から性格に異常と正常の区別をつけているわけではなく、つまり、閾値判断に利用することに向いていないことがわかり、Ｐ_ｃをＰ_ａの代わりに用いたほうが、より正確に正常と異常を切り分けられると判断し、Ｐ_ａをＰ_ｃに置き換え、Ｐ_ｃの正常と異常を分けているように見える値を閾値として設定する、結果、管理ルールの起動条件を「Ｐ_ｃ＞８ ＆ Ｐ_ｂ＞５」と変更する。 The management rule creator uses this display, and for P_a, P_a often takes a value close to the threshold value compared to P_c, and distinguishes between abnormal and normal characters from the shape of the graph. In other words, it turns out that it is not suitable for use in threshold judgment, and it is judged that using P_c instead of P_a can more accurately distinguish between normal and abnormal, and P_a is changed to P_c. As a result, the activation condition of the management rule is changed to “P_c> 8 & P_b> 5”.
　また、一日ごとに管理サーバからすべての品質項目について、過去２週間分の品質情報の履歴を取り、すべての品質項目の組み合わせについて相関値を計算し、管理ルール試験サーバの持つ、ＨＤＤに保存しておく。 Also, a history of quality information for the past two weeks is collected for all quality items from the management server every day, correlation values are calculated for all combinations of quality items, and stored in the HDD of the management rule test server. Keep it.
　また、すべての品質項目について、過去２週間分の履歴から頻度分布を作成し、頻度分布の検定値を求めて、管理ルール試験サーバのＨＤＤに保存しておく。 Also, for all quality items, a frequency distribution is created from the history for the past two weeks, and a test value for the frequency distribution is obtained and stored in the HDD of the management rule test server.
　本発明によれば、コンピュータ、もしくはネットワークでつながれた複数のコンピュータにより構成されるシステムを自動管理するシステムの管理ルール作成といった用途に適用できる。 According to the present invention, the present invention can be applied to a purpose of creating a management rule for a system that automatically manages a system constituted by a computer or a plurality of computers connected by a network.
　上述した本発明によると、作成した管理ルールが参照した品質項目が、閾値による条件判断に使用する目的に対して適切であるかどうか、管理ルール作成者に対して判断するための情報を提示することができる。 According to the above-described present invention, the management rule creator is presented with information for determining whether the quality item referred to by the created management rule is appropriate for the purpose used for the condition judgment based on the threshold. be able to.
　これは、管理ルールが参照した品質項目について、過去履歴から品質項目の値の頻度分布を表示できるからである。また、この品質項目に対して、相関が高く、閾値により頻度分布が二つの分布に分かれるような形状、つまり、極大値が複数あるような分布を持つ品質項目の頻度分布もあわせて表示することで、システムが発行する品質情報の中で、作成した管理ルールが参照した品質項目がどのような特徴を示すか管理ルール作成者が見ることができるかれである。その結果、その参照した品質項目が適切なものであるかどうか判断できるためである。 This is because the frequency distribution of the quality item value can be displayed from the past history for the quality item referenced by the management rule. In addition, the quality item has a high correlation and the frequency distribution of the frequency distribution is divided into two distributions according to the threshold, that is, the frequency distribution of quality items having a distribution with multiple local maximum values is also displayed. In the quality information issued by the system, the management rule creator can see the characteristics of the quality item referred to by the created management rule. As a result, it is possible to determine whether or not the referenced quality item is appropriate.
　また、本発明によると、作成した管理ルールの意味、つまり、どのようなときに管理ルールが作動するのかという大枠の変化が少なく、しかも、より、閾値による条件記述に適した他の品質項目を管理ルール作成者に提示できる。 In addition, according to the present invention, there is little change in the meaning of the created management rule, that is, when the management rule is activated, and other quality items suitable for the condition description by the threshold value are added. Can be presented to the management rule creator.
　その理由は、管理ルールが参照した品質項目に対して、相関が高く、閾値により頻度分布が二つの分布に分かれるような形状、つまり、極大値が複数あるような分布を持つ品質項目の頻度分布もあわせて表示していることにある。試験された管理ルールが参照している品質項目に対して相関が高いということは、片方の品質項目についてある閾値を超えた場合、もう片方の品質項目についても、同時に閾値を越えるといえるような閾値を持つことが期待できるということであり、同じ状況を判別するために代用することが可能であるということを意味する。 The reason is that the quality item referenced by the management rule has a high correlation, and the frequency distribution of the quality item has a shape in which the frequency distribution is divided into two distributions depending on the threshold value, that is, a distribution with multiple local maximum values. Is also displayed together. A high correlation with the quality item referenced by the tested control rule means that if a certain quality item exceeds a certain threshold value, the other quality item also exceeds the threshold value at the same time. This means that it can be expected to have a threshold value, which means that it can be used to determine the same situation.
　更に、本発明によると、頻度分布に適した品質項目の頻度分布を、管理ルール作成者に提示することで、作成した管理ルールの起動条件が参照する品質項目を変更することで、管理ルールがより適切に動作するかどうかを判断するための情報を提示することができる。 Furthermore, according to the present invention, by presenting the frequency distribution of quality items suitable for the frequency distribution to the management rule creator, the management rule is changed by changing the quality item referenced by the created management rule activation condition. Information for determining whether to operate more appropriately can be presented.
　本出願は、２００８年１月１０日に出願された日本出願特願２００８－００３６４９号を基礎とする優先権を主張し、その開示の全てをここに取り込む。 This application claims priority based on Japanese Patent Application No. 2008-003649 filed on January 10, 2008, the entire disclosure of which is incorporated herein.

Claims (19)

  1. 　情報提供システムであって、
    　管理対象である装置の動作品質を示す数値の履歴が品質項目毎に記憶されている記憶部と、
    　前記記憶部から品質項目毎に数値の履歴を収集する情報収集手段と、
    　前記収集した数値の履歴から頻度分布を作成し、この頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成手段と
    を有することを特徴とする情報提供システム。     An information providing system,
    A storage unit in which a history of numerical values indicating the operation quality of the device to be managed is stored for each quality item;
    Information collecting means for collecting a numerical history for each quality item from the storage unit;
    Generating means for generating a frequency distribution from the collected history of numerical values, and generating information for determining whether the quality item which is the start condition of the management rule is appropriate using the frequency distribution; An information provision system characterized by
  2. 　前記生成手段は、現在の管理ルールの起動条件として設定されている品質項目以外の品質項目において、その数値の履歴から作成された頻度分布が所定の特異的な特徴を有するか否かを判断し、前記特異的な特徴を有すると判断した場合に、その品質項目の頻度分布のグラフを、管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報として生成することを特徴とする請求項１に記載の情報提供システム。 The generating means determines whether or not the frequency distribution created from the numerical history of the quality item other than the quality item set as the current management rule activation condition has a specific characteristic. , Generating a frequency distribution graph of the quality item as information for determining whether the quality item that is the start condition of the management rule is appropriate when it is determined that the characteristic item has the specific feature The information providing system according to claim 1.
  3. 　前記生成手段は、現在の管理ルールの起動条件として設定されている品質項目以外の品質項目の頻度分布が複数の極大値をもつか否かの度合いである検定値を計算し、この検定値が閾値より大きい場合にその品質項目の頻度分布のグラフを、管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報として生成することを特徴とする請求項１に記載の情報提供システム。 The generating means calculates a test value that is a degree of whether or not the frequency distribution of quality items other than the quality item set as the start condition of the current management rule has a plurality of maximum values, and the test value is The frequency distribution graph of the quality item is generated as information for determining whether the quality item that is the start condition of the management rule is appropriate when the value is larger than the threshold value. Information provision system.
  4. 　前記生成手段は、現在の管理ルールの起動条件となっている品質項目の数値の履歴とその他の品質項目の数値の履歴との相関値が閾値より大きいと相関計算手段によって判断された場合に比較することを特徴とする請求項１から請求項３のいずれかに記載の情報提供システム。 The generation means is compared when the correlation calculation means determines that the correlation value between the numerical value history of the quality item that is the activation condition of the current management rule and the numerical history of the other quality items is greater than a threshold value. The information providing system according to any one of claims 1 to 3, wherein the information providing system is provided.
  5. 　前記相関計算手段により計算された各品質項目間の相関値が記されている相関値テーブルと、
    　前記相関値テーブルから、特定の二つの品質項目間の相関値を取得する相関値テーブル検索手段と
    を有することを特徴とする請求項４に記載の情報提供システム。     A correlation value table in which correlation values between the quality items calculated by the correlation calculation means are written;
    5. The information providing system according to claim 4, further comprising correlation value table search means for acquiring a correlation value between two specific quality items from the correlation value table.
  6. 　前記頻度分布と検定値とが対応付けられている頻度分布テーブルと、
    　前記頻度分布テーブルから頻度分布と検定値とを取得する頻度分布テーブル検索手段と
    を有することを特徴とする請求項３から５のいずれかに記載の情報提供システム。     A frequency distribution table in which the frequency distribution and the test value are associated;
    6. The information providing system according to claim 3, further comprising frequency distribution table search means for acquiring a frequency distribution and a test value from the frequency distribution table.
  7. 　情報提供装置であって、
    　管理対象である装置の動作品質を示す数値の履歴を品質項目毎に収集する情報収集手段と、
    　前記収集した品質項目の数値の履歴から頻度分布を生成し、この頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成手段と
    を有することを特徴とする情報提供装置。     An information providing device,
    Information collecting means for collecting a history of numerical values indicating the operation quality of the device to be managed for each quality item;
    Generating means for generating a frequency distribution from a numerical history of the collected quality items, and generating information for determining whether the quality item that is the start condition of the management rule is appropriate using the frequency distribution; An information providing apparatus comprising:
  8. 　前記生成手段は、現在の管理ルールの起動条件として設定されている品質項目以外の品質項目において、その数値の履歴の頻度分布が所定の特異的な特徴を有するか否かを判断し、前記特異的な特徴を有すると判断した場合に、その品質項目の頻度分布のグラフを、管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報として生成することを特徴とする請求項７に記載の情報提供装置。 In the quality item other than the quality item set as the start condition of the current management rule, the generation unit determines whether or not the frequency distribution of the numerical history has predetermined specific characteristics, and And generating a frequency distribution graph of the quality item as information for determining whether the quality item that is the start condition of the management rule is appropriate The information providing apparatus according to claim 7.
  9. 　前記生成手段は、現在の管理ルールの起動条件として設定されている品質項目以外の品質項目の頻度分布が複数の極大値をもつか否かの度合いである検定値を計算し、この検定値が閾値より大きい場合にその品質項目の頻度分布のグラフを、管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報として生成することを特徴とする請求項７に記載の情報提供装置。 The generating means calculates a test value that is a degree of whether or not the frequency distribution of quality items other than the quality item set as the start condition of the current management rule has a plurality of maximum values, and the test value is 8. The frequency distribution graph of the quality item is generated as information for determining whether the quality item that is the start condition of the management rule is appropriate when the value is larger than the threshold value. Information provision device.
  10. 　前記生成手段は、相関計算手段によって、現在の管理ルールの起動条件となっている品質項目の数値の履歴とその他の品質項目の数値の履歴との相関値が閾値より大きいと判断された場合に比較することを特徴とする請求項７から請求項９のいずれかに記載の情報提供装置。 When the correlation calculating unit determines that the correlation value between the numerical value history of the quality item that is the activation condition of the current management rule and the numerical value history of the other quality items is greater than a threshold value, The information providing apparatus according to claim 7, wherein comparison is performed.
  11. 　前記相関計算手段により計算された各品質項目間の相関値が記されている相関値テーブルと、
    　前記相関値テーブルから、特定の二つの品質項目間の相関値を取得する相関値テーブル検索手段と
    を有することを特徴とする請求項１０に記載の情報提供装置。     A correlation value table in which correlation values between the quality items calculated by the correlation calculation means are written;
    The information providing apparatus according to claim 10, further comprising a correlation value table search unit that acquires a correlation value between two specific quality items from the correlation value table.
  12. 　前記頻度分布と検定値とが対応付けられている頻度分布テーブルと、
    　前記頻度分布テーブルから、頻度分布と検定値とを取得する頻度分布テーブル検索手段と
    を有することを特徴とする請求項９から１１のいずれかに記載の情報提供装置。     A frequency distribution table in which the frequency distribution and the test value are associated;
    The information providing apparatus according to claim 9, further comprising: a frequency distribution table search unit that acquires a frequency distribution and a test value from the frequency distribution table.
  13. 　情報提供方法であって、
    　管理対象である装置の動作品質を示す数値の履歴が品質項目毎に記憶されている記憶部から品質項目毎に数値の履歴を収集する情報収集ステップと、
    　前記収集した数値の履歴から頻度分布を作成する頻度分布作成ステップと、
    　前記作成された頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成ステップと
    を有することを特徴とする情報提供方法。     An information providing method,
    An information collecting step for collecting a numerical history for each quality item from a storage unit in which a numerical history indicating the operation quality of the device to be managed is stored for each quality item;
    A frequency distribution creating step of creating a frequency distribution from the collected history of numerical values;
    And a generation step of generating information for determining whether or not the quality item that is the activation condition of the management rule is appropriate using the created frequency distribution.
  14. 　現在の管理ルールの起動条件として設定されている品質項目以外の品質項目において、その数値の履歴から作成された頻度分布が所定の特異的な特徴を有するか否かを判断する判断ステップを有し、
    　前記生成ステップは、前記判断ステップで特異的な特徴を有すると判断した場合に、その品質項目の頻度分布のグラフを、管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報として生成することを特徴とする請求項１３に記載の情報提供方法。     In a quality item other than the quality item set as the current management rule activation condition, a determination step is performed to determine whether or not the frequency distribution created from the numerical history has predetermined specific characteristics. ,
    In the generation step, when it is determined in the determination step that the characteristic item has a specific characteristic, the frequency distribution graph of the quality item is determined to determine whether the quality item that is the start condition of the management rule is appropriate. The information providing method according to claim 13, wherein the information providing method is generated as information for the purpose.
  15. 　現在の管理ルールの起動条件として設定されている品質項目以外の品質項目の頻度分布が複数の極大値をもつか否かの度合いである検定値を計算する検定値計算ステップを有し、
    　前記生成ステップは、前記検定値計算ステップで計算された検定値が閾値より大きい場合にその品質項目の頻度分布のグラフを、管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報として生成することを特徴とする請求項１３に記載の情報提供方法。     A test value calculation step for calculating a test value that is a degree of whether or not the frequency distribution of quality items other than the quality item set as a start condition of the current management rule has a plurality of maximum values;
    In the generation step, when the test value calculated in the test value calculation step is larger than a threshold value, a graph of the frequency distribution of the quality item is determined, and it is determined whether the quality item that is the start condition of the management rule is appropriate. The information providing method according to claim 13, wherein the information providing method is generated as information to be performed.
  16. 　現在の管理ルールの起動条件となっている品質項目の数値の履歴とその他の品質項目の数値の履歴との相関値が閾値より大きいか否かを判断する相関計算ステップを有し、
    　前記生成ステップは、前記相関計算ステップにおいて前記相関値が閾値より大きいと判断された場合に比較することを特徴とする請求項１３から請求項１５のいずれかに記載の情報提供方法。     A correlation calculation step for determining whether or not the correlation value between the numerical value history of the quality item that is the activation condition of the current management rule and the numerical value history of the other quality items is greater than a threshold;
    The information providing method according to any one of claims 13 to 15, wherein the generation step performs comparison when it is determined in the correlation calculation step that the correlation value is greater than a threshold value.
  17. 　前記相関計算ステップにより計算された各品質項目間の相関値が記されている相関値テーブルから、特定の二つの品質項目間の相関値を取得する相関値テーブル検索ステップを有することを特徴とする請求項１６に記載の情報提供方法。 A correlation value table search step for obtaining a correlation value between two specific quality items from a correlation value table in which a correlation value between the quality items calculated in the correlation calculation step is recorded; The information providing method according to claim 16.
  18. 　前記頻度分布と検定値とが対応付けられている頻度分布テーブルから、頻度分布と検定値とを取得する頻度分布テーブル検索ステップを有することを特徴とする請求項１５から１７のいずれかに記載の情報提供方法。 The frequency distribution table search step for obtaining a frequency distribution and a test value from a frequency distribution table in which the frequency distribution and the test value are associated with each other. 18. Information provision method.
  19. 　プログラムであって、前記プログラムは情報処理装置を、
    　管理対象である装置の動作品質を示す数値の履歴を品質項目毎に収集する情報収集手段と、
    　前記収集した品質項目の数値の履歴から頻度分布を生成し、この頻度分布を用いて管理ルールの起動条件となっている品質項目が適切であるかを判断するための情報を生成する生成手段と
    して機能させることを特徴とするプログラム。     A program comprising: an information processing device;
    Information collecting means for collecting a history of numerical values indicating the operation quality of the device to be managed for each quality item;
    As a generation means for generating a frequency distribution from the collected numerical history of quality items, and generating information for determining whether the quality item that is the start condition of the management rule is appropriate using the frequency distribution A program characterized by functioning.
PCT/JP2009/050012 2008-01-10 2009-01-06 Information providing system, information providing device, information providing method, and program WO2009087986A1 (en)

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