JP2016076026A - Problem structure extraction device and problem structure extraction method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable a problem structure about business to be presented for a user together with an influence range.SOLUTION: A problem structure extraction device 1000 comprises: a storage device 1100 which stores a model in which elements affecting a predetermined business and a correlation between the elements are described in a prescribed rule and a problem structure model in which elements likely to generate a problem regarding business and correlation between the elements are defined by the prescribed rule; and a computation device 1300 which extracts a problem structure regarding the predetermined business from the models by checking the model and the problem structure model, specifies, regarding the extracted problem structure, an influence range of the problem structure on the basis of range information of an element included in data of the model or designated by a user through an input device, and executes processing for outputting information of the problem structure and the influence range thereof to an output device.SELECTED DRAWING: Figure 4

Description

  The present invention relates to a problem structure extraction apparatus and a problem structure extraction method, and more specifically, to a technique that allows a user to present a structure and an influence range of a business problem together to a user.

  In the business field, in the process of grasping the current state of management or work, finding problems, and planning countermeasures, BPD (Business Process Diagram), BPD (Business Process Diagram), Methods for modeling management and operations such as related tree diagrams and fishbone diagrams have been widely used.

  Among such technologies, for example, as a conventional technique related to problem finding of business processes, a business problem analysis apparatus that quantitatively visualizes business processes in CRM consulting work and supports problem extraction and evaluation work (see Patent Document 1) Etc. have been proposed. In this technology, business processes to be improved are extracted by using the business processes, management issues, importance of management issues, and the distribution ratio of impacts, and problems are extracted in sub-process units for the business processes to be improved. Output.

  In connection with this, there is a technical idea of a causal loop diagram (CLD) for modeling a causal relationship between system components, and a system simulation method using this (see Non-Patent Document 1). ) Has also been proposed. In addition, based on such a causal loop diagram modeling technique, a technique (see Non-Patent Document 2) related to a system prototype (a structure frequently seen in system dynamics) regarded as a problem structure has been proposed.

JP 2005-71113 A

“Industrial Dynamics”, The MIT Press. J. et al. W. Forester, 1961 “The Fifth Discipline”, Doubleday, P.A. M.M. Senge, 1990

  However, according to the conventional technology, although the business process to be improved is extracted, the scope of influence of the problem, that is, the scope of influence (for example, organization) remains unclear. It was difficult to quickly select a problem to be performed. On the other hand, when a user plans a countermeasure for a problem, the difficulty level of the countermeasure planning varies greatly depending on the above-described influence range of the problem.

This situation will be described by taking an example in the manufacturing process of the manufacturer. “The manufacturing department took measures to increase the capacity utilization rate in order to eliminate the production quota failure rate, but due to the increase in working hours accompanying the increase in the capacity utilization rate, the production efficiency of employees decreased and the production quota could not be achieved. The problem of “removing” and “the manufacturing department took measures to increase the capacity utilization rate in order to eliminate the production quota failure rate, but the production engineering department lessened the frequency of maintenance of the equipment, resulting in equipment failure. Let us consider a case where the problem that the rate increases and the manufacturing quota cannot be achieved is extracted. For the former problem, countermeasures should be considered within the manufacturing department, but in order to solve the latter problem, it is necessary to search for countermeasures that take into account the effects on both the manufacturing department and the production engineering department.

  In other words, when presenting a problem extraction result to a user, presenting not only the problem but also the scope of influence of the problem is support for the user in planning a countermeasure and selecting a problem.

  SUMMARY OF THE INVENTION An object of the present invention is to provide a technology that can present to a user the structure and influence range of a business problem.

  The problem structure extraction apparatus of the present invention that solves the above problems includes a model in which elements that affect a predetermined business and relationships between elements are described by a predetermined rule, and a relationship between elements and elements that are likely to cause problems in business. A storage device storing the problem structure model defined by the predetermined rule; and comparing the model with the problem structure model to extract a problem structure related to the predetermined business from the model; The process of identifying the affected range of the relevant problem structure based on the range information of the element included in the model data or specified by the user using the input device, and outputting the information of the problem structure and the affected range to the output device It is characterized by comprising an arithmetic unit that executes

  In addition, the problem structure extraction method of the present invention includes a model in which elements that affect a predetermined business and the relationship between the elements are described in a predetermined rule, and the relationship between elements that are likely to cause a problem in the business and the element. An information processing apparatus comprising a storage device storing the problem structure model defined in step 1, wherein the model and the problem structure model are collated to extract a problem structure related to the predetermined business from the model, and the extracted For the problem structure, the influence range of the corresponding problem structure is specified based on the range information of the elements included in the model data or specified by the user using the input device, and the information on the problem structure and its influence range is output to the output device. A process for outputting is executed.

  According to the present invention, it is possible to present to a user the structure and influence range of a business problem. In this case, the user can quickly plan measures for the corresponding problem and select a problem to be solved.

It is a figure which shows an example of the causal loop diagram in this embodiment. It is a figure which shows an example of the system prototype in this embodiment. It is a figure which shows the system prototype structure which the causal loop figure in this embodiment contains. It is a figure which shows the structural example of the problem structure extraction apparatus in this embodiment. It is a figure which shows an example of the model data file in this embodiment. It is a figure which shows an example of the problem structure data file in this embodiment. It is a flowchart which shows the procedure example 1 of the problem structure extraction method in this embodiment. It is a figure which shows an example of the model data in this embodiment. It is a figure which shows an example of the problem structure data in this embodiment. It is a figure which shows the example of a list of the problem structure extracted in this embodiment. It is a figure which shows an example of the influence range information of the problem structure calculated in this embodiment. It is a figure which shows the example of an output in this embodiment. It is a flowchart which shows the procedure example 2 of the problem structure extraction method in this embodiment. It is a flowchart which shows the procedure example 3 of the problem structure extraction method in this embodiment. It is a flowchart which shows the procedure example 4 of the problem structure extraction method in this embodiment. It is a figure which shows the structural example of the link condition satisfaction state stack of this embodiment.

--- CLD and system prototype ---

  Hereinafter, embodiments of the present invention will be described in detail. In the present embodiment, it is assumed that a system prototype is extracted as a problem structure from a model using a causal loop diagram (hereinafter referred to as CLD). Prior to the description of the problem structure extraction apparatus, a CLD that is a model used in the present embodiment and a system prototype that is regarded as a problem structure will be described. An example of a model target is a process of a product manufacturing operation at a certain manufacturer.

  First, the model CLD will be described. The CLD is a model that expresses the causal relationship between system components. W. It is used in the system simulation method and system dynamics proposed by Forester in Non-Patent Document 1. The causal relationship between elements is classified by two scales: “whether the increase / decrease direction of the values matches between the cause and the result” or “the presence or absence of a time gap in which the cause is reflected in the result”. Hereinafter, “direct” indicates that the direction of increase / decrease matches in the cause and result, “opposite” indicates that the increase / decrease direction does not match, “delays” indicates that there is a temporal gap, and “ It is called “no delay” and the four types of causal relationships are distinguished from “normal / delayed”, “reverse / delayed”, “normal / delayed”, and “reverse / delayed”.

  FIG. 1 shows an example of CLD notation used in this embodiment. The CLD shown here is expressed by a combination of rounded squares (hereinafter referred to as nodes) representing elements and arrows (hereinafter referred to as links) representing causal relationships. In addition, in order to represent the classification of the causal relationship, the positive causal is described with a solid line arrow, the opposite causal is described with a dotted line arrow, and the causal with delay is described with a double line on the arrow. For example, a solid arrow ML001 connected from the node MN001 with the quota unachieved rate to the node MN002 with the production time indicates a causal relationship that “the production time is increased when the quota unreached rate rises”.

  Next, a system prototype that is regarded as a problem structure will be described. The prototype of the system is Non-Patent Document 2 by Professor of Business Administration, Massachusetts Institute of Technology. M.M. A structure proposed by Senge and frequently found in system dynamics.

  FIG. 2 is a diagram showing “first-aid failure” which is one of the system prototypes. The failure of first aid consists of the three symptoms of problem symptom PN001, first aid PN002, and unintended result PN003. The symptoms of the problem were alleviated (PL002) "" Increased increase in first aid increased the number of unintended results (PL003) " It means a causal relationship of “amplified (PL004)”.

FIG. 3 is a diagram showing the structure of “first aid failure” included in the above-mentioned CLD (FIG. 1). The quota failure rate MN001 corresponds to the symptom PN001 of the problem, the manufacturing time MN002 corresponds to the first aid PN002, and the employee fatigue level MN006 corresponds to the unintended result PN003. Looking at the causal relationship of each node, the relationship of “trying to increase manufacturing time MN001 (ML001) when the norm achievement rate MN001 increases” corresponds to the relationship PL001 between the symptom PN001 in question and the first aid PN002, When the manufacturing time MN001 increases, the facility operation time MN003 increases (ML002), so the manufacturing amount MN004 also increases (ML004), and as a result, the quota failure rate MN001 decreases (ML006). Corresponding to the relationship PL002 of the symptom PN001, the relationship of “working time MN005 increases as the manufacturing time MN001 increases (ML003), and as a result, the employee fatigue level MN006 gradually increases (ML008)” is an emergency. Corresponds to the relationship PL003 between treatment PN002 and unexpected result PN003 ”If the employee fatigue level MN06 increases, the employee production efficiency PN007 decreases (ML009), and the decrease in production efficiency PN007 causes the production number PN004 to decrease (PL010), so the norm achievement rate MN001 increases. “(ML006)” corresponds to the relationship PL004 between the unexpected result PN003 and the problem symptom PN001.

As can be seen from the relationship between the employee fatigue level MN006 and the quota failure rate MN001, when an even number of reverse links are included between nodes, the causal relationship between the two is positive. In addition, as can be seen from the relationship between the manufacturing time MN002 and the employee fatigue level MN006, when there is even one delayed link between nodes, it is considered that there is a delay in the causal relationship between the two. .
--- Equipment configuration ---

  Next, a configuration example of the problem structure extraction apparatus in this embodiment will be described. FIG. 4 is a diagram illustrating a configuration example of the problem structure extraction apparatus 1000 according to the present embodiment. A problem structure extraction apparatus 1000 shown in FIG. 4 is a computer apparatus that can present to the user the structure and the influence range of a business problem.

  The problem structure extraction apparatus 1000 includes a storage device 1100, a CPU 1300 (Central Processing Unit), an input / output interface 1400, and a communication interface 1400. Among these, the storage device 1100 is typified by a main storage device including a RAM (Random Access Memory) and a ROM (Read Only Memory), an HDD (Hard Disk Drive), an SSD (Solid State Drive), and a flash memory. This corresponds to the auxiliary storage device. The storage device 1100 stores a model data file 1210 in which CLD information is described and a problem structure data file 1220 in which problem structure information is stored (details will be described later).

  The CPU 1300 is an electronic circuit that performs overall control of the problem structure extraction apparatus and has functions for performing numerical operations, data reading / writing, and device control. For example, the CPU 1300 implements a necessary function by executing an appropriate program held in the storage device 1100.

  The input / output interface 1400 indicates USB (Universal Serial Bus), PCI Express, or the like, and performs communication with data input / output devices such as a mouse, a keyboard, and a display.

In the present embodiment, it is assumed that the user directly accesses the problem structure extraction apparatus 1000 via the input / output interface 1400. However, the problem structure extraction apparatus 1000 has a BRI (Basic Rate Interface) port or a LAN (Local Area).
In the case of having a communication interface represented by a (Network) port or the like, access may be established with a user terminal through communication via a network.

  Next, functional units included in the problem structure extraction apparatus 1000 according to the present embodiment will be described. As described above, the functional units described below are implemented by the CPU 1300 executing a program included in the problem structure extraction apparatus 1000, for example.

Such a problem structure extraction apparatus 1000 includes a problem structure extraction unit 1110, an influence range calculation unit 1120, and a problem structure display unit 1130. Among them, the problem structure extraction unit 1110 extracts a problem structure described in a problem structure model 1221 (described later) of the problem structure data file 1220 from a model 1211 (described later) included in the model data file 1210 described above. The influence range calculation unit 1120 calculates the influence range of each problem structure extracted by the problem structure extraction unit 1110 described above. Also, the problem structure display unit 1130 outputs, via the input / output interface 1400 or the communication interface 1500, each information of the problem structure extracted by the problem structure extraction unit 1110 and the influence range calculated by the influence range calculation unit 1120. To do.
--- Data structure example ---

  Next, an example of the data structure used by the problem structure extraction apparatus 1000 of this embodiment will be described. FIG. 5 is a diagram showing an example of the model data file 1210 held by the problem structure extraction apparatus 1000 according to this embodiment. The model data file 1210 stores, for example, a model 1211 corresponding to each business process, and one of them is illustrated in FIG. In addition to the description of the CLD shown in FIG. 1, the model 1211 is represented by range information MA001 described in parentheses around the node name and a predetermined icon (eg, star mark) at a predetermined position of the node. Node information MI001 and control enable / disable information MC001 expressed by highlighting a predetermined part of the node (eg, shadow) are included. As described above, it is assumed that the range information MA001, the important node information MI001, and the control permission / inhibition information MC001 are included in the model 1211 in advance, but these information are transmitted via a predetermined screen on the input / output interface 1400. It may be obtained by inputting by a user.

  FIG. 6 is a diagram showing an example of the problem structure data file 1220 held by the problem structure extraction apparatus 1000 according to this embodiment. This problem structure data file 1220 stores one or more problem structure models 1221 in which the elements that are likely to cause problems in business and the relationships between the elements are defined by the predetermined rule, and two of them are illustrated in FIG. doing.

  This problem structure model 1221 has the same structure as the system prototype shown in FIG. 2, and is assigned the name PT001 of the corresponding problem. The problem structure model 1221 also holds information as a condition structure extraction condition. In the present embodiment, the single line PD001 given on the arrow indicates whether or not there is any delay at the time of searching.

In this embodiment, it is assumed that the above-described problem data file 1220 (including the problem structure model 1221) is prepared in advance, and the problem structure is extracted based on all the problem structure models 1221 in the problem data file 1220. However, each of the problem structure models 1221 may be acquired by causing the user to input via a predetermined screen on the input / output interface 1400. In addition, the problem structure model 1221 included in the problem structure data file 1220 may be acquired by causing the user to select a problem structure extraction target via a predetermined screen on the input / output interface 1400.
--- Example of processing procedure 1 ---

  Hereinafter, the actual procedure of the problem structure extraction method in the present embodiment will be described with reference to the drawings. Various operations corresponding to the problem structure extraction method described below are realized by a program executed by the problem structure extraction apparatus 1000. And this program is comprised from the code | cord | chord for performing the various operation | movement demonstrated below.

FIG. 7 is a flowchart showing a processing procedure example 1 of the problem structure extraction method in the present embodiment. Here, first, the problem structure extraction unit 1110 of the problem structure extraction apparatus 1000 uses a predetermined model 1211 included in the model data file 1210 (if the model data file 1210 stores a plurality of models 1211, the user uses an input device). By extracting information on each node and each link constituting the model 1211 from what has been designated), the information is converted into a data format that is easy to extract the problem structure (S1100). Hereinafter, the converted data is referred to as model data 1215. In order to obtain such model data 1215, the problem structure extraction unit 1110 in step S1100 performs a depth-first search on the model 1211, for example, starting from a predetermined node, and finds all the nodes and links included in the corresponding model 1211. A process of assigning a model node ID that uniquely identifies the corresponding node to the searched node, a process of assigning a model link ID that uniquely identifies the corresponding link to the searched link, An acquisition process of information (eg, node name, node characteristic, link characteristic) held by each link is executed, and the model data 1215 is generated by tabulating the information obtained in each process.

  FIG. 8 is a diagram illustrating a format example of the model data 1215 created by the question structure extraction unit 1110 in step S1100 described above. The model data 1215 exemplified here has a model node list 1216 that holds information of each node included in the model 1211 that is a directed graph, and a model link list 1217 that holds information of each link connecting the nodes.

  Among these, the model node list 1216 is a collection of records in which model node IDs, node names, and node characteristics (range information, importance (KPI), controllability information) are associated with each other. The model node ID stores a node included in the above-described model 1211, that is, an ID that uniquely identifies the model node, and the node name stores the name of the element represented by the corresponding model node. Further, the contents shown as range information MA001, important node information MI001, and control enable / disable information MC001 in FIG. 5 are read in the range information, importance, and control enable / disable as node characteristics, respectively.

  On the other hand, the model link list 1217 is a collection of records in which model link ID, start point model node ID, end point model node ID, and link characteristics (forward / reverse, delay) are associated with each other. Among these, the model link ID stores an ID for uniquely identifying a link between model nodes indicated by the above-described model node list 1216, that is, a model link, and the model node ID that is the start point of the model link is stored in the start model node ID. The end model node ID stores the model node ID that is the end point of the model link. Further, the link characteristics (forward / reverse, delay) store forward / reverse information of the model link and information on whether or not the model link is delayed.

  Next, the problem structure extraction unit 1110 extracts information on each node and each link constituting the problem structure model 1221 from each problem structure model 1221 included in the problem structure data file 1220, thereby The data format is converted into an easy-to-contrast data format (S1200). Hereinafter, the converted data is referred to as problem structure data 1225. For the problem structure extraction unit 1110 in step S1200 to obtain the problem structure data 1225, a method similar to the process in which the model data 1215 is obtained in step S1100 described above may be employed.

  FIG. 9 is a diagram showing a format of the problem structure data 1225 created by the problem structure extraction unit 1110 in step S1200 described above. The problem structure data 1225 exemplified here includes a problem structure list 1226 that is a list of each problem structure model 1221 included in the problem structure data file 1220, a problem structure node list 1227 that is a list of nodes included in each problem structure model 1221, and The problem structure link list 1228, which is a list of links included in each problem structure model 1221, is provided.

  Among these, the problem structure list 1226 is a name list corresponding to each problem structure model 1221 and includes a problem structure ID for uniquely identifying the problem structure and a problem structure name for storing the name of the problem structure.

  The question structure node list 1227 is a list of nodes included in each question structure model 1221. The question structure node ID for storing an ID for uniquely identifying the question structure node and the question structure node are included. It consists of a problem structure ID indicating the model 1221 and a problem structure node name for recording the name of the problem structure node. This means that problem structure nodes having the same problem structure ID are included in the same problem structure model 1221. Therefore, in the example of FIG. 9, it can be read that the problem symptom PN001, the first aid PN002, and the unexpected result PN003 are nodes belonging to the problem structure PT001.

  The question structure link list 1228 is a list of links included in each question structure model 1221, that is, a question structure link, and includes a question structure link ID and a question structure link for storing an ID for uniquely identifying each question structure link. The problem structure ID indicating the problem structure model 1221 that is stored, the problem structure node ID that indicates the problem structure node ID that is the starting point of the problem structure link, and the problem structure node ID that indicates the problem structure node ID that is the end point of the problem structure link It holds ID and link characteristics (forward / reverse, delay) that mean forward / reverse / delay information to be satisfied by the problem structure link. This means that problem structure links having the same problem structure ID are included in the same problem structure model 1221. Therefore, in the example of FIG. 9, it means that PL001, PL002, PL003, and PL004 are links included in the problem structure PT001. The link characteristic is read from the description of the problem structure data file 1220. For example, in the problem structure model 1221 corresponding to “failure of first aid” shown in FIG. From the condition description “does not matter at the time of search”, “△” is acquired and set in the “delay” column in the link characteristics of the problem structure link list 1228 described above.

  Now, the description returns to the flow of FIG. Subsequently, the problem structure extraction unit 1110 calls one ID of the problem structure model 1221 that has not yet been collated with the model data 1215 (hereinafter referred to as an unverified problem structure ID) from the problem structure list 1226 of the problem structure data 1225 (S1300). ). The question structure extraction unit 1110 in this step S1300, for example, for a question structure model 1221 that has been collated with the model data 1215, a predetermined information that indicates that the collation has been completed (hereinafter, question structure collation information) has been secured in the storage device 1100. It shall be saved in the temporary storage area. In this case, the problem structure extraction unit 1110, for each problem structure ID included in the problem structure list 1226, the problem structure ID of the problem structure model 1221 to which the above-described problem structure matching information is not given, that is, unmatched, for example, This step is realized by sequentially acquiring from the top of the list.

  Next, when the unexamined problem structure ID is called from the problem structure list 1226 in step S1300 described above (S1400: Yes), the problem structure extraction unit 1110 stores the unmatched problem structure model 1221 from the model data 1215. The process proceeds to extraction processing (S1500). On the other hand, if the unmatched question structure ID cannot be called in step S1300 described above (S1400: No), the question structure extraction unit 1110 requests the question structure display unit 1130 to display the extraction result ( S1410).

On the other hand, in step S1500, the problem structure extraction unit 1110 collates the problem structure model 1221 corresponding to the unmatched problem structure ID called in step S1300 described above with the model data 1215, and is included in the model data 1215. Data extraction of the unmatched problem structure model 1221 is performed, and the extracted result is stored in the storage device 1100 as an extracted structure list 1260 (S1500). Details of this processing will be described later.

  FIG. 10 shows an example of an extracted structure list 1260 obtained in step S1500 described above. The extracted structure list 1260 exemplified here is a set of records having columns of an extracted structure ID, a problem structure ID, a problem structure link ID, a link assignment index, and a model link ID. Among these, the extraction structure ID stores an ID for uniquely specifying the extraction structure obtained in step S1500. A group of objects having the same extraction structure ID represents one extraction structure. For example, data of extraction structure ID = E001 represents the problem structure illustrated in FIG. The problem structure ID stores a problem structure ID corresponding to the extracted structure.

  Each column of the extracted structure list 1260 represents a model link belonging to the extracted structure, a question structure link ID column corresponding to the model link corresponding to the model link, and a link indicating the numbered link. Stored in the assigned index. For example, the content of the record “R003” is that the model link “ML004” has the problem structure ID “PT001” (first aid failure) and the second problem structure link ID “PL002” (first aid to problem link). (Link allocation index is “2”).

  Subsequently, the problem structure extraction unit 1110 creates the extracted structure list 1260 described above, and then acquires one extracted structure that is included in the extracted structure list 1260 and whose influence range has not been calculated (S1600). The question structure extraction unit 1110 in step S1600 stores, for example, predetermined information indicating that the influence range has been calculated for the extracted structures that have been subjected to the influence range calculation among the extraction structures described in the extraction structure list 1260 in the storage device 1100. It is assumed that the data is stored in a reserved predetermined temporary storage area. In this case, the problem structure extraction unit 1110 extracts, for each extraction structure ID included in the extraction structure list 1260, the ID of the extraction structure to which the above-described predetermined information is not given, that is, the influence range calculation is not calculated, that is, the influence range is not calculated For example, the structure ID is sequentially identified from the top of the extracted structure list 1260, and the data of the extracted structure of the corresponding ID is acquired to realize the step.

  If the extracted structure whose influence range has not been calculated can be acquired in step S1600 described above (S1700: Yes), the problem structure extraction unit 1110 delivers the extraction structure whose influence range has not been calculated to the influence range calculation unit 1120, and extracts the extracted structure. A process of calculating the influence range of the structure (S1900) is requested (S1710). On the other hand, if the extracted structure whose influence range has not been calculated cannot be acquired in step S1600 described above (S1700: No), the problem structure extraction unit 1110 proceeds to the problem structure matching information update process (S1800). In this case, as soon as there is no extracted structure whose influence range has not been calculated, the problem structure extraction unit 1110 updates the problem structure matching information so that the unmatched question structure extracted in step S1300 described above is matched (S1800). .

  On the other hand, the influence range calculation unit 1120 in step S1900 receives an extraction structure whose influence range has not been calculated from the above-described problem structure extraction apparatus 1110, and calculates the influence range of the extraction structure. Details of this processing will be described later.

  Subsequently, the influence range calculation unit 1120 stores the influence range information calculated in step S1900 described above in the storage device 1100 together with the extraction structure (S2000). FIG. 11 shows an example of the influence range information 1270 obtained by step S2000. The influence range information 1270 illustrated in FIG. 11 is represented as a list of pairs of extraction structure IDs and influence ranges, and each row stores one range in which the extraction structure ID and the corresponding extraction structure affect.

On the other hand, as a result of step S1400 described above, the problem structure display unit 1130 that has received a request from the problem structure extraction unit 1110 receives the extracted structure list 1260 calculated by the problem structure extraction unit 1110.
The influence range information 1270 calculated by the influence range calculation unit 1120 is called (S2100).

  Next, the problem structure display unit 1130 creates a result screen in consideration of the influence range indicated by the influence range information 1270 for each extraction structure included in the extraction structure list 1260 called in step S2100 described above, via the input / output interface 1400. The data is output to a predetermined output device (S2200). Details of this processing will be described later.

  Finally, the problem structure display unit 1130 outputs the extracted structure information extracted by the problem structure extraction unit 1110 to the output device together with, for example, the result screen (output in S2200) (S2300). At this time, it is preferable to sort the information display order of the extracted structure in the result screen based on the influence range created in step S2000 (for example, the higher the influence range, the higher).

  FIG. 12 shows an example of result screens 1280 and 1290 output by the problem structure display unit 1130. In the example of the result screen 1280 in FIG. 12, the extracted structure list 1260 created by the problem structure extraction unit 1110 and the summary 1281 of the influence range information 1270 calculated by the influence range calculation unit 1120 are sorted in descending order of influence range (included in the influence range). The list 1282 is displayed in descending order of the number of departments to be displayed. Further, the question structure display unit 1130, for example, based on the summary 1281 specified by the user via the input device in the summary 1281 in the list 1282 (highlighted according to the designation reception), the corresponding extraction structure. The influence range (for example, manufacturing department) of 1284 is highlighted on the CLD on the result screen 1280 by being surrounded by the closed region 1283.

  For example, when the user has selected another summary 1291 in the list 1282 described above, the problem structure display unit 1130 highlights the corresponding portion in the list 1282 and, based on the corresponding summary 1291, the corresponding extraction structure 1292. The influence range (for example, manufacturing department, production engineering department) is extended to the closed area 1293 corresponding to the influence area extending to “manufacturing department” and “production engineering department” on the CLD in the new result screen 1290. Each area is highlighted with a closed area 1294 corresponding to the affected area.

  The problem structure display unit 1130 generates a result screen each time the user changes the summary of the display target, that is, the designation of the extraction structure from the list 1282, and as illustrated in FIG. 12, the result screen 1280 changes to the result screen 1290. And so on.

The above is the outline of the processing flow in the present embodiment. Hereinafter, the contents of the processing whose details will be described later in the flow outline will be described.
--- Processing procedure example 2 ---

  Here, the details of step S1500 described above, in which the problem structure extraction unit 1110 extracts a problem structure from the model data 1215 and stores the extracted result as an extraction structure list 1260, will be described with reference to FIG. In this example, the unmatched problem structure ID corresponding to the problem structure extracted from the model data 1215 is described as being a first aid failure “PT001”.

In this flow, the problem structure extraction unit 1110 first lists all the unmatched problem structure links, and creates a problem structure link index representing the order of matching with the model data 1215 (S1501). This index is obtained by, for example, obtaining a node list and a link list corresponding to the question structure ID of the unmatched question structure from the question structure link list 1228 of the question structure data 1225, and then performing a depth-first search in order from the vertex having the smallest input order. It is possible to obtain the information by performing numbering in order from the searched links not indexed. In this example, it is assumed that index 1 is assigned to the problem structure link “PL001”, index 2 is assigned to “PL002”, index 3 is assigned to “PL003”, and index 4 is assigned to “PL004”.

  Next, the problem structure extraction unit 1110 pushes the initial state to the link condition satisfaction state stack (S1502). The link condition satisfaction state stack stores a state in which assignment of the problem structure link (problem structure data 1225) and model link (model data 1215) satisfies the forward / reverse / delay conditions (link characteristics) that the problem structure link should satisfy. Stack structure. The state referred to here is, for example, a collation link Index indicating an index of a problem structure link to be collated with the model data 1215 next, and vertex assignment indicating which model node is assigned to the problem structure node Information and link assignment information indicating which model link is assigned to the problem structure link. In this case, the initial state indicates that the next allocation index is “1” indicating the first problem structure link, and the vertex allocation information and the link allocation information are in a state where an empty list is set.

  FIG. 16 shows one implementation example of the link condition satisfaction state stack 1600 after pushing the above-described initial state. In the example shown in FIG. 16, the link condition satisfaction state stack 1600 is realized by the collation link index stack 1610, the link assignment stack 1620, and the vertex assignment stack 1630, and the stack ID that uniquely specifies the data unit stored in each stack. Each stack holds.

  Next, the problem structure extraction unit 1110 checks whether or not the link condition satisfaction state stack 1600 is empty, and if it is empty (S1503: Yes), ends the problem structure extraction process. On the other hand, if it is not empty (S1503: No), the problem structure extraction unit 1110 proceeds to a process S1504 for advancing the matching process for the extracted state remaining in the link condition satisfaction state stack 1600.

  In step S1504 described above, the problem structure extraction unit 1110 pops the top of the link condition satisfaction state stack 1600 to obtain collation link index / vertex assignment information and link assignment information.

  Subsequently, the problem structure extraction unit 1110 refers to the index information created in the above-described step S1501 using the matching link Index, and the problem structure link ID to be matched with the model data 1215 (hereinafter referred to as the matching link ID). Try to get. If this link does not exist (S1505: No), the problem structure extraction unit 1110 proceeds to extracted data storage processing S1514. Otherwise (S1505: Yes), the problem structure extraction unit 1110 proceeds to the collation process between the collation link and the model (S1506 and subsequent steps).

  In step S1506 described above, the problem structure extraction unit 1110 uses the matching link ID and the unmatched question structure ID to refer to the problem structure link list 1228 to obtain the question structure node ID (this is PNi) that becomes the starting point of the matching link. And search for whether there is a model node MNi corresponding to PNi from the vertex assignment information acquired in step S1504 described above.

  If there is a model node MNi corresponding to the above-described PNi as a result of this search (S1506: Yes), the problem structure extraction unit 1110 shifts the processing to the model link assignment processing (S1508 and later) starting from MNi, If it does not exist (S1506: No), the process proceeds to a process of assigning a model node to PNi (S1507).

  In step S1507 described above, the problem structure extraction unit 1110 acquires all the model nodes that can be assigned using the vertex assignment information, the link assignment information, and the model node list 1216 of the model data 1215. Further, the problem structure extraction unit 1110 adds, to the link condition satisfaction state stack 1600, a state in which the allocation information of PNi and MNi is added to the vertex allocation information for all the model nodes MNi obtained here.

  On the other hand, in step S1508 described above, the problem structure extraction unit 1110 obtains a model link having MNi as the starting point by extracting data whose starting point model node ID is MNi from the model link list 1217 of the model data 1215. In addition to the current state, the problem structure extraction unit 1110 adds link assignment information (problem structure link ID = collation link ID, link assignment index = 1, MLi) to all model links MLi obtained here. Add the given state to the link condition unsatisfied stack. The link condition unsatisfied state stack is a stack structure that saves the state, not only when the assignment of the problem structure link and the model link satisfies the forward / reverse / delay conditions that the problem structure link should satisfy. Since the possessed information is the same as that of the link condition satisfaction state stack 1600, details are omitted.

  If the link condition unsatisfied stack is empty (S1509: Yes), the problem structure extraction unit 1110 recognizes that all of the collation link allocation processes starting from MNi have been completed, and the next link collation process S1503. Return to. If not (S1509: No), the process proceeds to the collation link assignment process (after S1510) starting from MNi.

  In step S1510 described above, the problem structure extraction unit 1110 pops the top data of the link condition unsatisfied state stack to obtain collation link index / vertex assignment information and link assignment state.

  The problem structure extraction unit 1110 interprets the information of the model link currently assigned to the collation link based on the link assignment information obtained in step S1510 described above, thereby determining the link assignment to the collation link. Whether or not the above condition is satisfied is inspected (S1511). This condition is a forward / reverse / delay condition described in the link characteristic column of the line extracted from the problem structure link list 1228 of the problem structure data 1225 using the problem structure ID and the problem structure link ID as a key. is there.

  If the current link assignment satisfies the verification link condition (S1511: Yes), the problem structure extraction unit 1110 must proceed to the process of storing the information in the link condition satisfaction state stack 1600 (S1512). (S1511: No), the process proceeds to the subsequent process (S1513).

  In step S1512 described above, the problem structure extraction unit 1110 adds the end point of the link assignment information and the end point of the collation link as new vertex assignments, and adds the collation link index to the link condition satisfaction state stack 1600. To push. If the model link can be further assigned to the verification link in addition to the current link assignment state (S1513: Yes), the problem structure extraction unit 1110 proceeds to the process of adding the link condition unsatisfied state (S1514). If not (S1513: No), the process returns to the process for evaluating the next link condition unsatisfied state (S1509). This condition determination is made based on a condition such as “the current link assignment end point is not a vertex already assigned to a vertex and the current link assignment end point does not exist twice in the link assignment route with the collation link”. It is possible.

In step S1514 described above, the problem structure extraction unit 1110 adds, to all link MLj that can be added, a state in which MLj is further added to the link allocation information in the current state to the link condition unsatisfied state stack.

The above is the details of the process (S1500) in which the problem structure extraction unit 1110 extracts the problem structure from the model data 1215. In the present embodiment, it is assumed that the problem structure is extracted from the entire model data 1215. However, the user gives range information to the problem structure extraction apparatus 1000 in advance, and the above-described steps S1511, S1506, The problem structure to be extracted may be limited by changing the condition of S1513 according to the range information given in advance by the user.
--- Processing procedure example 3 ---

  Next, a process (S1900) in which the influence range calculation unit 1120 receives an extraction structure whose influence range has not been calculated from the problem structure extraction unit 1110 and calculates the influence range of the extraction structure will be described with reference to FIG.

  In this case, the influence range calculation unit 1120 first receives the extraction structure from the problem structure extraction unit 1110, and then initializes the range information reflection history (S1901). This range information reflection history is information indicating whether the range information of each model node has been reflected in the calculation of the influence range of the current extraction structure, and is realized as a vector having the same size as the number of model nodes, for example. . Information indicating that the range information of each model node is not reflected is stored in the range information reflection history in the initial state.

  Next, the influence range calculation unit 1120 refers to the information of the problem structure ID in the extracted structure list 1260 and extracts one piece of link information corresponding to the current extracted structure as a processing target (S1902). After all such link information in the extracted structure list 1260 is extracted as a processing target, the influence range calculation unit 1120 determines that there is no unspecified link information as a processing target (S1903: No), and influence range calculation processing Exit. On the other hand, if one piece of link information has been extracted (S1903: Yes), the influence range calculation unit 1120 moves the process to step S1904.

  In step S1904, the influence range calculation unit 1120 acquires the node characteristics of the start point model node and the end point model node for the link information acquired in step S1902 described above (S1904). This node characteristic is obtained by referring to the model link list 1217 of the model data 1215 based on the model link ID to determine the start model node ID and the end model node ID, and collating these information with the model node list 1216 of the model data 1215. Can be obtained.

  Subsequently, the influence range calculation unit 1120 updates the range information of the extraction structure using the node characteristics of the start model node and the node characteristics of the end model node acquired in step S1904 (S1905). In the example of this embodiment, the union of range information included in the node characteristics is calculated as range information. However, in updating the range information, importance other than the range information and controllability information are used. Also good. For example, the range information may be updated only when the node characteristics of the start point model node or the end point model node have a certain degree of importance or more. Alternatively, when the start point model node or the end point model node is a controllability node, a range in which each controllability node affects may be stored by performing a depth-first search starting from the controllability node. Further, for example, the above-mentioned depth-first search using the start point model node or the end point model node having an importance level equal to or higher than a predetermined level as an object of consideration of the influence range, and further starting from the above controllable node is performed. It is also possible to store the range affected by the control availability node.

Next, the influence range calculation unit 1120 updates the influence range reflection history (S1906). This process is realized, for example, by re-recording that the influence range has been reflected with respect to the start point model node and the end point model node.
--- Processing procedure example 4 ---

  Finally, the details of the drawing structure creation process (S2200) using the extracted structure and the influence range of the extracted structure by the problem structure display unit 1130 will be described. FIG. 15 shows a detailed flow of the drawing screen creation process S2200 using the extracted structure and the influence range of the extracted structure by the problem structure display unit 1130.

  In this case, the problem structure display unit 1130 acquires one piece of influence range information for the extracted structure obtained in step S2100 described above (S2201). This processing can be realized by referring to the influence range information in the influence range information 1270 using the extraction structure ID of the corresponding extraction structure as a key.

  If the processing has been completed for all the extracted structure ranges (S2202: No), the problem structure display unit 1130 proceeds to display information storage processing (S2204), and otherwise (S2202: Yes), the process proceeds to the process (S2203) for the information on the influence range obtained in step S2201 described above.

  The problem structure display unit 1130, based on the information on the influence range obtained in step S2201 (eg, “manufacturing department”, “production engineering department”), information on the extraction structure that is the problem structure for this influence range ( The drawing area of the result screens 1280 and 1290 already described with reference to FIG. 12 is configured (S2203). In this drawing area configuration process, the model node ID (model data 1215) corresponding to the model link ID (extraction structure list 1260) of the corresponding extraction structure is specified using the extraction structure ID of the influence range information 1270 as a key. The icon of each corresponding node indicated by the drawing data of the node corresponding to the node ID (for example, icon data held in advance by the model 1211 and may be stored in the model node list 1216 of the model data 1215). Based on the maximum and minimum X coordinate values and the maximum and minimum Y coordinate values among the display coordinate values, the vertices of the rectangular closed region 1283 for displaying information on a certain influence range (for example, manufacturing department) are displayed. It can be executed by a method of specifying and making this a drawing area. In addition, a drawing area may be created by creating a Voronoi diagram.

  The problem structure display unit 1130 saves the information on the drawing area thus obtained in the temporary storage area (S2204). Based on the information on the drawing area, the information related to the extraction structure is surrounded by the closed area 1283 and highlighted. The displayed result screen is created and output to a predetermined output device via the input / output interface 1400, and the process ends.

  Although the best mode for carrying out the present invention has been specifically described above, the present invention is not limited to this, and various modifications can be made without departing from the scope of the invention.

  According to this embodiment, it is possible to present to the user the structure and influence range of the business problem.

At least the following will be clarified by the description of the present specification. That is, in the problem structure extraction device of the present embodiment, the storage device stores a directed graph indicating a causal relationship according to the relevance between the elements as the model and the problem structure model, and each element is Range information that defines the range of influence is further stored, and the arithmetic unit, when specifying the range of influence of the problem structure, collates the model that is a directed graph with the problem structure model, A problem structure related to the predetermined business may be extracted, range information defined for elements included in the extracted problem structure may be read from a storage device, and the influence range may be specified based on the range information.

  According to this, the problem structure extraction process can be made efficient by using a model that accurately and concisely describes a business-affecting element and its relation by a directed graph.

  Further, in the problem structure extraction device of the present embodiment, the storage device further stores importance information of the element in the model, and the arithmetic device specifies the influence range of the problem structure, Extracting the importance level information of the elements included in the extracted problem structure and the range information defined for the corresponding elements from the storage device, and specifying the affected range based on the extracted importance level information and range information There may be.

  According to this, for example, it is possible to perform processing such as considering an element having an importance level of a predetermined level or higher among the elements to be considered in the influence range, and it is possible to omit wasteful processing and improve the overall processing efficiency. .

  Further, in the problem structure extraction device of the present embodiment, the storage device further stores controllability information of the element in the model, and the arithmetic device specifies the influence range of the problem structure, Extracting controllability information of elements included in the extracted problem structure and range information defined for the corresponding elements from the storage device, and specifying the influence range based on the extracted controllability information and range information There may be.

  According to this, for example, by performing a depth-first search in the model starting from an element (node) for which controllability information is set, the corresponding element (controllability information is set) It is possible to perform processing such as considering the range in which the controllable content of the object is affected.

  Further, in the problem structure extraction device of the present embodiment, the storage device further stores importance information of the element in the model, and the arithmetic device specifies the influence range of the problem structure, The importance level information of the elements included in the extracted problem structure, the controllability information, and the range information defined for the corresponding element are extracted from the storage device, and based on the extracted importance level information, controllability information, and range information The influence range may be specified.

  According to this, for example, an element having an importance level equal to or higher than a predetermined level is considered in the influence range, and further, for example, starting from an element (node) for which controllability information is set, By performing a depth-first search in the model, it is possible to perform processing such as considering the range in which the controllability content of the corresponding element (the one for which controllability information is set) is affected, thereby eliminating unnecessary processing. Thus, the overall processing efficiency can be further improved.

  Further, in the problem structure extraction apparatus of the present embodiment, when specifying the influence range of the problem structure, the arithmetic unit calculates a set of range information and the number of elements for each element included in the extracted problem structure, The influence range may be specified according to the set of calculated range information and the number thereof.

  According to this, it is possible to efficiently identify the range affected by the problem structure by taking the union of the range information of each element (eg, identification information of the affected department etc.). Further, the greater the number (range information included in the union = identification information such as a department), the wider the range of influence, and it can be easily identified that it is important as a target for taking measures against the problem.

  Further, in the problem structure extraction apparatus according to the present embodiment, the arithmetic unit, in the process of outputting the information of the problem structure and its influence range to the output device, based on the range information of the elements included in the extracted problem structure, Screen data that surrounds each element with a predetermined line segment for each corresponding range may be output.

  According to this, the problem structure and its influence range can be presented to the user in a form that can be easily visually recognized.

  Further, in the problem structure extraction apparatus according to the present embodiment, the arithmetic unit, in the process of outputting the information of the problem structure and its influence range to the output device, based on the range information of the elements included in the extracted problem structure, The information display positions may be rearranged and output among the extracted problem structures.

  According to this, for example, display information (for example, a directed graph, a name group of elements constituting the problem structure, an affected department, etc.) indicating the problem structure and its affected range is displayed on the output screen as the affected range becomes wider (for example, : The larger the number of affected departments), the higher the screen can be displayed, and the user viewing the screen can more easily visually recognize the problem structure and its affected range.

  Further, in the problem structure extraction method of the present embodiment, the information processing apparatus stores a directed graph indicating a causal relationship according to the relevance between the elements as the model and the problem structure model in the storage device. Further, range information defining the range affected by each element is further stored, and when the affected range of the problem structure is specified, the model that is a directed graph is collated with the problem structure model, and the predetermined model is obtained from the model. A problem structure related to business may be extracted, range information defined regarding elements included in the extracted problem structure may be read from the storage device, and the influence range may be specified based on the range information.

  Further, in the problem structure extraction method of the present embodiment, the information processing apparatus further stores the importance level information of the element in the model in the storage device, and specifies the influence range of the problem structure. The importance level information of the elements included in the problem structure and the range information defined for the corresponding elements may be extracted from the storage device, and the influence range may be specified based on the extracted importance level information and range information.

  Further, in the problem structure extraction method of the present embodiment, the information processing apparatus further stores controllability information of the element in the model in the storage device, and specifies the influence range of the problem structure when the extraction is performed. The controllability information on the elements included in the problem structure and the range information defined for the corresponding element may be extracted from the storage device, and the influence range may be specified based on the extracted controllability information and range information.

  Further, in the problem structure extraction method of the present embodiment, the information processing apparatus further stores the importance level information of the element in the model in the storage device, and specifies the influence range of the problem structure. The importance level information of the elements included in the problem structure, the controllability information, and the range information defined for the corresponding element are extracted from the storage device, and the above-described importance level information, the controllability information, and the range information are extracted from the storage device. The influence range may be specified.

  Further, in the problem structure extraction method of the present embodiment, when the information processing apparatus specifies the influence range of the problem structure, it calculates a set of range information and the number thereof for each element included in the extracted problem structure, The influence range may be specified according to the set of the calculated range information and the number thereof.

  Further, in the problem structure extraction method of the present embodiment, when the information processing apparatus outputs the problem structure and its influence range information to an output device, based on the range information of the elements included in the extracted problem structure. The screen data that encloses each element with a predetermined line segment for each corresponding range may be output.

  Further, in the problem structure extraction method of the present embodiment, when the information processing apparatus outputs the problem structure and its influence range information to an output device, based on the range information of the elements included in the extracted problem structure. The information display positions may be rearranged and output between the extracted problem structures.

1000 problem structure extraction apparatus 1100 storage apparatus 1110 problem structure extraction section 1120 influence range calculation section 1130 problem structure display section 1210 model data file 1211 model 1215 model data 1216 model node list 1217 model link list 1220 problem structure data file 1221 problem structure model 1225 Problem structure data 1226 Problem structure list 1227 Problem structure node list 1228 Problem structure link list 1260 Extracted structure list 1270 Influence range information 1280, 1290 Result screen 1300 CPU (computing device)
1400 I / O interface 1500 Communication interface 1600 Link condition satisfaction state stack 1610 Collation link index stack 1620 Link allocation stack 1630 Vertex allocation stack

Claims (16)

Stores a model that describes the elements that affect a given business and the relationship between the elements in a given rule, and a problem structure model that defines the elements that are likely to cause problems in the business and the relationships between the elements in the given rule. Storage device
The model and the problem structure model are collated, the problem structure related to the predetermined business is extracted from the model, and the extracted problem structure is included in the model data or the element specified by the user using the input device An arithmetic unit that executes a process of identifying an influence range of the corresponding problem structure based on the range information, and outputting information on the problem structure and the influence range to an output device;
A problem structure extraction apparatus comprising: The storage device
As the model and the problem structure model, storing a directed graph indicating a causal relationship according to the relevance between each of the elements, and further storing range information defining a range in which each element affects,
The arithmetic unit is:
When the influence range of the problem structure is specified, the model that is a directed graph and the problem structure model are collated, the problem structure related to the predetermined business is extracted from the model, and the elements included in the extracted problem structure are specified. Range information is read from the storage device, and the influence range is specified based on the range information.
The problem structure extraction apparatus according to claim 1, wherein: The storage device
Further storing importance information of the element in the model;
The arithmetic unit is:
When specifying the influence range of the problem structure, the importance information of the elements included in the extracted problem structure and the range information defined for the corresponding elements are extracted from the storage device, and the extracted importance information and range information are extracted. The influence range is specified based on
The problem structure extraction apparatus according to claim 2, wherein The storage device
Further storing controllability information of the element in the model;
The arithmetic unit is:
When specifying the influence range of the problem structure, the controllability information of the elements included in the extracted problem structure and the range information defined for the corresponding element are extracted from the storage device, and the controllability information and range information thus extracted are extracted. The influence range is specified based on
The problem structure extraction apparatus according to claim 2, wherein The storage device
Further storing importance information of the element in the model;
The arithmetic unit is:
When specifying the influence range of the problem structure, the importance information of the elements included in the extracted problem structure, the controllability information, and the range information defined for the corresponding elements are extracted from the storage device, and the extracted importance The influence range is specified based on degree information, controllability information and range information.
The problem structure extraction apparatus according to claim 4, wherein: The arithmetic unit is:
When specifying the influence range of the problem structure, a set of range information and the number thereof are calculated for each element included in the extracted problem structure, and the influence range is specified according to the set and the number of the calculated range information To do,
The problem structure extraction apparatus according to claim 1, wherein: The arithmetic unit is:
In the process of outputting the information of the problem structure and its influence range to the output device, screen data that surrounds each element with a predetermined line segment for each corresponding range is output based on the range information of the element included in the extracted problem structure. Is,
The problem structure extraction apparatus according to claim 1, wherein: The arithmetic unit is:
In the process of outputting the information of the problem structure and its influence range to the output device, the information display positions are rearranged and output based on the range information of the elements included in the extracted problem structure. Is,
The problem structure extraction apparatus according to claim 1, wherein: Stores a model that describes the elements that affect a given business and the relationship between the elements in a given rule, and a problem structure model that defines the elements that are likely to cause problems in the business and the relationships between the elements in the given rule. An information processing apparatus including the storage device
The model and the problem structure model are collated, the problem structure related to the predetermined business is extracted from the model, and the extracted problem structure is included in the model data or the element specified by the user using the input device Identifying the affected range of the relevant problem structure based on the range information, and outputting the problem structure and its affected range information to an output device;
The problem structure extraction method characterized by this. The information processing apparatus is
In the storage device, as the model and the problem structure model, a directed graph indicating a causal relationship according to the relevance between each of the elements is stored, and range information defining a range in which each element affects is further stored And
When the influence range of the problem structure is specified, the model that is a directed graph and the problem structure model are collated, the problem structure related to the predetermined business is extracted from the model, and the elements included in the extracted problem structure are specified. Range information is read from the storage device, and the influence range is specified based on the range information.
The method for extracting a problem structure according to claim 9. The information processing apparatus is
In the storage device, further stores importance information of the element in the model,
When specifying the influence range of the problem structure, the importance information of the elements included in the extracted problem structure and the range information defined for the corresponding elements are extracted from the storage device, and the extracted importance information and range information are extracted. Identifying the affected area based on
The problem structure extraction method according to claim 10. The information processing apparatus is
In the storage device, further storing control availability information of the element in the model,
When specifying the influence range of the problem structure, the controllability information of the elements included in the extracted problem structure and the range information defined for the corresponding element are extracted from the storage device, and the controllability information and range information thus extracted are extracted. Identifying the affected area based on
The problem structure extraction method according to claim 10. The information processing apparatus is
In the storage device, further stores importance information of the element in the model,
When specifying the influence range of the problem structure, the importance information of the elements included in the extracted problem structure, the controllability information, and the range information defined for the corresponding elements are extracted from the storage device, and the extracted importance Identifying the affected range based on degree information, controllability information and range information;
The problem structure extraction method according to claim 12, wherein: The information processing apparatus is
When specifying the influence range of the problem structure, a set of range information and the number thereof are calculated for each element included in the extracted problem structure, and the influence range is specified according to the set and the number of the calculated range information To
The method for extracting a problem structure according to claim 9. The information processing apparatus is
In the process of outputting the information of the problem structure and its influence range to the output device, screen data that surrounds each element with a predetermined line segment for each corresponding range is output based on the range information of the element included in the extracted problem structure. ,
The method for extracting a problem structure according to claim 9. The information processing apparatus is
In the process of outputting the information of the problem structure and its influence range to the output device, the information display positions are rearranged and output based on the range information of the elements included in the extracted problem structure. ,
The method for extracting a problem structure according to claim 9.