Business process design support system and business process design support method

Abstract

To provide a work design support system capable of selecting resilient business measures that are robust against various environmental changes, and a work design support method.SOLUTION: A work design support system 100 includes: a business measure scenario setting unit 101b that generates a scenario representing the details of business measures; a simulation unit 104 that executes a simulation on the scenario; a KPI calculation unit 106 that calculates the evaluation index based on the simulation results; and a sensitivity evaluation unit 107 that calculates the sensitivity of the evaluation index when changing the simulation condition parameters. The evaluation index and sensitivity for the scenario are presented.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a business process design support system and a business process design support method for supporting the design and improvement of various types of business processes such as maintenance work. [Background technology]

[0002] Patent Document 1 discloses a policy search device that "selects an action based on a value function that represents the value of the action for the state of a target environment, applies the selected action to simulate a state transition of the target environment, obtains the state of the target environment after the transition and a reward for the applied action indicated by a first index, executes an episode in which a series of processes up to updating the value function based on the state and the reward are repeated multiple times, accumulates episodes in which the second index satisfies a predetermined condition, improves the value function based on the accumulated episodes, repeats the series of processes from executing the episode to improving the value function until a predetermined termination condition is satisfied, and presents a policy determined based on the obtained value function." [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-219981 A Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, the business environment has changed rapidly, and various industries are required to review and improve their business design in response to the business environment. For example, in maintenance work for infrastructure, railways, industrial equipment, medical equipment, etc., it is necessary to continuously carry out maintenance such as inspection and repair to ensure the safe and stable operation of assets (facilities).

[0005] In this type of maintenance, organizational structures and work standards are designed taking into account the operating status and operational characteristics of assets, and the status of maintenance resources such as workers and tools. However, when the business environment changes, it is necessary to take some kind of business measures and redesign the maintenance work to suit the new environment.

[0006] Recently, various values ​​such as the environment, resilience, and human rights have been emphasized, and there is a demand to shift away from the traditional business design that emphasizes economy and cost. Therefore, Patent Document 1 describes a technology that searches for suitable measures according to the situation in an environment where various indicators exist.

[0007] In recent years, various values, such as the environment, resilience, and human rights, have come to be emphasized in business. In particular, as we are increasingly exposed to unexpected environmental changes such as natural disasters and epidemics, there is an increasing emphasis on resilient business design that can respond flexibly and robustly to various changes.

[0008] The above-mentioned Patent Document 1 describes a method for searching for suitable business measures that satisfy multiple evaluation indexes, but does not evaluate the amount of change (sensitivity) of the evaluation indexes (hereinafter referred to as "KPIs" (Key Performance Indicators)) when environmental factors change.

[0009] On the other hand, if the resilience of the explored business measures could be understood, it would contribute to more resilient business design, so there is room for improvement.

[0010] An object of the present invention is to provide a business process design support system and a business process design support method that enable the selection of resilient business measures that are robust against various environmental changes. [Means for solving the problem]

[0011] The present invention includes a number of means for solving the above-mentioned problems. One example of the present invention is characterized in that it has a business policy scenario setting unit that generates a scenario indicating the contents of a business policy, a simulation unit that executes a simulation for the scenario, an evaluation index calculation unit that calculates an evaluation index based on the result of the simulation, and a sensitivity evaluation unit that calculates the sensitivity of the evaluation index when a condition parameter of the simulation is changed, and presents the evaluation index and the sensitivity for the scenario. Effect of the Invention

[0012] According to the present invention, it is possible to select a resilient business measure that is robust against various environmental changes. Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0013] [Figure 1] FIG. 1 is a functional block diagram of a business process design support system according to a first embodiment. [Diagram 2] 13 is an example of a setting screen for a business measure scenario according to the first embodiment. [Diagram 3] 13 is an example of a setting screen for sensitivity parameters according to the first embodiment. [Figure 4] 13 is an example of a setting screen for a KPI item according to the first embodiment. [Diagram 5] 13 is an example of a result display screen according to the first embodiment. [Figure 6] FIG. 11 is a functional block diagram of a business process design support system according to a second embodiment. [Figure 7] FIG. 11 is a functional block diagram of a business process design support system according to a third embodiment. [Figure 8] FIG. 13 is a functional block diagram of a business process design support system according to a fourth embodiment. [Figure 9] 13 is an example of a setting screen for a KPI rank according to the fourth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, an embodiment of a business process design support system and a business process design support method according to the present invention will be described with reference to the drawings.

[0015] In each embodiment, a maintenance operation is taken as an example of the operation, but the operation design support system and the operation design support method of each embodiment can also be applied to other industries, such as the service industry, such as finance and transportation, the manufacturing industry, such as chemicals and automobiles, and agriculture.

[0016] In addition, all operations include various tasks such as inspection, repair, and maintenance, and the assets subject to maintenance operations include various items such as facilities, equipment, machinery, and products.

[0017] Furthermore, in the drawings used in this specification, the same or corresponding components are denoted by the same or similar reference numerals, and repeated description of these components may be omitted.

[0018] <Example 1> A first embodiment of a business process design support system and a business process design support method according to the present invention will be described with reference to FIGS. 1 to 5. FIG.

[0019] First, the overall configuration of the business process design support system will be described with reference to Fig. 1. Fig. 1 is a functional block diagram of the business process design support system according to the first embodiment.

[0020] As shown in FIG. 1, the business design support system 100 of the first embodiment has a scenario generation unit 101, a sensitivity parameter setting unit 102, a model generation unit 103, a simulation unit 104, a KPI setting unit 105, a KPI calculation unit 106, a sensitivity evaluation unit 107, a data storage unit 108, and a display unit 109.

[0021] This business design support system 100 can be realized by a general information processing device processing software, and is preferably composed of a computer or the like. The computer that constitutes the system is equipped with a CPU, memory, an interface, a display unit 109 such as a display that presents processing results and the like to a user, an input device such as a keyboard and mouse that accepts input from a user, a data storage unit 108 consisting of a recording device such as an SSD or HDD, and the control of the operation of each device and various arithmetic processing described later are executed based on various programs. These programs can be stored in the internal data storage unit 108, an external recording medium, a data server (all not shown), etc., and can be read and executed by the CPU.

[0022] The control processes may be integrated into one program, or may be divided into multiple programs, or may be a combination of these. Some or all of the programs may be realized by dedicated hardware, or may be modularized. Furthermore, the various programs may be installed from a program distribution server, an internal storage medium, or an external storage medium.

[0023] The scenario generating unit 101 is a part that generates a scenario that defines the state and conditions of a target business, and has a reference scenario setting unit 101a and a business measure scenario setting unit 101b.

[0024] The scenario generated by the scenario generation unit 101 is composed of a wide variety of information, such as information on the personnel and organization that executes the business, information on assets related to the business, information on the systems that configure the business, information on business processes related to the execution rules of the business, etc. For example, in the case of a maintenance business, the information is as follows:

[0025] Information on the personnel and organization that carry out the work includes information such as the organizational structure of the maintenance business company, the number and locations of service bases where maintenance is performed, the number and skills of maintenance workers, the work and assets they are responsible for, working hours, etc.

[0026] Information on assets related to business operations includes information on the type and model of assets, functions, components, causal relationships between components, failure modes, failure occurrence rates for each failure mode, number of units installed, installation locations, operation times, etc. Asset information also includes information on the type and model of components, such as parts, inventory numbers, production frequency, production times, etc.

[0027] Information on the systems that make up business operations includes asset management systems, business management systems, business log systems, sensors, condition monitoring systems, and IoT technologies such as predictive diagnosis and remote diagnosis, and for each system, information on performance, implementation costs, operating costs, applicable assets and organizational scope, etc. is included.

[0028] Business process information related to the execution rules of a business includes information such as business classification such as inspection and repair, frequency of occurrence of the work, work time, skills required for the work, tools required for the work, cost required for the work, travel time, and the like.

[0029] The various information contained in the above scenario is time-series information that includes not only the current state of the maintenance work, but also past states and hypothetical states expected in the future.

[0030] In addition, it does not matter whether the scenario generated by the scenario generating unit 101 is a virtual maintenance work state or a realistic maintenance work state.

[0031] A realistic scenario can be set based on design information and past history. For example, realistic asset information or part information can be set based on information such as an asset management system (EAM), asset design specifications, durability test data, fault log data, event log data, failure mode and effect analysis (FMEA), and fault tree analysis (FTA). Realistic maintenance work information can be set based on work log data that records the work start time, work end time, work content, worker name, tools used, required qualifications, and so on. By generating a realistic scenario in this way, a simulation can be performed that accurately reproduces real maintenance work.

[0032] In addition, the scenario may be a hypothetical one that does not actually occur. For example, if three maintenance personnel are scheduled to retire, a hypothetical scenario can be generated in which the current number of maintenance personnel is reduced by three, allowing a simulation to be performed to predict future maintenance work that may occur after the three personnel retire.

[0033] The reference scenario setting unit 101a sets a scenario of a maintenance work state that is in line with reality, using the method described above.

[0034] The business policy scenario setting unit 101b selects and sets a business policy scenario, which indicates the contents of business policies that can be taken for the current situation, from among business policy patterns prepared in advance. This business policy scenario setting unit 101b preferably executes the business policy scenario setting step.

[0035] Examples of business measure patterns include IoT measures to introduce new IoT solutions such as predictive diagnosis, repair recommendations, and remote diagnosis, organizational change measures to change the number and locations of service bases or the number of workers at each service base, and maintenance policy change measures to change regular inspection cycles, part replacement cycles, etc. Compound measures that combine multiple business measure patterns can also be considered as a single measure.

[0036] Here, the "measure" in the present invention means changing the parameters of the information that can be intentionally changed among various information contained in the scenario. For example, a maintenance staff increase measure can be said to be changing the number of maintenance staff to an increased value, and an IoT introduction measure can be said to be changing the number of IoT technologies such as predictive diagnosis to an increased value.

[0037] Note that changing includes changing to the same value, and can be considered as a status quo maintenance measure that continues the state of the maintenance work at a certain point in time. Also, the number of items to be changed is not limited to one, and multiple items may be changed at the same time.

[0038] An example of a business policy scenario setting screen is shown in Figure 2. In the example of Figure 2, three different business policy scenario screens, policy scenarios A, B, and C, are opened, and different policy settings are made for each.

[0039] In the example of Figure 2, predictive diagnosis is selected as the IoT policy pattern for the policy scenario C settings, and a false alarm rate of 10% and a missed alarm rate of 3% are entered as the performance values, which are the condition parameters. In addition, the area unit is selected as the scope of application of predictive diagnosis, and it is specified that predictive diagnosis is to be applied to the assets of site A.

[0040] In addition, change in the number of maintenance personnel is selected as the organizational change measure pattern, and the number of people to be changed is entered as +3 as the condition parameter. Also, the range of service bases to which the change will be applied is specified by SC unit, and SC1 and SC5 are specified.

[0041] Furthermore, change of regular inspection cycle is selected as the maintenance policy change measure pattern, and the target is specified as the A component inspection as the condition parameter, and the cycle is input as 6 months.In other words, measure scenario C in Figure 2 is an example of a business measure scenario that combines three measure patterns.

[0042] By adding the business measure scenario set in the business measure scenario setting unit 101b to the scenario based on the current business situation set in the reference scenario setting unit 101a, a virtual business scenario can be generated when the assumed business measure is executed. The scenario generation unit 101 sets multiple business measure scenarios and generates multiple virtual business scenarios.

[0043] The sensitivity parameter setting unit 102 sets the condition parameters to be varied and the range of variation among the various information condition parameters contained in the business scenario generated by the scenario generation unit 101, and generates a business scenario for the assumed business scenario when the condition parameters are varied.

[0044] Figure 3 shows an example of a sensitivity parameter setting screen. The example in Figure 3 assumes a natural disaster pattern, an epidemic pattern, and a cyber attack pattern as patterns of external factors that affect the business environment.

[0045] For example, in the natural disaster pattern, the affected condition parameters are specified as Site A, the affected base, -5 to 0 as the fluctuation range of the number of maintenance personnel, 0 to +100% as the fluctuation range of the travel time between the base and the site, and the status monitoring system as the stopped system. This is a condition setting that assumes a situation in which the assets of Site A stop simultaneously due to a natural disaster such as a typhoon, up to five maintenance personnel are unable to work at the service base of SC1, travel time between the base and the site is doubled, and the status monitoring system stops. Note that these multiple condition parameters may be varied individually or simultaneously, and there are many variations in the natural disaster pattern alone.

[0046] In the epidemic pattern example in Figure 3, SC1 and SC5 are specified as affected locations, and the fluctuation range of the number of maintenance personnel is specified as -20 to 0. This condition setting assumes a situation in which a maximum of 20 people are unable to work at each of the service locations SC1 and SC5 due to the epidemic.

[0047] In the cyber attack pattern, Site A and Site B are specified as affected sites, SC1 and SC5 are specified as affected bases, and the predictive diagnosis system is specified as the stopped system. This is a condition setting that assumes that a cyber attack causes the predictive diagnosis systems for assets at Site A and Site B to stop, making it impossible to access information at the service bases of SC1 and SC5.

[0048] A large number of variation conditions can be generated by varying the condition parameters of the various variation patterns described above independently. By adding these large number of variation conditions to the business scenario generated by the scenario generation unit 101, multiple business scenarios with various variations are generated.

[0049] Next, the generated business scenario is input to a model generation unit 103, which generates various models for operating a simulation unit 104. In the case of a simulation targeting maintenance work, a worker model, an asset model, a business process model including tasks, an IT system model, and the like are generated.

[0050] The simulation unit 104 uses the various models that have been generated to perform a simulation of the maintenance work. This simulation unit 104 preferably executes the simulation steps. A model is generated for each of the multiple work scenarios to which the above-mentioned various variations have been added, and a simulation is performed for each of the work scenarios.

[0051] The simulation method executed by the simulation unit 104 can be realized by, for example, agent simulation.

[0052] In agent simulation, asset data corresponding to each individual asset in the simulation world is generated for each management unit such as real-world assets or asset parts, and the behavior of real-world assets is reproduced by having these assets autonomously operate and break down. The data generated at this time is called an agent, and in the case of assets, it is called an asset agent.

[0053] Similarly, agents are generated in the simulation world for each maintenance worker, and are called maintenance worker agents. These agents perform actions such as waiting, moving, performing tasks, and resting in response to work instructions.

[0054] In addition, agents corresponding to real-world characters are generated, such as an operation agent who operates assets and requests troubleshooting when a problem occurs, and an allocation agent who assigns work to maintenance personnel.

[0055] At the start of the simulation, each agent is generated according to the input scenario, and each agent operates autonomously as the simulation time progresses, and the behavior of each agent is recorded as log data of the simulation. For example, in the asset agent, the operation start time, operation end time, time of failure, time of repair and recovery, inspection time, etc. are recorded as an asset operation log for each individual asset. Also, in the maintenance worker agent, the work start time, work end time, work content, work time, etc. are recorded as a maintenance worker work log for each maintenance worker. These log data are output as the results of the simulation unit 104.

[0056] The simulation method is not limited to agent simulation, and for example, a causal loop diagram (LCD) or a machine learning model may be used.

[0057] The simulation results for each business scenario obtained by the simulation unit 104 are input to the KPI calculation unit 106 .

[0058] The KPI calculation unit 106 is a part that calculates the KPI designated in advance by the KPI setting unit 105 based on the result of the simulation. The KPI calculated by the KPI calculation unit 106 is input to the sensitivity evaluation unit 107. This KPI calculation unit 106 is preferably the entity that executes the evaluation index calculation step.

[0059] Fig. 4 is an example of a KPI setting screen constituting the KPI setting unit 105. In the example of Fig. 4, the KPI items include asset utilization rate, CO2 emission amount, response time, policy cost, maintenance cost, labor cost, overtime hours, work efficiency, and total work man-hours.

[0060] For example, asset utilization rate can be calculated by statistically analyzing the asset operation log, which is a simulation result. Overtime hours can be calculated by statistically analyzing the maintenance staff work log, which is a simulation result. In the embodiment of FIG. 1, multiple KPIs can be selected. In the example of FIG. 3, three KPIs are selected: asset utilization rate, policy cost, and overtime hours. In this case, three KPIs (KPI1, KPI2, KPI3) are calculated for each simulated business scenario.

[0061] The sensitivity evaluation unit 107 compares the KPI for the business scenario generated by the scenario generation unit 101 with the KPI for the business scenario when the condition parameters of the simulation specified by the sensitivity parameter setting unit 102 are varied, and calculates the amount of change in the KPI. This sensitivity evaluation unit 107 is preferably the entity that executes the presentation step.

[0062] Here, in the present invention, the amount of change in the KPI when the condition parameter varies is called the KPI sensitivity. As described above, the variation of the condition parameter set by the sensitivity parameter setting unit 102 can have multiple diverse patterns, so that for one business scenario generated by the scenario generating unit 101, there exists a business scenario to which multiple variations have been added. Therefore, for the KPI of one business scenario, multiple KPI sensitivities are calculated according to the variation pattern of the condition parameter. Furthermore, when multiple KPIs are specified, there are multiple KPIs for one business scenario, and multiple KPI sensitivities are calculated for each of the multiple KPIs.

[0063] The data on the business scenarios, KPIs for each business scenario, and KPI sensitivity for each business scenario generated in the above-mentioned process are recorded in the data storage unit 108. Since the scenario generation unit 101 creates multiple business scenarios from among anticipated business measure scenario patterns, the data storage unit 108 stores a set of KPIs and KPI sensitivity for each of the multiple business scenarios.

[0064] The data for each business scenario stored in the data storage unit 108 is input to the display unit 109, which displays the input data for each business scenario on its screen. Fig. 5 shows an example of an output screen of the results of evaluating the business scenarios.

[0065] The KPIs to be output are selected in the upper part of the screen in Fig. 5. In this example, KPI1 asset utilization rate and KPI2 overtime hours are selected. The middle part of the screen displays the KPI evaluation results for each business measure scenario in a graph with KPI1 and KPI2 as the axes. The horizontal axis shows the value of KPI1, asset utilization rate, and the vertical axis shows the value of KPI2, overtime hours.

[0066] In the output screen of the results of evaluating a business scenario, such as that shown in Figure 5, it is desirable to plot each business measure with a marker of a different type (shape, color).

[0067] In Figure 5, in addition to the results of policy scenarios A, B, and C, the results of the current business situation without any measures are also shown (squares).

[0068] In addition, the results of each business action scenario are shown with a large plot without any change in condition parameters, and the results of sensitivity evaluation with the condition parameters changed are displayed with the same type of marker in a smaller plot. This makes it possible to visualize the range of change in KPI when various condition parameters are changed in each business action scenario. In Figure 5, the range of change for each business scenario is surrounded by a dashed line.

[0069] Furthermore, the lower part of Figure 5 shows the values ​​of each KPI and the sensitivity (range of change) of each KPI for policy scenario C, which was determined to be the best policy.

[0070] In the example of Figure 5, for the current situation, policy scenario A has the effect of improving KPI2, policy scenario B has the effect of significantly improving KPI1, and policy scenario C has the effect of improving KPI1 and KPI2. In this case, if you place importance on KPI1, you will tend to select policy scenario B, which improves KPI1 the most, as the best option.

[0071] However, in policy scenario B, the range of fluctuation when the condition parameters are changed is large, and in some cases, KPI1 and KPI2 may fall below the current level. As illustrated in Fig. 3, in Example 1, the condition parameter fluctuations assuming natural disasters, epidemics, and cyber attacks are set as the fluctuation patterns of the sensitivity parameters. Therefore, policy scenario B can be said to be a non-resilient business policy with low robustness against natural disasters, epidemics, and cyber attacks.

[0072] On the other hand, the range of fluctuations in Policy Scenario A and Policy Scenario C is smaller than the current situation, and they can be said to be resilient business measures. As a result, Policy Scenario C improves KPI1 and KPI2 while being highly robust against fluctuations, and can be judged to be the best policy when resilience is also taken into account.

[0073] Next, the effects of this embodiment will be described.

[0074] The business design support system 100 of the first embodiment of the present invention described above includes a business measure scenario setting unit 101b that generates a scenario indicating the contents of a business measure, a simulation unit 104 that executes a simulation for the scenario, a KPI calculation unit 106 that calculates an evaluation index based on the result of the simulation, and a sensitivity evaluation unit 107 that calculates the sensitivity of the evaluation index when the condition parameters of the simulation are changed, and presents the evaluation index and sensitivity for the scenario.

[0075] This makes it possible to select resilient business measures that are robust against various environmental changes.

[0076] In addition, since there are multiple evaluation indexes, the sensitivity evaluation unit 107 calculates the sensitivity when the condition parameters are changed for each of the multiple evaluation indexes, and presents the multiple evaluation indexes and their sensitivities, it is possible to take into account a variety of evaluation indexes in a well-balanced manner. Furthermore, even if the business environment changes and the evaluation indexes to be emphasized change in the future, it is possible to quickly make a decision to change measures. For example, in the example of Figure 5, if KPI1 is currently emphasized, but KPI2 suddenly becomes important, it is possible to immediately select measure scenario A that is effective for improving KPI2.

[0077] <Example 2> A business process design support system and a business process design support method according to a second embodiment of the present invention will be described with reference to Fig. 6. Fig. 6 is a functional block diagram of the business process design support system according to the second embodiment.

[0078] A business process design support system 100A of this embodiment shown in FIG. 6 is obtained by adding a policy evaluation / selection unit 111 to the business process design support system 100 of the first embodiment shown in FIG.

[0079] The policy evaluation / selection unit 111 receives data for each of the multiple business scenarios stored in the data storage unit 108, and compares and evaluates the KPI and KPI sensitivity values ​​for each business scenario to select a good business scenario from among the multiple business scenarios. More specifically, it is possible to preferentially select and present business policies with low sensitivity among scenarios whose evaluation indexes meet the reference values. This policy evaluation / selection unit 111 is preferably the entity that executes the policy evaluation / selection step.

[0080] As evaluation / selection criteria, first, a reference value of an important KPI is set, and business scenarios that satisfy the KPI reference value are extracted. If multiple business scenarios are extracted, the KPI sensitivity of each business scenario is compared, and the one with the smallest KPI sensitivity is selected preferentially. The data of the selected business scenario is passed to the display unit 109 and displayed.

[0081] The other configurations and operations are substantially the same as those of the business process design support system and the business process design support method of the first embodiment described above, and the details are omitted here.

[0082] The business process design support system and method according to the second embodiment of the present invention also provide substantially the same effects as those of the business process design support system and method according to the first embodiment described above.

[0083] In addition, by further having a policy evaluation / selection unit 111 that preferentially selects and presents business policies with low sensitivity among scenarios whose evaluation indexes meet the reference values, it is possible to preferentially select, from among business policies whose important KPIs meet the reference values, highly robust policies whose important KPIs are less likely to fluctuate in response to fluctuations in condition parameters, and it is possible to automatically select resilient business policies.

[0084] <Example 3> A business process design support system and a business process design support method according to a third embodiment of the present invention will be described with reference to Fig. 7. Fig. 7 is a functional block diagram of the business process design support system according to the third embodiment.

[0085] A business process design support system 100B of this embodiment shown in FIG. 7 is obtained by adding a policy learning unit 121 to the business process design support system 100 of the first embodiment.

[0086] The policy learning unit 121 is a part that learns the relationship between the condition parameters of a scenario and the evaluation index and sensitivity, and receives data for each of a plurality of business scenarios stored in the data storage unit 108. This policy learning unit 121 is preferably the entity that executes the policy learning step.

[0087] The policy learning unit 121 learns the relationship between various conditions of a business scenario (information on personnel and organizations performing the business, information on assets related to the business, information on systems that configure the business, information on business processes related to the execution rules of the business, etc.) and KPIs and KPI sensitivities under the conditions of the business scenario. Machine learning models such as multiple regression analysis and deep learning can be used for learning.

[0088] The policy learning unit 121 can support the selection of good business policy candidates by estimating, from the learning model, a business policy scenario in which the KPI specified by the KPI setting unit 105 has a good value and presenting the estimated business policy scenario to the business policy scenario setting unit 101b of the scenario generating unit 101. Similarly, the policy learning unit 121 can support the selection of resilient business policy candidates that are robust to condition parameter fluctuations by estimating, from the learning model, a business policy scenario in which the sensitivity of the KPI specified by the KPI setting unit 105 has a small value.

[0089] Data under various conditions, regardless of the type of business or field, may be stored in the data storage unit 108. For example, a simulation result for a wind turbine maintenance operation and a simulation result for a railway car maintenance operation may be stored simultaneously. By accumulating a large number of simulation results in the data storage unit 108, it is possible to learn the relationships between various KPIs and KPI sensitivities under various conditions, and it is possible to provide a general-purpose system that is not limited to a specific business or field.

[0090] The other configurations and operations are substantially the same as those of the business process design support system and the business process design support method of the first embodiment described above, and the details are omitted here.

[0091] The business process design support system and method according to the third embodiment of the present invention also provide substantially the same effects as those of the business process design support system and method according to the first embodiment described above.

[0092] In addition, by further having a policy learning unit 121 that learns the relationship between the scenario's condition parameters and the evaluation indexes and their sensitivities, it is possible to efficiently select good business policy scenarios that have a high business improvement effect for a specified KPI from among the countless business policy scenarios that exist.

[0093] The policy learning unit 121 of this embodiment is also applicable to the business process design support system 100A described in the second embodiment.

[0094] <Example 4> A business process design support system and a business process design support method according to a fourth embodiment of the present invention will be described with reference to Fig. 8 and Fig. 9. Fig. 8 is a functional block diagram of the business process design support system according to the fourth embodiment, and Fig. 9 is an example of a setting screen for KPI rank.

[0095] In the work process design support system 100C of this embodiment shown in FIG. 8, the sensitivity evaluation unit 107 in the work process design support system 100 of the embodiment 1 shown in FIG. 1 is changed to a sensitivity / rank evaluation unit 131, and a rank setting unit 132 is added.

[0096] The rank setting unit 132 sets a KPI rank for each KPI according to its value. The sensitivity / rank evaluation unit 131 receives the KPI for each business scenario calculated by the KPI calculation unit 106, calculates the KPI sensitivity when the condition parameters vary, and ranks each KPI according to the rank (reference value) set by the rank setting unit 132. The KPI sensitivity and KPI rank for each business scenario calculated by the sensitivity / rank evaluation unit 131 are saved in the data storage unit 108 as a set with the business scenario and the KPI.

[0097] Figure 9 shows an example of KPI ranking. For example, the standard values ​​for ranking can be the guaranteed value in the maintenance contract, the regulated value based on laws and regulations, the company's internal standards, or the minimum standard based on social demands. In the example of Figure 9, the range that is desired to be achieved is ranked A, the range that is acceptable based on social demands is ranked B, and outside the acceptable range is ranked C.

[0098] The other configurations and operations are substantially the same as those of the business process design support system and the business process design support method of the first embodiment described above, and the details are omitted here.

[0099] The business process design support system and method according to the fourth embodiment of the present invention also provide substantially the same effects as those of the business process design support system and method according to the first embodiment described above.

[0100] In addition, the sensitivity / rank evaluation unit 131 ranks the evaluation index based on the specified reference value and presents the rank together with the evaluation index and sensitivity, thereby enabling each business policy scenario set by the scenario generation unit 101 to be evaluated with a rank according to reference values ​​such as regulatory values ​​and guaranteed values, thereby simplifying the evaluation index and making it easier to judge the suitability of the business policy.

[0101] In addition, the sensitivity / rank evaluation unit 131 of this embodiment can also be applied to the business design support system 100A described in the second embodiment, the business design support system 100B described in the third embodiment, and a business design support system that combines the configurations of the second embodiment and the third embodiment.

[0102] <Other> The present invention is not limited to the above-described embodiment, but includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to the embodiment having all of the described configurations.

[0103] In addition, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Also, it is possible to add, delete, or replace a part of the configuration of each embodiment with the configuration of another embodiment. [Explanation of symbols]

[0104] 100, 100A, 100B, 100C...Business design support system 101…Scenario generation section 101a…Baseline scenario setting section 101b…Business policy scenario setting section 102...Sensitivity parameter setting section 103…Model generation unit 104…Simulation Department 105…KPI setting section 106…KPI calculation department 107…Sensitivity evaluation section 108...Data storage section 109...Display section 111…Policy Evaluation / Selection Department 121…Policy Learning Department 131...Sensitivity / Rank Evaluation Unit (Sensitivity Evaluation Unit) 132…Rank setting section

Claims

1. a business policy scenario setting unit for generating a scenario indicating the content of the business policy; a simulation unit that executes a simulation for the scenario; an evaluation index calculation unit that calculates an evaluation index based on a result of the simulation; a sensitivity evaluation unit that calculates the sensitivity of the evaluation index when a condition parameter of the simulation is changed, Presenting the evaluation metrics and the sensitivities to the scenarios A business design support system characterized by:

2. 2. The process design support system according to claim 1, There are a plurality of the evaluation indexes, The sensitivity evaluation unit calculates the sensitivity when the condition parameter is changed for each of the plurality of evaluation indexes, and displays the plurality of evaluation indexes and the sensitivities. A business design support system characterized by:

3. 2. The process design support system according to claim 1, The method further includes a policy evaluation / selection unit that selects and presents, with priority, a business policy having a low sensitivity from among the scenarios in which the evaluation index satisfies a reference value. A business design support system characterized by:

4. 2. The process design support system according to claim 1, The method further includes a policy learning unit that learns the relationship between the condition parameters of the scenario and the evaluation index and the sensitivity. A business design support system characterized by:

5. 2. The process design support system according to claim 1, The sensitivity evaluation unit ranks the evaluation index based on a specified reference value, and presents a rank together with the evaluation index and the sensitivity. A business design support system characterized by:

6. A business measure scenario setting step of generating a scenario indicating the contents of a business measure by a computer; a simulation step of executing a simulation on the scenario generated in the business action scenario setting step by the computer; an evaluation index calculation step of calculating an evaluation index based on a result of the simulation by the computer; a sensitivity evaluation step of calculating, by the computer, the sensitivity of the evaluation index when a condition parameter of the simulation is changed; and a presentation step of presenting, by the computer, the evaluation index and the sensitivity for the scenario. A business process design support method comprising:

7. 7. The process design support method according to claim 6, There are a plurality of the evaluation indexes, In the sensitivity evaluation step, the computer calculates the sensitivity when the condition parameter is changed for each of the plurality of evaluation indexes, and displays the plurality of evaluation indexes and the sensitivities. A business process design support method comprising:

8. 7. The process design support method according to claim 6, The method further includes a measure evaluation / selection step of causing the computer to preferentially select and present business measures having a low sensitivity from among the scenarios in which the evaluation index satisfies a reference value. A business process design support method comprising:

9. 7. The process design support method according to claim 6, The method further includes a policy learning step of learning the relationship between the condition parameters of the scenario, the evaluation index, and the sensitivity by the computer. A business process design support method comprising:

10. 7. The process design support method according to claim 6, In the sensitivity evaluation step, the computer ranks the evaluation indexes based on a specified reference value and presents a rank together with the evaluation indexes and the sensitivity. A business process design support method comprising:

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