JP5781382B2 - Improvement measure selection device, improvement measure selection method and improvement measure selection program - Google Patents

Description

  The present invention relates to an improvement measure selection device, an improvement measure selection method, and an improvement measure selection program.

  Equipment such as gas turbines may undergo renovation work aimed at improving performance and reducing environmental impact. Various facilities have many options for refurbishment, and the operational status of the facilities and the management environment of customers operating the facilities are different. For this reason, sales representatives have conventionally proposed renovation works based on their own experience and knowledge, taking into account various situations.

  In order to make a proposal based on a quantitative evaluation rather than a proposal that depends on the experience and knowledge of such individuals, for example, in Patent Document 1, three elements that are considered to be important for a service are three elements of red, green, and blue. A technique has been proposed in which three service colors are displayed in a mixed color of three colors in correspondence with three axes indicating the color definition.

Japanese Patent Laid-Open No. 05-290022

  By enabling quantitative evaluation as in the technique disclosed in Patent Document 1, it is possible to prevent the evaluation from being varied by the person in charge. However, since it is not possible to evaluate improvement measures according to the characteristics of each customer simply by performing quantitative evaluation, it is not always possible to select an improvement measure suitable for the customer.

  The present invention has been made in view of the above, and an object thereof is to provide an improvement measure selection device, an improvement measure selection method, and an improvement measure selection program capable of selecting an improvement measure suitable for a customer.

  In order to solve the above-described problems and achieve the object, the improvement measure selection apparatus according to the present invention includes plant information in which information related to installed facilities is registered, and improvement measures applied to the facilities. Storage unit for storing information related to the proposal result proposed to the customer who has introduced the equipment to which the system is applied, the target equipment for proposing improvement measures, and the equipment registered in the plant information A similarity calculation unit that calculates the similarity to the above, and based on the similarity calculated by the similarity calculation unit, the improvement plan proposed for the facility similar to the target facility for which an improvement plan is proposed A candidate extraction unit that is extracted from the result information, and an improvement measure that selects an improvement measure to be proposed from among the improvement plans extracted by the candidate extraction unit, based on information related to the proposal result registered in the result information And a tough.

  Here, as a desirable mode of the present invention, the similarity calculation unit calculates the facility similarity based on the facility specifications registered in the plant information.

  As a desirable mode of the present invention, the similarity calculation part calculates the similarity of equipment based on the operation status of the equipment registered in the plant information.

  Moreover, as a desirable aspect of the present invention, the storage unit further stores customer information including information related to customer characteristics, and the similarity calculation unit introduces facilities registered in the customer information. The facility similarity is calculated based on the customer characteristics.

  Moreover, as a desirable aspect of the present invention, the information related to the characteristics of the customer includes at least one of an approach to the environmental problem of the customer, a business plan, or an average operating rate.

  Moreover, as a desirable aspect of the present invention, the similarity calculation unit includes, based on the specifications of the facility registered in the plant information, the target facility for proposing improvement measures and the facility registered in the plant information. Similarity between the equipment registered in the plant information and the equipment determined to have the same identity as the equipment to be proposed for improvement and the equipment to be proposed for improvement Calculate the degree.

  Further, as a desirable mode of the present invention, the improvement measure selection unit is an improvement to be proposed based on an evaluation of an improvement measure by a customer who has received a proposal for an improvement measure, which is registered in the performance information as the proposal result. Select measures.

  Further, as a desirable aspect of the present invention, the improvement measure selection unit makes a suggestion based on whether or not the improvement measure is adopted by the customer who has received the improvement measure proposal, which is registered in the result information as the proposal result. Select improvement measures to be taken.

  Further, in order to solve the above-described problems and achieve the object, the improvement measure selection method according to the present invention is an improvement measure selection method executed by the information processing apparatus, and includes a target facility for proposing improvement measures A step of calculating the similarity with the facility registered in the plant information in which information about the installed facility is registered, and the facility to be proposed for improvement and the facility registered in the plant information. A step of calculating the similarity and information related to the result of the proposal proposed to the customer who has introduced the equipment to which the improvement measures are applied based on the calculated similarity are registered. Based on the information on the proposal result registered in the result information and the step of extracting the improvement plan proposed for the equipment similar to the target equipment for which improvement measures are proposed from the result information. And a step of selecting the improvements to be proposed from among been improvement plan.

  In addition, in order to solve the above-described problems and achieve the object, the improvement measure selection program according to the present invention registers, in the information processing apparatus, information on the equipment to be improved and the equipment that has been introduced. Calculating the degree of similarity with the equipment registered in the plant information to be calculated, and calculating the degree of similarity between the equipment to be proposed for improvement and the equipment registered in the plant information. Targets for proposing improvement measures based on performance information in which information related to the results of proposals that have been proposed to customers who have introduced the facilities to which the improvement measures are applied based on the similarities Should be proposed from the extracted improvement plans based on the step of extracting the proposed improvement plan for the equipment similar to the equipment and the information on the proposal result registered in the performance information And a step of selecting a good measure.

  The improvement measure selection device, the improvement measure selection method, and the improvement measure selection program according to the present invention have an effect that an improvement measure suitable for the customer can be selected.

FIG. 1 is a block diagram illustrating the configuration of the improvement measure selection device according to the first embodiment. FIG. 2 is a diagram illustrating an example of improvement measure information. FIG. 3 is a diagram illustrating an example of customer information. FIG. 4 is a diagram illustrating an example of plant information. FIG. 5 is a diagram illustrating an example of performance information. FIG. 6 is a flowchart illustrating a processing procedure of improvement measure selection processing according to the first embodiment. FIG. 7 is a block diagram illustrating the configuration of the improvement measure selection device according to the second embodiment. FIG. 8 is a flowchart illustrating a processing procedure for improvement measure selection processing according to the second embodiment. FIG. 9 is a block diagram illustrating the configuration of the improvement measure selection device according to the third embodiment. FIG. 10 is a flowchart illustrating a processing procedure of improvement measure selection processing according to the third embodiment. FIG. 11 is a flowchart showing the processing procedure of the popularity calculation process.

  Embodiments of an improvement measure selection device, an improvement measure selection method, and an improvement measure selection program according to the present invention will be described below in detail with reference to the drawings. Note that the present invention is not limited to the embodiments. Moreover, although the following example demonstrates the example which applies this invention to selection of the improvement plan regarding a gas turbine, the application object of this invention is not limited to this. In addition, the constituent elements in this embodiment include those that can be easily assumed by those skilled in the art, those that are substantially the same, and those in a so-called equivalent range.

  First, the configuration of the improvement measure selection device according to the first embodiment will be described. FIG. 1 is a block diagram illustrating the configuration of the improvement measure selection device according to the first embodiment. An improvement measure selection device 10 shown in FIG. 1 is an information processing device used to select a suitable improvement measure from among many improvement measures related to a gas turbine. The improvement measure selection device 10 includes a display unit 11, an input unit 12, a communication unit 13, a medium reading unit 14, a control unit 15, and a storage unit 16.

  The display unit 11 includes a display device such as a liquid crystal panel or an organic EL (Organic Electro-Luminescence) panel, and displays various information such as characters and figures based on a control signal transmitted from the control unit 15. The input unit 12 includes an input device such as a keyboard, and outputs a signal corresponding to an operation performed by the user on the input device to the control unit 15. The communication unit 13 controls transmission / reception of information with other devices based on a predetermined communication protocol. The medium reading unit 14 reads a program and data from a storage medium such as a CD-ROM.

  The control unit 15 includes a CPU (Central Processing Unit) 151 that is a calculation unit and a memory 152 that is a storage unit, and implements various functions by executing programs using these hardware resources. Specifically, the control unit 15 reads out a program stored in the storage unit 16 and expands it in the memory 152, and causes the CPU 151 to execute an instruction included in the program expanded in the memory 152. The control unit 15 reads / writes data from / to the memory 152 and the storage unit 16 and controls the operation of the communication unit 13 and the like according to the execution result of the instruction by the CPU 151.

  The storage unit 16 includes a nonvolatile storage device such as a magnetic storage device or a semiconductor storage device, and stores various programs and data. The data stored in the storage unit 16 includes improvement measure information 161, customer information 162, plant information 163, performance information 164, periodic inspection schedule 165, and parameter information 166. The programs stored in the storage unit 16 include an improvement measure selection program 167.

  Note that all or part of the programs and data that are stored in the storage unit 16 in FIG. 1 may be stored in a storage medium that can be read by the medium reading unit 14. Further, all or part of the program and data that the storage unit 16 stores in FIG. 1 may be acquired from another device through communication by the communication unit 13.

  The improvement measure information 161 holds information regarding improvement measures that can be selected for the gas turbine. The content of the improvement measure information 161 is updated every time a new improvement measure is conceived or an existing improvement measure is modified. FIG. 2 is a diagram illustrating an example of the improvement measure information 161. As shown in FIG. 2, the improvement measure information 161 has items such as an improvement measure ID, a model, an improvement location, an introduction cost, an output increase amount, a fuel consumption reduction amount, a carbon dioxide reduction amount, and a maintenance cost reduction amount. Data is stored for each measure.

  The improvement measure ID is an identification code for identifying the improvement measure. The model is an identification code for identifying the type of gas turbine to be improved. The same type is assigned to gas turbines with a common basic design. The improvement point is a part of the gas turbine where the improvement measure is applied.

  The introduction cost is a cost necessary for implementing the improvement measures. The output improvement amount is an amount of electric power per predetermined period (unit period) that is increased by the improvement measure. The fuel consumption reduction amount is a fuel consumption amount per predetermined period that is reduced by an improvement measure. The amount of carbon dioxide reduction is the amount of carbon dioxide emission per predetermined period that is reduced by improvement measures. The maintenance cost reduction amount is a maintenance cost per predetermined period reduced by the improvement measure.

  The customer information 162 holds information about customers who have installed gas turbines. FIG. 3 is a diagram illustrating an example of the customer information 162. As shown in FIG. 3, the customer information 162 includes items such as a customer number, an approach to environmental problems, a business plan, and an average operating rate, and data is stored for each customer.

  The customer number is an identification code for identifying the customer. Initiatives for environmental issues indicate the customer's aggressiveness in dealing with environmental issues such as global warming. In the business plan, values such as “sales-oriented”, “profit-oriented”, and “stability-oriented” indicating the tendency of the customer's business plan are set. The average operating rate is an average value of the operating rate of the gas turbine owned by the customer.

  The plant information 163 holds information about the introduced gas turbine. FIG. 4 is a diagram illustrating an example of the plant information 163. As shown in FIG. 4, the plant information 163 includes items such as a plant number, a customer number, a model, a bypass valve, a combustion nozzle, a combustion cylinder, a combustion method, an operating condition, an operating rate, a fuel unit price, and a power sale limit. Data is stored for each introduced gas turbine.

  The plant number is an identification code for identifying each installed gas turbine. The customer number is an identification code for identifying the customer. The model is an identification code for identifying the type of the gas turbine. The bypass valve is an identification code for identifying the type of bypass valve provided in the gas turbine. The combustion nozzle is an identification code for identifying the type of combustion nozzle provided in the gas turbine. The combustion cylinder is an identification code for identifying the type of combustion cylinder provided in the gas turbine.

  The combustion method indicates a combustion method that is employed. The operating condition indicates the start frequency (stop frequency) of the gas turbine. The operating rate is the operating rate of the gas turbine. The fuel unit price is a unit price of fuel used by the customer to operate the gas turbine. The power sale restriction indicates whether or not there is a restriction on buying and selling of electric power generated by the gas turbine to an electric power company.

  The track record information 164 holds information related to the proposal result of improvement measures. FIG. 5 is a diagram illustrating an example of the performance information 164. As shown in FIG. 5, the record information 164 includes items such as a plant number, an improvement measure ID, a proposal result, and a favorable rating, and the proposal results are sequentially added.

  The plant number is an identification code for identifying the gas turbine to be proposed for improvement. The improvement measure ID is an identification code for identifying the proposed improvement measure. The proposal result indicates whether the proposed improvement measure has been adopted or not. The popularity indicates how popular the proposed improvement measures are with customers. For example, “1.0” is set in the case of adoption, and “0.8” is set in the case that it is not done this time but is expected to be adopted after the next time. If it was evaluated favorably but was not adopted due to problems such as cost, “0.6” is set. Further, the favorable rating is set to “0.4” when favorable evaluation is not obtained from the customer, and is set to “0.2” when the customer shows no interest. .

  The periodic inspection schedule 165 holds information regarding the execution schedule of the periodic inspection performed on the introduced gas turbine and the scheduled execution site. Since improvement measures are often performed at the time of periodic inspection, the periodic inspection schedule 165 is used to determine when the improvement measure can be performed and when it can be performed. The parameter information 166 holds various other parameters (various unit prices, etc.) used for selecting improvement measures. The contents of the parameter information 166 are updated as appropriate to reflect the latest situation.

  The improvement measure selection program 167 provides a function for selecting a suitable improvement measure. The improvement measure selection program 167 includes a candidate extraction unit 167a, an evaluation value calculation unit 167b, and an improvement measure selection unit 167c. The candidate extraction unit 167a provides a function of extracting an improvement measure applicable to the designated gas turbine from the improvement measures registered in the improvement measure information 161. The evaluation value calculation unit 167b provides a function of calculating an evaluation value for comprehensively evaluating each extracted improvement measure from a plurality of viewpoints. The improvement measure selection unit 167c provides a function of selecting an improvement measure to be proposed based on the calculated evaluation value.

  The evaluation value calculation unit 167b calculates the evaluation value of the improvement measure by using, for example, the following formula (1).

  In Formula (1), V1 is a calculated evaluation value. V1 represents the ratio between the economic effect of the improvement measure and the introduction cost of the improvement measure in the evaluation period. A1 is an effect value due to an increase in output during the evaluation period, specifically, an increase in power sales revenue during the evaluation period. w1 is a weighting factor for reflecting in the evaluation value the degree to which the customer attaches importance to the effect of increased output. A2 is a reduction in fuel cost during the evaluation period. w2 is a weighting coefficient for reflecting the degree of importance of the fuel cost by the customer in the evaluation value.

  A3 is a value obtained by converting an effect value of reducing the environmental load during the evaluation period, specifically, a reduction amount of carbon dioxide emission during the evaluation period into a monetary amount. w3 is a weighting factor for reflecting the degree of importance of environmental issues by the customer in the evaluation value. A4 is a reduction in maintenance costs during the evaluation period. w4 is a weighting factor for reflecting the degree of importance of maintenance cost by the customer in the evaluation value. Ci is the cost of introducing an improvement measure. Ci is acquired from the improvement measure information 161.

  Note that the effect of the increase in output may be calculated not as an increase in power sales revenue but as a reduction in the cost of power purchased from an electric power company. In addition, the reduction amount of the environmental load may be calculated using not only the reduction amount of the carbon dioxide emission amount but also the reduction amount of other exhaust gas components such as carbon monoxide, nitrogen oxide, and sulfur oxide. Further, the evaluation value may be calculated by further using effect values other than the above A1 to A4.

  Said A1 is calculated using the following formula | equation (2), for example.

  In equation (2), Pu is the amount of power per predetermined period that increases due to the improvement plan to be evaluated. Pu is acquired from the output improvement amount item of the improvement measure information 161. Ce is a power selling unit price. Ce is acquired from the parameter information 166. Ro is the operating rate of the gas turbine to which the improvement measure is applied. Ro is acquired from the plant information 163. T is an evaluation period, and t is a predetermined period (unit period). If the fuel consumption increases as the output increases, the fuel cost corresponding to the increase may be subtracted from A1.

  Said A2 is calculated using the following formula | equation (3), for example.

  In Formula (3), Fd is the fuel consumption per predetermined period which decreases by the improvement measure to be evaluated. Fd is acquired from the item of fuel consumption reduction amount of the improvement measure information 161. Cf is a fuel unit price. Cf is acquired from the parameter information 166.

  Said A3 is calculated using the following formula | equation (4), for example.

  In the equation (4), Cd is the amount of carbon dioxide emission per predetermined period that is reduced by the improvement measure to be evaluated. Cd is acquired from the item of carbon dioxide reduction in the improvement measure information 161. Rc is a coefficient for converting the amount of carbon dioxide emission into the amount of fuel consumed when discharging that amount of carbon dioxide. Rc is acquired from the parameter information 166.

  Said A4 is calculated using the following formula | equation (5), for example.

  In Expression (5), Md is a maintenance cost per predetermined period that is reduced by the improvement measure to be evaluated. Md is acquired from the item of the maintenance cost reduction amount of the improvement measure information 161.

  Note that the evaluation value calculation unit 167b may calculate the evaluation value of the improvement measure using the following equation (6) instead of the above equation (1).

  In Expression (2), V2 is a calculated evaluation value. V2 indicates the difference between the economic effect of the improvement measure in the evaluation period and the introduction cost of the improvement measure, that is, the effect amount of the improvement measure in the evaluation period.

  As described above, by evaluating the improvement measures from a plurality of viewpoints, the improvement measures can be appropriately evaluated even when the experience and knowledge of the individual who performs the evaluation are poor.

  Next, the processing procedure of the improvement measure selection process executed by the improvement measure selection device 10 will be described with reference to FIG. FIG. 6 is a flowchart showing a processing procedure of improvement measure selection processing. The processing procedure shown in FIG. 6 is realized by the control unit 15 executing the improvement measure selection program 167. Prior to execution of the improvement measure selection process, the evaluation conditions such as the proposed gas turbine, the evaluation period of the evaluation value, the implementation timing of the improvement measure, etc. are selected by the operation of the input unit 12 or the communication of the communication unit 13. Input to the device 10.

  As shown in FIG. 6, the control unit 15 first extracts possible improvement measures from the improvement measure information 161 (step S101). Specifically, the control unit 15 acquires the type of the designated gas turbine from the plant information 163, and extracts the improvement plan to be implemented by the acquired type of gas turbine from the improvement plan information 161.

  In addition, when the execution time of improvement measures is designated, the control unit 15 acquires information related to the regular inspection scheduled for the designated gas turbine from the regular inspection schedule 165 and implements it during the regular inspection. Possible improvement measures are extracted from the extraction results. For example, when the location where the periodic inspection is performed is a compressor, the control unit 15 extracts an improvement measure for a part other than the compressor from the extraction result. The introduction timing of the gas turbine may be stored in the plant information 163, and the improvement measure selection device 10 may determine the implementation timing and the implementation location of the periodic inspection from the designated introduction timing of the gas turbine.

  Subsequently, the control unit 15 excludes improvement measures that have already been implemented for the specified gas turbine from the set of extracted improvement measures (step S102). Specifically, the control unit 15 acquires information on improvement measures that have already been implemented for the designated gas turbine from the performance information 164, and an improvement result corresponding to the acquired information is included in the extraction result. , Exclude the improvement measures from the extraction results.

  Steps S101 and S102 described above are realized by the functions provided by the candidate extraction unit 167a. In the above explanation, it was decided to exclude improvement measures that could not be implemented and improvement measures that had already been implemented after extracting the improvement measures using the specified gas turbine model as the extraction condition. Improvement measures in which improvement measures that cannot be implemented and improvement measures that have already been implemented are excluded in advance may be extracted.

  Subsequently, the control unit 15 determines a weighting factor for calculating the evaluation value (step S103). Specifically, the control unit 15 acquires the customer number of the customer who has installed the designated gas turbine from the plant information 163, and acquires data corresponding to the acquired customer number from the customer information 162. And each weighting coefficient is determined based on the acquired customer data.

  It is assumed that the control unit 15 calculates the evaluation value using the above formula (1) or formula (6). In this case, for example, if the business plan of the customer is “sales-oriented”, the control unit 15 sets w1 as a predetermined value so that the increase in power sales revenue that the customer is likely to be interested in is highly evaluated. Larger than. Further, if the business plan of the customer is “profit-oriented”, the control unit 15 increases w2 to be larger than the predetermined value so that the reduction amount of the fuel cost considered to be strongly interested by the customer is highly evaluated. .

  In addition, the control unit 15 sets w3 to be lower than a predetermined value so that if the customer's aggressiveness in the environmental problem is high, the reduction amount of the carbon dioxide emission that the customer is likely to be interested in is highly evaluated. Enlarge. In addition, the control unit 15 sets w4 larger than the predetermined value so that the reduction in maintenance cost that the customer is likely to be interested in is highly evaluated if the average operating rate is low.

  In this way, by determining the weighting factor based on characteristics that can be determined objectively by customers, such as those dealing with environmental issues, it is suitable for customers without relying on the experience and knowledge of specific individuals. A weighting factor can be set. As a result, it is possible to select an improvement measure suitable for the customer.

  Subsequently, the control unit 15 selects one unselected improvement measure from the extracted improvement measures (step S104). When an unselected improvement measure can be selected (step S105, Yes), the control unit 15 calculates an evaluation value of the selected improvement measure (step S106). For example, the above formula (1) or formula (6) is used to calculate the evaluation value. And the control part 15 repeatedly performs step S104 to step S106 until it calculates the evaluation value of all the extracted improvement measures. Steps S103 to S106 described above are realized by the functions provided by the evaluation value calculation unit 167b.

  When the unselected improvement measures cannot be selected, that is, when the evaluation values of all the extracted improvement measures have been calculated (step S105, No), the control unit 15 proposes based on the calculated evaluation values. An improvement measure to be selected is selected (step S107). For example, the control unit 15 may select an improvement measure whose improvement value is higher than a threshold value. Further, the control unit 15 may select a predetermined number or a predetermined ratio of improvement measures in order from the highest evaluation value as an improvement measure to be proposed. The above step S107 is realized by the function provided by the improvement measure selecting unit 167c.

  The improvement measures selected in this way may be output in the form of a proposal or the like as they are, or may be displayed on the display unit 11 and subjected to scrutiny (selection) by the user.

  As described above, in the first embodiment, the improvement measure selecting device 10 calculates the evaluation value of the improvement measure from a plurality of viewpoints. Therefore, regardless of the degree of experience and knowledge of the individual who performs the evaluation, It is possible to appropriately evaluate improvement measures. Further, in this embodiment, the improvement measure selection device 10 determines the weighting factor based on features that can be objectively determined with respect to the customer. Therefore, without relying on the experience and knowledge of a specific individual, An evaluation value adapted to the characteristic can be calculated.

  In the first embodiment, the improvement measure is selected by calculating the evaluation value. However, the improvement measure may be selected based on the actual evaluation of the customer who has already implemented the improvement measure. In Example 2 below, an example of selecting an improvement measure based on an actual evaluation by a customer will be described.

  First, the configuration of the improvement measure selection device according to the second embodiment will be described. In the following description, the same parts as those already described are denoted by the same reference numerals as those already described. In addition, overlapping description may be omitted. FIG. 7 is a block diagram illustrating the configuration of the improvement measure selection device according to the second embodiment. The improvement measure selection device 20 shown in FIG. 7 includes a display unit 11, an input unit 12, a communication unit 13, a medium reading unit 14, a control unit 15, and a storage unit 16.

  The programs stored in the storage unit 16 include an improvement measure selection program 267. The improvement measure selection program 267 provides a function for selecting a suitable improvement measure. The improvement measure selection program 267 includes a similarity calculation unit 267a, a candidate extraction unit 267b, and an improvement measure selection unit 267c.

  The similarity calculation unit 267a provides a function of calculating the similarity between a target gas turbine (equipment) for which an improvement plan is proposed and another gas turbine (equipment). The candidate extraction unit 267b provides a function of extracting an improvement measure highly evaluated by a customer from improvement measures already implemented in a gas turbine having a high degree of similarity with a target gas turbine for which an improvement plan is proposed. The improvement measure selection unit 267c provides a function of selecting an improvement measure to be proposed based on customer evaluation.

  Next, the processing procedure of the improvement measure selection process executed by the improvement measure selection device 20 will be described with reference to FIG. FIG. 8 is a flowchart showing the processing procedure of the improvement measure selection processing. The processing procedure shown in FIG. 8 is realized by the control unit 15 executing the improvement measure selection program 267. Prior to the execution of the improvement measure selection process, the evaluation conditions such as the proposed gas turbine and the implementation timing of the improvement measure are input to the improvement measure selection device 20 by the operation of the input unit 12 or the communication of the communication unit 13. .

  As shown in FIG. 8, the control unit 15 first selects one unselected gas turbine other than the designated gas turbine from the introduced gas turbines registered in the plant information 163 (step). S201). When the unselected gas turbine can be selected (step S202, Yes), the control unit 15 determines whether or not the selected gas turbine is identical to the designated gas turbine (step S203).

  The determination of the presence or absence of identity is performed to determine whether or not the same improvement measures can be implemented for those gas turbines. Even if the types of gas turbines are the same, if the parts such as the bypass valve, the combustion nozzle, and the combustion cylinder are different or the combustion system is different, the same improvement measures may not be applied. For this reason, in addition to the model registered in the plant information 163, the control unit 15 is identical when parts such as a bypass valve, a combustion nozzle, and a combustion cylinder are the same and the combustion method is the same. Judge that there is.

  When it determines with there being identity (step S204, Yes), the control part 15 calculates the similarity degree of the selected gas turbine and the designated gas turbine (step S205). The control unit 15 calculates the similarity based on the operation status of the gas turbine and the characteristics of the customer who has introduced the gas turbine.

  Specifically, the control unit 15 acquires values of items such as operating conditions, operating rate, fuel cost, power sale limit, and the like registered in the plant information 163 as information regarding the operation status of the gas turbine. In addition, the control unit 15 acquires values of items such as an approach to environmental problems, a business plan, an average operating rate, and the like registered in the customer information 162 as information on customer characteristics. And the control part 15 calculates the similarity of the selected gas turbine and the designated gas turbine based on the acquired information.

  The similarity may be calculated using a known method. For example, the control unit 15 may use a technique such as case database inference using the Eugrid distance. Further, the control unit 15 may use a collaborative filtering technique used for recommendation or the like.

  In this way, customers who are likely to have the same view as the customers who are making proposals by calculating the similarity based on the operation status of the gas turbine and the characteristics of the customers who have introduced the gas turbine It is possible to select improvement measures based on actual evaluation of

  When it determines with there being no identity (step S204, No), the control part 15 does not calculate a similarity degree (it determines with a similarity degree being the minimum). And the control part 15 repeats and performs step S201 to step S205 until the similarity with all the other gas turbines is calculated. The above steps S201 to S205 are realized by the functions provided by the similarity calculation unit 267a.

  When an unselected gas turbine cannot be selected, that is, when the similarity with all other gas turbines has been calculated (step S202, No), the control unit 15 is designated from among the other gas turbines. A gas turbine having a high degree of similarity with the gas turbine is selected (step S206). For example, the control unit 15 may select a gas turbine whose similarity is higher than a threshold value. The control unit 15 may select a predetermined number or a predetermined ratio of gas turbines in descending order of similarity.

  Subsequently, the control unit 15 acquires a set of combinations of improvement measure IDs and favorable responses of improvement measures that have been proposed for the selected gas turbine from the record information 164 (step S207). And the control part 15 excludes the thing containing improvement plan ID of the improvement plan already implemented with respect to the designated gas turbine from the acquired set of combinations (step S208). Furthermore, when the implementation time of the improvement measure is designated, the control unit 15 acquires information on the regular inspection scheduled for the designated gas turbine from the regular inspection schedule 165 and implements it during the regular inspection. A combination including an improvement measure ID of an impossible improvement measure is excluded from the set (step S209). The above steps S206 to S209 are realized by the functions provided by the candidate extraction unit 267b.

  Subsequently, the control unit 15 calculates a representative value of popularity for each improvement measure included in the set (step S210). For example, the control unit 15 sets the average value of the popularity calculated for each combination including the same improvement measure ID as a representative value of the popularity. The control unit 15 may use the maximum value, the minimum value, the median value, or the like of the popularity degree calculated for each combination including the same improvement measure ID as the representative value of the popularity degree.

  And the control part 15 selects the improvement measure which should be proposed based on the representative value of the calculated popularity (step S211). For example, the control unit 15 may select an improvement measure for which an improvement measure having a representative value of popularity higher than a threshold value should be proposed. In addition, the control unit 15 may select a predetermined number or a predetermined ratio of improvement measures to be proposed in order from the highest representative value of popularity. The above steps S210 to S211 are realized by the functions provided by the improvement measure selection unit 267c.

  As described above, in the second embodiment, the improvement measure is selected based on the actual evaluation of the customer who operates the plant in the same manner as the proposal destination. Therefore, it depends on the experience and knowledge of a specific individual. However, it is possible to select an improvement measure that can be expected to obtain a high evaluation from the proposed customer.

  In the above-described embodiment, the similarity of the gas turbine is calculated after determining that the gas turbine is identical. However, the identity of the gas turbine is determined without determining the identity of the gas turbine. The information used for the determination may be further used to calculate the similarity of the gas turbine. That is, the similarity may be calculated based on the characteristics (specifications) of the gas turbine itself, the operation status of the gas turbine, and the characteristics of the customer who has introduced the gas turbine. In this case, the improvement measure selection device 20 may separately determine whether or not the improvement measure can be applied to the proposed gas turbine.

  In the above embodiment, the improvement measure to be proposed is selected based on the representative value of the popularity. However, the improvement measure selection device 20 proposes based on whether or not the improvement measure is actually introduced. It is also possible to select improvement measures to be taken.

  Example 1 shows an example of selecting an improvement measure based on the evaluation value, and Example 2 shows an example of selecting an improvement measure based on the actual evaluation of the customer. It is good also as selecting improvement measures using together. In Example 3 below, an example in which an improvement measure is selected by using an evaluation value and an actual evaluation of a customer together will be described.

  First, the configuration of the improvement measure selection device according to the third embodiment will be described. FIG. 9 is a block diagram illustrating the configuration of the improvement measure selection device according to the third embodiment. The improvement measure selecting device 30 shown in FIG. 9 includes a display unit 11, an input unit 12, a communication unit 13, a medium reading unit 14, a control unit 15, and a storage unit 16.

  The programs stored in the storage unit 16 include an improvement measure selection program 367. The improvement measure selection program 367 provides a function for selecting a suitable improvement measure. The improvement measure selection program 367 includes a popularity calculation unit 367a, a candidate extraction unit 367b, an evaluation value calculation unit 367c, and an improvement measure selection unit 367d.

  The popularity calculation unit 367a provides a function of acquiring an actual evaluation of a customer regarding an improvement plan proposed for another gas turbine similar to a target gas turbine for which an improvement plan is proposed. The candidate extraction unit 367b provides a function of extracting an improvement measure applicable to the designated gas turbine from the improvement measures registered in the improvement measure information 161. The evaluation value calculation unit 367c provides a function of calculating an evaluation value for comprehensively evaluating each extracted improvement measure from a plurality of viewpoints in consideration of an actual evaluation of the customer. The improvement measure selection unit 367d provides a function of selecting an improvement measure to be proposed based on the calculated evaluation value.

  Next, the processing procedure of the improvement measure selection process executed by the improvement measure selection device 30 will be described with reference to FIGS. 10 and 11. FIG. 10 is a flowchart showing a processing procedure for improvement measure selection processing. FIG. 11 is a flowchart showing the processing procedure of the popularity calculation process. The processing procedure shown in FIGS. 10 and 11 is realized by the control unit 15 executing the improvement measure selection program 367. Prior to execution of the improvement measure selection process, the evaluation conditions such as the proposed gas turbine, the evaluation period of the evaluation value, the implementation timing of the improvement measure, etc. are selected by the operation of the input unit 12 or the communication of the communication unit 13. Input to the device 30.

  As shown in FIG. 10, the control unit 15 first executes a popularity calculation process based on the function provided by the popularity calculation unit 367a (step S301). Specifically, as shown in FIG. 11, the control unit 15 selects one unselected gas turbine other than the designated gas turbine from the introduced gas turbines registered in the plant information 163. (Step S401). When the unselected gas turbine can be selected (step S402, Yes), the control unit 15 determines whether or not the selected gas turbine is identical to the designated gas turbine (step S403).

  When it determines with there being identity (step S404, Yes), the control part 15 calculates the similarity degree of the selected gas turbine and the designated gas turbine (step S405). The method of calculating the similarity may be the same as in the second embodiment.

  When it determines with there being no identity (step S404, No), the control part 15 does not calculate a similarity degree (it determines with a similarity degree being the minimum). And the control part 15 repeatedly performs step S401 to step S405 until it calculates the similarity with all the other gas turbines.

  The improvement measure selecting device 30 may calculate the similarity of the gas turbine by further using the information used to determine the identity of the gas turbine without determining the identity of the gas turbine. That is, the similarity may be calculated based on the characteristics of the gas turbine itself, the operation status of the gas turbine, and the characteristics of the customer who has introduced the gas turbine.

  When an unselected gas turbine cannot be selected, that is, when the similarity with all other gas turbines has been calculated (step S402, No), the control unit 15 is designated from among the other gas turbines. A gas turbine having a high degree of similarity with the gas turbine is selected (step S406). For example, the control unit 15 may select a gas turbine whose similarity is higher than a threshold value. The control unit 15 may select a predetermined number or a predetermined ratio of gas turbines in descending order of similarity.

  Subsequently, the control unit 15 acquires a set of combinations of improvement measure IDs and popularity ratings of proposed improvement measures for the selected gas turbine from the performance information 164 (step S407). Then, the control unit 15 calculates a representative value of the popularity for each improvement measure included in the set (step S408). For example, the control unit 15 sets the average value of the popularity calculated for each combination including the same improvement measure ID as a representative value of the popularity. The control unit 15 may use the maximum value, the minimum value, the median value, or the like of the popularity degree calculated for each combination including the same improvement measure ID as the representative value of the popularity degree.

  When the popularity calculation process is thus completed, the control unit 15 extracts an improvement measure that can be implemented from the improvement measure information 161 as shown in FIG. 10 (step S302). The method of extracting improvement measures that can be implemented is the same as in the first embodiment. And the control part 15 excludes the improvement measure already implemented with respect to the designated gas turbine from the collection of the extracted improvement measures (step S303). Steps S302 and S303 described above are realized by the functions provided by the candidate extraction unit 367b.

  Subsequently, the control unit 15 determines a weighting coefficient for calculating the evaluation value (step S304). The method of determining the weighting factor is the same as in the first embodiment.

  Subsequently, the control unit 15 selects one unselected improvement measure from the extracted improvement measures (step S305). When an unselected improvement measure can be selected (step S306, Yes), the control unit 15 calculates an evaluation value of the selected improvement measure (step S307). For example, the above formula (1) or formula (6) is used to calculate the evaluation value.

  After calculating the evaluation value, the control unit 15 acquires the representative value of the popularity corresponding to the selected improvement measure from the processing result of the popularity calculation processing (step S308). When the representative value of the popularity corresponding to the selected improvement measure has been acquired (step S309, Yes), the control unit 15 corrects the evaluation value of the selected improvement measure with the representative value of the popularity (step S310). For example, the control unit 15 corrects the evaluation value by multiplying the evaluation value by a representative value of popularity.

  In this way, by correcting the evaluation value based on the actual evaluation obtained by proposing the same improvement measure to a plant with a high degree of similarity, the evaluation value is more suitable as an index for selecting the improvement measure. Can be a value. When the representative value of the popularity corresponding to the selected improvement measure cannot be acquired (No at Step S309), the evaluation value is not corrected.

  And the control part 15 repeatedly performs step S305 to step S310 until it determines the evaluation value of all the extracted improvement measures. Steps S305 to S310 described above are realized by the functions provided by the evaluation value calculation unit 367c.

  When the unselected improvement measures cannot be selected, that is, when the evaluation values of all the extracted improvement measures have been determined (No in step S306), the control unit 15 proposes based on the calculated evaluation values. An improvement measure to be selected is selected (step S311). For example, the control unit 15 may select an improvement measure whose improvement value is higher than a threshold value. Further, the control unit 15 may select a predetermined number or a predetermined ratio of improvement measures in order from the highest evaluation value as an improvement measure to be proposed. The above step S311 is realized by the function provided by the improvement measure selecting unit 367d.

  As described above, in the third embodiment, the improvement value is selected by using both the evaluation value and the customer's actual evaluation. Therefore, the proposal customer is not relied on based on the experience and knowledge of a specific individual. Therefore, improvement measures that can be expected to obtain high evaluation can be selected.

  In addition, the aspect of this invention shown by each said Example can be arbitrarily changed in the range which does not deviate from the summary of this invention. For example, each program shown in the above embodiment may be divided into a plurality of modules, or may be integrated with other programs. Further, in each of the above-described embodiments, an example in which the present invention is applied to selection of measures for improving a gas turbine has been described. However, the present invention improves various facilities such as steam turbines, processing machines, and printing machines, and industrial machines. It can be applied to the selection of measures.

10, 20, 30 Improvement measure selection device 11 Display unit 12 Input unit 13 Communication unit 14 Medium reading unit 15 Control unit 151 CPU
152 Memory 16 Storage unit 161 Improvement measure information 162 Customer information 163 Plant information 164 Performance information 165 Scheduled inspection schedule 166 Parameter information 167, 267, 367 Improvement measure selection programs 167a, 267b, 367b Candidate extraction units 167b, 367c Evaluation value calculation unit 167c 267c, 367d Improvement measure selection section
267a similarity calculation unit 367a popularity calculation unit

Claims (9)

Plant information in which information about the installed equipment is registered, and performance information in which information on the proposal results proposed to the customers who have installed the equipment to which the improvement measures are applied is applied to the equipment. And a storage unit for storing customer information including information on customer characteristics ,
A similarity calculation unit that calculates the similarity between the facility for which an improvement plan is proposed and the facility registered in the plant information;
Based on the similarity calculated by the similarity calculation unit, a candidate extraction unit that extracts an improvement plan proposed for the facility similar to the target facility for which an improvement plan is proposed from the performance information;
An improvement measure selection unit that selects an improvement measure to be proposed from the improvement plans extracted by the candidate extraction unit based on the information on the proposal result registered in the performance information, and
The improvement measure selection device, wherein the similarity calculation unit calculates the similarity of equipment based on the characteristics of the customer who has installed the equipment registered in the customer information . Information about the characteristics of the customer, the commitment to customer environmental problems, among business plans, or average occupancy rate, improvement selecting apparatus according to claim 1, characterized in that it comprises at least one. The similarity calculation unit, based on the equipment specifications of registered in the plant information, improvement selecting apparatus according to claim 1 or 2, characterized in that the similarity is calculated for equipment. The improvement measure according to any one of claims 1 to 3, wherein the similarity calculation unit calculates the similarity of equipment based on an operation status of the equipment registered in the plant information. Selection device. The similarity calculation unit determines, based on the specifications of the facility registered in the plant information, the identity of the facility to be proposed for improvement and the facility registered in the plant information, Of the facilities registered in the information, the similarity between the facility determined to be identical to the facility for which improvement measures are proposed and the facility for which improvement measures are proposed is calculated. The improvement measure selection device according to any one of claims 1 to 4 . The improvement measure selecting unit selects an improvement measure to be proposed based on an evaluation of an improvement measure by a customer who has received a proposal for an improvement measure, which is registered in the performance information as the proposal result. The improvement measure selection device according to any one of claims 1 to 5 . The improvement measure selecting unit selects an improvement measure to be proposed based on whether or not the customer who has received the proposal for the improvement measure adopts the improvement measure registered in the result information as the proposal result. The improvement measure selection device according to any one of claims 1 to 6 . An improvement measure selection method executed by an information processing apparatus,
Calculating the degree of similarity between the equipment for which an improvement plan is proposed and the equipment registered in the plant information in which information about the installed equipment is registered ;
Based on the calculated degree of similarity, propose improvement measures based on performance information that registers information related to the proposal results of improvement measures applied to equipment to customers who have installed the equipment to which the improvement measures are applied. Extracting proposed improvements for equipment similar to the equipment to be
Selecting an improvement measure to be proposed from the extracted improvement plans based on information on the proposal result registered in the performance information, and
In the step of calculating the degree of similarity , an improvement measure characterized in that the degree of similarity of the equipment is calculated based on the characteristics of the customer introducing the equipment registered in the customer information including information on the characteristics of the customer Selection method. In the information processing device,
Calculating the degree of similarity between the equipment for which an improvement plan is proposed and the equipment registered in the plant information in which information about the installed equipment is registered ;
Based on the calculated degree of similarity, propose improvement measures based on performance information that registers information related to the proposal results of improvement measures applied to equipment to customers who have installed the equipment to which the improvement measures are applied. Extracting proposed improvements for equipment similar to the equipment to be
Selecting an improvement measure to be proposed from the extracted improvement plans based on the information on the proposal result registered in the performance information, and
In the step of calculating the degree of similarity , an improvement measure characterized in that the degree of similarity of the equipment is calculated based on the characteristics of the customer introducing the equipment registered in the customer information including information on the characteristics of the customer Selection program.

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