TW202131267A - Energy management device, energy management method and recording medium thereof - Google Patents

Abstract

An energy management device (10) is provided with an index value calculation unit (23), a score calculation unit (24), and an information provision unit (25). The index value calculation unit (23) calculates at least one type of index value related to energy consumption of a diagnostic object including production equipment based on production-related information belonging to information about past production. The score calculation unit (24) calculates individual scores for the impact of each factor candidate on energy consumption that does not contribute to production based on the at least one type of index values ​​calculated by the index value calculation unit (23), wherein the factor candidates belong to candidates for factors of energy consumption that does not contribute to production. The information provision unit (25) outputs information of the factor candidates whose score calculated by the score calculation unit (24) ranks two or less from the top among all factor candidates.

Description

Energy management device, energy management method and recording medium

The present disclosure relates to an energy management device, an energy management method, and a recording medium for diagnosing factors of energy consumption (energy consumption) that do not contribute to production in a diagnostic object including production equipment.

In the past, the following technologies are known: specify factors of energy consumption in production equipment that are no longer helpful for production, and prompt users with information about the specified factors. For example, Patent Document 1 has disclosed the following technology: when a feature pattern has appeared, a message containing information on a factor of unnecessary energy consumption is output, and the feature pattern is used to display the cumulative production volume. Generated when unnecessary energy consumption occurs in graph data related to cumulative energy consumption. [Prior Technical Literature] [Patent Literature]

Patent Document 1: Japanese Patent Application Publication No. 2016-18242

[The problem to be solved by the invention]

However, the technique described in Patent Document 1 mentioned above narrows the energy consumption factor that no longer contributes to production to one. Therefore, if there are multiple factors of energy consumption that no longer contribute to production, it will be difficult. Properly implement countermeasures against energy consumption that does not contribute to production.

The present invention was developed in view of the above, and its purpose is to obtain an energy management device that can specify multiple factors that cause energy consumption that does not contribute to production. [Means to solve the problem]

In order to solve the above-mentioned problems and achieve the objective, the energy management device of the present disclosure includes an index value calculation unit, a score calculation unit, and an information provision unit. The index value calculation unit calculates more than one type of index value related to the energy consumption of the diagnostic object including the production equipment based on the production-related information belonging to the information about the past production. The score calculation unit is based on one or more types of index values calculated by the index value calculation unit to calculate the energy that is no longer helpful for the production of multiple factor candidates representing the candidates for the energy consumption factor that no longer contributes to production The impact score of the consumption. The information providing unit outputs the information of the two or more factor candidates whose scores are calculated by the score calculation unit among the plurality of factor candidates. [Efficacy of invention]

According to the present invention, the following effect is achieved: it is possible to specify multiple factors that generate energy consumption that does not contribute to production.

Hereinafter, the energy management device, the energy management method, and the recording medium of the implementation type will be described in detail based on the drawings. Furthermore, the disclosure is not limited by the implementation type.

[Embodiment 1] Fig. 1 is a diagram showing an example of the structure of a production facility including an energy management device of the first embodiment. As shown in Figure 1, the production facility 1 of the implementation type 1 is equipped with production equipment 2, related equipment 3, power sensors 4, 5, production volume sensors 6, environmental sensors 7, production management devices 8, and energy管理装置10。 Management device 10. Furthermore, although the energy used by the production equipment 2 and related equipment 3 in the following description is electricity, it may be primary energy such as petroleum, coal, gas, hydrogen, etc., or a combination of electricity and primary energy. .

The production equipment 2 executes the production process of producing a plurality of items. In the production facility 2, for example, although the production line is constituted by a plurality of production devices, the production facility 2 may have only one production device. The article produced by the production facility 2 is, for example, an industrial product or an unfinished product of an industrial product. In the following, there are cases where it is described as a production target product. Furthermore, the production target product may be liquid or gas.

Related equipment 3 refers to equipment used in connection with production equipment 2. For example, related equipment 3 refers to lighting devices, air conditioners, air compressors, dust collectors, etc. that are activated (On) by an operator when the production equipment 2 produces production objects. equipment. The related equipment 3 is also called utility equipment.

The power sensor 4 is installed on a transmission line or production equipment 2 that conducts power transmission to the production equipment 2. It regularly measures the power consumption of the production equipment 2 and transmits information indicating the measured power consumption through A dedicated line (not shown) or a network (not shown) is sent to the energy management device 10.

The power sensor 5 is installed on a power transmission line or related equipment 3 that conducts power transmission to the related equipment 3, and periodically measures the power consumption of the related equipment 3, and transmits information indicating the measured power consumption through The dedicated line not shown or the network not shown is sent to the energy management device 10. The amount of power consumption measured by the power sensor 4 is an example of the energy consumption of the production facility 2. The amount of power consumption measured by the power sensor 5 is an example of the energy consumption of the related equipment 3.

The production volume sensor 6 is installed in the production equipment 2 to periodically measure the production volume of the production equipment 2 and send the information indicating the measured production volume to the energy management via a dedicated line not shown or a network not shown The device 10 sends. The production volume sensor 6 counts, for example, the number of passes of the production target product on the production line of the production facility 2 and measures the counted value as the production volume. Furthermore, when the production target product is a liquid or a gas, the production volume measured by the production volume sensor 6 is the production flow rate. In addition, the production volume measured by the production volume sensor 6 can also be expressed in terms of weight or length.

The environment sensor 7 periodically measures the production environment belonging to the environment in the production process of the production equipment 2 and sends information indicating the measured production environment to the energy management device 10. The production environment measured by the environment sensor 7 is, for example, the temperature, humidity, carbon dioxide concentration, brightness, noise, or vibration in the room where the production equipment 2 is configured. Furthermore, the information representing the production environment can also be information that has been input to a terminal device not shown. In this case, the information representing the production environment is sent to the energy management device 10 via a non-illustrated terminal device via a non-illustrated dedicated line or a non-illustrated network.

The production management device 8 has a storage unit (not shown) that stores production management information. The production management information includes the type of the production target product, the person in charge of the production process, the error information of the production equipment 2, the lot number of the production target product, and the production interval time of the production equipment 2 ( tact time) and other information. The production interval time is, for example, the time obtained by dividing the operating time of the production equipment 2 in a day by the production volume of the day.

The processing unit (not shown) in the production management device 8 reads the production management information stored in the storage unit from the storage unit, and sends the read information to the energy management via a dedicated line (not shown) or a network (not shown) The device 10 sends. The production management device 8 can obtain part of the production management information from the production equipment 2 via a dedicated line not shown or a network not shown.

In addition, the production management device 8 can use an image sensor to indicate part of the production management information. In addition, the production management device 8 can also memorize information input from an input unit not shown as part of the production management information. The input unit can accept input by a keyboard or input by voice recognition, and output the accepted information to the production management device 8.

The energy management device 10 collects information from the power sensors 4 and 5, the production volume sensor 6, the environment sensor 7, and the production management device 8, and diagnoses the production equipment 2 and related equipment based on the collected information. The factor of energy consumption that is not conducive to production in the diagnosis target of 3. In the following, there are cases where energy consumption that does not contribute to the production of the diagnostic target is described as energy consumption or energy loss that does not contribute to production. Furthermore, the so-called energy consumption that does not contribute to production means that it also includes, for example, the energy consumption of heating required for the operation of the production facility 2 (the energy consumption of the production facility 2 at time T1 described later), etc., although there is The situation can also be regarded as indirectly contributing to production, but it will also become an energy loss and reduce energy consumption as much as possible.

Fig. 2 is a diagram showing an example of the configuration of the energy management device of the first embodiment. As shown in FIG. 2, the energy management device 10 includes a processing unit 11, a production-related information storage unit 12 and a display unit 13. The processing unit 11 includes an information collection unit 21, an information generation unit 22, an index value calculation unit 23, a score calculation unit 24, and an information provision unit 25.

The information collection unit 21 collects information from the power sensors 4 and 5, the production volume sensor 6, the environment sensor 7, and the production management device 8, and associates the time of collection with the collected information, and The production-related information added to the production-related information storage unit 12. The time of collection, for example, in addition to hour, minute, and second information, it also includes year, month, and day information. Production-related information refers to information about past production, and is the information collected by the information collection unit 21 and memorized in the production-related information storage unit 12.

The information collected by the information collecting unit 21 may also be any of information shown by analog signals and information shown by digital signals. When the collected information is an analog signal, the information collection unit 21 converts the collected information into a digital signal through AD (Analog to Digital) conversion. Furthermore, the information collection unit 21 may also perform effective value calculation or filter processing on the collected information, for example.

The information generating unit 22 generates factor candidate information based on the production-related information memorized in the production-related information storage unit 12, and the factor candidate information includes information of a plurality of factor candidates that are candidates for factors that cause energy loss. The factor candidate information system includes first factor candidate information and second factor candidate information.

The information generating unit 22 generates the first factor candidate information based on the calendar information held internally and the production-related information stored in the production-related information storage unit 12. FIG. 3 is a diagram showing an example of the first factor candidate information generated by the information generating unit of the energy management device of Embodiment 1. FIG.

As shown in Figure 3, the first factor candidate information includes "month", "week", "week", "production start time" and "production end time" for each "day", and "day" and "month" "," "week", "week", "production start time" and "production end time" are related to each other.

"Day" refers to the information of the year, month and day, "Month" refers to the information of the month, "Week" refers to the information of the week, and "Week" refers to the information of the week in which "Day" is "Month". The "production start time" is information indicating the time when the production of the production target product performed by the production equipment 2 starts. The "production end time" is information indicating the time when the production of the production target product performed by the production equipment 2 ends. In the example shown in Figure 3, "October 20, 2019" is expressed as the Sunday of the fourth week of October, and the production start time is 7 o'clock, and the production end time is 17:00.

The information generating unit 22 obtains the "month" of each "day" from the information of the month included in the "day". In addition, the information generating unit 22 determines the "week" and "week" of each "day" based on the internal calendar information, and includes the determined "week" and "week" in the first factor candidate information. In addition, the information generation unit 22 determines the daily "production start time" and "production end time" from the production-related information memorized in the production-related information storage unit 12, and calculates the determined "production start time" and "production end time" Time" is included in the candidate information for the first factor.

For example, the information generating unit 22 determines the time obtained by subtracting the time required to produce one production target product from the time when the power consumption of the production facility 2 becomes equal to or greater than the threshold value Pth set in advance, as the production start time. In addition, the information generating unit 22 determines, for example, the time when the production volume of the production facility 2 reaches the threshold value Mth that is set in advance as the production end time. Furthermore, the information generating unit 22 may also specify the "production start time" and "production end time" from the production related information when the production start time and the production end time are included in the production related information.

In addition, the candidate information for the first factor may include, for example, information on the production volume of the day and information on the production volume of the previous day. In this case, the information generating unit 22 calculates the total production volume of the day as the production volume of the day, and calculates the total production volume of the previous day as the production volume of the previous day. For example, "October 20, 2019" refers to the total production volume of "October 20, 2019", and "October 20, 2019" refers to the previous day's production volume information. Refers to the total production volume in "October 19, 2019".

In addition, the information generating unit 22 generates second factor candidate information from the production-related information stored in the production-related information storage unit 12. For example, when it has been assumed that the target model, the person in charge, and the error occurred are represented by numerical values, the second factor candidate information is the representative value of the target model, the person in charge, and each day where the error occurred. For example, the information generating unit 22 stores the most frequent values (most frequent values) of the target model, the person in charge, and the time-series information of the day contained in the production-related information of the production-related information storage unit 12, respectively. value), which is judged as the representative value of the target model, the person in charge, and the occurrence of the error. Furthermore, the target machine type indicates the type of the target production product, the person in charge indicates the person responsible for the production of the production equipment 2, and the occurrence of an error indicates the type of error generated in the production equipment 2.

FIG. 4 is a diagram showing an example of candidate information for the second factor determined by the information generating unit of the first embodiment. The second factor candidate information shown in Figure 4 includes the "target model", "person in charge" and "error occurred" on a "day" basis, and the "target model", "person in charge" and "error occurred" are mutually related. Establish an association relationship.

Figure 4 shows an example where the target model is at least "A1" or "A2", the person in charge is at least "B1" or "B2", and the error is at least "#1" or "#2". In the example shown in Figure 4, it is shown on October 20, 2019 that the target model was mainly produced by "A1", and the person in charge "B2" was mainly responsible for production. The most frequent error was "#2".

In addition, the second factor candidate information is, for example, information including the respective average values and fluctuation ranges of temperature, humidity, brightness, noise, and vibration in the room indicating the state of the production equipment 2 or the related equipment 3 in operation. For example, the information generating unit 22 calculates the respective average values and fluctuation ranges of the indoor temperature, humidity, brightness, noise, and vibration based on the environmental information contained in the production-related information stored in the production-related information storage unit 12 .

The index value calculation unit 23 calculates the value of more than one type of index related to the energy consumption of the diagnosis target including the production equipment 2 and the related equipment 3 based on the information memorized by the production-related information storage unit 12. Hereinafter, although the index value calculation unit 23 calculates the values of five types of indicators, the types of indicators whose values are calculated by the index value calculation unit 23 may be four or less, or six or more.

The index value calculation unit 23 calculates the respective values of the first index, the second index, the third index, the fourth index, and the fifth index based on the production-related information memorized in the production-related information storage unit 12. FIG. 5 is a diagram for explaining the first index, the second index, the third index, the fourth index, and the fifth index calculated by the index value calculation unit of the implementation pattern 1. FIG. Hereinafter, the value of the first index calculated by the index value calculation unit 23 is described as the first index value, and the value of the second index calculated by the index value calculation unit 23 is described as the second index value. The value of the third index calculated by the index value calculation unit 23 is described as the third index value. In addition, the value of the fourth index calculated by the index value calculation unit 23 is described as the fourth index value, and the value of the fifth index calculated by the index value calculation unit 23 is described as the fifth index value.

The first index value is the time T1 from the start of the production equipment 2 to the start of production of the production equipment 2. The index value calculation unit 23 calculates, for example, the difference between the time when the power consumption of the production facility 2 becomes equal to or greater than the threshold Pth set in advance, and the time when the production volume of the production facility 2 becomes equal to or greater than the threshold Mth set in advance. The index value calculation unit 23 can calculate the time obtained by subtracting the time required to produce one production target product in the production facility 2 from the calculated difference as the first index value. Such a first index can be said to be the unnecessary time after the start of the production equipment 2 until the start of production, and it can be said to be the time when energy consumption does not contribute to production.

The second index value refers to the time T2 after the end of the production of the production equipment 2 until the production equipment 2 is turned off (OFF). The index value calculation unit 23 can calculate, for example, the time when the production volume of the production facility 2 reaches the pre-set less than threshold Mth, and the time when the power consumption of the production facility 2 becomes the pre-set less than threshold Pth. Difference, and use the difference as the second index value. Such a second index can be said to be the unnecessary time after the end of production until the stop of the production equipment 2, and it can be said to be the time that does not contribute to the generation of energy consumption for production.

The third index value represents the time T3 that is the difference between the time T4 when the related equipment 3 is activated and the time T5 when the production equipment 2 is activated. Such a third index represents the time when the production equipment 2 is stopped but the related equipment 3 is started, which can be said to be useless time, and can be said to be time when energy consumption does not contribute to production.

The fourth index value represents the proportion of the time during which production by the production equipment 2 is performed during the time during which the production equipment 2 is active. The index value calculation unit 23 is, for example, the ratio of the time T6 when the production volume of the production facility 2 is equal to or greater than the preset threshold value Mth to the time T5 when the power consumption of the production facility 2 is equal to or greater than the preset threshold value Pth. . It can be said that the smaller the fourth index value is, the more time the production will stop needlessly during the time when the production equipment 2 is started. The more time the useless stop time becomes, the more energy consumption that does not contribute to production will increase.

The fifth index value indicates the power consumption per unit output. The power consumption per unit of output is, for example, obtained by dividing the power consumption in a day by the output in a day. The output is an arbitrary unit such as the number, weight, or length of the product to be produced.

The index value calculation unit 23 is based on the production volume information contained in the production-related information stored in the production-related information storage unit 12, and the production equipment 2 and related information contained in the production-related information stored in the production-related information storage unit 12 The information on the power consumption of the device 3 is used to calculate the fifth index value.

Specifically, the index value calculation unit 23 calculates the total daily production volume based on the production volume information included in the production-related information. In addition, the index value calculation unit 23 calculates the power consumption of the production equipment 2 and the power consumption of the related equipment 3 on a daily basis based on the information on the power consumption of the production equipment 2 and the related equipment 3 included in the production-related information The total power consumption after addition. The index value calculation unit 23 calculates the fifth index value by dividing the total power consumption by the total production volume on a daily basis. It can be said that the larger the value of the fifth index becomes, the more unnecessary energy consumption that does not contribute to production will increase.

Furthermore, the index value calculation unit 23 may also calculate index values of types other than the above-mentioned indexes. For example, the index value calculation unit 23 may calculate the total power consumption per day, the total production per day, or the power consumption during rest periods, etc., as the index value. In addition, the index value calculation unit 23 may integrate the above-mentioned plural types of index values as one index value and calculate it. In this case, the index value calculation unit 23 calculates, for example, a value obtained by weighting and adding each index value in accordance with the degree of importance as one index value.

FIG. 6 is a diagram showing an example of plural types of index values calculated by the index value calculation unit of the implementation pattern 1. FIG. In the example shown in FIG. 6, the first index value, the second index value, the third index value, the fourth index value, and the fifth index value are calculated on a daily basis. For example, in "October 20, 2019", the first index value is "15", the second index value is "14", the third index value is "213", the fourth index value is "31", and the The five index value is "0.37".

The score calculation unit 24 calculates a score showing the degree of influence of each of the plurality of factor candidates on the energy loss based on the daily index value calculated by the index value calculation unit 23 for each index. The score calculation unit 24 generates integrated information in which multiple types of index values and multiple factor candidates are associated with each other. FIG. 7 is a diagram showing an example of integrated information of implementation type 1. The integrated information shown in Fig. 7 is information in which the first index value is associated with a plurality of factor candidates, and the first index value is set as the target variable, and includes the first factor candidate information and the second factor candidate information. The information of multiple factor candidates is set as explanatory variables.

Although not shown in FIG. 7, in the integrated information, the information of factor candidates such as the respective average values and fluctuation ranges of indoor temperature, humidity, brightness, noise and vibration is also set as explanatory variables. In addition, the score calculation unit 24 also generates the same integrated information as the integrated information shown in FIG. 7 for the second index value, the third index value, the fourth index value, and the fifth index value, respectively.

The score calculation unit 24 uses data mining using the above-mentioned integrated information to calculate each of the first index, the second index, the third index, the fourth index, and the fifth index. The score for the impact of energy loss. The higher the score of the factor candidate, the greater the impact on energy loss.

The analytical methods used in data exploration are, for example, regression analysis, clustering analysis, or frequent pattern extraction. Hereinafter, although the score calculation unit 24 is described as an example in which the score is calculated by regression analysis, the score calculation unit 24 may also perform data exploration using analytical methods other than multiple regression analysis.

The score calculation unit 24 performs pre-processing on the factor candidates and determines the value of each explanatory variable. The score calculation unit 24 performs type pre-processing corresponding to the factor candidates. The types of pre-processing performed on the factor candidates are the first pre-processing and the second pre-processing. First, the first pre-processing will be described.

The first pre-processing is processing for factor candidates that cannot be displayed as a quantity. Candidates for factors that cannot be displayed as quantities are, for example, "month", "week", "week", "production start time", "production end time", "target model", "person in charge", or "error occurred", etc.

When the factor candidate is "week", the score calculation unit 24 expresses "week" with seven types of explanatory variables. Specifically, the score calculation unit 24 sets the seven types of explanatory variables of "1" to indicate the week when the week corresponds to the seven types of weeks from Sunday to Monday. The score calculation unit 24, for example, when "week" is "Sunday", sets the value of the explanatory variable corresponding to Sunday among the seven types of explanatory variables to "1", and sets the values of other explanatory variables to "0". In addition, when the "week" is "Monday", the score calculation unit 24 sets the value of the explanatory variable corresponding to Monday among the seven types of explanatory variables to "1", and sets the values of other explanatory variables Set to "0".

In addition, the score calculation unit 24 expresses the "person in charge" with explanation variables of the same number as the number of persons in charge. For example, when the number of persons in charge is 4, the score calculation unit 24 expresses the "person in charge" with four types of explanatory variables. In addition, the score calculation unit 24 expresses the "target model" with descriptive variables of the same number as the target model. For example, the score calculation unit 24 expresses the "target model" with descriptive variables of the five types when the target model is five types. In addition, the score calculation unit 24 expresses "an error has occurred" with the same number of descriptive variables as the type in which the error has occurred. For example, the score calculation unit 24 expresses "an error has occurred" with 10 types of explanatory variables when there are 10 types of errors.

Next, the second processing will be described. The second process is a process performed on the factor candidates that can be displayed as a quantity, and through the second process, the factor candidates that can be displayed as a quantity are represented by an explanatory variable. Candidates for factors that can be displayed by quantity, such as "average temperature", "variation range of temperature", "average humidity", "variation range of humidity", "average value of carbon dioxide", "variation range of carbon dioxide" ", "Average of brightness" and "Range of variation of brightness", etc.

The score calculation unit 24 performs a process of adjusting each explanatory variable so that the average becomes 0 and the dispersion becomes 1 as the second pre-processing. Specifically, in the second process, the score calculation unit 24 calculates the average value of the factor candidates for each factor candidate, subtracts the average value of the factor candidates from the value of the daily factor candidates, and divides the result of the subtraction by the standard The deviation is used to calculate the value of the explanatory variable. When the score calculation unit 24 calculates the score of the factor candidate relative to the index that the greater the energy loss, the smaller the value becomes, and reverses the positive and negative values of the explanatory variable calculated by the above-mentioned method. The index value becomes the fourth index value as the energy loss becomes smaller as the value becomes larger.

The score calculation unit 24 performs multiple regression analysis using the following formula (1) for each index. In the following formula (1), "n" is the total number of explanatory variables mentioned above, "y" is the index value, and "x ₁ ", "x ₂ ", "x ₃ ",..., "x _n "are explanatory The value of the variable, "a ₁ ", "a ₂ ", "a ₃ ", ..., "a _n "are the coefficients. y = a ₁ × x ₁ + a ₂ × x ₂ + a ₃ × x ₃ + …a _n × x _n …(1)

The score calculation unit 24 substitutes the values of multiple explanatory variables set with integrated data into "x ₁ ", "x ₂ ", "x ₃ ", ..., "x _n " for each indicator on a daily basis, and calculates The difference between the value of "y" obtained by formula (1) and the value of the target variable set by integrated information. Score calculating unit 24, for example, an average value for each index value of the difference or the sum of the calculated becomes minimum for "a _1", "a _2", "a _3", ..., optimizing "a _n" of.

The score calculation unit 24 calculates the absolute value of each coefficient for each index as the score of the factor candidate. For example, when "x ₁ "is the explanatory variable corresponding to Sunday, the score for Sunday is "a ₁ ". Also, when "x ₂ "is an explanatory variable corresponding to Monday, the score for Monday is "a ₂ ". The absolute value of the coefficient with respect to the factor candidate that can be displayed as a quantity becomes the score. For example, when "x ₃ "is an explanatory variable relative to the average value of temperature, the score of the average value of temperature is the absolute value _{of "a 3 ".}

In the above-mentioned example, although the score calculation unit 24 generates integrated information, as long as data mining can be performed for each index, the integrated information may not be generated. For example, when the score calculation unit 24 calculates the score of each factor candidate by multiple regression analysis, it only needs to use the index value as the value of the target variable based on the information obtained from the information generation unit 22 and the index value calculation unit 23 The value of each factor candidate may be used as the value of the explanatory variable, and it is not limited to the above example.

The information providing unit 25 shown in FIG. 2 outputs information for each index whose score calculated by the score calculating unit 24 is the top two or more factor candidates. For example, the information providing unit 25 arranges multiple factor candidates in the order of the higher score calculated by the score calculation unit 24 and generates ranking information representing the multiple factor candidates in the form of a ranking table, and outputs all factors. Information on at least the top two factor candidates among the generated ranking information. The information providing unit 25 includes: a ranking information generating unit 41 that generates the above-mentioned ranking information; and a display processing unit 42 that includes loss factor information including at least a part of the ranking information generated by the ranking information generating unit 41 Displayed on the display section 13.

The display processing unit 42 displays, for example, information including the number of factor candidates set in advance in the order of higher scores among the ranking information on the display unit 13 in the form of a ranking table. In addition, the display processing unit 42 may also display loss factor information on the display unit 13. The loss factor information is information obtained by displaying factor candidates whose scores are higher than a value set in advance among the ranking information in the form of a ranking table. In addition, the display processing unit 42 can also display all of the ranking information on the display unit 13 in the form of a ranking table. Furthermore, the display processing unit 42 can display the loss factor information on the display unit 13 in a form other than the form of a ranking table.

FIG. 8 is a diagram showing an example of loss factor information displayed on the display unit by the information providing unit of Embodiment 1. FIG. The loss factor information shown in Fig. 8 contains the categories and contents of the top five factor candidates for the first index as the estimated factor of energy loss.

In the example shown in Figure 8, the first indicator shows that the score of the week "Monday" is the highest, and the score is based on the target model "A", the week "fourth week", the month "March" and the production end time "17" Time” becomes lower in the order.

In this way, the energy management device 10 can use the index related to the energy consumption of the diagnosis target to calculate the score showing the degree of influence of each of the plurality of factor candidates on the energy loss, thereby indicating the plurality of factors that have a higher degree of influence on the energy loss. factor. In addition, the energy management device 10 can present to the user information in the form of a ranking table in which a plurality of factor candidates are arranged in the order of the degree of influence on the energy loss. For this reason, the user can grasp items that have a high degree of influence on energy loss, and can use the diagnosis results of the energy management device 10 to review the improvement activities of energy loss.

In the above example, although the score calculation unit 24 calculates the score of each factor candidate for each index, it may calculate a total score for each factor candidate, and the total score is a value obtained by adding up the scores of a plurality of indicators. In this case, the ranking information generating unit 41 arranges a plurality of factor candidates in the order of the larger total score calculated by the score calculating unit 24 and generates ranking information representing the plurality of factor candidates in the form of a ranking table.

In the above example, although the score calculation unit 24 calculates the scores of a plurality of factor candidates for a plurality of indicators, it is also possible to aggregate the plurality of indicators as an integrated index, and calculate the number of factor candidates for the integrated index. Score. For example, the score calculation unit 24 may multiply the first index value, the second index value, the third index value, the fourth index value, and the fifth index value by the corresponding coefficients or sum them, and calculate them on a daily basis. The total value of the multiplication result or the total value of the total result is used as the value of the integration index. Then, the score calculation unit 24 can calculate the respective scores of the plurality of factor candidates for the integration index through data mining from the values of the integration index and the values of the plurality of factor candidates.

Next, the processing performed by the processing unit 11 of the energy management device 10 will be explained using a flowchart. FIG. 9 is a flowchart showing an example of processing performed by the processing unit of the energy management device of Embodiment 1.

As shown in FIG. 9, the processing unit 11 of the energy management device 10 determines whether or not it is the information collection sequence (step S10). In step S10, the processing unit 11 determines when the information sent from the power sensor 4, the power sensor 5, the production volume sensor 6, the environment sensor 7 or the production management device 8 is received To become the information gathering sequence. In addition, the processing unit 11 may determine that it is the information collection sequence when it is the sequence that comes in the period set in advance.

When the processing unit 11 determines that it is the information collection sequence (step S10: Yes), it updates the production-related information (step S11). In step S11, the processing unit 11 adds the information sent from the power sensor 4, the power sensor 5, the production volume sensor 6, the environment sensor 7 or the production management device 8 to the production-related memory. The production-related information of the information storage unit 12 is used to update the production-related information.

In addition, when the information collection timing is a timing that arrives at the period set in advance, the processing unit 11 will perform a response to the power sensor 4, the power sensor 5, the production volume sensor 6, and the environment sensor in step S11. The measuring device 7 and the production management device 8 request information to be sent. In this case, the processing unit 11 receives the information sent from the power sensor 4, the power sensor 5, the production volume sensor 6, the environment sensor 7, and the production management device 8 as needed. The processing unit 11 adds the received information to the production-related information stored in the production-related information storage unit 12, thereby updating the production-related information.

When the processing of step S11 has ended, or when it is determined that the information collection sequence has not been reached (step S10: No), the processing unit 11 determines whether it has reached the diagnosis start sequence (step S12). In step S12, the processing unit 11 determines that it is the diagnosis start sequence when there is a diagnosis request from the user, for example.

When the processing unit 11 determines that it is the diagnosis start sequence (step S12: Yes), it acquires production-related information from the production-related information storage unit 12 (step S13). Then, the processing unit 11 generates factor candidate information based on the production-related information and calendar information obtained in step S13 (step S14). In addition, the processing unit 11 calculates a daily index value for each index based on the production-related information obtained in step S13 (step S15).

Next, the processing unit 11 calculates the score of each factor candidate for each index based on the factor candidate information generated in step S14 and the index value generated in step S15 (step S16). The processing unit 11 generates ranking information in which a plurality of factor candidates are arranged in the order of higher scores for each index based on the score of each factor candidate calculated in step S16 (step S17). Then, the processing unit 11 displays at least a part of the ranking information of each index on the display unit 13 (step S18). In step S18, the processing unit 11, for example, displays the information of the top two or more factor candidates among the ranking information of each index on the display unit 13 in the form of a ranking table.

The processing unit 11 ends the processing shown in FIG. 9 when the processing of step S18 has ended, or when it is determined that the diagnosis start sequence has not been reached (step S12: No).

FIG. 10 is a diagram showing an example of the hardware configuration of the processing unit of the energy management device of Embodiment 1. FIG. As shown in FIG. 10, the processing unit 11 of the energy management device 10 includes a computer, and the computer includes a processor 101, a memory 102 and an input/output interface 103. The input/output interface 103 includes a communication unit that performs information transmission and reception with the power sensors 4 and 5, the production volume sensor 6, the environment sensor 7, and the production management device 8.

The processor 101, the memory 102, and the input/output interface 103 can exchange data with each other through a bus 104, for example. A part of the information collection unit 21 of the processing unit 11 and a part of the display processing unit 42 of the processing unit 11 are implemented by the input/output interface 103, respectively. The processor 101 reads and executes the program stored in the memory 102, thereby executing the functions of the information collecting unit 21, the information generating unit 22, the index value calculating unit 23, the score calculating unit 24, and the information providing unit 25. The processor 101, for example, is an example of a processing circuit, including one of a CPU (Central Processing Unit), a DSP (Digital Signal Processor), and an LSI (Large Scale Integration) above.

The memory 102 includes RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), and can be erased Programmable Read Only Memory) and EEPROM (registered trademark) (Electrically Erasable Programmable Read Only Memory). In addition, the memory 102 includes a recording medium in which a computer-readable program is recorded. The recording medium includes non-volatile or volatile semiconductor memory, magnetic disks, flexible memory, optical discs, compact disks, and DVDs (Digital Versatile Discs). More than one of them. Furthermore, the energy management device 10 may also include integrated circuits such as ASIC (Application Specific Integrated Circuit) and FPGA (Field Programmable Gate Array).

As described above, the energy management device 10 of the first embodiment includes the index value calculation unit 23, the score calculation unit 24, and the information provision unit 25. The index value calculation unit 23 calculates more than one type of index value related to the energy consumption of the diagnostic target including the production equipment 2 based on production-related information belonging to information about past production. The score calculation unit 24 is based on one or more types of index values calculated by the index value calculation unit 23 to calculate a plurality of factor candidates that are candidates for energy consumption factors that do not contribute to the production of the diagnostic target. Each of the plurality of factor candidates does not help The score of the impact of the energy consumption of the production. The information providing unit 25 outputs the information of the two or more factor candidates whose scores calculated by the score calculating unit 24 are the top two or more factor candidates among the plurality of factor candidates. In this way, the energy management device 10 can calculate the scores representing the degree of influence of each of the plurality of factor candidates on the energy consumption that does not contribute to production, and specify the plurality of factors that have a higher degree of influence on the energy consumption that does not contribute to production. factor. In addition, the energy management device 10 can specify the energy consumption factors that do not contribute to production by manually establishing a correspondence between the energy consumption factors that do not contribute to production and the characteristic patterns in advance, for example.

In addition, the relevant equipment 3 used in connection with the production equipment 2 is included in the diagnosis target. The production-related information includes: information indicating the energy consumption of the production equipment 2; information indicating the energy consumption of the related equipment 3; and information indicating the production volume of the production equipment 2. The index value calculation unit 23 calculates more than one type of index value based on the information indicating the energy consumption of the production equipment 2, the information indicating the energy consumption of the related equipment 3, and the information indicating the production volume of the production equipment 2. In this way, since the energy management device 10 also treats the energy consumption of the related equipment 3 as a factor of energy consumption that does not contribute to production, for example, it can provide users with benefits that contribute to the overall energy consumption of the production facility 1 Information on the energy consumption of production for improvement activities.

In addition, the index value calculated by the index value calculation unit 23 includes at least one of the first index value, the second index value, the third index value, the fourth index value, and the fifth index value. The first index value indicates the time after the production facility 2 becomes active until the production of the production facility 2 starts. The second index value indicates the time after the end of production by the production equipment 2 until the production equipment 2 becomes out of service. The third index value represents the difference between the time when the related equipment 3 is activated and the time when the production equipment 2 is activated. The fourth index value indicates the proportion of the time during which production by the production equipment 2 is performed among the time during which the production equipment 2 is activated. The fifth index value represents the energy consumption of the diagnostic object per unit output caused by the production equipment 2. In this way, the energy management device 10 can provide the user with information useful for improvement activities of energy consumption that does not contribute to production, from the standpoint of being easy to grasp.

Furthermore, the energy management device 10 includes an information generating unit 22 that generates information of a plurality of factor candidates based on production-related information. The score calculation unit 24 is based on the index value of the plural types calculated by the index value calculation unit 23 and the information of the multiple factor candidates generated by the information generation unit 22 to calculate the energy that indicates that each of the multiple factor candidates does not contribute to production. The impact score of the consumption. In this way, since the energy management device 10 generates information of multiple factor candidates for production-related information, it can greatly reduce the burden on the user compared to the case where the information of multiple factor candidates is manually input.

Furthermore, multiple factor candidate systems include the week, week, and month of the day when the item was produced by production facility 2, the person in charge of production, the type of item generated by production facility 2, the error that occurred in production facility 2, and production facility 2. More than two in the environment. In this way, the energy management device 10 can specify multiple factors that have a high degree of influence on energy consumption that does not contribute to production from the viewpoint of time, people, production targets, production equipment 2 or the environment. .

Furthermore, the score calculation unit 24 calculates the scores of each of the plurality of factor candidates for the index values of the plural types, respectively. The information providing unit 25 outputs information of the factor candidates whose scores calculated by the score calculating unit 24 are the top two or more factor candidates among a plurality of factor candidates for index values of plural types. In this way, since the energy management device 10 uses a plurality of indicators, it is possible to provide the user with information useful for improvement activities of energy consumption that does not contribute to production for the plurality of viewpoints.

Furthermore, the information providing unit 25 outputs ranking information representing the number of factor candidates set in advance in the form of a ranking table in order from the factor candidate with the larger score among the plurality of factor candidates. In this way, the energy management device 10 can provide users with information on multiple factors that have a high degree of influence on energy consumption that does not contribute to production in the form of a ranking table.

[Implementation Type 2] The difference from the energy management device 10 of the implementation type 1 is that the energy management device of the implementation type 2 is based on the contribution of a plurality of factor candidates to the improvement activities of the energy consumption that does not contribute to production. Correct the score. Hereinafter, constituent elements having the same functions as those of the first embodiment are given the same reference numerals, and the description is omitted, and the description will be centered on the differences from the energy management device 10 of the first embodiment.

FIG. 11 is a diagram showing an example of the configuration of the energy management device of the second embodiment. As shown in FIG. 11, the difference from the energy management device 10 of the first embodiment is that the energy management device 10A of the second embodiment includes an input unit 14 and a contribution information storage unit 15, and a processing unit 11A instead of处理部11。 Processing section 11. The input unit 14 is, for example, an input device such as a keyboard, a mouse, or a touch panel of a mobile terminal.

The processing unit 11A includes a contribution degree estimation unit 26. Furthermore, the processing unit 11A is provided with an information providing unit 25A instead of the information providing unit 25. The contribution degree estimation unit 26 estimates the contribution rate of each of the plurality of factor candidates to the improvement activity of the user to the energy consumption that does not contribute to production based on the information input by the input unit 14. The contribution degree estimation unit 26 memorizes in the contribution degree information storage unit 15 information indicating the respective contribution degrees of the estimated plural factor candidates.

The information providing unit 25A includes a ranking information generating unit 41A and a display processing unit 42A. The ranking information generating unit 41A corrects the scores of the factor candidates corresponding to the plurality of factor candidates based on the respective contributions of the plurality of factor candidates estimated by the contribution degree estimating portion 26 and memorized in the contribution degree information storage unit 15. The ranking information generating unit 41A generates ranking information based on the corrected score.

The display processing unit 42A displays on the display unit 13 loss factor information including an input box for inputting the user's evaluation, in addition to the types and contents of the plurality of top estimated factors. FIG. 12 is a diagram showing an example of loss factor information displayed on the display part by the information providing part of the second embodiment.

In addition to the content of the loss factor information shown in FIG. 8, the loss factor information shown in FIG. 12 also includes an input box useful for inputting the user's evaluation of each of the plurality of factor candidates. Specifically, the factor information includes a first input box corresponding to "useful" and a second input box corresponding to "useless" for each of a plurality of factor candidates. The user inputs a check mark in the first input box corresponding to the factor candidate deemed useful, and inputs the check mark in the second input box corresponding to the factor candidate deemed useless. The check mark is performed by, for example, a click operation of a mouse or a touch operation on the touch panel.

The contribution degree estimation unit 26 estimates the contribution degree of each factor candidate to the user's energy consumption activities that do not contribute to production based on the input history of the first input box or the second input box opposite to each factor candidate. For example, the contribution degree estimation part 26 estimates the contribution degree of each factor candidate to the user's energy consumption activity which does not contribute to production by using the following formula (2). In the following equation (2), "Z" is the contribution to the activity that brings users to energy consumption that does not contribute to production, "α" is a coefficient greater than 1, and "β" is a coefficient less than 1. In addition, in the following formula (2), "N" is the number of times the user has entered the check mark in the first input box in the past, and "M" is the number of times the user has entered the check box in the second input box in the past . Z = α ^N × β ^M …(2)

The greater the contribution Z, the higher the usefulness of the improvement activities for energy consumption that is not conducive to production relative to the user. Furthermore, the contribution degree estimating unit 26 may replace the calculation of the contribution degree by the above-mentioned formula (2), and estimate the user's contribution degree to each factor candidate by machine learning.

The input method of the evaluation by the user is not limited to the first input box and the second input box. For example, it may also be a method of selecting one of "useful" and "useless" on the selection box to input. In addition, the evaluation system performed by the user is not limited to the two types of "useful" and "useless", and can also be selected and input from more than three levels of information. Furthermore, it is also possible to input a numerical value indicating the degree of usefulness based on the evaluation performed by the user.

The ranking information generating unit 41A obtains from the contribution information storage unit 15 the information representing the contribution of each of the plurality of factor candidates estimated by the contribution estimation unit 26. The ranking information generation unit 41A multiplies the respective scores of the plurality of factor candidates calculated by the score calculation unit 24 by the contribution degree of the corresponding factor candidate among the contribution degrees of the plurality of factor candidates, thereby correcting the plurality of factors The scores of the alternates.

For example, suppose that the factor candidate is "Monday", the score of "Monday" is "0.2", and the contribution degree of "Monday" is "3". In this case, the ranking information generating unit 41A corrects the score of "Monday" from "0.2" to "0.6" by multiplying "0.2" by "3". The revised score can also be said to be a value obtained by quantifying the usefulness of the user's improvement activities on energy consumption that does not contribute to production.

The ranking information generating unit 41A arranges a plurality of factor candidates in the order of higher scores after correction as described above, and generates ranking information representing the plurality of factor candidates in a ranking format. The display processing unit 42A displays loss factor information on the display unit 13. The loss factor information includes at least a part of the ranking information generated by the ranking information generating unit 41A, as well as the above-mentioned first input box and second input Information about the box. For example, the ranking information generating unit 41A causes the loss factor information shown in FIG. 12 to be displayed on the display unit 13.

Furthermore, as described above, the score calculation unit 24 may also calculate the respective scores of a plurality of factor candidates for the integrated index. In this case, the score calculation unit 24 multiplies the respective scores of the plurality of factor candidates by the contribution degree of the corresponding factor candidate among the contribution degrees of the plurality of factor candidates for the integration index, thereby correcting the plurality of factor candidates Their respective scores. The ranking information generating unit 41A generates ranking information based on the respective scores of a plurality of factor candidates after corrections related to the integration index.

In this way, the energy management device 10A, like the energy management device 10, can specify multiple factors that have a high degree of influence on energy consumption that does not contribute to production. Furthermore, the energy management device 10A can provide the user with priority, for example, factor candidates that give the user a high degree of contribution to the improvement activity of energy consumption that does not contribute to production. In this way, the user can grasp the factors that have a higher effect on the improvement activities of energy consumption that do not contribute to production by the user, and use them to review the improvement activities of energy consumption that do not contribute to production.

Next, the processing performed by the processing unit 11A of the energy management device 10A will be explained using a flowchart. FIG. 13 is a flowchart showing an example of processing performed by the processing unit of the energy management device of Embodiment 2. Since the processing from step S20 to step S22 shown in FIG. 13 is the same as the processing from step S10 to step S12 shown in FIG. 9, the description is omitted.

As shown in FIG. 13, the processing unit 11A of the energy management device 10A, when it is determined that the diagnosis start sequence is reached (step S22: Yes), performs the diagnosis process (step S23). The processing of step S23 refers to the processing of step S30 to step S36 shown in FIG. 14, and will be described in detail later.

The processing unit 11A determines whether there is a user's input when the processing of step S23 is completed or when it is determined that the diagnosis start sequence has not been reached (step S22: No) (step S24). In step S24, the processing unit 11A, for example, determines that a check mark has been input to the first input box corresponding to "useful" or the second input box corresponding to "useless" shown in FIG. 12 There is user input.

When the processing unit 11A determines that there is an input from the user (step S24: Yes), based on the input history of the user, it calculates the comparison with the improvement activity of the user's energy loss that is not contributing to the energy consumption of production. The contribution degree of each factor candidate of (step S25). Then, the processing unit 11A stores the information indicating the calculated contribution degree of each factor candidate in the contribution degree information storage unit 15 (step S26).

The processing unit 11A ends the processing shown in FIG. 13 when the processing of step S26 has ended, or when it is determined that there is no user input (step S24: No).

FIG. 14 is a flowchart showing an example of the diagnosis process performed by the processing unit of the energy management device of Embodiment 2. Since the processing from step S30 to step S33 shown in FIG. 14 is the same as the processing from step S13 to step S16 shown in FIG. 9, the description is omitted.

When the processing from step S30 to step S33 ends, the processing unit 11A corrects each of the scores of a plurality of factor candidates based on the contribution degree of the corresponding factor candidate (step S34). Then, the processing unit 11A generates ranking information for each index based on the corrected score for each index (step S35). In step S35, the processing unit 11A generates ranking information in which a plurality of factor candidates are arranged in the order of higher scores for each index based on the scores of each factor candidate corrected in step S34.

In step S35, the processing unit 11A generates ranking information in which a plurality of factor candidates are arranged in the order of the higher the corrected scores based on the scores of each factor candidate modified in step S34. Then, the processing unit 11A displays at least a part of the ranking information generated in step S35 on the display unit 13 (step S36), and ends the processing shown in FIG. 14.

An example of the hardware configuration of the processing unit 11A of the energy management device 10A of the second embodiment is the same as the hardware configuration of the processing unit 11 of the energy management device 10 shown in FIG. 10. The processor 101 reads and executes the program stored in the memory 102, thereby executing the information collecting unit 21, the information generating unit 22, the index value calculating unit 23, the score calculating unit 24, the information providing unit 25A, and the contribution degree estimating unit 26 functions.

As described above, the energy management device 10A of the second embodiment includes the contribution degree estimation unit 26. The contribution degree estimation unit 26 estimates the contribution degree of each of the plurality of factor candidates to the improvement activity of the energy consumption that does not contribute to the production of the user. The information providing unit 25A corrects the scores of the corresponding factor candidates among the plurality of factor candidates based on the respective contribution degrees of the plurality of factor candidates that have been estimated by the contribution degree estimating portion 26, and based on the corrected scores To generate ranking information. Thereby, the energy management device 10A can provide the user with priority, for example, with factor candidates that give the user a high degree of contribution to the improvement activity of energy consumption that does not contribute to production. For this reason, the user can grasp the factors that have a high effect on the improvement activities of the energy consumption that does not contribute to the production by the user, and can be used in the review of the improvement activities of the energy consumption that does not contribute to the production.

Although the processing units 11 and 11A of the energy management devices 10 and 10A specify index values and factor candidates in daily units, they can also specify index values and factor candidates in time zone units, weekly units, or monthly units. In addition, the processing units 11 and 11A may calculate the score of each factor candidate using indexes other than the above-mentioned indexes, or may calculate the score of each factor candidate using only a part of the indexes of the above-mentioned plural indexes. Furthermore, the processing units 11 and 11A may calculate the scores of factor candidates other than the aforementioned factor candidates, or may calculate only the scores of some factor candidates among the aforementioned plural factor candidates.

Furthermore, the energy management devices 10 and 10A may also be composed of a plurality of devices arranged at different positions. For example, the energy management devices 10 and 10A may also have a configuration including a collection device and a processing device. The collection device collects information from the power sensors 4 and 5, the production volume sensor 6, the environment sensor 7, and the production management device 8. The processing device outputs at least a part of the ranking information according to the information collected by the collecting device. In this case, the collection device can also be constituted by a PLC (Programmable Logic Controller) or a data logger, for example, and the processing device can also be constituted by a cloud server, for example. Or constituted by mobile terminals. The collection device and the processing device can communicate with each other by wireless or wired connection.

The configuration shown in the above embodiment is an example, which can be combined with other well-known technologies, can also be combined with each other, and part of the configuration can be omitted or changed without departing from the gist.

1: Production facilities 2: Production equipment 3: Related equipment 4,5: Power sensor 6: Production volume sensor 7: Environmental sensor 8: Production management device 10, 10A: Energy management device 11, 11A: Processing Department 12: Production-related information memory department 13: Display 14: Input section 15: Contribution Information and Memory Department 21: Information Collection Department 22: Information Generation Department 23: Indicator value calculation section 24: Score calculation department 25, 25A: Information Provision Department 26: Contribution Estimation Department 41, 41A: Ranking Information Generation Department 42,42A: Display processing section 101: processor 102: memory 103: Input and output interface 104: bus

Fig. 1 is a diagram showing an example of the structure of a production facility including an energy management device of the first embodiment. Fig. 2 is a diagram showing an example of the configuration of the energy management device of the first embodiment. FIG. 3 is a diagram showing an example of first factor candidate information generated by the information generating unit of the energy management device of Embodiment 1. FIG. FIG. 4 is a diagram showing an example of candidate information for the second factor determined by the information generating unit of the first embodiment. FIG. 5 is a diagram for explaining the first index, the second index, the third index, the fourth index, and the fifth index of the values calculated by the index value calculation unit of the implementation pattern 1. FIG. FIG. 6 is a diagram showing an example of index values of plural types calculated by the index value calculation unit of the first embodiment. FIG. 7 is a diagram showing an example of integrated information of Implementation Type 1. FIG. 8 is a diagram showing an example of loss factor information displayed on the display part by the information providing part of the first embodiment. FIG. 9 is a flow chart showing an example of processing performed by the processing unit of the energy management device of Embodiment 1. FIG. 10 is a diagram showing an example of the hardware configuration of the processing unit of the energy management device of the first embodiment. FIG. 11 is a diagram showing an example of the configuration of the energy management device of the second embodiment. FIG. 12 is a diagram showing an example of loss factor information displayed on the display part by the information providing part of the second embodiment. FIG. 13 is a flowchart showing an example of processing performed by the processing unit of the energy management device of Embodiment 2. FIG. 14 is a flowchart showing an example of the diagnosis process performed by the processing unit of the energy management device of Embodiment 2.

4,5: Power sensor

6: Production volume sensor

7: Environmental sensor

8: Production management device

10: Energy management device

11: Processing Department

12: Production-related information memory department

13: Display

21: Information Collection Department

22: Information Generation Department

23: Indicator value calculation section

24: Score calculation department

25: Information Provision Department

41: Ranking Information Generation Department

42: Display Processing Department

Claims (10)

An energy management device including: The index value calculation unit calculates more than one type of index value related to the energy consumption of the diagnostic object including the production equipment based on the production-related information that belongs to the information about the past production; The score calculation unit calculates the multiple factor candidates that are candidates for the energy consumption factor that does not contribute to the production based on the indicator values of one or more types calculated by the indicator value calculation unit. The score of the impact of energy consumption; and The information providing unit outputs information of the two or more factor candidates whose scores calculated by the score calculation unit among the plurality of factor candidates are the top ranked factors. The energy management device according to claim 1, wherein the aforementioned diagnostic target system includes related equipment used in relation to the aforementioned production equipment; The aforementioned production-related information includes information indicating the energy consumption of the aforementioned production equipment, information indicating the energy consumption of the aforementioned related equipment, and information indicating the production volume of the aforementioned production equipment; The aforementioned index value calculation unit calculates the aforementioned one or more types of index values based on the information representing the energy consumption of the aforementioned production equipment, the information representing the energy consumption of the aforementioned related equipment, and the information representing the production volume of the aforementioned production equipment. The energy management device according to claim 2, wherein the index value of one or more of the aforementioned types includes at least one of a first index value, a second index value, a third index value, a fourth index value, and a fifth index value , The first index value represents the time after the production equipment becomes active until the production of the production equipment starts, and the second index value represents the time after the production by the production equipment ends until the production equipment becomes inactive The third index value represents the difference between the time when the relevant equipment is activated and the time when the production equipment is activated, and the fourth index value represents the time during which the production equipment is activated. The ratio of the production time, the fifth index value represents the energy consumption of the diagnostic object per unit output caused by the production equipment. The energy management device described in any one of claims 1 to 3 is provided with: an information generating unit that generates the information of the plurality of factor candidates based on the aforementioned production-related information; The score calculation unit calculates the score based on the index values of the one or more types calculated by the index value calculation unit and the information of the plurality of factor candidates generated by the information generation unit. The energy management device according to any one of claims 1 to 3, wherein the plurality of factor candidates include the week, week, and month of the day when the article is produced by the production equipment, the person in charge of the production, and the Two or more of the types of items generated by the production equipment, the errors that occurred in the aforementioned production equipment, and the environment of the aforementioned production equipment. The energy management device according to any one of claims 1 to 3, wherein the index values of one or more of the aforementioned types are index values of a plurality of types; The aforementioned score calculation unit calculates the respective scores of the aforementioned plural factor candidates for the aforementioned plural types of index values; The information providing unit outputs the information of the two or more factor candidates whose scores are the top ranked among the plurality of factor candidates for the index values of the plurality of types. The energy management device described in any one of claims 1 to 3 is provided with: a contribution degree estimation unit that estimates that each of the aforementioned multiple factor candidates will bring the user an improvement activity on energy consumption that does not contribute to the aforementioned production Contribution The information providing unit modifies the scores of the factor candidates corresponding to the plurality of factor candidates based on the respective contribution degrees of the plurality of factor candidates estimated by the contribution degree estimation unit, and generates the corrected scores Information for the top two or more factor candidates. The energy management device according to any one of claims 1 to 3, wherein the information providing unit displays the prior information in the form of a ranking table in order from the factor candidate with the larger score among the plurality of factor candidates. The ranking information of the factor candidates of the set number is output as the information of the aforementioned two or more factor candidates. An energy management method for computer executors. The energy management method includes: The index value calculation step is to calculate more than one type of index value related to the energy consumption of the diagnostic object including the production equipment based on the production-related information belonging to the information about the past production; The score calculation step is based on the index values of one or more of the aforementioned types calculated in the aforementioned index value calculation step to calculate the respective pairs of multiple factor candidates that are candidates for energy consumption factors that do not contribute to production. Score of the impact of energy consumption; and The output processing step is to output information that the score calculated in the score calculation step is the top two or more factor candidates among the plurality of factor candidates. A recording medium on which an energy management program is recorded. The energy management program causes a computer to perform the following steps: The index value calculation step is to calculate more than one type of index value related to the energy consumption of the diagnostic object including the production equipment based on the production-related information belonging to the information about the past production; The score calculation step is based on the index values of one or more of the aforementioned types calculated in the aforementioned index value calculation step to calculate the respective pairs of multiple factor candidates that are candidates for energy consumption factors that do not contribute to production. Score of the impact of energy consumption; and The output processing step is to output information that the score calculated in the score calculation step is the top two or more factor candidates among the plurality of factor candidates.

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