Analysis system and analysis method

Abstract

And operators are easy to determine equipment and work with large discharge amount. This analysis system is provided with: a measurement unit that measures the amount of consumed emissions in a plurality of steps; a notification unit that notifies the plurality of consumption emissions; a storage device for storing a plurality of consumption emissions; and an analysis unit that analyzes the plurality of consumption emissions, extracts steps corresponding to the consumption emissions that are equal to or greater than a first threshold value, and sets, as a profile, information that variably defines the configuration of the measured data or the measurement method of the data, and the measurement unit sets the measurement unit of the consumption emissions or the measurement method of the consumption emissions on the basis of the profile.

Description

Technical Field

[0001] The technology disclosed in this application specification relates to analysis technology. Background Art

[0002] Conventional greenhouse gas emission management devices output information on emission of raw materials or services for each batch in order to efficiently track and investigate the cause of increase in greenhouse gas (carbon dioxide, etc.) emissions (see, for example, Patent Document 1).

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent Application Publication No. 2012-247954 Summary of the invention

[0006] In the above technology, by displaying the carbon dioxide emissions for each process or each reason of the target product, the process causing the deviation of the carbon dioxide emissions is determined. In addition, the raw materials and services causing the deviation are determined. Therefore, it is possible to confirm the change over time or the equipment efficiency of the service equipment in the original unit of the service, confirm the carbon dioxide emissions per 1 unit input of the raw material, or confirm the carbon dioxide emissions per 1 unit usage of the service in the original unit.

[0007] In such a greenhouse gas emission management device, the amount of information on the original units of all the equipment is enormous, and it is difficult to identify equipment and operations that emit a large amount of carbon dioxide or the like.

[0008] The technology disclosed in the present application specification has been accomplished in view of the above-described problems, and is a technology for easily identifying facilities and operations with large discharge amounts.

[0009] The analysis system of the first scheme of the technology disclosed in the present application specification comprises: at least one measuring unit, which measures the amount of energy consumed and the amount of wastewater or exhaust gas discharged as consumption emissions in multiple processes including the preparation of parts constituting a target product, the manufacture of the target product using the parts, the transportation of the target product and the sale of the target product; at least one notification unit, which notifies the multiple consumption emissions measured by the measuring unit; a storage device, which stores the multiple consumption emissions notified from the notification unit; and an analysis unit, which extracts the process corresponding to the consumption emissions above a first threshold value by analyzing the multiple consumption emissions stored in the storage device, sets information that variably defines the structure of measured data or the measurement method of the data as a profile, and the measuring unit sets the measurement unit of the consumption emissions or the measurement method of the consumption emissions according to the profile.

[0010] According to at least the first aspect of the technology disclosed in the present application specification, since processes with large consumption and emission amounts are extracted, the analysis frequency of processes with relatively small consumption and emission amounts can be reduced. Therefore, the amount of information to be analyzed can be reduced, and processes with relatively large consumption and emission amounts can be efficiently identified.

[0011] In addition, the objects, features, aspects, and advantages associated with the technology disclosed in the present application specification will become more apparent from the following detailed description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a diagram showing an example of the overall configuration of the environmental index improvement system according to the embodiment.

[0013] Figure 2 This is a diagram showing an example of data (information) in a profile according to an embodiment.

[0014] Figure 3 1 is a diagram showing an example of information on the amount of consumed emissions (consumed emissions information) generated by the consumed emissions measurement unit according to the embodiment.

[0015] Figure 4 This is a diagram showing an example of data (information) in the overall profile of the environment data management center according to the embodiment.

[0016] Figure 5 It is a diagram showing an example of information generated by an analysis unit of the environment data management center according to the embodiment.

[0017] Figure 6 It is a diagram showing an example of information in a profile according to an embodiment.

[0018] Figure 7It is a diagram showing an example of the overall configuration of the environmental index improvement system according to the embodiment.

[0019] Figure 8 It is a diagram showing an example of the overall configuration of the environmental index improvement system according to the embodiment.

[0020] Fig. 9 It is a diagram showing an example of the overall configuration of the environmental index improvement system according to the embodiment.

[0021] Fig.10 This is a rough example of practical application. Figure 1 , Figure 7 , Figure 8 , Fig. 9 This is a diagram illustrating a hardware configuration in the case of an environmental indicator improvement system of an analysis system.

[0022] Fig.11 This is a rough example of practical application. Figure 1 , Figure 7 , Figure 8 , Fig. 9 This is a diagram illustrating a hardware configuration in the case of an environmental indicator improvement system of an analysis system.

[0023] Fig.12 This is a diagram schematically showing an example of a configuration (functional unit) of an analysis system according to an embodiment. DETAILED DESCRIPTION

[0024] In the following embodiments, detailed features and the like are shown for technical description, but these are examples, and not all of these features are necessarily required in order for the embodiments to be implemented.

[0025] In addition, the drawings are schematically shown, and for the convenience of explanation, the structure is appropriately omitted or simplified in the drawings. In addition, the size and position of the structures shown in different drawings are not necessarily correctly described, and can be changed appropriately. In addition, in drawings such as top views that are not cross-sectional views, hatching is sometimes added to facilitate understanding of the contents of the embodiments.

[0026] In the following description, the same components are shown with the same reference numerals, and their names and functions are the same. Therefore, in order to avoid duplication, their detailed description may be omitted.

[0027] In addition, in the description described in the specification of the present application, when a certain component is described as “having”, “including” or “having”, it is not an exclusive description excluding the existence of other components unless otherwise specified.

[0028] In addition, in the description recorded in the specification of this application, there are cases where ordinal numbers such as "1st" or "2nd" are used, but these terms are used appropriately to facilitate understanding of the contents of the implementation methods, and the contents of the implementation methods are not limited to the order that may be generated by these ordinal numbers.

[0029] <About the conceptual structure of the analysis system>

[0030] Fig.12 This is a diagram conceptually showing an example of the configuration (functional unit) of the analysis system according to the present embodiment.

[0031] like Fig.12 By way of example, the analysis system includes at least one measuring unit 3001 , at least one notifying unit 3002 , a storage device 3003 , and an analyzing unit 3004 .

[0032] The measuring unit 3001 measures the amount of energy consumed and the amount of wastewater or exhaust gas discharged as consumption and emission amounts in multiple processes including preparation of parts constituting the target product, manufacture of the target product using the parts, transportation of the target product, and sale of the target product.

[0033] The notification unit 3002 notifies the plurality of consumption and emission amounts measured by the measurement unit 3001. The storage device 3003 stores the plurality of consumption and emission amounts notified from the notification unit 3002.

[0034] The analysis unit 3004 analyzes the plurality of consumption and emission amounts stored in the storage device 3003 , and extracts processes corresponding to consumption and emission amounts that are equal to or greater than a first threshold value.

[0035] Here, information that defines the structure of data to be measured or the method of measuring data in a changeable manner is referred to as a profile.

[0036] Furthermore, the measuring unit 3001 sets a measurement unit of the consumption and emission amount or a measurement method of the consumption and emission amount according to the profile.

[0037] In the following embodiments, the above-mentioned embodiments are described in more detail using the respective structures shown in the drawings and the like. Fig.12 An example of the structure is shown.

[0038] <First Embodiment>

[0039] Hereinafter, the analysis system and the analysis method according to the present embodiment will be described.

[0040] <About the structure of the analysis system>

[0041] Figure 1 : is a diagram showing an example of the overall structure of the environmental index improvement system according to the present embodiment. Figure 1By way of example, the environmental index improvement system includes a parts procurement source 102 , a manufacturing plant 104 , a logistics process 106 , a sales store 108 , a product 110 , and an environmental data management center 112 .

[0042] The product 110 is, for example, a precision instrument, etc. The product 110 is manufactured by processing or assembling a plurality of parts prepared from the parts preparation source 102 in the manufacturing plant 104. The manufactured product 110 is then delivered from the manufacturing plant 104 to a sales store 108 via a logistics process 106, and then to a consumer via the logistics process 106.

[0043] Parts preparation source 102 and manufacturing plant 104 consume energy during processing, assembly and evaluation required for manufacturing parts or products 110. Logistics process 106 consumes energy when transporting parts or products 110, sales store 108 consumes energy when selling products 110 in retail stores, and consumers consume energy when using products.

[0044] The parts procurement source 102 for procuring parts of target products includes a consumption emission amount notification unit 102A and a consumption emission amount measurement unit 102B, and has data corresponding to a profile 102C.

[0045] The manufacturing plant 104 that manufactures the target product using the parts includes a processing device 104A and a work process 104B. The processing device 104A includes a consumption emission notification unit 1104A and a consumption emission measurement unit 1104B, and has data corresponding to the profile 1104C. In addition, the work process 104B includes a consumption emission notification unit 2104A and a consumption emission measurement unit 2104B, and has data corresponding to the profile 2104C.

[0046] The physical distribution process 106 for transporting the target product includes a transport device 106A. The transport device 106A includes a consumption emission amount notification unit 1106A and a consumption emission amount measurement unit 1106B, and has data corresponding to a profile 1106C.

[0047] The sales store 108 that sells the target product is equipped with an operation device 108A. The operation device 108A is equipped with a consumption and emission amount notification unit 1108A and a consumption and emission amount measurement unit 1108B, and has data corresponding to a profile 1108C.

[0048] The product 110 includes a consumption and emission amount notification unit 110A and a consumption and emission amount measurement unit 110B, and has data corresponding to a profile 110C.

[0049] The environment data management center 112 includes an analysis unit 112A and a storage device 112B, and has data corresponding to the overall profile 112C.

[0050] Figure 2 FIG. 1 is a diagram showing an example of data (information) in a profile according to the present embodiment. Figure 1 As shown, a profile is provided for each object (process) that consumes energy.

[0051] like Figure 2 For example, the profile of each object (process) has measurement unit information of energy such as a measurement cycle. The measurement unit information includes, in addition to the measurement cycle, for example, the structure of the measured data, the measurement method of the data, etc. According to the profile (profile 102C, profile 1104C, profile 2104C, profile 1106C, profile 1108C, profile 110C), it is possible to set a trigger for measuring energy.

[0052] Figure 3 This is a diagram showing an example of information on consumed emissions (consumed emissions information) generated by the consumed emissions measurement unit of the present embodiment. Here, the consumed emissions refer to at least one of the amount of electricity (energy) consumed in the target product itself, the amount of exhaust gas of the target product itself, the amount of electricity (energy) consumed in the target process, the amount of combustion in the target process, the amount of water discharged in the target process, or the amount of exhaust gas in the target process. Figure 3 In FIG. 1 , as an example of consumption and emission amount, the amount of electricity consumed by the target product (consumed energy) is shown along with the passage of time.

[0053] The consumption emission amount measuring unit (consumption emission amount measuring unit 102B, consumption emission amount measuring unit 1104B, consumption emission amount measuring unit 2104B, consumption emission amount measuring unit 1106B, consumption emission amount measuring unit 1108B, consumption emission amount measuring unit 110B) measures and records the consumption emission amount consumed between the last trigger and the current trigger for each item or order of the target product based on the trigger set according to the measurement unit information of the profile. In addition, one consumption emission amount measuring unit is provided for each process, but in the case where it does not correspond to the number of processes, for example, one consumption emission amount measuring unit may be provided for all processes.

[0054] In addition, the consumption emission notification unit (consumption emission notification unit 102A, consumption emission notification unit 1104A, consumption emission notification unit 2104A, consumption emission notification unit 1106A, consumption emission notification unit 1108A, consumption emission notification unit 110A) notifies the consumption emission recorded by the consumption emission measurement unit to the environmental data management center 112. In addition, the consumption emission notification unit can also collect multiple consumption emission records and notify the environmental data management center 112. In addition, one consumption emission notification unit is provided for each process, but in the case of not corresponding to the number of processes, for example, one consumption emission notification unit can be provided corresponding to all processes.

[0055] The environmental data management center 112 collects the consumption and emission amounts notified from each consumption and emission amount notification unit (consumption and emission amount notification unit 102A, consumption and emission amount notification unit 1104A, consumption and emission amount notification unit 2104A, consumption and emission amount notification unit 1106A, consumption and emission amount notification unit 1108A, consumption and emission amount notification unit 110A) and stores them in the storage device 112B.

[0056] Figure 4 FIG. 1 is a diagram showing an example of data (information) in the overall profile 112C of the environment data management center 112 of the present embodiment. Figure 4 By way of example, the overall profile 112C includes information on a reference time and information on a threshold value of the consumption emission amount.

[0057] Figure 5 1 is a diagram showing an example of information generated by the analysis unit 112A of the environmental data management center 112 of the present embodiment. The analysis unit 112A analyzes the data (consumption and emission amount) of each target process with the same reference for each measurement period based on the reference time in the overall profile 112C, and extracts the target process whose consumption and emission amount is greater than the threshold value in the overall profile 112C.

[0058] exist Figure 5 In the example shown, the consumption and emission amounts of the object A and the object B measured for each measurement period based on the reference time are respectively shown.

[0059] According to such a structure, the analysis frequency of processes (measurement objects) with relatively small consumption and emission can be reduced. Therefore, the amount of information to be analyzed can be reduced, and processes (measurement objects) with relatively large consumption and emission, i.e., processes that become bottlenecks, can be efficiently identified. Furthermore, the cause of the increase in consumption and emission can be identified by focusing on the data (consumption and emission) of measurement objects with large consumption and emission.

[0060] <Second Embodiment>

[0061] In the following description, the same components as those described in the above-described embodiment are denoted by the same reference numerals, and their detailed description is appropriately omitted.

[0062] <About the structure of the analysis system>

[0063] The information in the profile can also be used for processing the measured data. For example, for the consumption emission information when the consumption emission is recorded every 10ms in the target process, if the measurement period in the corresponding profile is 100ms, the consumption emission recorded every 10ms can be added up to 10 and processed as the consumption emission every 100ms, as the consumption emission information related to the consumption emission every 100ms.

[0064] According to such a configuration, it is possible to calculate the consumption and emission amounts by unifying and treating the consumption and emission amount information having different measurement periods into the same unit (same measurement period).

[0065] <Third Embodiment>

[0066] In the following description, the same components as those described in the above-described embodiment are denoted by the same reference numerals, and their detailed description is appropriately omitted.

[0067] <About the structure of the analysis system>

[0068] Figure 6 FIG. 4 is a diagram showing an example of information in a profile according to the present embodiment. Figure 6 For example, the profile of each target process includes, in addition to the measurement cycle, measurement unit information of the measurement work, measurement processing, etc. Furthermore, for each measurement unit information, a trigger for measurement and validity or invalidity of measurement can be set.

[0069] The measurement operation in the measurement unit information is used to define operations such as batches or transportation, and is used to obtain the consumption and emission amount and required time from the start of the operation to the end of the operation.

[0070] The measurement process in the measurement unit information is used to obtain the consumption and emission amount and the time required from the start to the end of the software execution. The time from the start to the end of the software execution is stored in Figure 3 The time field of the consumption emission amount information is shown, and the consumption emission amount is stored in the consumption energy field of the consumption emission amount information.

[0071] According to such a configuration, even when the object of measurement changes, it is possible to appropriately measure the consumption emission amount for each product or part that is a different object such as a measurement operation or a measurement process.

[0072] <Fourth Implementation Method>

[0073] In the following description, the same components as those described in the above-described embodiment are denoted by the same reference numerals, and their detailed description is appropriately omitted.

[0074] <About the structure of the analysis system>

[0075] Figure 7 : is a diagram showing an example of the overall structure of the environmental index improvement system according to the present embodiment. Figure 7 By way of example, the environmental index improvement system includes a parts procurement source 102 , a manufacturing plant 104 , a logistics process 106 , a sales store 108 , a product 110 , and an environmental data management center 212 .

[0076] The environmental data management center 212 includes an analysis unit 212A, a storage device 212B, a consumption and emission amount learning unit 213 , and a consumption and emission amount estimating unit 214 .

[0077] The analysis unit 212A unifies the data (consumption and emission amounts) of each target process based on the same standard for each measurement cycle based on the reference time in the overall profile 212C, and extracts target processes whose consumption and emission amounts are equal to or greater than the threshold value in the overall profile 212C.

[0078] The storage device 212B stores the consumed emission amounts notified from the respective consumed emission amount notification units (consumed emission amount notification unit 102A, consumed emission amount notification unit 1104A, consumed emission amount notification unit 2104A, consumed emission amount notification unit 1106A, consumed emission amount notification unit 1108A, consumed emission amount notification unit 110A).

[0079] The consumption and emission amount learning unit 213 performs machine learning based on the consumption and emission amount 220 stored in the storage device 212B, and generates a consumption and emission model 221 for estimation.

[0080] The consumption and emission amount estimation unit 214 outputs consumption and emission prediction data 222 corresponding to the predicted value of future consumption and emission amount based on the consumption and emission model 221 and the consumption and emission amount 220 .

[0081] In the environmental data management center 212 , the consumption and emission amount estimation unit 214 outputs consumption and emission prediction data 222 corresponding to the predicted value of future consumption and emission amounts based on the consumption and emission model 221 and the consumption and emission amounts 220 .

[0082] The analysis unit 212A then extracts objects (processes) whose future consumption and emission amounts will be equal to or larger than a threshold value based on the emission amounts acquired so far and the consumption and emission prediction data 222 which is a predicted value of future consumption and emission amounts.

[0083] According to such a configuration, it is possible to estimate an object (process) whose consumption and emission amount will increase in the future.

[0084] <Fifth Implementation Method>

[0085] In the following description, the same components as those described in the above-described embodiment are denoted by the same reference numerals, and their detailed description is appropriately omitted.

[0086] <About the structure of the analysis system>

[0087] Figure 8 : is a diagram showing an example of the overall structure of the environmental index improvement system according to the present embodiment. Figure 8 By way of example, the environmental index improvement system includes a parts procurement source 102 , a manufacturing plant 104 , a logistics process 106 , a sales store 108 , a product 110 , and an environmental data management center 312 .

[0088] The environmental data management center 312 includes an analysis unit 312A, a storage device 312B, a consumption and emission amount learning unit 313 , a consumption and emission amount estimation unit 314 , a replacement unit 316 , and a consumption and emission amount estimation unit 317 .

[0089] The analysis unit 312A unifies the data (consumption and emission amounts) of each target process based on the same standard for each measurement cycle based on the reference time in the overall profile 312C, and extracts target processes whose consumption and emission amounts are equal to or greater than the threshold value in the overall profile 312C.

[0090] The storage device 312B stores the consumed emission amounts notified from the consumed emission amount notifying units (consumed emission amount notifying unit 102A, consumed emission amount notifying unit 1104A, consumed emission amount notifying unit 2104A, consumed emission amount notifying unit 1106A, consumed emission amount notifying unit 1108A, consumed emission amount notifying unit 110A).

[0091] The consumption and emission amount learning unit 313 performs machine learning based on the consumption and emission amount 320 stored in the storage device 312B, and generates a consumption and emission model 321 for estimation.

[0092] Furthermore, the consumption and emission amount learning unit 313 performs additional learning based on the consumption and emission amount 320 stored in the storage device 312B, and generates a consumption and emission additional learning model 323 for estimation.

[0093] The consumption and emission amount estimation unit 314 outputs consumption and emission prediction data 322 corresponding to the predicted value of the future consumption and emission amount based on the consumption and emission model 321 and the consumption and emission amount 320 .

[0094] The consumption and emission amount estimation unit 317 outputs consumption and emission prediction data 324 corresponding to the predicted value of future consumption and emission amount based on the consumption and emission additional learning model 323. The consumption and emission amount estimation unit 317 may be the same as the consumption and emission amount estimation unit 314.

[0095] The consumption and emission model 321 is generated using the consumption and emission amount 320 stored in the storage device 312B at a specific time, and is not updated thereafter until a re-learning instruction is issued.

[0096] The consumption and emission additional learning model 323 is a result obtained by re-learning based on the consumption and emission amounts 320 added later in addition to the consumption and emission amounts 320 in the storage device 312B used when making the consumption and emission model 321, a part of the result obtained by re-learning based on the consumption and emission amounts 320 added later in addition to the consumption and emission amounts 320 in the storage device 312B used when making the consumption and emission model 321, or a result obtained by learning only based on the consumption and emission amounts 320 added later.

[0097] The analysis unit 312A compares the consumption emission prediction data 322 produced by the consumption emission model 321 and the consumption emission prediction data 324 produced by the consumption emission additional learning model 323 with the actual value of the above time interval. Furthermore, the difference between the predicted value and the actual value of the consumption emission amount based on the consumption emission prediction data 322 and the difference between the predicted value and the actual value of the consumption emission amount based on the consumption emission prediction data 324 are compared, and the consumption emission prediction data with the smaller difference is selected.

[0098] If the consumption and emission prediction data selected by the analysis unit 312A is produced based on the consumption and emission additional learning model 323 , the replacement unit 316 replaces the consumption and emission model 321 with the consumption and emission additional learning model 323 .

[0099] With such a structure, it is possible to update the consumption and emission model 321 based on actual results and to estimate the target process with a large consumption and emission amount with high accuracy.

[0100] <Sixth Implementation Method>

[0101] In the following description, the same components as those described in the above-described embodiment are denoted by the same reference numerals, and their detailed description is appropriately omitted.

[0102] <About the structure of the analysis system>

[0103] The environmental index improvement system can be configured by adding an update notification unit and a profile update unit to the first to fifth embodiments described above.

[0104] Fig. 9 : is a diagram showing an example of the overall structure of the environmental index improvement system according to the present embodiment. Fig. 9 By way of example, the environmental index improvement system includes a parts procurement source 102 , a manufacturing plant 104 , a logistics process 106 , a sales store 108 , a product 110 , and an environmental data management center 412 .

[0105] The environment data management center 412 includes an analysis unit 112A, a storage device 112B, an update notification unit 420 , and a profile update unit 421 , and has data corresponding to the overall profile 112C.

[0106] exist Fig. 9 In the embodiment, the update notification unit 420 and the profile update unit 421 are set as the components of the environment data management center 412, but the update notification unit 420 and the profile update unit 421 can also be added as the components of the measurement object. In addition, only one of the update notification unit 420 and the profile update unit 421 can be a component of the environment data management center 412, and the other can be a component of the measurement object.

[0107] The update notification unit 420 has setting conditions set by the data user according to the purpose for each measurement object, and performs determination based on the setting conditions for the time series change of the consumption and emission of the measurement object. Furthermore, the update notification unit 420 notifies the profile update unit 421 whether the profile needs to be updated.

[0108] The above-mentioned setting conditions are provided as, for example, a condition that the consumption and emission amount is above a threshold value allowed by the data user, or a condition that the ratio of the daily or per unit time change in the consumption and emission amount allowed by the data user is above a threshold value, but in addition to these, conditions such as a value obtained by performing four arithmetic operations or one or more calculus operations on the consumption and emission amount converges within a certain range, or a condition such as a change different from past time series changes using the results of machine learning is achieved, etc., which are combined with conditions of general analysis methods for time series data.

[0109] The judgment according to the above-mentioned setting conditions is implemented for each measurement period using the whether to update notification unit 420, which confirms whether the time series change of the consumption and emission of the measured object has changed from a state that meets the setting conditions to a state that does not meet the setting conditions, or whether the time series change of the consumption and emission of the measured object has changed from a state that does not meet the setting conditions to a state that meets the setting conditions.

[0110] When the time series change of the consumption and emission amount of the measurement object changes from a state satisfying the setting condition to a state not satisfying the setting condition, the update notification unit 420 notifies the profile update unit 421 to shorten the measurement cycle of the consumption and emission amount.

[0111] On the contrary, when the time series change of the consumption and emission amount of the measurement object changes from a state not satisfying the setting condition to a state satisfying the setting condition, the update notification unit 420 notifies the profile update unit 421 to extend the measurement cycle of the consumption and emission amount.

[0112] The profile updating unit 421 updates the content of the profile set for the measurement target based on the notification from the update notification unit 420 .

[0113] When notified to shorten or lengthen the measurement cycle, the profile updating unit 421 shortens or lengthens the measurement cycle according to a preset rule.

[0114] Regarding the rules for shortening the measurement cycle, for example, one may consider: setting the data volume according to a ratio such as increasing it by 10, or setting it in a manner that maximizes the amount of data that can be collected, taking into account the data collection capabilities of the measuring instrument and the amount of communication with the environmental data management center, etc.

[0115] In addition, regarding the rule for extending the measurement cycle, for example, it is possible to set the measurement cycle according to a ratio such as doubling the data volume by 1 / 10 or returning the data volume to the value at the start of the operation.

[0116] Furthermore, the update notification unit 420 may have two or more setting conditions for one measurement target. In this case, the above determination is performed for each setting condition, and the result is notified to the profile update unit 421.

[0117] The profile updating unit 421 has a rule for changing the measurement cycle for each setting condition, and changes the profile according to the corresponding rule in response to the notification from the update notification unit 420 .

[0118] According to this embodiment, it is possible to detect that the consumption and emission of the measured object changes to a level above the permissible range of the data user due to changes in the production object or environment. In addition, the profile can be dynamically changed in a manner that measures detailed data on the consumption and emission of the measured object according to the detected situation.

[0119] Therefore, it is possible to identify factors causing changes in the amount of consumption and emission, and as a result, it is possible to contribute to improving the activities of the amount of consumption and emission permitted for data users.

[0120] <About the hardware structure of the analysis system>

[0121] Fig.10 as well as Fig.11 This is a rough example of practical application. Figure 1 , Figure 7 , Figure 8 , Fig. 9 This is a diagram illustrating a hardware configuration in the case of an environmental indicator improvement system of an analysis system.

[0122] also, Fig.10 as well as Fig.11 The hardware structure of the example is sometimes different from Figure 1 , Figure 7 , Figure 8 , Fig. 9 The structure of the example does not match the number of examples, because Figure 1 , Figure 7 , Figure 8 , Fig. 9 The illustrated structures represent conceptual units.

[0123] Therefore, it is at least conceivable Figure 1 , Figure 7 , Figure 8 , Fig. 9 The structure shown in the example is Fig.10 as well as Fig.11 In the case of multiple hardware configurations, Figure 1 , Figure 7 , Figure 8 , Fig. 9 The example structure is Fig.10 as well as Fig.11 The case where a part of the hardware configuration shown as an example corresponds to Figure 1 , Figure 7 , Figure 8 , Fig. 9 The illustrated multiple structures are set in Fig.10 as well as Fig.11 This is an example of a hardware configuration.

[0124] exist Fig.10 As a tool for implementing Figure 1 , Figure 7 , Figure 8 , Fig. 9 The hardware configuration of the consumption emission measurement unit, analysis unit, consumption emission learning unit, consumption emission estimation unit, replacement unit, etc. in the embodiment shows a processing circuit 3102A for performing calculations and a storage device 3103 capable of storing information. This configuration is the same in any of the above-mentioned embodiments.

[0125] exist Fig.11 As a tool for implementing Figure 1 , Figure 7 , Figure 8 , Fig. 9 The hardware configuration of the consumption and emission amount measuring unit, analyzing unit, consumption and emission amount learning unit, consumption and emission amount estimation unit, replacement unit, storage device, etc. in FIG. 3 shows a processing circuit 3102B for performing calculations. This configuration is the same in any of the above-mentioned embodiments.

[0126] The storage device 112B (or the storage device 212B, the storage device 312B) is implemented by the storage device 3103 or other storage devices (not shown here).

[0127] The storage device 3103 may be, for example, a hard disk drive (HDD), a random access memory (RAM), a read only memory (ROM), a flash memory, an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or other volatile or non-volatile semiconductor memory, a memory (recording medium) including a magnetic disk, a floppy disk, an optical disk, a compact disk, a mini disk, or a DVD, or all recording media used in the future.

[0128] The processing circuit 3102A may also be used to execute a program stored in the storage device 3103, an external CD-ROM, an external DVD-ROM, or an external flash memory, etc. That is, for example, it may be a central processing unit (CPU), a microprocessor, a microcomputer, or a digital signal processor (DSP).

[0129] When the processing circuit 3102A is used to execute a program stored in the storage device 3103, an external CD-ROM, an external DVD-ROM, or an external flash memory, the consumption emission amount measuring unit, the analysis unit, the consumption emission amount learning unit, the consumption emission amount estimation unit, and the replacement unit are implemented by software, firmware, or a combination of software and firmware that uses the processing circuit 3102A to execute the program stored in the storage device 3103. In addition, the functions of the consumption emission amount measuring unit, the analysis unit, the consumption emission amount learning unit, the consumption emission amount estimation unit, and the replacement unit may also be implemented by, for example, a plurality of processing circuits cooperating with each other.

[0130] The software and firmware may be described as programs and stored in the storage device 3103. In this case, the processing circuit 3102A realizes the above functions by reading and executing the programs stored in the storage device 3103. That is, the storage device 3103 may be used to store programs that are executed by the processing circuit 3102A to realize the above functions.

[0131] In addition, the processing circuit 3102B may also be dedicated hardware, that is, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a combination thereof.

[0132] When the processing circuit 3102B is dedicated hardware, the consumption emission amount measuring unit, the analyzing unit, the consumption emission amount learning unit, the consumption emission amount estimation unit, and the replacement unit are realized by the operation of the processing circuit 3102B. In addition, the functions of the consumption emission amount measuring unit, the analyzing unit, the consumption emission amount learning unit, the consumption emission amount estimation unit, and the replacement unit may be realized by each independent circuit or by a single circuit.

[0133] In addition, the functions of the consumption and emission measurement unit, the analysis unit, the consumption and emission learning unit, the consumption and emission inference unit, and the replacement unit may be partially implemented in the processing circuit 3102A for executing the program stored in the storage device 3103, and partially implemented in the processing circuit 3102B which is dedicated hardware.

[0134] <Effects Produced by the Multiple Embodiments Described Above>

[0135] Next, examples of the effects produced by the multiple embodiments described above are shown. In addition, in the following description, the effects are recorded according to the specific structures exemplified by the multiple embodiments described above, but they can also be replaced with other specific structures exemplified in the specification of this application within the scope of producing the same effects. That is, for the sake of convenience of description, sometimes only any one of the corresponding specific structures is recorded representatively, but the specific structure recorded representatively can also be replaced with other corresponding specific structures.

[0136] In addition, the replacement may be performed across a plurality of embodiments. That is, the same effect may be produced by combining the respective structures illustrated in different embodiments.

[0137] According to the above-described embodiment, the analysis system includes at least one measuring unit, at least one notifying unit, a storage device 112B (or a storage device 212B, a storage device 312B), and an analyzing unit 112A (or an analyzing unit 212A, an analyzing unit 312A). Here, the measuring unit corresponds to, for example, at least one of the consumption emission amount measuring unit 102B, the consumption emission amount measuring unit 110B, the consumption emission amount measuring unit 1104B, the consumption emission amount measuring unit 1106B, the consumption emission amount measuring unit 1108B, and the consumption emission amount measuring unit 2104B. In addition, the notifying unit corresponds to, for example, at least one of the consumption emission amount notifying unit 102A, the consumption emission amount notifying unit 110A, the consumption emission amount notifying unit 1104A, the consumption emission amount notifying unit 1106A, the consumption emission amount notifying unit 1108A, and the consumption emission amount notifying unit 2104A. The consumption emission amount measuring unit 102B measures the amount of energy consumed and the amount of wastewater or exhaust gas discharged in a plurality of processes including the preparation of parts constituting the target product, the manufacture of the target product using the parts, the transportation of the target product, and the sale of the target product as the consumption emission amount 220 (or the consumption emission amount 320). The consumption emission amount notification unit 102A notifies the plurality of consumption emission amounts 220 measured by the consumption emission amount measuring unit 102B. The storage device 112B stores the plurality of consumption emission amounts 220 notified from the consumption emission amount notification unit 102A. The analysis unit 112A extracts the process corresponding to the consumption emission amount 220 that is greater than or equal to the first threshold value by analyzing the plurality of consumption emission amounts 220 stored in the storage device 112B. Here, information that variably defines the structure of the measured data or the measurement method of the data is set as the profile 102C (or the profile 110C, the profile 1104C, the profile 2104C, the profile 1106C, the profile 1108C). Furthermore, the consumption emission amount measurement unit 102B sets the measurement unit of the consumption emission amount 220 or the measurement method of the consumption emission amount 220 according to the profile 102C.

[0138] According to the above-described embodiment, the analysis system includes a processing circuit 3102A that executes a program and a storage device 3103 that stores the executed program. Then, the following operations are realized by the processing circuit 3102A executing the program.

[0139] That is, in a plurality of processes including the preparation of parts constituting the target product, the manufacture of the target product using the parts, the transportation of the target product, and the sale of the target product, the amount of energy consumed and the amount of wastewater or exhaust gas discharged are measured as the consumption emission 220. Furthermore, the measured plurality of consumption emission 220 is notified. Furthermore, the notified plurality of consumption emission 220 is stored. Furthermore, by analyzing the stored plurality of consumption emission 220, the process corresponding to the consumption emission 220 that is greater than the first threshold value is extracted. Here, information that variably defines the structure of the data to be measured or the measurement method of the data is set as the profile 102C. In addition, when measuring the consumption emission 220, the measurement unit of the consumption emission 220 or the measurement method of the consumption emission 220 is set according to the profile 102C.

[0140] According to the above-described embodiment, the analysis system includes the processing circuit 3102B as dedicated hardware. The processing circuit 3102B as dedicated hardware performs the following operations.

[0141] That is, the processing circuit 3102B as dedicated hardware measures the amount of energy consumed and the amount of wastewater or exhaust gas discharged as the consumption emission 220 in a plurality of processes including the preparation of parts constituting the target product, the manufacture of the target product using the parts, the transportation of the target product, and the sale of the target product. Furthermore, the measured plurality of consumption emission 220 is notified. Furthermore, the notified plurality of consumption emission 220 is stored. Furthermore, by analyzing the stored plurality of consumption emission 220, the process corresponding to the consumption emission 220 that is greater than the first threshold value is extracted. Here, information that variably defines the structure of the measured data or the measurement method of the data is set as the profile 102C. In addition, when measuring the consumption emission 220, the measurement unit of the consumption emission 220 or the measurement method of the consumption emission 220 is set according to the profile 102C.

[0142] According to such a structure, the process with large consumption and emission amount is extracted, so the analysis frequency of the process (measurement object) with relatively small consumption and emission amount can be reduced. Therefore, the amount of information to be analyzed can be reduced, and the process (measurement object) with relatively large consumption and emission amount, that is, the process that becomes a bottleneck, etc. can be efficiently identified. In addition, the data (consumption and emission amount) of the measurement object with large consumption and emission amount can be focused on to identify the cause of the increase in consumption and emission amount.

[0143] Furthermore, even when other structures exemplified in the specification of the present application are appropriately added to the above-mentioned structures, that is, when other structures not mentioned as the above-mentioned structures in the specification of the present application are appropriately added, the same effects can be produced.

[0144] In addition, according to the above-described embodiment, the consumed energy to be measured includes the energy consumed by the target product itself. According to such a configuration, it is possible to extract processes with large consumption and emission amounts including the energy consumed by the target product in the process.

[0145] In addition, according to the above-described embodiment, the consumption and emission amount measuring unit and the consumption and emission amount notifying unit are respectively provided corresponding to the plurality of processes. Moreover, the storage device 112B stores the plurality of consumption and emission amounts notified from the plurality of consumption and emission amount notifying units in a centralized manner. According to such a structure, the consumption and emission amounts measured by the respective measuring units can be managed in a centralized manner in the environmental data management center, and the consumption and emission amounts between the plurality of processes can be easily compared.

[0146] In addition, according to the above-described embodiment, the consumption emission measurement unit 102B measures the consumption emission 220 for each type or each order of the target product. According to such a configuration, when the production target changes, the factor of the consumption emission being large can be identified for each part (type, order) of the produced product.

[0147] In addition, according to the above-described embodiment, the analysis system includes: a learning unit that performs machine learning using the consumption emission 220 (or the consumption emission 320) to generate a first consumption emission model (e.g., the consumption emission model 221, the consumption emission model 321); and a first inference unit that generates first prediction data (e.g., consumption emission prediction data 222, the consumption emission prediction data 322) as data related to the predicted amount of the consumption emission 220 based on the consumption emission model 221. Here, the learning unit corresponds to, for example, at least one of the consumption emission learning unit 213 and the consumption emission learning unit 313. In addition, the first inference unit corresponds to, for example, at least one of the consumption emission inference unit 214 and the consumption emission inference unit 314. Moreover, the analysis unit 212A extracts a process corresponding to the consumption emission 220 that is greater than the first threshold value by analyzing the predicted amount of the consumption emission 220 based on the consumption emission prediction data 222. According to such a structure, it is possible to infer an object (process) whose consumption emission will increase in the future.

[0148] In addition, according to the above-described embodiment, in the analysis system, the consumption emission learning unit 313 performs additional learning using the consumption emission 320 to generate a second consumption emission model (e.g., the consumption emission additional learning model 323). A second inference unit is provided for generating second prediction data (e.g., consumption emission prediction data 324) as data related to the predicted amount of the consumption emission 320 based on the consumption emission additional learning model 323. Here, the second inference unit corresponds to the consumption emission inference unit 317, etc., for example. Moreover, the analysis unit 312A selects and analyzes the data of the predicted amount of the consumption emission 320 that is small in the consumption emission prediction data 322 and the consumption emission prediction data 324 related to a specific time interval, thereby extracting the process corresponding to the consumption emission 320 that is greater than the first threshold. According to such a structure, by generating a plurality of prediction data using additional learning and selecting one prediction data from them, the accuracy of the prediction data can be improved, and the target process with a large consumption emission can be inferred with high accuracy.

[0149] In addition, according to the above-described embodiment, the analysis system includes a replacement unit 316 that replaces the consumption emission model 321 with the consumption emission additional learning model 323 when the analysis unit 312A selects the consumption emission prediction data 324. According to such a structure, the consumption emission model 321 can be updated based on the actual results and the target process with large consumption emission can be estimated with high accuracy.

[0150] In addition, according to the above-described embodiment, the analysis system includes an updating unit that updates the profile 102C when the time series change of the consumption emission amount 220 is greater than the second threshold value. Here, the updating unit corresponds to, for example, the profile updating unit 421. According to such a configuration, when the production object or environment changes and the factor that becomes a bottleneck changes, the profile can be dynamically updated to determine the process with a large consumption emission amount.

[0151] According to the above-described embodiment, in the analysis method, the amount of energy consumed and the amount of wastewater or exhaust gas discharged in a plurality of processes including the preparation of parts constituting the target product, the manufacture of the target product using the parts, the transportation of the target product, and the sale of the target product are respectively measured as the consumption emission 220. Furthermore, the measured plurality of consumption emission 220 is notified. Furthermore, the notified plurality of consumption emission 220 is stored. Furthermore, by analyzing the stored plurality of consumption emission 220, the process corresponding to the consumption emission 220 that is greater than the first threshold value is extracted. Here, information that variably defines the structure of the measured data or the measurement method of the data is set as the profile 102C. In addition, when measuring the consumption emission 220, the measurement unit of the consumption emission 220 or the measurement method of the consumption emission 220 is set according to the profile 102C.

[0152] According to such a structure, since processes with large consumption and emission amounts are extracted, the analysis frequency of processes (measurement objects) with relatively small consumption and emission amounts can be reduced. Therefore, the amount of information to be analyzed can be reduced, and processes (measurement objects) with relatively large consumption and emission amounts, i.e., processes that become bottlenecks, etc. can be efficiently identified. Furthermore, the cause of the increase in consumption and emission amounts can be identified by focusing on the data (consumption and emission amounts) of measurement objects with large consumption and emission amounts.

[0153] Furthermore, the order in which each process is performed can be changed without particular limitation.

[0154] In addition, even when other structures exemplified in the specification of the present application are appropriately added to the above-mentioned structure, that is, when other structures not mentioned as the above-mentioned structure in the specification of the present application are appropriately added, the same effect can be produced.

[0155] <Regarding Modifications of the Multiple Embodiments Described Above>

[0156] In the multiple embodiments described above, the material, size, shape, relative arrangement relationship or implementation conditions of each component are sometimes described, but these are examples in all aspects and are not restrictive.

[0157] Therefore, numerous variations and equivalents not shown in the examples can be envisioned within the scope of the technology disclosed in the present specification, including, for example, the case where at least one component is deformed, at least one component is added, or at least one component is omitted, and further, at least one component in at least one embodiment is extracted and combined with components in other embodiments.

[0158] Furthermore, when the above-described embodiment states that “one” component is included, “one or more” of the component may be included unless a contradiction occurs.

[0159] Furthermore, each component in the above-described embodiments is a conceptual unit, and within the scope of the technology disclosed in the present application specification, it includes a case where one component is composed of multiple structures, a case where one component corresponds to a part of a certain structure, and further a case where multiple components are arranged in one structure.

[0160] In addition, the components in the above-described embodiments may include components having other structures or shapes as long as they exhibit the same function.

[0161] In addition, the descriptions in the specification of the present application are referred to for all purposes related to the present technology and are not to be regarded as prior art.

[0162] In addition, each component described in the above-described embodiments may be conceived as software or firmware, or may be conceived as corresponding hardware. For example, software may be referred to as a "unit" or the like, and for example, hardware may be referred to as a "processing circuit" or the like.

[0163] Furthermore, the technology disclosed in the present specification may be a case where each component is dispersedly provided in a plurality of devices, that is, a system which is a combination of a plurality of devices.

[0164] (Explanation of Reference Numerals)

[0165] 102C: profile; 110: product; 110C: profile; 112A: analysis unit; 112B: storage device; 212A: analysis unit; 212B: storage device; 220: consumption and emission; 221: consumption and emission model; 312A: analysis unit; 312B: storage device; 316: replacement unit; 320: consumption and emission; 321: consumption and emission model; 1104C: profile; 1106C: profile; 1108C: profile; 2104C: profile; 3001: measurement unit; 3002: notification unit; 3003: storage device; 3004: analysis unit; 3103: storage device.

Claims

1. An analysis system comprising: at least one measuring unit that measures, as consumption and emission amounts, the amount of energy consumed and the amount of wastewater or exhaust gas discharged in a plurality of processes including preparation of parts constituting a target product, manufacture of the target product using the parts, transportation of the target product, and sale of the target product; at least one notification unit for notifying the plurality of consumption emission amounts measured by the measurement unit; a storage device for storing the plurality of consumption emission amounts notified from the notification unit; as well as an analyzing unit that extracts the process corresponding to the consumption and emission amount that is greater than or equal to a first threshold value by analyzing the plurality of consumption and emission amounts stored in the storage device; information that defines the structure of measured data or the method of measuring the data in a changeable manner is set as a profile, The measuring unit sets a measurement unit of the consumption and emission amount or a measurement method of the consumption and emission amount according to the profile.

2. The analysis system according to claim 1, wherein: The consumed energy includes at least one of the energy consumed by the target product itself and the energy consumed in the process.

3. The analysis system according to claim 1 or 2, wherein: The measuring unit and the notifying unit are provided corresponding to the plurality of steps, respectively. The storage device collectively stores the plurality of consumed emission amounts notified from the plurality of notification units.

4. The analysis system according to any one of claims 1 to 3, wherein: The measuring unit measures the consumption emission amount for each item or each order of the target product.

5. The analysis system according to any one of claims 1 to 4, further comprising: a learning unit that performs machine learning using the consumption and emission amounts to generate a first consumption and emission model; and a first estimation unit that generates first prediction data as data related to a predicted amount of the consumption and emission amount based on the first consumption and emission model; The analysis unit extracts the process corresponding to the consumption and emission amount equal to or greater than the first threshold value by analyzing the predicted amount of the consumption and emission amount based on the first prediction data.

6. The analysis system according to claim 5, wherein: The learning unit performs additional learning using the consumption and emission amount to generate a second consumption and emission model. The analysis system further includes a second estimation unit that generates second prediction data as data related to a predicted amount of the consumption and emission amount based on the second consumption and emission model. The analysis unit selects and analyzes the first prediction data related to a specific time interval and the data of the predicted amount of consumption and emission that has a small difference from the actual value corresponding to the time interval, thereby extracting the process corresponding to the consumption and emission amount above the first threshold value.

7. The analysis system according to claim 6, further comprising: The replacing unit replaces the first consumption and emission model with the second consumption and emission model when the analyzing unit selects the second prediction data.

8. The analysis system according to any one of claims 1 to 7, further comprising: The updating unit updates the profile when the time series change in the consumption and emission amount is equal to or greater than a second threshold value.

9. An analytical method, wherein: In a plurality of processes including preparation of parts constituting a target product, manufacture of the target product using the parts, transportation of the target product, and sale of the target product, the amount of energy consumed and the amount of wastewater or exhaust gas discharged are measured as consumption and emission amounts, notifying the measured plurality of said consumption emissions, storing the notified plurality of consumption emissions, By analyzing the plurality of the stored consumption and emission amounts, the process corresponding to the consumption and emission amount being greater than a first threshold value is extracted, The profile includes information that variably defines the structure of the measured data or the method of measuring the data. When measuring the consumption emission amount, a measurement unit of the consumption emission amount or a measurement method of the consumption emission amount is set according to the profile.

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