Information processing device, information processing method, program, and recording medium

Abstract

To provide a technology for enabling a user to easily grasp a relationship of the use, added value, or the like of power consumption generated in each element about a facility (including a device, equipment, a system, or the like) including a plurality of elements that consume power.SOLUTION: An information processing device includes a classification information acquisition part for acquiring classification group information including a plurality of groups with classification items formed, and association information for associating the classification items of the plurality of classification groups to each other, a data acquisition part for acquiring data of power consumed by a facility, and a classification processing part for classifying the data acquired by the data acquisition part by using the classification group information acquired by the classification information acquisition part and the association information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and the like. [Background technology]

[0002] 2. Description of the Related Art Conventionally, attempts have been made in various fields to analyze energy usage and reduce waste.

[0003] Patent Document 1 proposes a device that uses energy information and production status information of production equipment to create a graph that correlates production status information and energy usage for each piece of equipment. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2013-222256 A Summary of the Invention [Problem to be solved by the invention]

[0005] Patent Document 1 describes a method of graphing the power consumption of production equipment used in product production, power consumption when idle, power consumption during brief stops, power consumption when waiting for the previous process, and power consumption when waiting for the next process.

[0006] With this method, it is easy to grasp how much power is being consumed at what state the production equipment is in, but it is difficult to grasp where and how much of the power consumption is being consumed, which is essential and other.As a result, it is difficult for facility managers and operators to distinguish between essential power consumption and other power consumption that occurs at each location and for each purpose, making it difficult to consider effective improvement measures to reduce power consumption (for example, improving or replacing equipment).

[0007] Therefore, there was a demand for technology that would enable users to easily grasp the relationships between the use of electricity consumed by each element, its added value, etc., in facilities (including devices, equipment, systems, etc.) that contain multiple elements that consume electricity. [Means for solving the problem]

[0008] A first aspect of the present invention is an information processing device comprising: a classification information acquisition unit that acquires classification group information including a plurality of classification groups composed of classification items and association information that associates the classification items of the plurality of classification groups; a data acquisition unit that acquires data on electricity consumed in a facility; and a classification processing unit that classifies the data acquired by the data acquisition unit using the classification group information and the association information acquired by the classification information acquisition unit.

[0009] Also, a second aspect of the present invention is an information processing method comprising: a classification information acquisition step in which a classification information acquisition unit acquires classification group information including a plurality of classification groups constituted by classification items and association information that associates the classification items of the plurality of classification groups; a data acquisition step in which an acquisition unit acquires data on electricity consumed in a facility; and a classification step in which a classification processing unit classifies the data acquired in the data acquisition step using the classification group information and the association information acquired in the classification information acquisition step. Effect of the Invention

[0010] According to the present invention, for a facility (including devices, equipment, systems, etc.) that contains multiple elements that consume electricity, the user can easily understand the relationships between the use of electricity consumed by each element, added value, etc. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a schematic block diagram illustrating the configuration of an information processing apparatus according to an embodiment. [Diagram 2]A schematic diagram showing how multiple DBs are systematically related in a hierarchical structure. [Diagram 3] FIG. 1 is a schematic diagram illustrating a classification system used to classify uses related to energy consumption. [Figure 4] A schematic diagram illustrating a classification system used to classify added value. [Diagram 5] FIG. 1 is a schematic diagram illustrating a hierarchical example of items when classifying available operation time by time period. [Figure 6] FIG. 1 is a schematic diagram illustrating classification items used for classifying energy consumption contents. [Figure 7] 6 is a flowchart for explaining a process flow in which the classification processing unit 3 classifies and displays the results. [Figure 8] A diagram illustrating a graph of energy consumption categorized by workplace and use. [Figure 9] 1 is a diagram illustrating the trend in energy consumption across the entire facility. [Figure 10] (A) An example of a graph showing the classification results for equipment and operation details. (B) An example of a graph showing the classification of waste levels by time. [Figure 11] A diagram showing an example of the results of comparing the amounts and ratios of net, incidental, and waste between multiple pieces of equipment. [Figure 12] A diagram illustrating a graph of the classification results by unit and consumption content. [Figure 13] 1 is a schematic diagram showing a step-by-step operation of a cutting device cutting away a target material in cutting processing. [Figure 14] 11A to 11C are schematic diagrams showing step-by-step operations of a cutting device for cutting away a target material using another method in cutting processing. [Figure 15] FIG. 1 is a schematic block diagram illustrating the configuration of an information processing apparatus according to an embodiment. [Figure 16] This is a diagram illustrating the results of comparing the actual energy consumption rate during operation hours with the reference value to determine whether energy usage is normal or abnormal. [Figure 17] This is a diagram illustrating the results of comparing the actual values ​​of equipment outside operating hours with reference values ​​to determine whether energy usage is normal or abnormal. [Figure 18] FIG. 1 is a schematic block diagram illustrating the configuration of an information processing apparatus according to an embodiment. [Figure 19] FIG. 13 is a diagram showing an example of the results of displaying the renewable energy introduction status of a target facility on the display unit 4. [Figure 20] A diagram showing an example of the results of a simulation of the predicted costs for each procurement method based on the amount of electricity required by the target facility. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] An information processing device, an information processing method, and the like according to embodiments of the present invention will be described with reference to the drawings. The embodiments described below are merely examples, and those skilled in the art can appropriately modify and implement the detailed configurations without departing from the spirit and scope of the present invention.

[0013] In the drawings referred to in the following description of the embodiments, elements denoted by the same reference numerals have the same functions unless otherwise noted. When a plurality of identical elements are arranged in a drawing, the reference numerals and their descriptions may be omitted.

[0014] In addition, since the drawings may be represented diagrammatically for the convenience of illustration and explanation, the shape, size, arrangement, etc. of the elements depicted in the drawings may not strictly correspond to the actual objects.

[0015] [Embodiment 1] FIG. 1 is a schematic block diagram illustrating the configuration of an information processing device according to the first embodiment. In FIG. 1, functional elements necessary for explaining the features of the present embodiment are shown as functional blocks, but general functional elements that are not directly related to the problem-solving principle of the present invention are omitted. In addition, each functional element illustrated in FIG. 1 is a functional concept, and does not necessarily have to be physically configured as illustrated. For example, the specific form of distribution and integration of each functional block is not limited to the illustrated example, and all or a part of them can be functionally or physically distributed and integrated in any unit depending on the usage situation, etc.

[0016] Each functional block can be configured using software or hardware executed by a computer. That is, each functional block can be configured, for example, by a CPU reading and executing a control program. Alternatively, some or all of the functional blocks can be configured using hardware such as an ASIC provided in an information processing device. Some or all of the functional blocks may be configured by mounting one of the above-mentioned CPUs, or some or all of the functional blocks may be configured by mounting multiple CPUs and coordinating the respective CPUs. Some or all of the functional blocks may be configured using a CPU having multiple cores.

[0017] The information processing device of this embodiment may include a CPU, an I / O port, and a computer-readable recording medium. As the computer-readable recording medium, a non-transient recording medium that stores a processing program executed by the CPU, parameters necessary for executing the processing, etc. may be used. As the non-transient recording medium, for example, a flexible disk, an optical disk, a magneto-optical disk, a magnetic tape, a USB memory, an SSD, etc. may be used. In addition, the information processing device may include a rewritable storage medium (such as a RAM) that provides a recording area necessary for processing such as calculation.

[0018] The information processing device of this embodiment may include a display device and / or an input device. The information processing device may be configured to be connectable to an external display device and / or input device. The display device and / or the input device may be used as a user interface. The display device may be, for example, a liquid crystal display or an organic EL display, and the input device may be, for example, a keyboard, a jog dial, a mouse, a pointing device, a voice input device, or the like.

[0019] The information processing device of this embodiment can display a work support screen on a display device when a user creates, edits, checks the contents of, or otherwise processes various databases described below. The information processing device of this embodiment can also accept and acquire information (e.g., instructions and data relating to the creation and editing of databases) input via an input device.

[0020] FIG. 1 illustrates an example of the configuration of an information processing device according to this embodiment. The information processing device includes an energy consumption input unit 1, an energy use condition input unit 2, a classification processing unit 3, and a display unit 4. In FIG. 1, each of Gr.1 to Gr.4 is a classification group in which classification items are hierarchically configured, and Gr.1 to Gr.4 can be collectively called classification group information. The energy consumption input unit 1 is an input unit that acquires data on power consumption consumed in a facility. The energy consumption input unit 1 can also be called a data acquisition unit. The energy use condition input unit 2 is a classification information acquisition unit that acquires classification group information including a plurality of classification groups in which classification items are hierarchically configured, and association information that associates the classification items of the plurality of classification groups. The classification processing unit 3 is a classification processing unit that classifies the power consumption data acquired by the input unit using the classification group information and the association information acquired by the classification information acquisition unit. Each block illustrated in FIG. 1 will be described below.

[0021] The energy usage condition input unit 2 has a database (hereinafter sometimes referred to as DB) in which the energy usage conditions of facilities such as production factories that consume electricity are classified into a number of categories and organized and stored so as to be searchable according to purpose. Note that the term facility may refer to the whole, including devices, equipment, systems, production lines, etc., or may refer to individual elements that make up the whole.

[0022] The substation DB 201 is a database that records information on substations that are hierarchically installed in facilities and equipment that are the subject of information processing. It records the names of extra-high voltage substations that transform extra-high voltage power (e.g., 66 kV) to high voltage power (e.g., 6 kV) used in facilities and supply it, and sub-substations that are installed in electrical rooms in facilities and transform high voltage power to low voltage power (e.g., 400 V, 200 V, 100 V, etc.).

[0023] In addition, each substation usually has a measuring device that transforms voltage and measures the amount of power, which is the amount of energy consumed. Therefore, when measurement data from the measuring device is input to the energy consumption input unit 1, the classification processing unit 3 can classify the amount of power in association with the names of extra-high voltage substations and sub-substations in the substation DB 201. This makes it possible to know how much energy was consumed in which substation and for what period of time, and to display the classification processing results on the display unit 4. Also, the unit of measurement data input to the energy consumption input unit 1 may be power (W), power amount (kWh), or (Wh).

[0024] The distribution board DB202 of the energy usage condition input unit 2 is a database that records information (e.g., names) of distribution boards that receive electricity transformed by the transformer of the sub-substation, distribute it to each area within the facility, and transmit it.

[0025] The distribution board DB203 is a database that records information (e.g., names) of distribution boards that have the function of distributing power to loads further downstream in the power system from the distribution board, that is, to equipment used in each workplace of the facility. Since distribution boards are placed downstream in the power system (energy flow) after branching off from the distribution board, there are more of them than distribution boards, and many are placed in each area of ​​the facility.

[0026] The building DB204 is a database that records information (e.g., names) of buildings that constitute a facility that consumes electricity. In large-scale facilities such as production plants and development offices, multiple buildings are arranged, and a building (building) is one of the components of the facility. By associating the building DB204 with the substation DB201 and the switchboard DB202 and classifying the energy consumption, it becomes possible to grasp the energy consumption on a building-by-building basis.

[0027] The range of the substation and building configuration unit varies depending on the facility. For example, there are cases where one substation supplies power to multiple buildings, cases where the relationship between the substation and the building is 1:1, and cases where multiple substations supply power to one building. This is because the facility is designed and constructed in various ways according to the scale of its energy consumption. In addition, for reasons of facility operation, such as the introduction of multiple pieces of equipment that consume a lot of power after the construction of the facility, it may be necessary to add a substation, and the relationship between the substation DB201 and the building DB204 may need to be updated. Therefore, by accumulating and organizing information on the substation, which is the source and measurement point of energy, and the building, which is the demand side, in a database, it becomes easier to manage the energy consumption.

[0028] Similarly, with regard to switchboards and distribution boards, for example, new ones may be installed because the number of branches is insufficient due to the addition of equipment that consumes electricity after the facility is constructed. Or, there may be cases where they existed at the time of construction but were demolished or reinstalled later. Therefore, by recording the names of switchboards and distribution boards in the switchboard DB202 and distribution board DB203 and updating them regularly, it becomes easier to manage energy consumption.

[0029] The workplace DB205 is a database that records information (e.g., name) of workplaces, which are units for operating facilities that consume electricity. In the description of this embodiment, a unit for managing energy consumption is defined as a workplace for convenience. A workplace is one form of division of a place where people work, and can be said to be a concept narrower in scope than physical divisions such as facilities and buildings. In general, a workplace is composed of personnel, fixed assets owned by an organization such as equipment, and tools necessary for performing work such as consumable tools and fixtures. Work within a facility is performed by each workplace organized according to the purpose, and is operated using various equipment arranged within the facility. In addition, since the purpose of the work changes over time, the organization of the workplace also changes according to the purpose.

[0030] In addition, in the workplace DB205, not only the name of the workplace but also information on the job content may be recorded. For example, if the workplace is responsible for production, process information on which process of the process of manufacturing the product the workplace is responsible for may be recorded. Alternatively, if the workplace is classified by product model and organized as a factory that produces multiple products in total, information on the product model may be added. Alternatively, if the workplace commonly produces parts for multiple models, rather than by model, information on the type of parts may be added because it is more efficient to operate the facility if the workplace is organized by the type of parts. Alternatively, if the workplace is not directly responsible for production but is an indirect business necessary for the management of the facility, information on the work content of the workplace, such as development work for the next product, planning work, human resources work, and general affairs work, may be added. By adding such information on the workplace, the characteristics of the workplace can be understood, and the content of the database recorded in the workplace DB205 is not subject to any restrictions as long as it contributes to the classification of the workplace, which is the operating unit of the facility.

[0031] Each workplace recorded in the workplace DB 205 is responsible for managing the amount of energy consumption and for activities to reduce energy consumption. As will be described later, by correlating the amount of energy consumption for a certain period inputted to the energy consumption input unit 1 with the workplace DB 205, it is possible to grasp the amount of energy consumption for each workplace.

[0032] In this way, the workplace defined as a concept in this embodiment has the characteristics that its configuration changes depending on the purpose of operation, and that it is an energy consumer in the facility and is responsible for managing energy consumption and energy reduction activities. In the information processing device of this embodiment, the names of workplaces, etc. are recorded in the workplace DB205, and the database is updated according to changes, making it easy to manage the energy consumption of each workplace.

[0033] The equipment DB206 is a database that records information on various equipment that constitutes the facility, such as equipment that is installed in each workplace of the facility and performs functions such as production and development necessary for operation, or infrastructure equipment. Infrastructure equipment includes electronic devices such as PCs, displays, and printers, equipment for improving the facility's operating environment such as air conditioning and lighting, and shared equipment such as elevators, security cameras, toilet drainage, and smoke exhaust in the event of a disaster.

[0034] The equipment DB 206 may record information such as names of all equipment constituting the facility, or may record only the names of major equipment that consumes a large amount of power. When the energy consumption of a facility that consumes power is tallied and analyzed using the information processing device of this embodiment, the user may select whether to record only the major equipment or to include smaller equipment in the database, depending on the target accuracy of analysis.

[0035] Furthermore, the equipment DB 206 may record not only the name of the equipment, but also information on the magnitude of power consumption such as the rated voltage, rated current, and rated power of the equipment, information on the phase of the power supply such as three-phase or single-phase, or information on the function that the equipment performs. Alternatively, process information on which process in production the equipment performs may be recorded. For example, a database may be constructed that links the names of equipment and the names of processes, such as injection molding machine A being the equipment responsible for the molding process of molded parts used in a specific product, and the database may be used as a classification item for managing energy consumption.

[0036] The unit DB207 is a database that records elements that constitute the equipment described in the equipment DB206. For example, an injection molding machine may be registered as equipment that performs an injection molding process, and the injection molding machine includes components (units) such as an injection motor, a cylinder heater, a metering motor, a mold clamping motor, and an eject motor. A mold temperature regulator, which is ancillary equipment of an injection molding machine, includes units such as a circulating cooling water pump and a heater. A plastic material dryer, which is another ancillary equipment of an injection molding machine, includes units such as a blower and a heater. In this way, equipment for operating a facility that consumes electricity is arranged with units having specific functions as components, and functions as equipment are exerted by combining the units, and the equipment itself operates as one system. The unit DB207 records information on such units (for example, names).

[0037] In addition, in the unit DB207, not only the name of the unit but also information on the magnitude of power consumption such as the rated voltage, rated current, and rated power of the unit, and information on the phase of the power supply such as three-phase or single-phase, similar to the above-mentioned equipment assignment information, may be recorded. Alternatively, information on the function of the equipment (for example, an explanation that an injection motor is a unit that injects plastic material melted by a cylinder heater toward a mold) may be recorded. The units are configured in various configuration systems according to the form of the equipment, such that a large-scale equipment has many units as components and a small-scale equipment has a few units. The units listed in the unit DB207 can be the smallest unit among the components that consume energy in a facility that consumes electricity.

[0038] Fig. 2 is a schematic diagram showing that in an embodiment, a building DB204, a workplace DB205, an equipment DB206, and a unit DB207 are systematically related to each other in a hierarchical structure. In Fig. 2, facilities that consume electricity are classified into categories that are subdivided in stages from buildings in a higher hierarchy to lower hierarchy, such as workplaces, equipment, and units, and are constructed as a database of facilities as a whole. For example, a facility that consumes electricity is made up of multiple buildings. One of the buildings is made up of multiple workplaces. One of the workplaces is made up of multiple equipment. One of the equipment is made up of multiple units with various types according to the type of the equipment.

[0039] In view of this configuration, the databases of the building DB204, workplace DB205, equipment DB206, and unit DB207 can be said to be relational databases having relationships with each other. In this embodiment, the relationships between the classification items are systematically constructed and managed in advance. By defining the relationships in advance in this manner, it is possible to systematically manage (e.g., accumulate, analyze, and visualize) the amount of energy consumed by a group of components while maintaining the relationships between the consumption elements.

[0040] Incidentally, the power receiving and distribution equipment described in the substation DB201, switchboard DB202, and distribution board DB203 are arranged at the time of construction of the facility according to the branch system of the power for the purpose of supplying power within the facility. For this reason, the power receiving and distribution equipment is arranged without necessarily being related to the type of equipment or unit that is the load that consumes the power. The power receiving and distribution equipment is arranged, for example, so that the transmission loss (energy loss) during supply is small and the return on investment of the construction costs is good.

[0041] For this reason, the substation DB 201, the switchboard DB 202, and the distribution board DB 203 are related to each other as a single classification group (Gr.1) as shown in Fig. 1. On the other hand, the building DB 204, the workplace DB 205, the equipment DB 206, and the unit DB 207 are organized for purposes different from (Gr.1), and are related to each other as a single classification group (Gr.2).

[0042] For example, if the facility is a manufacturing factory, the workplaces will be organized to maximize the efficiency of the operation mode of mass-producing multiple types of products, so there may be multiple workplaces within a certain building, or a shared workplace across multiple buildings. Many pieces of equipment are placed in the workplace, but the relationship between the workplace and the equipment is not necessarily related to the energy flow, and there may be cases where a distribution board branches out to multiple workplaces, there may be a 1:1 relationship between a distribution board and a workplace, or there may be cases where multiple distribution boards are placed in one workplace.

[0043] Therefore, for the relationship between classification group Gr.1 and classification group Gr.2, an arithmetic expression for apportioning the energy consumption of one distribution board or calculating the sum of the energy consumption of multiple distribution boards is defined in advance in the energy usage condition input unit 2. For example, consider a case where the data input to the energy consumption input unit 1 is data for each distribution board recorded in the distribution board DB 203, and the range supplied by the distribution board spans multiple workplaces. In order to tally up the energy consumption for each workplace, it is necessary to perform an apportionment calculation to determine what proportion of the measured energy is attributable to the molding workplace in Figure 2 and what proportion is attributable to the electrical equipment workplace.

[0044] For example, let us consider a case where compressed air generated by a compressor is supplied to a molding workplace and an electrical equipment workplace through piping. The energy usage condition input unit 2 can calculate the apportionment rate by estimating the amount of air consumption in advance from the specifications of the air flow rate of the equipment. Alternatively, the apportionment rate can be calculated based on the actual consumption value obtained by measuring the amount of consumption over a certain period of time such as one week or one month, and can be recorded in association with the workplace name in the workplace DB 205.

[0045] On the other hand, in the case of the 1,000 ton molding machine in the molding workplace in Figure 2, if the machine is supplied with electricity from a distribution board specific to the molding workplace, the energy consumption measured at that distribution board will be calculated as 100% attributable to the molding workplace.

[0046] Furthermore, the turbo chiller, which generates chilled water to cool the air taken in from outdoors by the air handling unit, is responsible for cooling the air in all workplaces in the facility, so the area of ​​each workplace is calculated in advance and the area ratio is recorded in the workplace DB 205 as the air conditioning apportionment rate. Similarly, the energy load of lighting equipment can also be treated as being proportional to the area of ​​the workplace. Therefore, by recording the area ratio, even if the area illuminated by the lighting equipment spans multiple workplaces, the energy consumption measured at the distribution board can be calculated and apportioned for each workplace based on a reasonable basis.

[0047] For example, in cases where cold water is generated in a centralized cooling tower and circulated to cool multiple pieces of equipment, or where power for robots is supplied to multiple assembly workplaces from a factory line connected to a single distribution board, the allocation rate may be determined based on the rated power of the equipment that is the load. Alternatively, a more accurate allocation rate may be determined based on actual measured values ​​over a certain period of time.

[0048] Similarly, allocation rates for each workplace can be determined for equipment for other purposes. According to this embodiment, it is possible to comprehensively investigate in advance which workplace the energy consumption measured at a measurement point such as a distribution board belongs to, calculate allocation rates based on predetermined rules such as equipment specifications and actual measured values, and build a database in the workplace DB205. For example, when the range to which energy is supplied from the measurement point is narrower or equal to that of a single workplace, 100% of the measured amount of power is allocated to that workplace and tabulated. When the range to which energy is supplied from the measurement point is wider than that of a single workplace, it is possible to allocate, tabulate, and classify the amount of power to each workplace according to a predetermined allocation rate.

[0049] Alternatively, the energy consumption of air conditioning equipment such as turbo refrigerators and air handling units can be added up and then allocated to all workplaces based on the area ratio. In this way, the allocation result can be obtained without comprehensively understanding the relationship between the workplaces and the distribution boards to which the many individual air handling units installed in the facility are connected. Similarly, the energy consumption of distribution boards used for lighting can be added up and then allocated to the workplaces based on their area.

[0050] It is also possible to add up the power consumption of production equipment such as molding machines and assembly robots, and then allocate it to each workplace based on the rated power of the equipment. However, in this case, there is a possibility that the allocated value will be concentrated in workplaces with high rated power of the equipment. Therefore, if the purpose is to obtain a simple allocated value, it is recommended to allocate it from the total value, and if the purpose is to obtain accuracy, it is recommended to comprehensively investigate the relationship between the distribution boards to which each equipment is connected and the workplaces, and allocate it within the range of the workplaces that the equipment is responsible for.

[0051] Therefore, the rules may be set so that the energy from distribution boards connected to building infrastructure such as air conditioning and lighting is allocated to all workplaces based on the total value for each use.On the other hand, the energy from distribution boards connected to equipment used to produce products and parts such as molding machines and assembly robots may be allocated to workplaces within the scope of each distribution board.

[0052] By defining and managing the relationships between such classification items in advance, it is possible to properly grasp the energy consumption generated by each element of devices, equipment, systems, etc. that include multiple elements that consume power, regardless of whether they are in the same physical branch system in the power supply. The classification processing unit 3 executes classification processing of the energy consumption inputted to the energy consumption input unit 1 according to the classification items of the relational database recorded in the energy use condition input unit 2. This makes it possible to tabulate and analyze the energy consumption without omissions or duplications.

[0053] In the first embodiment, the acquisition point on the power system where energy is metered does not have to be a distribution board, and may be, for example, a switchboard. Of the facilities that consume power, power can be supplied by all distribution boards, but the data of the energy consumption cannot necessarily be measured by all distribution boards. In the following, the unit of the number of distribution boards is called a surface, and for example, of 100 distribution boards, data can be acquired from both the distribution board and the distribution board for 80 surfaces, and data can be acquired from the remaining 20 surfaces by the upstream distribution board, but cannot be acquired by the distribution board, so a case is considered in which there is a constraint on data acquisition.

[0054] In such cases, the energy consumption obtained from either the distribution board or the switchboard is allocated to each workplace as in the above example. Since the switchboard is located upstream of the distribution board in the power system, it is preferable to allocate from a downstream distribution board to each workplace in order to improve the accuracy of the allocation result. Therefore, if energy consumption can be measured at the distribution board level, it is preferable to allocate from the distribution board to each workplace, and if it can only be measured at a distribution board at a higher level, it is preferable to allocate the energy consumption measured at the distribution board to each workplace without going through the distribution board.

[0055] In this case, if the classification processing unit 3 performs a process of allocating 80 surfaces from the distribution board to workplaces and the remaining 20 surfaces from the distribution board to workplaces, the calculation process may become complicated because the measurement points to be measured differ depending on whether data can be acquired at each level on the power system. Therefore, for the 20 surfaces that can only be measured at the distribution board, it is preferable that the classification processing unit 3 associates the distribution board DB202 with the distribution board DB203, and allocates the energy consumption measured at the distribution board to the distribution board level in advance. In this way, the classification processing unit 3 can align the energy consumption data whose data levels are not aligned at the time of measurement to the distribution board level on the power system. Through this process, all energy consumption data can be allocated to each workplace collectively from the distribution board level.

[0056] The application DB208 is a database that records the applications of energy consumed by facilities that consume electric power. The application DB208 constitutes Gr.3, which is separate from the above-mentioned Gr.1 and Gr.2. The applications of energy are broadly divided into two categories: infrastructure, which is the application of energy to improve the living environment, and production, which is the application of energy to operate production equipment. The infrastructure is further divided into, for example, lighting, air conditioning, and other infrastructure, and the production is further divided into heat, drive, air, vacuum, and other production.

[0057] Fig. 3 is a schematic diagram illustrating a classification system used to classify uses related to energy consumption in an embodiment. In Fig. 3, energy uses are classified into infrastructure and production systems in a higher level of classification. The infrastructure system is subdivided into lighting, air conditioning, and other infrastructure systems in a lower level, and the production system is subdivided into heat, drive, air, vacuum, and other production systems in a lower level. By using such a hierarchical structure to organize energy uses and construct a database, it is possible to classify the energy of facilities that consume electricity without omissions or duplications.

[0058] In contrast to the classification of Gr.2 buildings, workplaces, equipment, and units, which are vertically organized according to the system functions that operate the facility, the classification items for Gr.3 energy uses are organized as common (cross-sectional) classification concepts common to buildings, workplaces, equipment, and units. For example, the use of heat energy is applied as a common use to the cylinder heaters of the injection molding machines in the molding workplace, the reflow furnaces in the electrical equipment workplace, and the electric furnaces in other workplaces, and the corresponding energy consumption is classified.

[0059] Based on the method of classifying the energy usage in this embodiment, it can be understood that, in the classification hierarchy of workplaces in the workplace DB 205, for example, all of the workplaces, such as the molding workplace, the electrical equipment workplace, and the fixing belt workplace, consume heat-based energy. In addition, in the classification hierarchy of equipment in the equipment DB 206, the consumed energy can be classified from the perspective of the energy usage. For example, the 1000 ton molding machine, the 650 ton molding machine, and the 180 ton molding machine all consume heat-based energy, and the reflow oven belonging to the electrical equipment workplace, which is another workplace, also consumes heat-based energy. In this way, the consumed energy can be classified from the perspective of the energy usage.

[0060] On the other hand, the 1000t molding machine in the molding workshop can be classified as having energy uses that are classified as drive systems, such as the metering motor, injection motor, mold clamping motor, and eject motor. The mounters in the electrical equipment workshop can also be classified as drive system energy uses, and the transport robots in other workshops can also be classified as drive systems in terms of energy uses. Furthermore, the automated assembly workshop has automated assembly equipment that automatically assembles product units, and the equipment intended to assemble these product units can also be classified as drive systems in terms of energy uses.

[0061] In light of this energy classification system, the energy consumption at a certain workplace level can be classified as a certain percentage for heat system use and another percentage for drive system use. Also, the energy consumption at a certain equipment level can be classified as a certain percentage for heat system use and another percentage for drive system use.

[0062] For example, in building A1 of a factory, there are energy uses that fall under all categories, but building A2 is a power building that converts energy, so there are cases where energy is not consumed for heat purposes.Specifically, in building A2, energy is consumed intensively for specific purposes, such as the turbo chiller for the air conditioning system, the lighting system for using building A2, and the air compressor for supplying energy to the entire facility.

[0063] In this embodiment, the use DB208 has items of energy use that can be commonly (cross-sectionally) applied to one or more levels of the facility's levels (buildings, workplaces, equipment, units constituting the equipment, etc.) in the facility's operation system. That is, the use DB208 can have a database structure in which the energy consumption content used by each level of the facility is classified by energy use, including heat system, drive system, air system, vacuum system, etc. Therefore, at any level of the facility's operation system, the energy consumption can be commonly (cross-sectionally) classified based on the energy use.

[0064] In the example shown in Figure 3, the upper-level uses are classified as infrastructure and production, but these names do not necessarily have to be used in a fixed manner, and other use names may be used as long as they explain the concept. For example, in a development facility whose operational purpose is product development, the facilities may be classified as infrastructure and development. Alternatively, in a production factory, if the proportion of other production systems is high, specific uses classified as other production systems may be grouped together as independent uses.

[0065] For example, in a factory that uses a large amount of light such as lasers for processing or light sources for inspection equipment, a classification item called a light source system that is not classified as a heat system, drive system, air system, or vacuum system may be defined to configure the application DB 208. Note that the light source system in this case does not refer to lighting such as LEDs or fluorescent lights for improving the visibility of human work in general offices or production factories, but rather refers to the application as optical energy required to generate ultraviolet light required in the production process of products.

[0066] Also, in facilities such as data centers that are equipped with large amounts of computing equipment such as computers and servers, and communication equipment, the proportion of energy consumption accounted for by electronic equipment is larger than that of normal production factories. For this reason, among the uses accounted for in other production systems, an independent classification item called "electronic equipment" may be set up to construct the use DB208. Also, since data centers are not production factories, the database may be constructed by classifying the higher hierarchical levels under names such as "infrastructure" and "data processing" rather than "infrastructure" and "production."

[0067] In this way, the information processing device according to this embodiment configures a use DB 208 that classifies the uses of electricity consumed in the facility. The use classification is commonly (cross-sectionally) applied to one or more levels of the facility. The classification items are set according to the content of the energy consumption used by the level, but there is no restriction on the number of classification items or specific names.

[0068] Meanwhile, energy supplied from a power distribution facility such as a distribution board may be consumed for a single purpose (for example, heat system) recorded in the purpose DB 208, or may be consumed for multiple purposes (for example, heat system and drive system). In this regard, the purpose DB 208 prepares in advance an allocation ratio indicating what percentage of the energy consumption obtained at a measurement point such as a distribution board is allocated to the heat system purpose and what other percentage is allocated to the drive system purpose, and records the ratio in association with the purpose name in the purpose DB 208. The allocation ratio may be calculated based on the rated power of the facility as described in the workplace DB 205, or may be calculated based on the measured results for a certain period of time.

[0069] When the energy consumption measured at the facility's power distribution equipment such as a substation, switchboard, distribution board, or breaker of the distribution board is for one type of use of the power supplied from the measurement point, the use DB208 allocates 100% of the measured power amount to that use and tallys it up. On the other hand, when the use of the electric energy supplied from the measurement point spans multiple types of uses, the use DB208 allocates the measured value to workplaces at a predetermined allocation rate and tallys it up, and classifies and tallys it up by use.

[0070] In this way, even if the uses of energy measured based on the energy flow in a substation, a switchboard, a distribution board, etc. span a plurality of types, the names of the uses, which are classification items, and the proportional allocation rates for the uses are defined in advance. As a result, in the use DB 208 of this embodiment, a database can be constructed by classifying the energy consumption by use.

[0071] In this embodiment, the value-added DB209 can be commonly (cross-sectionally) applied to one or more levels of the facilities that consume electricity. The value-added DB209 is a database that classifies and records power consumption according to the added value into which energy is converted, such as net, incidental, and waste. In the value-added DB209, classification can be configured as the priority order of energy reduction according to the operation details or energy consumption details for each level. The value-added DB209 is related to the operation details DB210 and consumption details DB211 described below, and together with them, configures Gr.4.

[0072] For example, in a facility such as a production factory, equipment belonging to a workplace arranged in a building or units that compose the equipment consume energy. This energy is used to perform operations such as processing and assembly on target parts of materials and parts, and these operations add the desired added value to produce the desired product. This process can be considered as the conversion of energy (power consumption) into the added value of the product. In this embodiment, the energy consumption is classified based on the type of added value created.

[0073] FIG. 4 is a schematic diagram illustrating a classification system used for classifying added value in an embodiment. In FIG. 4, classification items based on added value are conveniently defined as net, incidental, and waste in the upper hierarchy. "Net" means that the consumed energy is used to directly or effectively add value to the object (processed material or part). For example, the electricity consumed by equipment or units that handle processes such as processing and assembly can be considered net. "Incidental" is a classification item indicating that the consumed energy does not directly add value to the object (processed material or part), but is a necessary energy consumption under the current usage conditions of the equipment or unit. "Waste" is a classification item indicating that the consumed energy does not directly add value to the object (processed material or part) and is not an essential consumption under the usage conditions.

[0074] For example, if equipment is turned on and consuming energy even though production has stopped, the equipment is not adding value to the product in its intended operation, and the energy consumption is not necessary for production, so this consumption is classified as waste.

[0075] As another example, if equipment such as an electric furnace is turned on during a changeover period for a different product model, the energy consumption during that period does not add value to the product. However, if the electric furnace is turned off during the changeover period, the electric furnace cannot operate at a temperature that guarantees product quality when the product is produced immediately after the changeover. For this reason, although this energy consumption does not directly create added value, it is classified as ancillary because it is an item that is necessary under the current conditions of use.

[0076] On the other hand, for example, during the period when the target parts are put into an electric furnace and heated and melted, the added value of melting is converted into the target parts, so the energy consumption is classified as net.

[0077] In Figure 4, "Net" is one of the upper-level classifications, and is classified into "Net time" and "Net energy" as lower-level classifications. Furthermore, "Associated" is classified into "Associated time" and "Associated energy", and "Waste" is classified into "Waste time" and "Waste energy". The lower-level classifications allow for more detailed classification of net, associated, and waste, such as net time, associated time, and time waste, based on the breakdown of operation content by time. Alternatively, the energy consumed by the operations performed by the units that make up the equipment can be further classified into net energy, associated energy, and waste energy, based on the energy consumption content.

[0078] In this embodiment, the classification items of Gr.4 are mutually associated with each other based on the relationship between the classification items of the operation DB 210 or the consumption DB 211 in Fig. 1 and the added value DB 209, and the operation contents or the energy consumption contents are classified into types of added value. A specific description will be given below.

[0079] In this embodiment, the operation content DB210 is a database for classifying energy consumption of facilities that consume electricity based on the breakdown of operation content by time of one or more of workplace, equipment, and unit. Specifically, the consumed energy is classified according to the type and level of value, such as whether the consumed energy adds value to the target part, whether it does not add value but is essential under the current usage conditions of the facility, or whether it does not add value and is not essential under the current usage conditions. The operation content DB210 is a database that the classification processing unit 3 refers to when classifying consumed energy based on such added value.

[0080] FIG. 5 shows an example of hierarchically configured classification items in this embodiment. FIG. 5 is a schematic diagram showing hierarchically exemplified items when classifying available operation time by time. For example, this hierarchical classification item can be applied to workplaces, equipment, and units in a facility that consumes electricity. In this embodiment, the available operation time of the facility is classified into specified operation time and non-operation time in the upper hierarchy. The specified operation time is classified into excluded time, special operation time, and actual operation time in the middle hierarchy. Furthermore, the excluded time is classified into planned stop, others (breaks, etc.), and regular PM (PM: plant maintenance) in the lower hierarchy. Also, the actual operation time is classified into daily inspection and cleaning, etc., changeover and adjustment, replacement and replenishment of consumables, start-up, stop-down, breakdown, frequent stop and idle, speed reduction, defective product processing, and non-defective product processing time in the lower hierarchy. Note that when the classification is the same in the upper, middle, and lower classifications, for example, non-operation time has the same classification item in all hierarchies, the classification frames in FIG. 5 are integrated into one and illustrated. The hierarchical classification shown in FIG. 5 is just an example, and it goes without saying that it can be changed as appropriate depending on the operation content.

[0081] In this manner, in this embodiment, the breakdown of operation contents by time is classified hierarchically from top to bottom. Then, by linking each subclassification to the added value classification in FIG. 4, the result is the added value classification shown at the right end of FIG. 5. For example, energy consumed during non-operational time is classified as wasteful because it does not add value and is not necessary under the current facility usage conditions. Similarly, energy consumed during replacement and replenishment of consumables is classified as incidental because it does not create added value but is necessary under the current facility usage conditions. Energy consumed during non-defective product processing time is classified as net because it adds added value to the target parts such as materials and parts.

[0082] In this way, according to this embodiment, it is possible to classify consumed energy based on added value and build a database. In this way, the energy classified into net, incidental, and waste in the higher classification of the added value DB 209 can be further classified into net per hour, incidental per hour, and waste per hour in more detail by relating it to the breakdown of the operation contents by time recorded in the operation contents DB 210.

[0083] In this embodiment, the consumption content DB 211 is a database for classifying the energy consumption of a facility that consumes electric power based on the type of operation, such as processing or assembly, that one or more of the equipment or units performs on a target part. Specifically, the classification is based on whether the energy consumed by the equipment or unit adds value to the target part, does not add value but is necessary under the current usage conditions of the facility, or does not add value and is not essential under the current usage conditions. The consumption content DB 211 is a database that the classification processing unit 3 refers to when classifying the energy consumption based on such added value.

[0084] Another example of hierarchical classification items in this embodiment is shown in Fig. 6. Fig. 6 is a schematic diagram illustrating classification items used to classify operations performed by equipment or units in a facility by energy consumption content. In Fig. 6, operations performed by units constituting the facility while consuming energy are classified into a hierarchy of energy consumption content.

[0085] For example, the cylinder heater of a molding machine is responsible for melting materials. The energy consumed in this operation can be classified into energy used directly to melt the material and energy dissipated from the unit during the melting process. Therefore, the energy consumption of a cylinder heater is classified into material melting and heat dissipation. Furthermore, if the added value classification in Figure 4 is linked to each of the energy consumption contents, it will be shown in the hierarchy of added value classification in Figure 6. For example, energy classified as material melting is classified as net energy because it adds added value to the material by melting it. On the other hand, energy classified as heat dissipation is classified as wasted energy because it simply dissipates heat from the cylinder heater and does not add value to the material and is not essential under the current specification conditions.

[0086] As another specific example, an example of cutting will be described. FIG. 13 shows step-by-step operations of a cutting device for cutting off a target material in cutting. In this device, a material 1101 is placed on a stage 1103. When processing starts, a cutting tool 1102 is set at a predetermined position relative to the material 1101 in process (A), a cutting operation is performed in process (B), and after cutting of a specific portion is completed in process (C), the posture of the material is reversed to cut another portion in process (D). In a general cutting device, this reversing operation is performed by an operator grabbing and reversing the material. After the material 1101 is reversed, the cutting tool 1102 cuts the target portion in process (E), an article with the target shape is completed, and the cutting process is completed.

[0087] For this series of processes, the classification processing unit 3 classifies the energy consumption from the perspective of the operation content by time and the energy consumption content of the operations performed by the units that make up the equipment. The energy classified from the perspective of the operation content by time is associated with either net energy, incidental energy, or wasted time shown in Figure 4. On the other hand, the energy classified from the perspective of the energy consumption content is associated with either net energy, incidental energy, or wasted energy shown in Figure 4.

[0088] First, the criteria by which the classification processor 3 classifies the measured energy consumption according to the breakdown of operation contents by time will be explained. When a non-defective product that meets the quality standard is obtained by the process described with reference to Fig. 13, the energy was consumed during the time period when added value was added to the material, so the classification processor 3 classifies the energy as time-net, as shown in Fig. 5. When a defective product is obtained, the defective product does not add value and is not essential for production activities under the current conditions, so the classification processor 3 classifies the energy as time waste. On the other hand, the energy consumed by the equipment during idling operation during the time when the part number is changed and the setup is changed to cut a part of a different shape is necessary under the current conditions but does not add value to the material, so the classification processor 3 classifies the energy as time-related.

[0089] Next, the criteria by which the classification processor 3 classifies the measured energy consumption according to the content of energy consumption will be explained. The energy consumed by the machining motor, which is a component unit of the cutting device, to make the cutting tool cut the material is classified as net. This is because the added value of cutting the material and processing it into the desired shape is created in the process.

[0090] For example, to provide a raw material with the function of a bracket, which is a support part for connecting parts, the initial rectangular parallelepiped shape shown in Fig. 13(A) cannot fulfill the intended function, and it is necessary to process it into an S-shaped shape as shown in Fig. 13(E). Therefore, the classification processing unit 3 classifies the operation of the cutting device into a net operation, such that added value is added to the material by the energy for the processing. Then, the energy consumed by the cutting device for this operation is classified into net energy.

[0091] Regarding the posture reversal performed when going from process (C) to process (D), the cutting tool is once removed from the material, the stage is moved to the posture control position, and then the posture of the material is manually reversed by the operator. The energy required to drive the stage at this time is necessary in the current device configuration, but since it is not an operation that directly adds value in the form of the targeted removal processing, the classification processing unit 3 classifies the energy required for this as energy-related.

[0092] In addition, if the worker is idling the cutting tool while rotating when reversing the position, the non-defective machining time is further classified. The energy consumed by the equipment while idling is not essential for the current equipment configuration and is not necessary for production, so the classification processing unit 3 classifies the energy as wasted energy.

[0093] Furthermore, when the cutting tool is rotated by the motor without contacting the material during the transition from process (A) to process (B), this idling is a necessary operation for the cutting tool to reach the desired rotation speed from a stopped state. Therefore, the classification processing unit 3 classifies the energy consumed by idling as incidental energy. In this way, the energy classified as net, incidental, or waste in the higher classification of the value-added DB209 can be classified more finely by relating it to the energy consumption content of the unit operation recorded in the consumption content DB211.

[0094] Specifically, net energy, incidental energy, and energy waste can be extracted as part of the components that make up net, incidental, and waste. By combining this classification based on energy consumption content with the classification based on the breakdown of operation content by time described above, the net of the higher-level classification (higher hierarchical level) can be further classified into net time and net energy, as shown in Figure 4. Similarly, incidental of the higher-level classification can be further classified into incidental time and incidental energy, and waste of the higher-level classification can be further classified into waste of time and waste of energy.

[0095] In addition, in Fig. 6, the units are classified in association with the energy consumption content, but the equipment and the energy consumption content may be classified in association with each other. For example, if the equipment is composed of a single unit, the equipment granularity (the unit that distinguishes each equipment) and the unit granularity (the unit that distinguishes each unit) are equal, so the equipment and the energy consumption content can be directly linked. On the other hand, even if the equipment is composed of multiple units, if the operation is roughly classified, the measured energy consumption may be classified into net energy, incidental energy, and wasted energy based on the energy consumption content for the operation of the entire equipment.

[0096] As described above, according to this embodiment, the measured energy consumption can be classified by interrelating each DB constituting Gr.2 and each DB constituting Gr.4 of the energy use condition input unit 2 shown in Fig. 1. That is, the building DB204, workplace DB205, equipment DB206, and unit DB207 classified in Gr.2 are interrelated with the added value DB209, operation details DB210, and consumption details DB211 classified in Gr.4 to classify the energy consumption.

[0097] With this configuration, energy consumption can be classified vertically according to the hierarchical items in the facility's operation system (e.g., workplace, equipment, unit).Furthermore, energy consumption can be classified horizontally according to the level of waste (e.g., net, incidental, waste) based on the added value items linked to the operation details by time or energy consumption details of these hierarchical items.

[0098] Next, with reference to the flowchart in FIG. 7 and the block diagram in FIG. 1, a process flow will be described in which the classification processing unit 3 classifies the energy consumption inputted to the energy consumption input unit 1 based on a plurality of types of items recorded in the energy use condition input unit 2 and displays the processing result.

[0099] In step S1, the information processing device of this embodiment accepts energy data input by a user and acquires the energy data. First, the user inputs energy data to the energy consumption input unit 1 from an energy management system (EMS) or a current sensor installed in the building, or a watt-hour meter installed in the facility. The input data is time-series power data, and is recorded in units of kWh, for example. The time resolution for recording the energy data is input power data measured every second, every minute, every hour, every day, every month, or the like. Alternatively, the energy information processing device and the EMS installed in the facility may be connected on a server, and the time-series energy data acquired by the distribution board may be automatically input. Similarly, the energy data acquired by a current sensor installed in the facility or a watt-hour meter installed in the facility may be automatically input to the energy consumption input unit 1.

[0100] Next, in step S2, the information processing device of this embodiment accepts input of a period by the user and acquires information related to the period. The user inputs information on the period from when to when the energy consumption is to be visualized in the time-series energy data. The period can be any period such as one year, one month, one week, one day, one hour, one minute, etc., depending on the purpose. For example, by visualizing (displaying) the total consumption for one year, it is possible to grasp an overall view of the energy consumption of the entire facility. If the period range is set to one year, the granularity of the scale displayed in the time-series graph may be set to one month to display the monthly transition. Alternatively, the period may be set to two weeks, the granularity of the scale may be set to one week, and a comparison of the energy consumption of the previous week and this week may be visualized (displayed). In this way, the PDCA (Plan, Do, Check, Action) cycle of the energy reduction activity of each workplace can be executed every week. Alternatively, the period range may be set to one hour, and the granularity of the scale may be set to one second, so that the transition of the energy consumption can be tracked in real time.

[0101] Next, in step S3, the information processing device of this embodiment accepts the user's selection of the visualization mode and acquires information related to the selection of the visualization mode. The user selects the visualization mode according to the purpose of analyzing the energy consumption based on which classification item from the energy use condition input unit 2 shown in FIG. 1. If the data input to the EMS is used as is, the amount of energy consumption (power amount) during the period selected by the user can be visualized for each substation, each distribution board, and each distribution board using data with the selected time resolution. The information processing device of this embodiment is characterized in that the data is classified according to the classification items of the classification groups Gr.2, Gr.3, and Gr.4, and the energy data is reconstructed. For this classification process, multiple classification items are prepared in the database in advance. Then, information that is the axis of classification, that is, the axis for the purpose of analysis on which the energy consumption is to be visualized, is specified. In this embodiment, the specification of the classification conditions is called the visualization mode for convenience.

[0102] For example, when reconstructing energy data based on two classification items, the workplace DB205 of Gr.2 and the use DB208 of Gr.3, the visualization mode is configured as a visualization mode by workplace and use. In this mode, the energy consumption is visualized for each workplace recorded in the workplace DB205, and the same energy consumption is visualized by use.

[0103] Next, in step S4, the information processing device of this embodiment executes a classification process of energy consumption based on the visualization mode selected in step S3. For example, in the case of the visualization mode by workplace / purpose, the classification processing unit 3 first classifies the energy consumption belonging to each category of the workplace information recorded in the workplace DB 205, that is, the workplace names such as the molding workplace, electrical equipment workplace, fixing belt workplace, automatic assembly workplace, and manual assembly workplace in Fig. 2. As a calculation process for processing this classification, for example, the energy consumption of one distribution board is calculated by apportioning it using the apportionment rate linked to the workplace name recorded in the workplace DB 205, or the sum of the energy consumption of multiple distribution boards is calculated.

[0104] Next, the classification processing unit 3 classifies the usage information recorded in the usage DB 208. That is, the energy consumption is classified based on each item of usage such as infrastructure system and production system in the higher classification in Fig. 3, and lighting system, air conditioning system, other infrastructure system, heat system, drive system, air system, vacuum system, other production system, etc. in the lower classification. As a calculation process for this classification, for example, the energy consumption of one distribution board is calculated by apportioning it using an apportionment rate linked to the usage name in the usage DB 208 and recorded, or the sum of the energy consumption of multiple distribution boards is calculated.

[0105] In this way, for example, the energy consumption amount belonging to the molding workplace and the heat system can be output as numerical data based on the two classification items of workplace and use. In the information processing device of this embodiment, the classification processing unit 3 classifies the energy data for other workplaces and uses in the same way, and outputs the reconstructed energy data to the display unit 4.

[0106] Next, in step S5, the information processing device of this embodiment graphs the energy data classified by the classification processing unit 3, for example, by workplace, and displays it on the display unit 4. For example, as illustrated in FIG. 8, a graph is created and displayed so that the user can easily understand which workplace and which purpose consumes a lot of energy. FIG. 8 is a graph of energy consumption by workplace and purpose visualized as a stacked bar graph, and shows the annual energy consumption of a production factory. In FIG. 8, the horizontal axis shows the classification of workplaces, and the vertical axis shows the classification of purposes, and textures such as horizontal and diagonal lines are used to display the type of energy consumed in each workplace in the entire facility over the course of a year in an easy-to-identify manner. In this example, the texture of the graph is used to improve the distinguishability, but the display mode in this embodiment is not limited to this, and each purpose may be displayed by distinguishing it by color, for example. In addition, the period may be any period selected in step S2 according to the purpose of the energy reduction activity.

[0107] In FIG. 8, an example of visualizing a specific period is shown, but the user may input two different periods, and the classification processing unit 3 may select the energy consumption corresponding to each period and display the energy consumption on the display unit 4. For convenience of explanation, an example in which the number of workplaces is five is shown, but in the case of a large-scale production factory, for example, the number of workplaces may be greater. In addition, the uses are not limited to the example described, and for example, use groups such as a vacuum system, a light source system, and an electronic device system may be extracted from other production systems and listed as classification items in parallel with a heat system, a drive system, an air system, etc.

[0108] In Fig. 2, a facility is composed of multiple buildings, and multiple workplaces are organized in each building. In such a case, the energy consumption by workplace may be aggregated within the range of each building, and the energy consumption by building may be displayed. In addition, in Fig. 2, the workplace hierarchy has a hierarchy of processing workplaces and assembly workplaces, and the hierarchy below the processing workplace has a multi-layer hierarchy of molding workplaces, electrical equipment workplaces, and fixing belt workplaces. In this case, the energy consumption may be classified and visualized in the hierarchy of molding workplaces, electrical equipment workplaces, and fixing belt workplaces, or the energy consumption may be visualized in the hierarchy of higher processing workplaces and assembly workplaces. In some facilities, organizational hierarchies such as sections and departments exist, and similarly, the hierarchy of sections and departments can be arbitrarily selected to classify and display the energy consumption. Alternatively, the classification unit of energy consumption may be determined based on the concept of place rather than organization, such as the entire first floor of A1 building, which includes the molding workplace, and the entire second floor of A1 building, which includes the electrical equipment workplace, and visualized. Alternatively, a part of the first floor of A1 building may be defined as the first area, the second area, etc., and the energy consumption may be visualized for each area within a specific floor. In this way, it is possible to visualize energy consumption at any organizational or location hierarchy, as shown in the example of Figure 2.

[0109] Users can get a comprehensive understanding of the energy consumption of the entire facility by referring to the graph of energy consumption categorized by workplace and application shown in Fig. 8. Furthermore, they can understand which workplaces in the entire facility have the highest energy consumption and prioritize energy reduction activities. For example, in the visualization results shown in Fig. 8, the molding workplace has the highest energy consumption, followed by the electrical equipment workplace, the fixing belt workplace, the automatic assembly workplace, and the manual assembly workplace. Therefore, when reducing energy, it is possible to prioritize the allocation of personnel and money, which are the resources for reduction activities, to the molding workplace, thereby achieving greater reduction effects in a shorter time.

[0110] If only the consumption amount based on the energy flow measured for each distribution equipment such as a distribution board were visualized, it would be impossible to determine the priority of each workplace. For this reason, organizations (activity units) with low energy consumption, such as manual worksites, would also be forced to work on reduction activities at the same time, which would tend to disperse limited resources. In contrast, by using the information processing device of this embodiment, such a decrease in return on investment can be suppressed.

[0111] 8 shows an example in which the horizontal axis of the graph represents workplaces input to the workplace DB 205, and the vertical axis represents energy consumption. As another example, because time-series energy consumption data is input to the energy consumption input unit 1, the horizontal axis may be used to display the transition of energy consumption for any organizational hierarchy, with the horizontal axis representing time and the vertical axis representing energy consumption.

[0112] FIG. 9 shows the trend of energy consumption throughout the facility to be visualized. The horizontal axis is month, and displays the actual monthly energy consumption. The first vertical axis on the left side of FIG. 9 represents the actual energy consumption for a single month, shown as a stacked bar graph by use. The second vertical axis on the right side of FIG. 9 represents the cumulative actual energy consumption, shown as a line graph. For example, the line graph plot for February is the sum of the actual values ​​for January and February, and the line graph plot for December is the sum of the actual values ​​from January to December. When displayed in this way, users can easily grasp the trend of the actual energy values ​​of any organization by use.

[0113] In Fig. 9, the energy consumption of the entire facility is selected and displayed, but a specific workplace such as the molding workplace may be selected. Also, the horizontal axis is in months, but the time granularity may be finer and the trend in energy consumption may be displayed in units of days, hours, minutes, seconds, etc. If the energy consumption input unit 1 receives data that is updated in real time, less than once per second, the display unit 4 can track and display the trend in energy consumption of any equipment in real time. Also, the selection of the equipment is not limited to one, and multiple pieces of equipment may be selected and displayed simultaneously to compare the trends in energy consumption of different equipment.

[0114] Alternatively, instead of inputting the actual energy consumption value into the energy consumption input unit 1, the planned energy consumption value may be input, and the transition of the planned value may be displayed. Furthermore, the classification processing unit 3 may select both the planned value and the actual energy consumption value, and the planned value and the actual energy consumption value may be displayed on the display unit 4 so that they can be compared. In this way, for example, it is easy to check whether the actual energy consumption value is within the planned energy consumption value set at the beginning of the year. For example, if it is displayed in June that the accumulated value as of June of the year exceeds the planned value, the plan can be revised to reduce the consumption between July and December of the year and to bring the accumulated actual value as of December into the plan at the beginning of the year. In this way, the planned and actual energy consumption can be managed.

[0115] In order to analyze the high priority areas of energy reduction activities, the user can return to step S3 and select the visualization mode by equipment and operation content for a workplace such as a molding workplace that has a high priority due to its large energy consumption. When the visualization mode by equipment and operation content is selected, the classification processing unit 3 in FIG. 1 refers to the classification of equipment information recorded in the equipment DB 206 and the time-series energy data input to the energy consumption input unit 1. The classification processing unit 3 extracts energy data for each equipment acquired by equipment equipped with a current sensor or a watt-hour meter from the referred energy data. For example, when reducing energy waste in a molding workplace, the energy data of the 1000t molding machine in FIG. 2 is selectively extracted. Then, the energy of the 1000t molding machine is classified by operation content based on the breakdown of operation content by time recorded in the operation content DB 210 shown in FIG. 5.

[0116] Next, in step S4, the information processing device executes classification processing using added value in the added value DB 209, in which the relationship between the operation content and the operation content is defined in advance. Fig. 10(A) and Fig. 10(B) show examples of visualization by equipment and operation content, which are classified by visualization mode by equipment and operation content and output by the display unit 4.

[0117] Figure 10(A) is a graph showing the energy consumption of a 1000t molding machine over time, with the vertical axis representing power consumption (kW) and the horizontal axis representing time (h), and is broken down by equipment and operation type, and plotted as area based on power consumption (kW) x time (h) = electric energy (kWh). When applying the hierarchical classification items in Figure 5, the energy consumed by the 1000t molding machine during planned shutdown and start-up is classified as time waste, that is, waste based on the breakdown of operation type by time. In addition, the energy consumed during the non-defective product processing time period is classified as time net, and the energy consumed during the changeover time period is classified as time incidental.

[0118] Figure 10(B) shows a stacked bar graph in which the results of classifying the waste levels by time in Figure 10(A) are tallied as the total consumption of a 1000t molding machine. This makes it possible to tabulate the amount of wasted energy consumed by a specific piece of equipment over a certain period of time.

[0119] In this way, the information processing device of this embodiment can analyze the level of waste based on added value among the energy consumed by a specific facility over a certain period of time, so that the user can implement reduction measures that are prioritized. For example, as a result of visualizing the graph in FIG. 10(A), it can be easily determined that the energy during the time periods of planned shutdown and start-up does not add value to materials and is a "waste of time" that is not essential even under the conditions of using the current facility. Therefore, the user can immediately implement measures such as turning off the power during those time periods.

[0120] These measures have a higher return on investment in terms of time and cost than measures such as changing the design of injection molding machines to energy-saving specifications to reduce the "time-related" changeover time, or using insulation to prevent heat loss to reduce the "time-related" changeover time. As a result of visualizing the analysis results, in this example, the user can make the decision to eliminate time waste before time-related, and prioritize cost-effective reduction activities.

[0121] Alternatively, based on the visualization result in Fig. 10(B), the amount of time waste is greater than the amount of time-related energy consumed by the 1000t molding machine in a certain period, so the user can easily determine that time waste should be reduced first. In this way, the information processing device of this embodiment can provide and display information related to the judgment criteria for reducing wasteful energy consumption by prioritizing reduction measures in consideration of return on investment.

[0122] In Fig. 10(B), the visualization results for a single piece of equipment, a 1000t molding machine, are shown as a stacked bar graph, but as in Fig. 11, stacked bar graphs for multiple pieces of equipment can be arranged side by side to compare the amounts and percentages of net, incidental, and waste between pieces of equipment. For example, graphs for a 1000t molding machine and a 650t molding machine can be arranged side by side for comparison. Alternatively, the net, incidental, and waste classification results for multiple molding machines, such as a 1000t molding machine and a 650t molding machine, can be summed up, and the classification results can be grouped together as the molding workplace, which is a higher level than the equipment, and displayed as a stacked bar graph.

[0123] In the breakdown of the operation contents by time shown in FIG. 5, the operation contents DB 210 is configured so that the time of the changeover is, for example, time-related, but the time period may be further subdivided into changeovers within standard time and changeovers outside standard time. The time within standard time refers to a time set in advance for each device in the workplace within which the changeover should be completed. The operation contents DB 210 may be configured so that a changeover that falls within the standard time is classified as time-related, and a changeover outside standard time is classified as time waste if the changeover is prolonged beyond the standard time. Similarly, start-up, start-up, regular PM, daily inspection and cleaning, adjustment, and replacement and replenishment of consumables may also be subdivided into within standard time and outside standard time, and classified as time-related if it is within standard time and as time waste if it is outside standard time.

[0124] By setting the standard time in this way, the threshold for determining whether something is time-related or time-wasteful can be adjusted according to the characteristics of the workplace and the equipment. For example, a standard start-up time is set in advance for equipment that must stabilize its temperature for a certain amount of time before starting processing, and the classification processing unit 3 classifies that time as time-related. If the standard time is exceeded, the classification processing unit 3 can perform a detailed analysis to determine that this is not caused by the equipment, but is time-wasteful due to the extended start-up time caused by human error or the like. Alternatively, for equipment that completes start-up before processing immediately after being turned on, the standard time can be set to zero, and all start-up time can be set as wasteful, and the threshold for classifying operation time can be adjusted in this way.

[0125] As another example, energy reduction measures in the case of cutting processing will be described. In the information processing device of the embodiment, the energy consumed by the cutting processing device while idling during the time period when the changeover is performed is classified as time-related. By checking the results visualized by the information processing device, the user can determine that the time-related energy can be reduced by reducing the changeover time.

[0126] For example, it can be determined that a reduction measure would be to organize and arrange materials for the next part number in advance so that they can be easily fed into the equipment during the processing time for a non-defective product before the changeover. Alternatively, there are cases where manual work requires many changeovers in order to produce a wide variety of products, which takes a lot of time. In such cases, it can be determined that the energy consumed by the automatic transport device can be reduced more than the energy consumed during idling by attaching the automatic transport device to the cutting equipment. This reduces the energy associated with time.

[0127] Alternatively, by checking the results visualized by the information processing device, the user can determine that it is effective to improve the yield rate of parts produced by the cutting machine in order to reduce time waste, which is the energy consumed in processing defective products. In this embodiment, the energy of one piece of equipment is classified in the visualization mode by equipment and operation content, but the energy of multiple pieces of equipment, such as a 1000t molding machine and a 650t molding machine, may be classified by equipment and visualized (displayed). The user may decide which energy to prioritize by comparing the two based on the visualized graph. In addition, since the user can arbitrarily select the measurement period, for example, one week may be selected to compare the operation content of this week and last week, or one year may be selected to compare from a long-term perspective. In addition, a graph of the energy data of the equipment may be visualized in a unit time finer than the time resolution shown in FIG. 10(A), for example, every second.

[0128] In the visualization mode by equipment and operation contents, the classification processing unit 3 can classify and process the energy of multiple equipment by operation contents, but generally, production equipment is often operated as a group of multiple equipment. For example, in the case of a molding machine, not only the 650t molding machine itself is operated, but a set of auxiliary equipment such as a mold temperature regulator for the 650t molding machine and a plastic material dryer for the 650t molding machine are arranged and operated together with the 650t molding machine. In such a case, the details of the operation contents by time may be recorded separately for the three types of equipment in the operation contents DB 210, but since these equipment are operated to process the same parts, the operation contents will end up being the same. Therefore, among the equipment names recorded in the equipment DB 206, a group of equipment having the same operation contents by time may be grouped together as an equipment group (equipment Gr.) and recorded in the equipment DB 206. Similarly, a set of operation details may also be recorded in the operation details DB 210, and the classification processing unit 3 may classify the operation details of the equipment group by associating the equipment DB 206 with the operation details DB 210. Alternatively, both the equipment group and individual equipment may be recorded in the equipment DB 206, and classification processing may be performed for both individual equipment and equipment groups.

[0129] In this way, the efficiency of classification processing can be improved when operation details by time overlap. Or, in some workplaces, operation details by time are recorded only for the 650t molding machine itself. In that workplace, even if there is no operation details for ancillary equipment such as a mold temperature regulator or a plastic material dryer, classification processing can be performed as an equipment group based on the fact that they are operating together.

[0130] Next, the user selects a visualization mode by unit / consumption content for the energy classified by time net as a result of the above mode, and executes classification processing and graph display in the same manner as the above-mentioned flow. That is, the information processing device of the embodiment accepts the selection of the visualization mode by the user, and executes classification processing and graph display according to the selected mode.

[0131] The classification processing unit 3 in Fig. 1 refers to the classification items recorded in the unit DB 207 and the consumption content DB 211. Then, based on the referred classification items, the classification processing unit 3 further classifies the energy consumption classified on a net hourly basis among the classification results visualized by equipment and operation content in the previous visualization mode. Specifically, the classification results are classified based on the type of energy consumption content consumed by the operation performed by the unit on the target part.

[0132] In the visualization mode by unit and consumption, energy data measured by a current sensor or a watt-hour meter installed in each unit constituting the 1000t molding machine, such as a cylinder heater and a metering motor, is input to the energy consumption input unit 1. The classification processing unit 3 extracts only the energy consumption classified as net per hour from the energy data visualized in the visualization mode by equipment and operation as described above. At this time, the net per hour energy is stored in a database in mutual association with the energy data measured for each unit. In other words, the consumed energy classified as net per hour can be reclassified according to which unit consumed the energy. This allows more detailed classification into types of added value according to the energy consumption by the operation of each unit shown in Figure 6.

[0133] For example, the energy consumed by melting material in a cylinder heater is classified as net energy because it is energy that acts directly to change the state of the workpiece and adds value to the material. Energy that escapes into the air through heat radiation is classified as wasted energy because it does not add value and is not essential under the current conditions. Energy consumed by weighing parts is classified as incidental energy because it does not add value but is necessary under the current conditions, i.e., the current equipment configuration.

[0134] In Figure 6, the melting action performed by the cylinder heater is associated with two energy consumptions: material melting and heat dissipation. This is because even a single unit operation can be classified into two energy consumptions. In such cases, first, the energy equivalent to the net energy is calculated as a theoretical value from the theoretical formula for the thermal energy required for melting. Next, the difference obtained by subtracting the theoretical value from the energy consumption measured for each unit is classified as energy waste due to heat dissipation.

[0135] For example, when subclassifying melting, the net energy can be calculated using the following formula (1). Q = mcΔT (1) however, Q: Amount of heat required for melting (J) m: mass of material (kg) c: specific heat of the material (J / kg K) ΔT: Temperature change required for melting (K) It is.

[0136] Alternatively, when subclassifying, for example, conveying equipment as a unit belonging to the use of a drive system, the net energy can be calculated from the kinetic energy required to convey a part using the following formula (2). E=1 / 2mv 2 (2) however, E: Kinetic energy required for transport (J) m: mass of material (kg) v: conveying speed (m / s) It is.

[0137] Furthermore, if there is a difference in height at the position where the parts are held during the part transport process, the accuracy of calculating the net energy may be improved by considering not only the kinetic energy of mechanical energy but also potential energy. Alternatively, for units classified as electronic equipment, the net energy may be calculated from electrical energy. For units classified as light source, the net energy may be calculated from a theoretical formula for optical energy.

[0138] On the other hand, the energy required for weighing parts, which is the operation of the metering motor, is not classified as net energy because it does not add value, but is not classified as wasted energy because it is an operation necessary for molding materials. Therefore, all of the energy consumption measured by the metering motor as a unit can be classified as "energy-related" without going through arithmetic processing based on theoretical calculations. In this way, in the classification according to this embodiment, the energy consumption details are classified according to the type of operation performed by the unit, and the classification items are stored in the consumption details DB 211.

[0139] Figure 12 is an example of visualization of the classification results by unit and consumption content, which can be displayed on the display unit 4 in Figure 1. In Figure 12, the hourly net energy, which is classified and displayed in the previous visualization mode by equipment and operation content, is further classified into energy waste, energy incidental, and net energy in the visualization mode by unit and consumption content. Based on the classification results visualized by the information processing device, the user can more accurately analyze energy waste, prioritize it, and implement waste reduction.

[0140] For example, among the units shown as examples, the heat radiation energy that is classified as energy waste due to the operation of the cylinder heater can be reduced by insulating the cylinder. By insulating the cylinder by installing an insulating cover, the user can reduce waste with a relatively high cost-effectiveness in terms of net time. In other words, if the perspective of classification is changed, it can be seen that "energy waste" is hidden in the net time obtained by classification by operation content. According to the information processing device of this embodiment, this can be classified in stages and hierarchically and visualized, so that the user can accurately and precisely extract energy waste and find reduction measures.

[0141] As for the energy classified as incidental energy caused by emissions in Figure 6, one measure to reduce it is to modify the exhaust unit to one that is more energy efficient than the current one. However, since modifications take more time and money than installing a heat insulating cover on the cylinder heater mentioned above, users can determine that it is more cost-effective to make this the second priority and to carry it out in stages.

[0142] To give another example, the energy of melting materials, classified and visualized in terms of net energy, is necessary to add value to the material, so users can determine that it is a low priority for reduction. On the other hand, it is not impossible to reduce net energy, and it can be said that by changing to a material that melts at a lower temperature, it is possible to reduce net energy. However, since the material properties of the molded parts produced by the molding machine also change when the material is changed, it is necessary to carry out functional and quality assurance tests of the final product in which the molded parts are installed before making the change. Therefore, by deliberately lowering the priority, the cost-effectiveness of the overall energy reduction activities carried out for the molding machine can be maximized.

[0143] As another example, the case of a cutting machine will be described. During the posture reversal described with reference to FIG. 13, the energy required to drive the stage to move the material to a position where manual work is possible is classified as energy-associated. In order to reduce this energy, for example, it is possible to configure the device so that the cutting tool can contact the material from the back side of the stage. As shown in FIG. 14, the shape of the material gripping part can be configured so that it can grip the position of the material that is not to be removed, and the cutting machine can be equipped with this. In addition, the energy consumed by the cutting tool running idle during posture reversal is classified as energy-associated. If the material holding part is configured so that the cutting tool can contact it from the back side, the posture reversal operation is not required, and this energy can also be reduced at the same time. Alternatively, in the case of a part with a complex shape in which a material gripping shape that does not require posture reversal cannot be configured, the stage itself must be used as shown in FIG. 13. However, if the rotation of the cutting tool during the posture reversal operation is stopped and restarted after the end of the reversal operation, and the motor is replaced with one that can operate stably even if the rotation speed of the cutting tool is suddenly increased to the desired speed, the energy classified as energy-associated can be reduced. If this measure is applied to the energy consumed by the idling rotation between process (A) and process (B) when the cutting tool comes into contact with the material, it is possible to similarly reduce energy consumption by shortening the idling time.

[0144] By broadly applying this concept to equipment other than molding machines, workplaces other than molding workplaces, and other buildings, it is possible to prioritize the reduction measures for the entire large-scale production factory. Although it is theoretically not impossible to simultaneously implement all possible energy reduction measures, this requires large-scale personnel and investment. If the energy consumption of a facility can be reduced, the effect in terms of reducing the burden on the environment is great, but the cost reduction effect obtained by this is not necessarily large, depending on the unit price of electricity. In view of this, it is effective to clarify the cost-effectiveness by classification processing and to prioritize and implement reduction measures. Furthermore, since a production factory plays a role of producing products in large quantities more quickly and more cheaply, there are cases in which large-scale investments cannot be easily implemented just because energy can be reduced. In view of such characteristics of a production factory, the classification processing executed by the information processing device of this embodiment allows the user to set industrially useful priorities.

[0145] In the information processing device of this embodiment, at least three types of visualization modes are accepted in the selection of the visualization mode in step S3 of FIG. 7, namely, a visualization mode by workplace and use, a visualization mode by equipment and operation content, and a visualization mode by unit and consumption content. Although the embodiment has been described in which these modes are performed serially and sequentially, only one of the above modes may be executed. Alternatively, the information processing device may execute a plurality of modes separately in parallel. In the above example, the visualization mode by unit and consumption content is applied only to the time net energy screened in the first visualization mode based on the execution result of the visualization mode by equipment and operation content. On the other hand, instead of executing the visualization modes serially, the visualization mode by unit and consumption content may be executed in parallel processing for all of the time waste, time-associated, and time net, which are the results of the visualization mode by equipment and operation content. In this case, the time-associated can be further classified into energy waste, energy-associated, and energy net based on the energy consumption content caused by the operation of each unit. This allows the user to extract energy waste more accurately and precisely and implement reduction measures.

[0146] Moreover, the visualization modes executed by the information processing device of this embodiment are not limited to the above three types. For example, any of the items in Gr.2, Gr.3, and Gr.4 in FIG. 1 may be selected within the range of at least two items. The order may be reversed, and the items may be executed either serially or in parallel, and there is no limitation thereto.

[0147] For example, the overall energy consumed by the facility may be classified based on the use in the use DB 208, and also based on the operation content DB 210. For example, a turbo chiller that supplies chilled water to the entire facility may be centrally managed as an air conditioning use. For this reason, after classifying the entire facility by use, rather than by workplace, energy waste may be classified in association with added value, as shown in Figure 5, based on the breakdown of operation content by time as a centrally managed facility. In this case, the user can easily find measures that cover the entire facility, such as turning off the power to the turbo chiller, during planned shutdowns of the entire facility.

[0148] Alternatively, if the information processing device classifies the air conditioning system by workplace and the visualization mode by workplace and purpose identifies a workplace where the air conditioning load is high locally due to the concentration of heat-generating equipment, the user may install a packaged air conditioner that acts locally in that workplace. This allows the entire facility to be kept at a comfortable temperature without having to operate a large turbo chiller to the limit of its rated power, resulting in cost-effective energy reduction.

[0149] Alternatively, the measures that the user finds as a result of visualizing the classification process using one of the visualization modes described above by the information processing device may be deployed across and commonly to buildings, workplaces, equipment, and units that belong to the same purpose. For example, if the equipment that handles the melting process in the thermal system is also located in places other than the molding workplace in Figure 2, such as the reflow furnace in the electrical equipment workplace or the electric furnace in the fixing belt workplace, it is possible to implement heat dissipation measures, which are the same thermal reduction measures.

[0150] Therefore, if the reduction measures found by the user are recorded in a database (not shown) provided in the information processing device of the embodiment in association with the purpose, workplace, equipment, unit, and type of added value, the reduction measures can be deployed across purposes, workplaces, equipment, and units. Also, if the reduction measures are stored in the database in association with the purpose, workplace, equipment, and unit, and a recommendation display unit is further provided that, when the user selects a specific purpose, recommends and displays on the display unit the reduction measures associated with the purpose, the cross-sectional deployment of reduction measures becomes easy.

[0151] As described above, the information processing device according to the embodiment accepts and stores the settings of multiple types of classification items for classifying power consumption in a facility. Information (e.g., measurement data) related to power consumed in the facility is acquired, and classified based on at least two or more classification items selected by the user. Each of the multiple types of classification items is hierarchically configured, and can include the following specific examples.

[0152] First, the multiple types of items may include a hierarchically configured power system (e.g., a substation, a distribution board, a switchboard, etc.). Furthermore, the multiple types of items may include items (e.g., a building, a workplace, a facility, a unit constituting a facility, etc.) hierarchically classified based on an operation system of a facility whose configuration does not necessarily match that of a power system.

[0153] In addition, the multiple types of items may include energy usage items (e.g., thermal system, drive system, air system, vacuum system, etc.) that are applied across one or more levels of the facility and are categorized according to the energy consumption content consumed on that level.

[0154] Furthermore, the multiple types of items may include value-added items (e.g., net, incidental, waste, etc.) that are applied across one or more levels of the facility and are created according to the operation or energy consumption of the level. Value-added items may be classified as a criterion for prioritizing energy reduction. For example, when analyzing power consumption related to the manufacture or processing of goods, "net" as a value-added classification item is set corresponding to essential work content and time that directly contributes to the manufacture or processing. Since "net" corresponds to essential or equivalent power consumption, it is treated as a lower priority than "waste" and "incidental" in terms of the priority for considering energy reduction.

[0155] The information processing device of the embodiment accepts and stores a combination of classification items selected by a user from among these multiple types of hierarchical classification items. Then, information (e.g., measurement data) related to the electricity consumed by a facility or the like is acquired, and the information is classified based on the selected combination of classification items. When classifying, the consumed electricity may be distributed to each classification item according to a preset proportional distribution ratio.

[0156] The information processing device can store the classification results and can display information related to the classification results on the display unit. The classification results can be displayed on the display unit as a graph linked to the classification items, for example, so that the user can easily understand intuitively. The information processing device may display prioritization according to added value items (for example, net, incidental, waste, etc.) to serve as a guide for the user when considering energy reduction.

[0157] The information processing device can transmit information related to the classification results to an external device (for example, an external computer or database) via a network, store the information in a storage medium, or print the information on a printing device.

[0158] According to the information processing device of the embodiment, the total energy consumption of a large-scale facility that consumes electricity can be comprehensively grasped, and waste can be visualized by associating it with buildings, workplaces, equipment, units, etc. that do not necessarily match the physical configuration of the power system. For example, by visualizing the order of consumption, it is possible to support a user in considering cost-effective reduction measures for buildings, workplaces, equipment, units, etc. The user can, for example, deploy reduction measures across buildings, workplaces, equipment, and units that belong to the same energy use, and efficiently carry out energy reduction activities on a large scale.

[0159] [Embodiment 2] Fig. 15 is a schematic block diagram illustrating the configuration of an information processing device according to embodiment 2. In embodiment 2, in addition to the configuration shown in Fig. 1 of embodiment 1, a production volume DB 212 and a judgment coefficient DB 213 are provided. The production volume DB 212 and the judgment coefficient DB 213 belong to Gr.5 in the classification group information.

[0160] The production volume DB212 is a database that records information on the production volume of products or parts that constitute products produced in the building DB204, workplace DB205, equipment DB206, unit DB207, etc. of classification group Gr.2. The production volume DB212 records the name of a product or part, the production volume corresponding to the product or part, and the time when the product or part was produced in association with each other. In this way, the classification processing unit 3 can grasp, for example, what kind of product or part was produced, in what time period, and how many units (how many pieces) were produced for each workplace in the workplace DB205 by associating each classification item of classification group Gr.2 with each classification item of classification group Gr.5. The name of a product or part recorded in the production volume DB212 may be a name such as "Model A" or "Molded part A-1", or a part number (part number) in a format determined to identify the name, such as a symbol such as "1125".

[0161] The classification processing unit 3 associates the amount of power input to the energy consumption input unit 1 with the classification items of the classification group Gr.2 and the classification items of the classification group Gr.5, and calculates the energy intensity by the following formula (3). (Energy intensity) = (Amount of electricity) / (Amount of production) (3)

[0162] In equation (3), the amount of power in the numerator on the right side is a value calculated in advance by the classification processing unit 3 for each element that consumes power, such as a workplace or equipment, in the same manner as in embodiment 1, based on the association information. The production amount in the denominator on the right side of equation (3) is calculated by the classification processing unit 3 for each element that consumes power, such as the same workplace or equipment, as used when calculating the numerator, based on the association information in embodiment 2. The energy intensity on the left side obtained by equation (3) is the energy required to produce one product or one part.

[0163] The classification processing unit 3 displays the result of dividing the amount of power by the amount of production on the display unit 4, so that the user can be aware that power may be being wasted. For example, when comparing the energy consumption during production yesterday and today, the energy consumption today may be 90% of yesterday's, and it may appear that the energy consumption has been reduced by only 10%. However, the production volume has dropped to 80% compared to the previous day, so the energy consumption per product may be higher than the previous day. Specifically, the amount of power required for production yesterday was 100kWh and the amount of production was 10 products, while the amount of power required for production today was 90kWh and the amount of production was 8 products. In this case, the energy intensity yesterday = 100kWh / 10 products = 10kWh, while the energy intensity today = 90kWh / 8 products = 11.25kWh. If only the amount of power in the numerator, that is, the "amount" consumed, is known, it may appear that the energy consumption has been reduced, but by knowing the intensity, it is clear that the energy required for production per product has increased.

[0164] When the display unit 4 displays the calculated energy intensity in this way, the user recognizes the possibility that energy is being wasted, and can execute the visualization mode by equipment and operation content described in the first embodiment. The classification processing unit 3 associates and classifies the operation content and the energy consumption in a time series as shown in FIG. 10(A) by associating the equipment DB 206 with the value-added DB 209, and displays it on the display unit 4. At this time, the cause of the waste, that is, the increase in energy consumption during the planned stoppage as a result of the planned stoppage being longer than the previous day due to the effect of the production volume decreasing to 80% compared to the previous day, can be analyzed from the graph on the display unit 4. In the second embodiment, the situation in which the consumption amount is decreased compared to the comparison period, but the amount of waste per product is increasing, can be visualized and the cause can be analyzed. Furthermore, the classification items of the classification group Gr.2 and the classification items of the classification group Gr.5 are associated with each other. Therefore, the energy intensity can be grasped by selecting any element that consumes electricity from the classification items constituting the classification group Gr.2, such as by building, by workplace, by equipment, or by unit.

[0165] Depending on the workplace, it may be appropriate to use the weight of parts (kg) or processing time (min) as the denominator of the formula for calculating the energy intensity, rather than the number of units or the number of pieces. In that case, an arbitrary unit such as weight or processing time may be set as the unit of the production volume DB 212 in association with each workplace in the workplace DB 205. In addition, since the unit of the denominator of the energy intensity varies depending on the workplace, it may be difficult to calculate the energy intensity for a building as a whole. For example, in an assembly workplace, the denominator is the number of products (units), and in a molding workplace, the denominator is the weight of parts (kg), and it is not possible to simply add up the energy intensity. In such a case, a unified index that is proportional to the production volume, such as the sales amount of products or parts, may be used as the denominator. In this way, by providing multiple types of units for the denominator of the energy intensity, the energy intensity can be calculated at any level, such as a building, a workplace, equipment, or a unit.

[0166] Furthermore, since the production volume DB212 records information on part numbers, the energy consumption amount corresponding to the numerator of the energy intensity can be displayed in a stacked bar graph for each part number. At this time, by linking the workplace DB205 and the production volume DB212, a specific workplace can be selected and the energy consumption amount for each part number in the workplace can be displayed in a stacked bar graph. Alternatively, the horizontal axis can be time, and the energy consumption amount for each of a plurality of part numbers can be plotted in a time-series line graph for a specific period for comparison. Two different periods can also be selected, and the energy consumption amount for the two periods can be compared in a line graph for a specific part number.

[0167] Alternatively, the data to be input to the energy consumption input unit 1 may be a planned value of energy consumption, instead of an actual value of past energy consumption, so that the plan and the actual value can be compared for each part number. Also, by associating the energy consumption input unit 1 with the classification group Gr.2, the planned value can be displayed on the display unit 4 for each level such as a building, workplace, or equipment. Furthermore, the classification processing unit 3 can switch between displaying the planned value of energy consumption or the planned value of energy intensity.

[0168] In the second embodiment, the classification processing unit 3 calculates the standard value of the energy intensity unit using the value of the judgment coefficient DB 213, and by comparing the standard value of the energy intensity unit with the actual value of the energy intensity unit, it is possible to notify the user when the standard value is exceeded. This process will be described below.

[0169] The judgment coefficient DB213 records values ​​for adjusting the standard value of the energy consumption rate, which is used to determine the extent of normal energy usage and the extent of abnormal energy usage. Here, normal usage means that the energy required for production is used in a reasonable manner. Abnormal usage means that an abnormally large amount of energy is used due to incorrect production conditions, such as when the temperature setting of an injection molding machine is abnormally higher than a predetermined value, resulting in an abnormally large amount of energy usage compared to normal times. Alternatively, in the second embodiment, a situation in which the energy consumption per good product (finished product) is significantly higher than normal due to frequent production of defective products is also judged to be abnormal.

[0170] The classification processing unit 3 calculates the reference value of the energy intensity as shown in formula (4). (Standard value of energy intensity) = (amount of electricity) / (amount of production) × (determination coefficient) (4)

[0171] The judgment coefficient can be set at any level by the classification processing unit 3 associating the judgment coefficient DB213 of classification group Gr.5 with the classification items of classification group Gr.2. For example, the judgment coefficient can be set for each workplace by associating the judgment coefficient DB213 with the workplace DB205, or it may be set for each facility by associating it with the equipment DB206. Alternatively, the judgment coefficient may be set for each part number or product model name by associating the judgment coefficient DB213 of classification group Gr.5 with the production volume DB212 and the classification items of classification group Gr.2.

[0172] Figure 16 shows the daily energy intensity per part at the molding workshop. In the example in Figure 16, the standard value is 75 kWh, and a line is drawn at this standard value of 75 kWh from Monday, April 3rd to Friday, April 7th. Any energy intensity that exceeds the standard value is displayed in black as an abnormal value, and any that falls within the standard value is displayed in white as a normal value.

[0173] The classification processing unit 3 extracts the amount of power consumed in a given hierarchical level for a given period by associating the energy consumption input unit 1 with the classification group Gr.2. The classification processing unit 3 then extracts the production amount for that period and hierarchical level from the production amount DB 212 based on the association, and divides the amount of power consumed by the production amount. The classification processing unit 3 multiplies the divided value by a judgment coefficient, and for example, consider a case where the judgment coefficient is set to 1. In this case, the actual value of the energy intensity for the given period is adopted as the reference value. For example, the energy intensity for one month from Wednesday, March 1st to Friday, March 31st may be adopted as the given period, and the sum of the energy consumption for one month may be taken as the amount of power consumed in the numerator, and the sum of the part production amounts of the molding workshops for one month may be taken as the production amount in the denominator.

[0174] The classification processing unit 3 compares the actual value of the energy intensity with the reference value, and when the reference value is exceeded, displays the amount of the intensity that exceeds the reference value in a color-coded manner as shown in FIG. 16, and notifies the user. The notification method may be a graph display as shown in FIG. 16, or a notification by e-mail in addition to the graph display, or a notification to a smartphone or a smartwatch. In this way, the information processing device of the second embodiment can quickly detect a workplace that is consuming abnormally large amounts of energy based on the reference value of the energy intensity, and notify the user. In addition, since the classification group Gr.2 and the classification group Gr.5 are associated as in the configuration of FIG. 15, an abnormality can be notified at any level, such as a building, workplace, equipment, or unit.

[0175] Furthermore, since the classification group Gr.5 also records information on the product model name and part number, it is possible to judge whether an arbitrary model and part number are abnormal or normal. In addition, in Fig. 16, the energy intensity is calculated and displayed daily, but it is also possible to divide the amount of electricity for one week by the amount of production for one week, or the amount of electricity for one hour by the amount of production for one hour, and it is possible to calculate and display the energy intensity for any period. In this case, since the unit of the energy intensity is kWh / piece, the value of the standard value of the energy intensity is fixed as the energy per product or part, regardless of the granularity of the horizontal axis of the graph in Fig. 16, such as one hour, one day, or one week. Therefore, when the period and granularity of the display change, the standard value and the judgment result do not fluctuate up or down, and the display unit 4 can maintain the standard for judging normal and abnormal at a constant height unless the user changes it with the judgment coefficient.

[0176] Since time-series data is input into the energy consumption input unit 1 every moment, the classification processing unit 3 can judge production activities in real time and quickly notify the user of abnormal consumption. Upon receiving this notification, the user can quickly begin to review device settings, etc. Alternatively, as mentioned above, even if the amount of electricity appears to have been reduced by 90% compared to the previous day, but the production volume has fallen to 80% compared to the previous day, causing the energy intensity to increase, the classification processing unit 3 can also notify the user that the energy intensity is an abnormal value.

[0177] The judgment coefficient may be 1, but it may be set to a stricter value such as 0.8 based on the reduction target of the workplace, and the reference value may be set to a smaller value. The smaller the reference value is set, the more frequently the classification processor 3 will judge a value to be abnormal. For this reason, the judgment coefficient can be considered a value that adjusts the sensitivity for detecting abnormalities.

[0178] In the first embodiment, the amount of wasteful consumption is quantitatively visualized based on the priority order of energy usage, but the second embodiment is characterized in that it promptly issues a notification that a situation of wasteful consumption is occurring. Therefore, it is possible to combine the first and second embodiments to immediately detect a situation of wasteful consumption and then classify and display the amount of waste. Alternatively, if the user can visually recognize that the temperature setting of the molding machine is abnormal based on the notification, the process of extracting the amount of waste can be skipped and measures can be taken first, and reduction measures can be taken immediately. After that, the visualization mode by equipment and operation content of the first embodiment can be executed, and the effectiveness of the reduction measures can be verified by comparing the energy usage and wasteful consumption before and after the measures.

[0179] In the above, a method for determining whether a state is normal or abnormal by calculating a reference value for the energy intensity has been described, but a production factory does not necessarily operate continuously 24 hours a day, and in such cases, there may be cases where production volume data for the denominator of the energy intensity does not exist. In this embodiment, the time when production is taking place is defined as during operation hours, and the time when production is not taking place is defined as outside operation hours. Below, a method for determining whether a state is normal or abnormal outside operation hours will be described.

[0180] Outside of operating hours, the classification processing unit 3 obtains in advance from the energy consumption input unit 1 the power (kW) of the equipment outside of operating hours for a certain period of time, and adopts this power value as the power in a normal state.

[0181] Then, the classification processing unit 3 acquires a judgment coefficient from the judgment coefficient DB 213, and calculates the reference value of the power outside the operation hours by the formula (5). (Reference value of power outside operating hours) = (Power in normal state outside operating hours) × (Decision coefficient) (5)

[0182] Here, the unit of power is kW (kilowatt) or W (watt), and is used to distinguish it from the unit of electric energy, kWh or Wh. The power in a normal state outside operation hours can be set at any hierarchical level, such as a building, workplace, equipment, or unit, by the classification processing unit 3 associating the energy consumption input unit 1 with classification group Gr.5. The judgment coefficient can be set at any hierarchical level, as with the reference value during operation hours, by the classification processing unit 3 associating the judgment coefficient DB213 of classification group Gr.5 with the classification items of classification group Gr.2.

[0183] FIG. 17 shows an example of the result of the classification processing unit 3 judging whether the energy usage status of the molding workshop is normal or abnormal by comparing the actual value of the equipment outside the operating hours with the reference value. The area shown with the diagonal line texture is the power during the operating hours, and is not subject to the judgment of formula (5). In FIG. 17, from 0:00 to 8:00 on April 3rd is outside the operating hours, and the power during that time period is 1 kW, while the reference value is 2 kW, so the classification processing unit 3 judges it to be in a normal state. On the other hand, from 0:00 to 7:00 on April 7th is outside the operating hours, and the power during that time period is 8 kW, while the reference value is 2 kW, so the classification processing unit 3 judges it to be in an abnormal state. This abnormal state indicates that the equipment is consuming abnormally large amounts of power for some reason, even though it is outside the operating hours, that is, the time period when production is not being performed. In this way, the classification processing unit 3 can immediately detect a state in which power is being consumed abnormally compared to normal outside the operating hours and notify the user.

[0184] At this time, the classification processing unit 3 may set the judgment coefficient in the formula (5) to a smaller value, set the judgment reference value more strictly, and judge anomalies sensitively. The normal state power outside the operation hours adopted above may be updated for a certain period other than the period adopted when the reference value was calculated in the past, for example, when the equipment is replaced with a new one. The value adopted by the classification processing unit 3 as the normal state power varies depending on the equipment, and for example, the reference value may be 0 kW for an assembly robot that is completely stopped outside the operation hours. Also, there are cases where the normal state is to consume power in a stable state, such as a server or exhaust equipment, which does not become 0 kW. Furthermore, since the classification group Gr.5 is also associated with Gr.1, a reference value may be set for the power data for each distribution board, rather than judging the power data for each equipment, and a normal / abnormal judgment may be performed.

[0185] [Embodiment 3] In the third embodiment, an example will be described in which an information processing device is provided with a database that records information on the usage status of renewable energy, thereby visualizing the introduction status of renewable energy in facilities that consume electricity. FIG. 18 is a schematic block diagram illustrating the configuration of an information processing device according to the third embodiment. In the third embodiment, a power procurement means DB214 is provided in addition to the configuration shown in FIG. 15 of the second embodiment. The power procurement means DB214 belongs to Gr.6 in the classification group information.

[0186] The power procurement means DB214 is a database that records the means by which facilities that consume electricity, such as production factories, procure renewable energy. Renewable energy is energy that exists in nature and does not emit greenhouse gases, and renewable energy sources include solar, wind, hydroelectric, geothermal, and biomass. Regardless of the type of power source, the power procurement means DB214 records information on the means by which the facility procures renewable energy.

[0187] Examples of procurement methods include procuring a renewable energy menu from a retail electricity supplier, purchasing a renewable energy certificate, self-generation, power purchase agreements (PPAs), etc. Procuring a renewable energy menu from a retail electricity supplier means selecting and procuring from a renewable energy sales menu of a retail electricity supplier, just like purchasing electricity generated from normal fossil fuels. For example, there are options such as purchasing a menu of 100% renewable energy, or purchasing an electricity menu consisting of 50% renewable energy and the remaining 50% thermal power generation. Purchasing a certificate means purchasing a certificate such as a non-fossil certificate, green power certificate, or J-credit from a certificate issuing company, and obtaining official certification by regarding the purchased portion of the electricity consumed by the facility as generated from renewable energy. Self-generation means that the operator of the facility generates and consumes electricity within the facility by constructing a renewable energy power generation facility himself. Possible methods of self-generation include installing solar panels on the roof of a factory or installing a wind power generator on the premises. A power purchase agreement (PPA) is a long-term contract to purchase electricity generated from renewable energy power generation facilities, and is also called a power purchase agreement. For example, an on-site PPA may be an arrangement in which a renewable energy generation source such as solar panels is installed on the purchaser's premises under a long-term contract with a leasing company, and the generated electricity is used. Alternatively, an off-site PPA may be an arrangement in which electricity is generated by solar panels installed by a leasing company outside the premises, and the obtained electricity is procured through public transmission and distribution lines.

[0188] The power procurement means DB214 records information on how much power is procured by which method among such multiple types of procurement means and used in the facility. The classification processing unit 3 can grasp the procurement situation, for example, how much power is procured in which building and from which renewable energy procurement means by associating classification group Gr.2 with classification group Gr.6. The building information recorded in the building DB204 of classification group Gr.2 may record the building names across multiple facilities.

[0189] FIG. 19 is an example in which the classification processing unit 3 executes classification processing in the third embodiment, and the renewable energy introduction status of the facility to be visualized is displayed on the display unit 4. In FIG. 19, the actual value of the amount of electricity procured in the facility is displayed on a monthly basis. In FIG. 19, the types of procurement means are stacked in the vertical axis direction with textures such as diagonal lines and horizontal lines, and displayed as a bar graph. The renewable energy menu is the amount of renewable energy menu procured from a retail electricity supplier. The certificate is the amount procured by purchasing the certificate. The PPA is the amount procured by a power purchase agreement. The normal electricity is the amount procured from a power generation source using fossil fuels other than renewable energy.

[0190] When displayed in this manner, it is possible to comprehensively grasp information on how much renewable energy has been introduced in a certain facility. The vertical axis is in units of actual power amount (MWh), and the procurement amount is the same as the actual value of the usage amount. Alternatively, the vertical axis may be converted into a ratio (%) to display the ratio of power amount for each procurement means. Alternatively, it is possible to record the power unit price for each procurement means by linking it to the procurement means in the power procurement means DB214. In this way, it is also possible to display the procurement cost for each procurement means in monetary terms by multiplying the actual value of the power amount by the power unit price for each procurement means. Since the power unit price may differ depending on the procurement means, it is possible to switch between displaying the power amount and displaying the procurement cost, or to simultaneously display the two types of graphs side by side for comparison.

[0191] In FIG. 19, the procurement amount for one facility is displayed. However, when a company owns multiple facilities, information on the buildings of the multiple facilities is recorded in the building DB204 of classification group Gr.2, and this is associated with information in the power procurement method DB214 of classification group Gr.6. This makes it possible to display the total amount of power procurement for multiple facilities. Alternatively, the usage amount for each facility may be displayed side by side. A company's facilities are also called business establishments, and it is also possible to compare the introduction status of renewable energy between business establishments. Alternatively, it is possible to grasp the introduction status within a specific facility, where solar panels are installed in building A and self-generating electricity, but building B has not yet introduced it.

[0192] When electricity obtained from renewable energy sources is consumed, carbon dioxide emissions are reduced, so if renewable energy has been introduced to most of the equipment in a certain building, the generation of greenhouse gases due to electricity consumption in that building is suppressed to a certain extent. Therefore, if the equipment installed in that building is operated by renewable energy, there may be little need to implement activities to reduce electricity consumption from the perspective of environmental burden. Therefore, based on the display results of the third embodiment, it is possible to determine that reduction measures should be prioritized for buildings that consume electricity from power generation means that use a large amount of fossil fuels.

[0193] Alternatively, the introduction status of renewable energy may be visualized for each workplace using information recorded in the workplace DB205 of the classification group Gr.2. The workplace DB205 can record not only workplaces in a specific facility, but also broader workplace units such as sections, departments, and business headquarters that make up a workplace, and can systematically manage organizational hierarchies. In addition, when the classification processing unit 3 associates the workplace DB205 with the power procurement means DB214, it is possible to visualize the introduction status of renewable energy for each organization at various levels, such as workplaces, sections, departments, and business headquarters that make up a certain company. In addition, it is also possible to visualize the usage status of electricity derived from fossil fuels that is not renewable energy for each organization.

[0194] In the third embodiment, the classification processing unit 3 can classify and display the procurement amount and procurement cost for each electricity procurement means as actual values, but can also assume the future procurement amount for each procurement means and simulate the procurement cost. To do so, the user only needs to input in advance the predicted amount of energy usage required in the future in addition to the actual values ​​into the energy consumption input unit 1. Next, the classification processing unit 3 associates the electricity procurement means DB 214 of classification group Gr.2 with that of classification group Gr.6. This allows the classification processing unit 3 to simulate the procurement cost required for each procurement means based on the predicted amount of energy usage and the electricity unit price of any floor such as a building or workplace.

[0195] Figure 20 is an example of a simulation of the predicted costs for each procurement method, based on the amount of electricity required by the target facility in Figure 19. Compared to Figure 19, Figure 20 shows the predicted costs when less regular electricity derived from fossil fuels etc. is procured, and more electricity is procured from the renewable energy menu and private power generation than before.

[0196] When displayed in this manner, the costs required for increasing or decreasing renewable energy in the future can be understood for any floor, such as a building or workplace, by referring to the actual values ​​of past energy usage. In addition, a planned production volume value may be input into the production volume DB212 of classification group Gr.5, and the classification processing unit 3 may calculate a predicted value of energy usage for any floor by relating classification group Gr.2 with classification group Gr.5. In this manner, the classification processing unit 3 may calculate a predicted value of energy usage based on the production plan, and further calculate a predicted cost for each procurement means based on the predicted value, and display it on the display unit 4.

[0197] [Other embodiments] The present invention is not limited to the above-described embodiments and examples, and many modifications are possible within the technical spirit of the present invention. For example, the above-described different embodiments may be combined in whole or in part. The above-described information processing may be performed by a computer using a program, and a computer-readable recording medium having the program stored therein may also be included in the embodiments of the present invention.

[0198] The information processing method and information processing device of the present invention can be applied to analyze power consumption in various machines and equipment, such as industrial robots, service robots, processing machines operated by computer numerical control, etc., in addition to production equipment. For example, the information processing method and information processing device of the present invention can be applied to acquire, classify, display, etc., power consumption data for machines and equipment that can automatically perform operations such as expansion and contraction, bending and stretching, vertical movement, horizontal movement, or rotation, or a combination of these operations, based on information from a storage device provided in a control device.

[0199] When analyzing power consumption by applying the information processing method and information processing device of the present invention, the operations executed by the device are typically operations related to the manufacture of goods, such as assembly of parts, transportation, processing (including cutting, polishing, drilling, painting, bonding, welding, etc.), cleaning, etc. However, the information processing such as acquisition, analysis, and display of power consumption according to this embodiment may also be applied when executing operations other than those.

[0200] The present invention can also be realized by a process in which a program for implementing one or more functions of the embodiments is supplied to a system or device via a network or a storage medium, and one or more processors in a computer of the system or device read and execute the program. The present invention can also be realized by a circuit (e.g., ASIC) that implements one or more functions.

[0201] This specification discloses at least the following: [Matter 1] a classification information acquiring unit that acquires classification group information including a plurality of classification groups each composed of classification items, and association information that associates the classification items of the plurality of classification groups with each other; A data acquisition unit that acquires data on electricity consumed in the facility; a classification processing unit that classifies the data acquired by the data acquisition unit using the classification group information and the association information acquired by the classification information acquisition unit; An information processing device comprising: [Matter 2] The classification group information includes classification groups that hierarchically classify the power system of the facility, 2. The information processing device according to item 1, [Matter 3] The classification group in which the power system of the facility is hierarchically classified includes any one of a substation, a distribution board, and a distribution board as a classification item, 3. The information processing device according to item 2. [Matter 4] The classification group information includes classification groups that hierarchically classify the operation system of the facility, 4. The information processing device according to any one of items 1 to 3. [Matter 5] The classification group, which is a hierarchical classification of the operation system of the facility, includes any one of a building, a workplace, equipment, and a unit constituting the equipment as a classification item, 5. The information processing device according to item 4. [Matter 6] The classification group information includes classification groups that hierarchically classify uses of energy consumed in the facility. 6. The information processing device according to any one of items 1 to 5. [Matter 7] The classification group, which is a hierarchical classification of the uses of energy consumed in the facility, includes any one of a heat system, a drive system, an air system, and a vacuum system as a classification item, 7. The information processing device according to item 6, [Matter 8] The classification group information includes classification groups that hierarchically classify added value created by the facility, 8. The information processing device according to any one of items 1 to 7, [Matter 9] The classification group, which classifies the added value created by the facility hierarchically, includes any one of the following classification items: net, incidental, or waste. 9. The information processing device according to item 8, [Matter 10] The classification group that hierarchically classifies the added value created by the facility includes a classification item related to time and / or a classification item related to energy, 10. The information processing device according to item 8 or 9. [Matter 11] The classification processing unit classifies the data acquired by the data acquisition unit using classification groups obtained by hierarchically classifying the power system of the facility included in the classification group information and classification groups obtained by hierarchically classifying the operation system of the facility. 2. The information processing device according to item 1, [Matter 12] The classification processing unit classifies the data acquired by the data acquisition unit using classification groups that hierarchically classify the operation systems of the facility included in the classification group information and classification groups that hierarchically classify added value created by the facility. 2. The information processing device according to item 1, [Matter 13] and displaying information about the classification result by the classification processing unit on a display unit. 13. The information processing device according to any one of items 1 to 12, [Matter 14] and displaying information about the classification result by the classification processing unit in the form of a graph on a display unit. 13. The information processing device according to any one of items 1 to 12, [Matter 15] determining whether or not an abnormality has occurred in the power consumed by the facility based on a reference value related to the operation time of the facility; 15. An information processing device according to any one of items 1 to 14, characterized in that [Matter 16] The classification group information includes a classification group that classifies energy consumed in the facility into renewable energy, 16. The information processing device according to any one of items 1 to 15, [Matter 17] Classifying the data as incidental or wasteful based on the standard time of the operations performed in the facility; 17. The information processing device according to any one of items 1 to 16, [Matter 18] Groups can be set for equipment in the facility based on the operations performed by the equipment. 18. An information processing device according to any one of items 1 to 17. [Matter 19] The data, which is not aligned at the time of acquisition, is aligned to the hierarchy of the distribution board. 19. The information processing device according to any one of items 1 to 18. [Matter 20] Setting a basic unit for the energy consumed in said facility; 20. An information processing device according to any one of items 1 to 19, [Matter 21] a classification information acquiring step of acquiring classification group information including a plurality of classification groups each composed of classification items and association information associating the classification items of the plurality of classification groups with each other by a classification information acquiring unit; a data acquisition step in which an acquisition unit acquires data on electricity consumed in the facility; a classification process in which a classification processing unit classifies the data acquired in the data acquisition process using the classification group information and the association information acquired in the classification information acquisition process; An information processing method comprising: [Matter 22] 22. A program for causing a computer to execute the information processing method according to item 21. [Matter 23] 23. A computer-readable recording medium having the program according to item 22 recorded thereon. [Explanation of symbols]

[0202] 1···Energy consumption input section / 2···Energy usage condition input section / 3···Classification processing section / 4···Display section / 201···Substation DB / 202···Switchboard DB / 203···Distribution board DB / 204···Building DB / 205···Workplace DB / 206···Equipment DB / 207···Unit DB / 208···Use DB / 209···Added value DB / 210···Operation details DB / 211···Consumption details DB

Claims

1. Obtaining association information associating a plurality of classification items, obtaining data on the power consumed at a facility, when classifying the data into the classification items, using the association information to associate and classify the data among the classification items, An information processing method characterized by the above.

2. The classification items are further classified into a plurality of classification groups, the association information includes information associating the classification groups, when classifying the data into the classification items, using the association information to associate and classify the data among the classification groups, The information processing method according to claim 1, characterized by the above.

3. The classification group includes a group related to the power system of the facility, The information processing method according to claim 2, characterized by the above.

4. The group related to the power system of the facility includes, as the classification items, at least one of a substation, a switchboard, and a distribution board, The information processing method according to claim 3, characterized by the above.

5. The classification group includes a group related to the operation system of the facility, The information processing method according to claim 2, characterized by the above.

6. The group related to the operation system of the facility includes, as the classification items, at least one of a building, a workplace, a facility, and a unit constituting the facility, The information processing method according to claim 5, characterized by the above.

7. The classification group includes a group related to the use of energy consumed at the facility, The information processing method according to claim 2, characterized by the above.

8. The group related to the use of energy consumed at the facility includes, as the classification items, at least one of a heat system, a drive system, an air system, and a vacuum system, The information processing method according to claim 6, characterized by the above.

9. The classification group includes a group related to the added value created at the facility, The information processing method according to claim 2, characterized by the above.

10. The group related to the added value created at the facility includes, as the classification items, at least one of net, incidental, and waste, The information processing method according to claim 9, characterized by the above.

11. The group related to the added value created at the facility includes classification items related to time and / or classification items related to energy, The information processing method according to claim 9, characterized by the above. Using a group related to the power system of the facility and a group related to the operation system of the facility, classify the data by associating it between the classification groups. The information processing method according to claim 2, characterized in that. Using a group related to the operation system of the facility and a group related to the added value created in the facility, classify the data by associating it between the classification groups. The information processing method according to claim 2, characterized in that.

14. Display information regarding the classification result of the data on a display unit. The information processing method according to any one of claims 1 to 12, characterized in that.

15. Graphically display information regarding the classification result of the data on a display unit. The information processing method according to any one of claims 1 to 12, characterized in that.

16. Based on a reference value related to the operation time in the facility, determine whether there is an abnormality in the power consumed in the facility. The information processing method according to any one of claims 1 to 12, characterized in that.

17. The classification group includes a group related to renewable energy consumed in the facility. The information processing method according to claim 2, characterized in that.

18. Based on the standard time in the operation content implemented in the facility, classify the data as attendant or wasteful. The information processing method according to any one of claims 1 to 12, characterized in that.

19. Based on the operation content implemented by the facility's equipment, groups can be set for the equipment. The information processing method according to any one of claims 1 to 12, characterized in that.

20. Align the data, which is not hierarchical at the time of acquisition, to the hierarchy of the distribution board. The information processing method according to any one of claims 1 to 12, characterized in that.

21. Set a unit consumption for the energy consumed in the facility. The information processing method according to any one of claims 1 to 12, characterized in that. An information processing apparatus having a processing unit, wherein The processing unit Obtains association information associating a plurality of classification items, Obtains data on the power consumed in the facility, When classifying the data into the classification items, classifies the data by associating it between the classification items using the association information. An information processing apparatus characterized in that.

23. A program for causing a computer to execute the information processing method according to any one of claims 1 to 12.

24. A computer-readable recording medium having recorded thereon the program according to claim 23.

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