WO2022118601A1 - 設備管理装置および設備管理方法 - Google Patents
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- 238000007726 management method Methods 0.000 title claims abstract description 132
- 238000005265 energy consumption Methods 0.000 claims abstract description 140
- 230000005856 abnormality Effects 0.000 claims abstract description 106
- 238000012423 maintenance Methods 0.000 claims abstract description 99
- 230000008859 change Effects 0.000 claims abstract description 74
- 238000001514 detection method Methods 0.000 claims abstract description 58
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000009472 formulation Methods 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 3
- 230000006866 deterioration Effects 0.000 description 20
- 238000010586 diagram Methods 0.000 description 19
- 238000005259 measurement Methods 0.000 description 8
- 238000004519 manufacturing process Methods 0.000 description 7
- 238000000034 method Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 3
- 238000012552 review Methods 0.000 description 3
- 230000001629 suppression Effects 0.000 description 3
- 230000007423 decrease Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000004378 air conditioning Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
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- 230000000630 rising effect Effects 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4184—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by fault tolerance, reliability of production system
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31455—Monitor process status
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Definitions
- the present invention relates to an equipment management system that manages equipment such as manufacturing equipment, and relates to a method for modifying an operation plan, a maintenance plan, etc. of the equipment based on the result of abnormality detection.
- Patent Document 1 a technique has been proposed to support the formulation of a maintenance plan in consideration of the tendency of increasing energy consumption in the past and the tendency of suppressing the increase in energy consumption due to maintenance work.
- Patent Document 1 since a maintenance plan is formulated based on the increasing tendency of energy consumption in the past, when a sudden failure occurs infrequently or when a plurality of deterioration modes are combined with an unprecedented deterioration state, There was a problem that it was difficult to reflect it in the conservation plan because it was not possible to refer to statistically sufficient past cases and its impact could not be estimated.
- An object of the present invention is an equipment management device and equipment management that can accurately calculate the influence on energy consumption even when a sudden failure that occurs infrequently occurs, and can create a maintenance plan at a lower cost. To provide a method.
- the present invention is, for example, an equipment management device that supports the operation and maintenance planning of equipment, and has an abnormality detection unit that detects an abnormality of equipment based on information obtained by measuring the state of equipment, and an abnormality.
- the maintenance management department that manages the maintenance of equipment by inputting the detection result of Energy consumption change estimation unit that estimates changes in equipment consumption energy from abnormality detection results, energy management department that manages equipment consumption energy and calculates energy costs by inputting estimated energy consumption changes, and energy management department
- a cost comparison unit is provided to compare the cost information calculated by the maintenance management department, and the maintenance plan of the maintenance management department and the operation plan of the operation management department are reviewed based on the results of the cost comparison department.
- FIG. It is a functional block diagram of the equipment management system in Example 1.
- FIG. It is a block diagram of the hardware image of the equipment management system in Example 1.
- FIG. It is a functional block diagram of the maintenance management part in Example 1.
- FIG. It is a functional block diagram of the operation management part in Example 1.
- FIG. It is explanatory drawing of the relationship between the abnormality degree detection result and the energy consumption change in Example 1.
- FIG. It is a functional block diagram of the energy management part in Example 1.
- FIG. It is explanatory drawing of the relationship between maintenance cost and energy consumption increase cost in Example 1.
- FIG. It is a functional block diagram of the equipment management apparatus in Example 2.
- FIG. It is explanatory drawing of the operation rate suppression in consideration of the energy consumption upper limit value in Example 2.
- FIG. It is explanatory drawing of the estimation of the energy consumption change in Example 3.
- It is a functional block diagram of the energy consumption change model creation part in Example 4.
- FIG. 1 is a functional configuration diagram of an equipment management system that manages equipment such as manufacturing equipment in this embodiment.
- the equipment management system is composed of a state measuring unit 101, a network 150, and an equipment management device 100.
- the state measurement unit 101 is connected to industrial equipment such as an air conditioning fan in a factory and a motor which is a manufacturing facility, and measures the state of the industrial equipment using various sensors such as a current sensor, a vibration sensor, and a noise meter. Or, the state is measured from the signal in the control device of the industrial equipment.
- industrial equipment such as an air conditioning fan in a factory and a motor which is a manufacturing facility
- sensors such as a current sensor, a vibration sensor, and a noise meter.
- the state is measured from the signal in the control device of the industrial equipment.
- the equipment management device 100 receives the result measured by the state measuring unit 101 via the network 150.
- the equipment management device 100 has an abnormality detection unit 102, a maintenance management unit 103, an operation management unit 104, an energy consumption change estimation unit 106, an energy management unit 107, and a cost comparison unit 108.
- the equipment management device 100 is a device having a processing device (CPU) 201, a storage device (memory) 202, a display device 203, and an input / output interface (I / F) 204, which are general information processing devices. Realized by. That is, each process of the abnormality detection unit 102, the maintenance management unit 103, the operation management unit 104, the energy consumption change estimation unit 106, the energy management unit 107, and the cost comparison unit 108 is a program stored in the memory 202 to process them. It is executed by the CPU 201 performing software processing based on the data. It is connected to the network 150 via the input / output I / F, and the result measured by the state measuring unit 101 is obtained. In addition, the display device 203 displays the maintenance plan and the operation plan that will be described later.
- CPU processing device
- memory memory
- I / F input / output interface
- the abnormality detection unit 102 detects signs of failure of industrial equipment and behavior different from normal by using the results measured by the state measurement unit 101. Normally, when an abnormality that is a sign of failure is detected, the detected information is sent to the maintenance management unit 103 or the operation management unit 104.
- FIG. 3 is a functional configuration diagram of the maintenance management unit 103 in this embodiment.
- the maintenance management unit 103 formulates a maintenance plan by the maintenance planning unit 306 based on the information of the maintenance equipment information 301 and the maintenance work item 302, which are databases, and the maintenance plan, the maintenance work cost 303, the parts replacement cost 304, and the like.
- the maintenance cost estimation unit 305 estimates the maintenance cost from the information in.
- FIG. 4 is a functional configuration diagram of the operation management unit 104 in this embodiment.
- the operation management unit 104 formulates an operation plan such as when to operate the equipment in order to correspond to the production plan 401 such as how many are required by when.
- FIG. 5 shows an example of the abnormality detection result and the change in energy consumption.
- the abnormality detection unit 102 performs an abnormality degree analysis on two deteriorations, deterioration A (solid line) and deterioration B (broken line), for a certain industrial device.
- the abnormality degree analysis detects the deviation of the state monitoring result from the normal state as the abnormality degree, and assumes that the abnormality is detected at the timing when the abnormality degree exceeds a certain threshold value.
- FIG. 5 shows an example of the abnormality detection result and the change in energy consumption.
- the abnormality degree analysis detects the deviation of the state monitoring result from the normal state as the abnormality degree, and assumes that the abnormality is detected at the timing when the abnormality degree exceeds a certain threshold value.
- the deterioration A is detected earlier than the deterioration B, and finally the abnormality degree of the deterioration B exceeds the deterioration A.
- An example is shown in the lower part of FIG. It can be seen that the rate of change in energy consumption corresponding to each deterioration increases in the transition of the abnormality detection timing in the upper row, and the energy consumption tends to increase due to the deterioration of the equipment. However, the increasing tendency of the degree of abnormality and the increasing tendency of energy consumption do not always match. If the operation is continued until the normal maintenance work period in the state where the energy consumption is increased more than usual in this way, more energy cost than usual is required.
- the energy consumption change estimation unit 106 performs such estimation of the energy consumption change tendency.
- the energy consumption change estimation unit 106 sends the estimated energy consumption change tendency to the energy management unit 107.
- FIG. 6 is a functional configuration diagram of the energy management unit 107 in this embodiment.
- the energy management unit 107 has energy unit price information 601 and has an energy consumption estimation unit 602 that estimates energy consumption based on the operation plan sent from the operation management unit 104. Then, it has an energy cost estimation unit 603 that estimates the energy consumption cost from these information.
- the energy consumption limit value 604 will be described later.
- FIG. 7 is a diagram illustrating the relationship between the maintenance cost and the energy consumption increase cost in this embodiment.
- the horizontal axis shows the elapsed time from the replacement of parts due to the previous maintenance work
- the vertical axis shows the maintenance cost and the energy consumption increase cost
- the downward-sloping graph 10 shows the maintenance cost
- the upward-sloping graph 21. , 22 indicate the cost of increasing energy consumption.
- the energy consumption increase cost when an abnormality is detected is shown by a solid line graph 21
- the energy consumption increase cost when an abnormality is not detected is shown by a broken line graph 22.
- the optimum maintenance timing is at the intersection of graph 10 and graph 22, whereas when an abnormality is detected and energy consumption increases, the corrected optimum maintenance plan timing is a graph. It becomes the intersection of 10 and the graph 21, the optimum time is shortened, and the overall cost can be suppressed by modifying the maintenance plan ahead of schedule.
- the cost comparison unit 108 performs such cost comparison. However, as a result of abnormality detection, energy consumption may decrease, and in that case, the maintenance plan may be revised backward unless a failure occurs. Upon receiving the output of the cost comparison unit 108, the maintenance plan in the maintenance management unit 103 and the operation plan in the operation management unit 104 are reviewed.
- the equipment management device that supports the operation and maintenance planning of the equipment, the abnormality detection unit that detects the abnormality of the equipment based on the information that measures the state of the equipment, and the abnormality.
- the maintenance management department that manages the maintenance of equipment by inputting the detection result of Energy consumption change estimation unit that estimates changes in equipment consumption energy from abnormality detection results, energy management department that manages equipment consumption energy and calculates energy costs by inputting estimated energy consumption changes, and energy management department It is equipped with a cost comparison unit that compares cost information calculated by the maintenance management department, and configures a facility management device that reviews the maintenance plan in the maintenance management department and the operation plan in the operation management department based on the results of the cost comparison department. can.
- it is a facility management method that supports the operation of equipment and the formulation of maintenance plans. It detects equipment abnormalities based on the information that measures the equipment status, and inputs the abnormality detection results to manage and maintain the equipment maintenance. Cost calculation and maintenance plan are formulated, the operation of the equipment is managed by inputting the abnormality detection result, the operation plan is formulated, the change of the equipment consumption is estimated from the abnormality detection result, and the estimated change of the energy consumption is estimated. It is possible to construct a facility management method that manages the energy consumption of the equipment, calculates the energy cost, compares the maintenance cost and the energy cost, and reviews the maintenance plan and the operation plan based on the comparison result.
- FIG. 8 is a functional configuration diagram of the equipment management device in this embodiment.
- configurations having the same functions as those in FIG. 1 are designated by the same reference numerals, and the description thereof will be omitted.
- the difference from FIG. 1 in FIG. 8 is that the maintenance management unit 103 and the cost comparison unit 108 are not provided, and the operation management unit 104 is controlled by the output of the energy management unit 107. That is, as shown in the energy consumption limit value 604 of FIG. 6, the energy management unit 107 may set an upper limit value of energy consumption from the viewpoint of energy consumption reduction and power contract fee suppression.
- FIG. 9 is an explanatory diagram of operating rate suppression in consideration of the upper limit of energy consumption in this embodiment.
- FIG. 9 when an abnormality is detected at a certain time, it is estimated that the energy consumption increases due to the abnormality detection, and the estimated energy consumption estimated by the energy management unit 107 exceeds the upper limit of the energy consumption. , The information is sent to the operation management unit 104, and the operation plan is revised so as to suppress the operation rate of the device.
- the actual energy consumption becomes smaller corresponding to the suppressed operating rate, and even if the energy consumption increases due to deterioration, the operation can be continued until the next maintenance work.
- the increase in energy consumption disappears, so that the operating rate can be returned to normal.
- this embodiment is characterized by operation management in which the upper limit of energy consumption is taken into consideration, maintenance management and operation management by the maintenance management unit 103 and the cost comparison unit 108 in FIG. 1 may be used together.
- the equipment management device that supports the operation and maintenance planning of the equipment, the abnormality detection unit that detects the abnormality of the equipment based on the information that measures the state of the equipment, and the abnormality.
- the operation management unit that manages the operation of the equipment and formulates an operation plan by inputting the detection result of the It is equipped with an energy management unit that estimates whether the amount of energy consumed by the equipment exceeds the upper limit of energy consumption as an input, and the operation management department can configure the equipment management device that reviews the operation plan based on the results estimated by the energy management department. ..
- it is an equipment management method that supports the operation of equipment and the formulation of maintenance plans. It detects equipment abnormalities based on the measured information on the equipment status, and inputs the abnormality detection results to manage and operate the equipment operations. A plan is made, the change in the energy consumption of the equipment is estimated from the detection result of the abnormality, and the estimated change in the energy consumption is input to determine whether the energy consumption of the equipment exceeds the upper limit of the energy consumption. Based on this, it is possible to configure a facility management method for reviewing the operation plan.
- FIG. 10 is a functional configuration diagram of the equipment management device 100 in this embodiment.
- configurations having the same functions as those in FIG. 1 are designated by the same reference numerals, and the description thereof will be omitted.
- the difference from FIG. 1 in FIG. 10 is that it has an energy consumption change model creating device 120 including an abnormality degree history 121, an energy consumption history 122, and an energy consumption change model creating unit 123.
- the abnormality degree history 121 stores the history of the abnormality degree detection result in the past operation. Further, the energy consumption history 122 stores a change history of energy consumption during the past operation.
- FIG. 11 shows an example of the stored energy consumption and the history of the degree of abnormality.
- it is stored as a history that the device deteriorates and the energy consumption increases with the passage of time.
- the deterioration of the device corresponding to the work content is recovered, and the energy consumption is reduced.
- the middle part of FIG. 11 the history of the two abnormality degree detection results of deterioration A and deterioration B when the energy consumption in the upper part is observed is shown. It can be seen that the degree of abnormality of each deterioration increases with the passage of time, and the degree of abnormality decreases after the maintenance work corresponding to the deterioration is performed.
- the energy consumption change model creation unit 123 shown in FIG. 10 shows the relationship between the degree of abnormality of the equipment and the change in the energy consumption of the equipment as shown in the lower part of FIG. 11 by using regression analysis or the like. , Calculate the energy consumption change model, which is dependent on the degree of abnormality of the energy consumption change.
- the energy consumption change model By calculating the energy consumption change model in this way, it is possible to evaluate the relationship between the deterioration of the device and the change in energy consumption even when the energy consumption change cannot be directly obtained from the abnormality detection.
- this energy consumption change model it is possible to accurately estimate the energy consumption change from the energy consumption change model and the abnormality detection result even in the combination of the degree of deterioration that has never occurred in the past. It becomes.
- the energy consumption change estimated in this way is estimated, and the maintenance cost estimated from the maintenance management unit 103 and the comparison result in the cost comparison unit 108 are obtained.
- the overall cost can be reduced.
- FIG. 12 is a functional configuration diagram of the energy consumption change model creating device 120 in this embodiment.
- FIG. 12 configurations having the same functions as those in FIG. 10 are designated by the same reference numerals, and the description thereof will be omitted.
- FIG. 12 is a modification of the energy consumption change model creating device 120 in FIG. 10, and the equipment management device in this embodiment is the same as that in FIG. 10 except for the energy consumption change model creating device 120.
- the difference from the energy consumption change model creating device 120 in FIG. 10 is that it has a plurality of abnormality degree histories 121 and energy consumption histories 122.
- the provider of the equipment management system asks a plurality of operators who operate the same system to provide the abnormality degree history 121 and the energy consumption history 122, and the provider of the equipment management system consumes the energy consumption change model.
- the energy change model creation unit 123 it is possible to create an energy consumption change model with high accuracy even if an individual operator cannot obtain a sufficient history.
- the energy consumption change model creation device 120 is operated as a single device and the created energy consumption change model is sent to and provided to the operator of the equipment management system.
- the equipment management system can use the energy consumption change model with high accuracy and can accurately estimate the energy consumption change. Then, by modifying the maintenance plan based on the comparison result of the maintenance cost and the energy consumption cost, it is possible to further reduce the overall cost.
- the energy consumption change model creation device used for the equipment management device that supports the operation and maintenance planning of the equipment and the energy consumption change model is the degree of abnormality of the equipment and the equipment. It is a model that shows the relationship between changes in energy consumption. It acquires the history of equipment abnormality detection and the history of changes in equipment energy consumption from multiple equipment operators, and creates and creates an energy consumption change model from those histories. It is possible to configure an energy consumption change model creation device that sends the completed energy consumption change model to the equipment operator.
- FIG. 13 is a functional configuration diagram of the state measurement unit and the abnormality detection unit in this embodiment.
- a current measuring unit 130 that measures a current is used as a state measuring unit, and an abnormality detecting unit 102 detects an abnormality in an industrial device provided with a rotating machine such as an electric motor.
- the abnormality detection unit 102 includes a feature amount calculation unit 131, a normal model creation unit 132, and an abnormality analysis unit 133.
- the feature amount calculation unit 131 calculates one of the fundamental wave frequency intensity of the current calculated from the result of the current measurement, the current effective value, and the average value of the direct current calculated from the alternating current as the feature amount. Further, the normal model creation unit 132 generates a model of the feature amount when the equipment is normal. Then, the abnormality analysis unit 133 compares the measured feature amount with the model of the normal feature amount generated by the normal model creation unit 132, performs an abnormality analysis, and outputs the degree of abnormality.
- the present invention is not limited to the above-mentioned examples, and includes various modifications.
- each of the above embodiments has been described in detail in order to explain the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to the one including all the components described above.
- 100 Equipment management device, 101: Status measurement unit, 102: Abnormality detection unit, 103: Maintenance management unit, 104: Operation management unit, 106: Energy consumption change estimation unit, 107: Energy management unit, 108: Cost comparison unit, 120: Energy consumption change model creation device, 121: Abnormality history, 122: Energy consumption history, 123: Energy consumption change model creation unit, 130: Current measurement unit, 131: Feature amount calculation unit, 132: Normal model creation unit, 133: Abnormality analysis department, 150: Network
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Abstract
Description
そのため、特許文献1のように過去の消費エネルギーの増加傾向や保全作業による消費エネルギーの増加の抑制傾向を加味して保全計画策定を支援する技術が提案されている。
Claims (9)
- 設備の運用や保全の計画策定を支援する設備管理装置であって、
前記設備の状態を計測した情報に基づき該設備の異常を検知する異常検知部と、
前記異常の検知結果を入力とし前記設備の保全を管理し保全コストの算出と保全計画を立案する保全管理部と、
前記異常の検知結果を入力とし前記設備の運用を管理し運用計画を立案する運用管理部と、
前記異常の検知結果から前記設備の消費エネルギーの変化を推定する消費エネルギー変化推定部と、
前記推定した消費エネルギーの変化を入力とし前記設備の消費エネルギーを管理しエネルギーコストを算出するエネルギー管理部と、
前記エネルギー管理部と前記保全管理部で算出されたコスト情報を比較するコスト比較部を備え、
前記コスト比較部の結果に基づき前記保全管理部での保全計画および前記運用管理部での運用計画の見直しを行うことを特徴とする設備管理装置。 - 設備の運用や保全の計画策定を支援する設備管理装置であって、
前記設備の状態を計測した情報に基づき該設備の異常を検知する異常検知部と、
前記異常の検知結果を入力とし前記設備の運用を管理し運用計画を立案する運用管理部と、
前記異常の検知結果から前記設備の消費エネルギーの変化を推定する消費エネルギー変化推定部と、
前記推定した消費エネルギーの変化を入力とし前記設備の消費エネルギー量が消費エネルギー上限値を超えるかを推定するエネルギー管理部を備え、
前記運用管理部は、前記エネルギー管理部が推定した結果に基づき前記運用計画の見直しを行うことを特徴とする設備管理装置。 - 請求項1に記載の設備管理装置であって、
前記異常の検知履歴と前記消費エネルギーの履歴から異常の検知結果が消費エネルギーに与える影響をモデル化する消費エネルギー変化モデルを作成する消費エネルギー変化モデル作成部を備え、
前記消費エネルギー変化推定部は、前記異常の検知結果と前記消費エネルギー変化モデルから前記設備の消費エネルギーの変化を推定することを特徴とする設備管理装置。 - 請求項3に記載の設備管理装置であって、
前記消費エネルギー変化モデル作成部は、前記異常の検知履歴と前記消費エネルギーの履歴を複数の設備運用者から取得し、それらの履歴から前記消費エネルギー変化モデルを作成することを特徴とする設備管理装置。 - 請求項1から4の何れか1項に記載の設備管理装置において、
前記設備の状態を計測した情報は電流センサを用いて計測した情報であって、
前記異常検知部は、基本波周波数の電流強度、電流実効値、直流電流平均値のうちの少なくとも一つを特徴量として算出する特徴量算出部と、
前記設備が正常な場合の特徴量のモデルを生成する正常モデル作成部と、
前記算出された特徴量と前記正常な場合の特徴量のモデルと比較し異常度を出力する異常分析部を有することを特徴とする設備管理装置。 - 設備の運用や保全の計画策定を支援する設備管理方法であって、
前記設備の状態を計測した情報に基づき該設備の異常を検知し、
前記異常の検知結果を入力とし前記設備の保全を管理し保全コストの算出と保全計画を立案し、
前記異常の検知結果を入力とし前記設備の運用を管理し運用計画を立案し、
前記異常の検知結果から前記設備の消費エネルギーの変化を推定し、
前記推定した消費エネルギーの変化を入力とし前記設備の消費エネルギーを管理しエネルギーコストを算出し、
前記保全コストと前記エネルギーコストを比較し、
該比較結果に基づき前記保全計画および前記運用計画の見直しを行うことを特徴とする設備管理方法。 - 請求項6に記載の設備管理方法であって、
前記異常の検知履歴と前記消費エネルギーの履歴から異常の検知結果が消費エネルギーに与える影響をモデル化する消費エネルギー変化モデルを作成し、
前記異常の検知結果と前記消費エネルギー変化モデルから前記設備の消費エネルギーの変化を推定することを特徴とする設備管理方法。 - 請求項7に記載の設備管理方法であって、
前記異常の検知履歴と前記消費エネルギーの履歴を複数の設備運用者から取得し、それらの履歴から前記消費エネルギー変化モデルを作成することを特徴とする設備管理方法。 - 請求項6から8の何れか1項に記載の設備管理方法において、
前記設備の状態を計測した情報は電流センサを用いて計測した情報であって、
前記異常の検知は、
基本波周波数の電流強度、電流実効値、直流電流平均値のうちの少なくとも一つを特徴量として算出し、
前記設備が正常な場合の特徴量のモデルを生成し、
前記算出された特徴量と前記正常な場合の特徴量のモデルと比較し異常度を出力することを特徴とする設備管理方法。
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Publication number | Priority date | Publication date | Assignee | Title |
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US20070050221A1 (en) * | 2005-08-29 | 2007-03-01 | Abtar Singh | Dispatch management model |
US20140188434A1 (en) * | 2012-12-27 | 2014-07-03 | Robin A. Steinbrecher | Maintenance prediction of electronic devices using periodic thermal evaluation |
US20150059492A1 (en) * | 2012-04-03 | 2015-03-05 | Trendiwell Oy | Measurement arrangement and related method |
JP2017182245A (ja) | 2016-03-29 | 2017-10-05 | 株式会社インティ | 保全計画支援システム、及び保全計画支援方法 |
US20190073619A1 (en) * | 2016-03-31 | 2019-03-07 | Nuovo Pignone Tecnologie Srl | Methods and systems for optimizing filter change interval |
JP2020521200A (ja) * | 2017-05-25 | 2020-07-16 | ジョンソン コントロールズ テクノロジー カンパニーJohnson Controls Technology Company | ビルディング機器用のモデル予測的メンテナンスシステム |
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US20070050221A1 (en) * | 2005-08-29 | 2007-03-01 | Abtar Singh | Dispatch management model |
US20150059492A1 (en) * | 2012-04-03 | 2015-03-05 | Trendiwell Oy | Measurement arrangement and related method |
US20140188434A1 (en) * | 2012-12-27 | 2014-07-03 | Robin A. Steinbrecher | Maintenance prediction of electronic devices using periodic thermal evaluation |
JP2017182245A (ja) | 2016-03-29 | 2017-10-05 | 株式会社インティ | 保全計画支援システム、及び保全計画支援方法 |
US20190073619A1 (en) * | 2016-03-31 | 2019-03-07 | Nuovo Pignone Tecnologie Srl | Methods and systems for optimizing filter change interval |
JP2020521200A (ja) * | 2017-05-25 | 2020-07-16 | ジョンソン コントロールズ テクノロジー カンパニーJohnson Controls Technology Company | ビルディング機器用のモデル予測的メンテナンスシステム |
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