WO2023039729A1 - Procédé et appareil d'évaluation de plan de production, et support de stockage lisible par ordinateur - Google Patents

Procédé et appareil d'évaluation de plan de production, et support de stockage lisible par ordinateur Download PDF

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Publication number
WO2023039729A1
WO2023039729A1 PCT/CN2021/118348 CN2021118348W WO2023039729A1 WO 2023039729 A1 WO2023039729 A1 WO 2023039729A1 CN 2021118348 W CN2021118348 W CN 2021118348W WO 2023039729 A1 WO2023039729 A1 WO 2023039729A1
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production
energy consumption
data
equipment
model
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PCT/CN2021/118348
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English (en)
Chinese (zh)
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白新
周晓舟
孙天瑞
李奂轮
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西门子（中国）有限公司
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Priority to PCT/CN2021/118348 priority Critical patent/WO2023039729A1/fr
Publication of WO2023039729A1 publication Critical patent/WO2023039729A1/fr

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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
    • 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]

Definitions

  • the invention relates to the technical field of intelligent manufacturing and energy-saving manufacturing, in particular to an evaluation method, device and computer-readable storage medium of a production plan.
  • Energy-efficient manufacturing and/or carbon-neutral production set higher standards for energy performance.
  • embodiments of the present invention provide a method, device, and computer-readable storage medium for evaluating a production plan.
  • the present invention first proposes a method for evaluating a production plan, including:
  • the production plan is evaluated based on the overall energy consumption forecast data.
  • the implementation of the present invention introduces energy measurement to evaluate the production plan, which can evaluate the production plan from the dimension of energy consumption, and provide accurate judgment basis for energy-saving manufacturing.
  • the determining the overall energy consumption prediction data of the production plan based on the production data and the equipment-level energy consumption data includes:
  • the overall energy consumption prediction data of the production plan is output from the overall energy consumption prediction model.
  • the overall energy consumption data can be predicted conveniently.
  • the establishment of the overall energy consumption prediction model of the production line includes:
  • model of each device in the production line from a preset device library, wherein the model of each device includes the energy consumption attribute of each device and the production attribute of each device;
  • the models of each device are sequentially connected to form an overall energy consumption prediction model of the production line.
  • the overall energy consumption prediction model of the production line can be constructed through the model of each equipment.
  • the establishment of the overall energy consumption prediction model of the production line includes:
  • the overall energy consumption prediction model of the production line can be conveniently constructed through the existing production line model.
  • the model of the equipment is updated based on the historical production data and the historical energy consumption data.
  • the device model can also be calibrated based on historical data to improve the accuracy of the device model.
  • Adjust the enabling status of the equipment adjust the utilization rate of the equipment; adjust the working hours of the equipment; adjust the production load of the production plan; adjust the process parameters of the production plan.
  • said obtaining the production data related to the production plan of the production line includes at least one of the following: obtaining the production data from an enterprise resource planning system; obtaining the production data from an advanced planning and scheduling system;
  • the manufacturing execution system acquires the production data;
  • the acquiring the equipment-level energy consumption data of the production line includes: acquiring the energy consumption data of each equipment in the production line from an energy management system or an asset management system.
  • Another aspect of the present invention also proposes an evaluation device for a production plan, including:
  • the first obtaining module is used to obtain production data related to the production plan of the production line;
  • a second acquisition module configured to acquire equipment-level energy consumption data of the production line
  • a determining module configured to determine overall energy consumption prediction data of the production plan based on the production data and the equipment-level energy consumption data
  • An evaluation module configured to evaluate the production plan based on the overall energy consumption prediction data.
  • the implementation of the present invention introduces energy measurement to evaluate the production plan, which can evaluate the production plan from the dimension of energy consumption, and provide accurate judgment basis for energy-saving manufacturing.
  • the determining module is configured to establish an overall energy consumption prediction model of the production line; input the production data and the equipment-level energy consumption data into the overall energy consumption prediction model; The energy consumption prediction model outputs the overall energy consumption prediction data of the production plan.
  • the overall energy consumption data can be predicted conveniently.
  • the determining module is configured to select a model of each device in the production line from a preset device library, wherein the model of each device includes the energy consumption attribute and The production attributes of each device; based on the operation sequence of the production line, the models of each device are sequentially connected to form an overall energy consumption prediction model of the production line.
  • the overall energy consumption prediction model of the production line can be constructed through the model of each equipment.
  • the determination module is configured to select a production line model closest to the production line from a preset model library; based on the production line, adjust the model and/or equipment of the equipment in the production line model The connection relationship between the models of each device, wherein the model of each device includes the energy consumption attribute of each device and the production attribute of each device.
  • the overall energy consumption prediction model of the production line can be conveniently constructed through the existing production line model.
  • the determining module is further configured to acquire historical production data of the equipment; acquire historical energy consumption data of the equipment; based on the historical production data and the historical energy consumption data, the The model is updated.
  • the device model can also be calibrated based on historical data to improve the accuracy of the device model.
  • An optimization module configured to determine production constraints from the production data; determine overall energy consumption constraints; and adjust the production plan when the overall energy consumption prediction data of the production plan does not meet the overall energy consumption constraints so that the adjusted production plan meets the production constraints and the overall energy consumption prediction data of the adjusted production plan meets the overall energy consumption constraints; wherein the adjustment includes at least one of the following:
  • Adjust the enabling status of the equipment adjust the utilization rate of the equipment; adjust the working hours of the equipment; adjust the production load of the production plan; adjust the process parameters of the production plan.
  • the first obtaining module is configured to perform at least one of the following: obtaining the production data from an enterprise resource planning system; obtaining the production data from an advanced planning and scheduling system; obtaining the production data from a manufacturing execution system Acquiring the production data; the second obtaining module is configured to obtain the energy consumption data of each device in the production line from an energy management system or an asset management system.
  • Another aspect of the present invention proposes a device for optimizing a production plan, including a processor and a memory;
  • An application program that can be executed by the processor is stored in the memory, and is used to make the processor execute the method for evaluating a production plan as described in any one of the above items.
  • the embodiment of the present invention proposes an optimization device with a processor-memory architecture, and introduces an energy measurement to evaluate the production plan, which can evaluate the production plan from the dimension of energy consumption, and provide accurate judgment basis for energy-saving manufacturing.
  • Another aspect of the present invention provides a computer-readable storage medium, in which computer-readable instructions are stored, and the computer-readable instructions are used to execute the method for evaluating a production plan as described in any one of the above items.
  • the embodiment of the present invention proposes a computer-readable storage medium storing computer-readable instructions, introduces energy measurement to evaluate the production plan, can evaluate the production plan from the dimension of energy consumption, and provides accurate judgment basis for energy-saving manufacturing.
  • FIG. 1 is a flowchart of a method for evaluating a production plan according to an embodiment of the present invention.
  • FIG. 2 is an exemplary schematic diagram of an evaluation and optimization process of a production plan according to an embodiment of the present invention.
  • Fig. 3 is a schematic diagram of calibration of a device model according to an embodiment of the present invention.
  • Fig. 4 is a schematic diagram of an overall energy consumption prediction model of a production line according to an embodiment of the present invention.
  • Fig. 5 is a flowchart of a method for optimizing a production plan according to an embodiment of the present invention.
  • FIG. 6 is a structural diagram of an evaluation device of a production plan according to an embodiment of the present invention.
  • FIG. 7 is a layout diagram of an evaluation device of a production plan according to an embodiment of the present invention.
  • FIG. 8 is a structural diagram of an evaluation device for a production plan with a processor-memory architecture according to an embodiment of the present invention.
  • the energy efficiency improvement method in the prior art is not associated or integrated with the production system, and cannot be directly used to guide the production activities of the production system.
  • each potential production plan should have a forecast for energy consumption, but the related concepts of energy consumption prediction models for production plans are lacking in the prior art.
  • the embodiment of the present invention proposes a technical solution for bridging the energy management system and the production system to evaluate and improve the production plan, which is helpful for energy-saving manufacturing.
  • FIG. 1 is a flowchart of a method for evaluating a production plan according to an embodiment of the present invention.
  • the method 100 includes:
  • Step 101 Obtain production data related to the production plan of the production line.
  • the production line is the route that the product production process goes through, that is, the route formed by a series of production activities such as processing, transportation, assembly, and inspection, starting from the entry of raw materials into the production site.
  • a production line can contain mandatory and optional equipment. Among them: mandatory equipment is the equipment that needs to be selected in the production line; optional equipment is included in the production line and can be selected or not.
  • the production parameters of the selected equipment for example, the utilization rate of the equipment, the working time of the equipment, etc.
  • the production load of the production line or the process parameters of the production line, etc. can be planned One or more production plans.
  • a production line contains equipment 1, equipment 2, equipment 3, and equipment 4.
  • Device 1 and Device 4 are required devices.
  • Device 3 and device 4 are between device 1 and device 4, and device 3 and device 4 are optional devices.
  • the line requires at least one optional piece of equipment.
  • the execution sequence of the production line is equipment 1 -> equipment 2 -> equipment 4.
  • a production plan 1 corresponding to this execution sequence is planned. That is, production plan 1 includes equipment 1, equipment 2, and equipment 3, and the execution sequence is equipment 1 -> equipment 2 -> equipment 4.
  • the execution sequence of the production line is equipment 1 -> equipment 3 -> equipment 4.
  • a production plan 2 corresponding to this execution sequence is planned. That is, the production plan 2 includes equipment 1, equipment 3 and equipment 4, and the execution sequence is equipment 1 -> equipment 3 -> equipment 4.
  • the execution sequence of the production line is equipment 1 -> equipment 2 and equipment 3 -> equipment 4.
  • a production plan 3 corresponding to this execution sequence is planned. That is, the production plan 3 includes equipment 1, equipment 2, equipment 3 and equipment 4, and the execution sequence is equipment 1 -> equipment 2 and equipment 3 -> equipment 4.
  • Production data related to the production plan of the production line can be obtained from the production system.
  • the production data may include: the production load of the production plan, the utilization rate of the equipment, the process parameters of the production plan, the running time of the equipment, the starting state of the equipment, and so on.
  • production data is obtained from an enterprise resource planning system (Enterprise Resource Planning, ERP). In one embodiment, in step 101, production data is obtained from an Advanced Planning and Scheduling (APS) system. In one embodiment, in step 101, production data is obtained from a Manufacturing Execution System (MES).
  • ERP Enterprise Resource Planning
  • APS Advanced Planning and Scheduling
  • MES Manufacturing Execution System
  • Step 102 Obtain equipment-level energy consumption data of the production line.
  • equipment-level energy consumption data is: energy consumption data describing the size and type of energy consumption of each equipment (including mandatory equipment and optional equipment) in the production line.
  • equipment-level energy consumption data may include: power consumption indicators of smoke exhaust fans (for example, by year); power consumption indicators of variable frequency water supply units (for example, by year); power consumption indicators of automatic sprinkler pumps (for example, by month), and so on.
  • the equipment-level energy consumption data of the production line is obtained from an energy management system (Energy Management System, EnM) or an asset management system (Asset Management System, AMS).
  • EnM Energy Management System
  • AMS Asset Management System
  • Step 103 Based on the production data and the equipment-level energy consumption data, determine overall energy consumption prediction data of the production plan.
  • determining the overall energy consumption forecast data of the production plan includes: establishing an overall energy consumption forecast model of the production line; inputting production data and equipment-level energy consumption data into the overall energy consumption forecast A model; outputting the overall energy consumption prediction data of the production plan from the overall energy consumption prediction model.
  • the specific ways to establish the overall energy consumption prediction model of the production line may include:
  • Method (1) Select the model of each device in the production line from the preset device library, where the model of each device includes the energy consumption attribute of each device and the production attribute of each device; the operation based on the production line In sequence, the models of each device are connected in turn to form the overall energy consumption prediction model of the production line.
  • Method (2) Select the production line model closest to the production line from the preset model library; based on the production line, adjust the connection relationship between the model of the equipment in the production line model and/or the model of the equipment, wherein the model of each equipment Contains the energy consumption attribute of each device and the production attribute of each device.
  • Fig. 4 is a schematic diagram of an overall energy consumption prediction model of a production line according to an embodiment of the present invention.
  • the overall energy consumption prediction model of a production line has a structure similar to that of a production line.
  • the overall energy consumption prediction model includes a device 41 , a device 42 , a device 43 , a device 44 , a device 45 and a device 46 .
  • device 41, device 45 and device 46 are mandatory devices.
  • the number of devices 45 may be one or more.
  • Device 42, device 43 and device 44 are optional devices.
  • Device 42 , device 43 and device 44 are arranged between device 41 and device 45 .
  • the model of each of the equipment 43, 44, 45 and 46 includes the energy consumption attribute of the equipment and the production attribute of the equipment. Then, based on the job sequence of the production line, the models of each device are sequentially connected to form the overall energy consumption prediction model of the production line.
  • the respective energy consumption data of equipment 41, equipment 42, equipment 43, equipment 44, equipment 45 and equipment 46 are obtained from the energy management system, and the data of equipment 41, equipment 42, equipment 43, equipment 44, equipment 45 and equipment 46 are The energy consumption data are respectively assigned to the energy consumption attributes in the respective equipment models.
  • the production data related to the production plan of the production line is acquired from the production system of the production line.
  • the production data includes: (1), the activation status of each equipment in equipment 41, equipment 42, equipment 43, equipment 44, equipment 45 and equipment 46 (the activation status includes selected or not selected); (2) , device 41, device 42, device 43, device 44, device 45, and device 46; (3), device 41, device 42, device 43, device 44, device 45, and device 46 The working time of each device; (4), the production load of the production plan; (5), the process parameters of the production plan, and so on.
  • the production data of each device is extracted from the production data, and are respectively assigned to the production attributes in the device model of the device. After the production data and equipment-level energy consumption data are assigned to each equipment model in the overall energy consumption prediction model, the overall energy consumption prediction model can output the overall energy consumption prediction data of the production plan.
  • only equipment 42 among the optional equipment when in a certain production plan, only equipment 42 among the optional equipment is selected, it means that only equipment 42 is selected, and the execution sequence of the production line is equipment 41->equipment 42->equipment 45-> device46.
  • Based on the working hours of equipment 41 and the unit power consumption of equipment 41 determine the power consumption of equipment 41 when the production plan is completed; based on the working hours of equipment 42 and the unit power consumption of equipment 42, determine the completion of production
  • the unit power consumption of the device 46 is used to determine the power consumption of the equipment 46 when the production plan is completed.
  • the overall energy consumption prediction model determines the sum of the power consumption of the equipment 41, the power consumption of the equipment 42, the power consumption of the equipment 45 and the power consumption of the equipment 46, and outputs the summation result as completing the production plan
  • the predicted power consumption of the time and production line is the overall energy consumption forecast data.
  • Step 104 Evaluate the production plan based on the overall energy consumption prediction data.
  • the overall energy consumption forecast data is compared with a preset threshold value, wherein when the overall energy consumption forecast data is greater than the threshold value, it is evaluated that the production plan has not reached the energy-saving manufacturing target; when the overall energy consumption forecast data When it is less than or equal to the threshold value, it is evaluated that the production plan reaches the energy-saving manufacturing target.
  • the method further includes: acquiring historical production data of the equipment; acquiring historical energy consumption data of the equipment; and updating a model of the equipment based on the historical production data and the historical energy consumption data.
  • Fig. 3 is a schematic diagram of calibration of a device model according to an embodiment of the present invention.
  • production data measurement 31 provides equipment model calibration 32 with production history data for the equipment.
  • Energy consumption measurements 33 provide equipment model calibration 32 with historical data on the equipment's energy consumption.
  • the equipment model calibration 32 calibrates the equipment model based on the historical production data and energy consumption data (for example, calibrates the historical assignment of the energy consumption attribute and the production attribute), and uses the calibrated equipment model to execute the process of updating the equipment model 34 .
  • the calibrated device model For example: use the calibrated device model to update the corresponding device model in the device library; use the energy consumption attribute value of the calibrated device model to update the energy consumption data of the device in the energy management system or asset management system; use the calibrated The production attribute value of the equipment model is updated to update the production data of the equipment in the production plan in the generation system.
  • the embodiments of the present invention can also optimize the production plan.
  • the method 100 further includes: determining the production constraints from the production data; determining the overall energy consumption constraints; when the overall energy consumption forecast data of the production plan does not meet the overall energy consumption constraints, adjusting the production plan to Make the adjusted production plan conform to the production constraints and the overall energy consumption prediction data of the adjusted production plan conform to the overall energy consumption constraints; wherein the adjustment includes at least one of the following: adjusting the activation status of the equipment; adjusting the utilization rate of the equipment; Adjust the working time of the equipment; adjust the production load of the production plan; adjust the process parameters of the production plan, etc.
  • Fig. 5 is a flowchart of a method for optimizing a production plan according to an embodiment of the present invention.
  • the method includes:
  • Step 51 Store the production data and energy consumption data of the last production plan in the historical database.
  • Step 52 Based on the historical production data and historical energy consumption data stored in the historical database, update the equipment model in the overall energy consumption prediction model.
  • Step 53 Based on the current production plan 62 provided by the user and the production constraints 61 for the current production plan 62, use the overall energy consumption prediction model to output the energy consumption prediction result of the current production plan.
  • the production constraints 61 can be extracted from production data related to the current production plan.
  • Step 54 Judging whether the energy consumption prediction result satisfies the overall energy consumption constraint condition set by the user. If yes (corresponding to "Y” branch), execute step 55 and its subsequent steps; if not, (corresponding to "N” branch), execute step 56 and its subsequent steps.
  • Step 55 Execute the current production plan 62, and return to step 51.
  • Step 56 Optimizing the current production plan 62 .
  • FIG. 2 is an exemplary schematic diagram of the evaluation and optimization process of the production plan according to the embodiment of the present invention.
  • the evaluation and optimization process 20 of the production plan is respectively connected to the production system and the energy management system through the southbound data connector 27 , and communicates with the upper system through the northbound API 26 .
  • a database 21 is included in the evaluation and optimization process 20 of the production plan.
  • the database 21 includes an equipment library 211 , a model library 212 and a history database 213 .
  • the equipment library 211 contains models of various equipment, wherein each equipment model includes energy consumption attributes and production attributes.
  • the model library 212 contains various existing production line models.
  • the history database 213 saves the production history data and energy consumption history data of each equipment respectively received from the production system and the energy management system via the southbound data connector 27 .
  • the prediction model configuration processing 22 supports the configuration of the overall energy consumption prediction model based on actual application scenarios.
  • the predictive model configuration process 22 can construct an overall energy consumption predictive model by connecting various devices used on the production line, wherein each device is endowed with two types of attributes: energy consumption attributes (such as: energy efficiency, performance curve, utility type, utility cost rates, etc.) and production attributes (e.g. load levels, utilization, etc.).
  • energy consumption attributes such as: energy efficiency, performance curve, utility type, utility cost rates, etc.
  • production attributes e.g. load levels, utilization, etc.
  • device-to-device interconnections can be built manually or imported from other systems or simulation software (such as SCADA, Plant Simulation, Preactor, etc.).
  • SCADA Plant Simulation, Preactor, etc.
  • the new device model can then be saved in the device library for future use.
  • KPI visualization processing 213 data points related to energy and production and statistical KPIs are displayed to provide data transparency of the target system. Based on KPI visualization processing 213, users can view the production status and energy consumption data of each device, production line and the entire factory in a unified interface. Historical data can be viewed in the same interface to help users detect anomalies in production operations.
  • the forecasting process 24 provide forecasts related to energy consumption according to the overall energy consumption forecasting model and the production plan extracted from the production system. Once the production plan is obtained, it is decomposed and assigned to individual equipment. Based on the equipment model, the energy consumption of the production plan can be calculated according to the load, utilization rate, running time, energy performance curve, etc., and then the energy KPI of the entire production plan can be predicted, and The total energy KPI can be broken down to each device.
  • FIG. 6 is a structural diagram of an evaluation device of a production plan according to an embodiment of the present invention.
  • the evaluation device 600 of the production plan includes:
  • the first acquisition module 601 is configured to acquire production data related to the production plan of the production line;
  • the second acquisition module 602 is configured to acquire equipment-level energy consumption data of the production line
  • a determining module 603, configured to determine the overall energy consumption prediction data of the production plan based on the production data and equipment-level energy consumption data;
  • An evaluation module 604 configured to evaluate the production plan based on the overall energy consumption prediction data.
  • the determination module 603 is used to establish an overall energy consumption prediction model of the production line; input production data and equipment-level energy consumption data into the overall energy consumption prediction model; output the overall energy consumption of the production plan from the overall energy consumption prediction model forecast data.
  • the determining module 603 is configured to select a model of each device in the production line from a preset device library, where the model of each device includes the energy consumption attribute of each device and the Production attributes; based on the operation sequence of the production line, the models of each device are connected in turn to form the overall energy consumption prediction model of the production line.
  • the determining module 603 is configured to select the production line model closest to the production line from a preset model library; based on the production line, adjust the connection relationship between the model of the equipment in the production line model and/or the model of the equipment , where the model of each device includes the energy consumption attribute of each device and the production attribute of each device.
  • the determining module 603 is further configured to acquire historical production data of the equipment; acquire historical energy consumption data of the equipment; and update a model of the equipment based on the historical production data and the historical energy consumption data.
  • it also includes an optimization module 605, which is used to determine the production constraints from the production data; determine the overall energy consumption constraints; when the overall energy consumption forecast data of the production plan does not meet the overall energy consumption constraints, adjust the production Plan so that the adjusted production plan meets the production constraints and the overall energy consumption prediction data of the adjusted production plan meets the overall energy consumption constraints; wherein the adjustment includes at least one of the following: adjusting the enabled state of the equipment; adjusting the use of the equipment rate; adjust the working hours of the equipment; adjust the production load of the production plan; adjust the process parameters of the production plan.
  • the first obtaining module 601 is configured to perform at least one of the following: obtaining production data from an enterprise resource planning system; obtaining production data from an advanced planning and scheduling system; obtaining production data from a manufacturing execution system;
  • the second obtaining module 602 is used to obtain the energy consumption data of each device in the production line from the energy management system or asset management system.
  • FIG. 7 is a layout diagram of an evaluation device of a production plan according to an embodiment of the present invention.
  • an evaluation device 600 as shown in FIG. 6 is arranged between an energy management system/asset management system 701 and a production system 702 .
  • the evaluation device 600 has two-way communication links with the energy management system/asset management system 701 and the production system 702 respectively.
  • the production system 702 can be implemented as an ERP system, APS or MES system.
  • a two-way communication link may be implemented as a wired communication link or a wireless communication link.
  • the wired communication link may include at least one of the following: universal serial bus, controller area network, serial port, etc.; the wireless wired communication link may include at least one of the following: Ethernet link, infrared link interface, near field communication link, Bluetooth link, Zigbee link, wireless communication link, wireless broadband link, etc.
  • FIG. 8 is a structural diagram of an evaluation device for a production plan with a processor-memory architecture according to an embodiment of the present invention.
  • the evaluation device 800 of the production plan includes a processor 801, a memory 802, and a computer program stored on the memory 802 and operable on the processor 801.
  • the computer program is executed by the processor 801, any of the above The evaluation method of the production plan.
  • the memory 802 can be specifically implemented as various storage media such as electrically erasable programmable read-only memory (EEPROM), flash memory (Flash memory), and programmable program read-only memory (PROM).
  • the processor 801 may be implemented to include one or more central processing units or one or more field programmable gate arrays, wherein the field programmable gate arrays integrate one or more central processing unit cores.
  • the central processing unit or central processing unit core may be implemented as a CPU or MCU or DSP, and so on.
  • the hardware modules in the various embodiments may be implemented mechanically or electronically.
  • a hardware module may include specially designed permanent circuits or logic devices (such as special-purpose processors, such as FPGAs or ASICs) to perform specific operations.
  • Hardware modules may also include programmable logic devices or circuits (eg, including general-purpose processors or other programmable processors) temporarily configured by software to perform particular operations.
  • programmable logic devices or circuits eg, including general-purpose processors or other programmable processors

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Abstract

La présente invention concerne un procédé et un appareil d'évaluation de plan de production, ainsi qu'un support de stockage lisible par ordinateur. Le procédé comprend les étapes consistant à : obtenir des données de production associées à un plan de production d'une ligne de production (101) ; obtenir des données de consommation d'énergie au niveau des dispositifs de la ligne de production (102) ; déterminer des données de prédiction de consommation d'énergie globale du plan de production sur la base des données de production et des données de consommation d'énergie au niveau des dispositifs (103) ; et évaluer le plan de production sur la base des données de prédiction de consommation d'énergie globale (104). Ce procédé introduit une mesure de l'énergie pour évaluer le plan de production, et peut également améliorer le plan de production sur la base de la mesure de l'énergie. Il présente l'avantage d'une bonne évolutivité et convient à divers scénarios d'application.
PCT/CN2021/118348 2021-09-14 2021-09-14 Procédé et appareil d'évaluation de plan de production, et support de stockage lisible par ordinateur WO2023039729A1 (fr)

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Cited By (1)

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