WO2023039729A1 - Production plan evaluation method and apparatus, and computer readable storage medium - Google Patents

Abstract

A production plan evaluation method and apparatus, and a computer readable storage medium. The method comprises: obtaining production data related to a production plan of a production line (101); obtaining device-level energy consumption data of the production line (102); determining overall energy consumption prediction data of the production plan on the basis of the production data and the device-level energy consumption data (103); and evaluating the production plan on the basis of the overall energy consumption prediction data (104). The above method introduces an energy measurement to evaluate the production plan, and can also improve the production plan on the basis of the energy measurement, has the advantage of good expansibility, and is suitable for various application scenarios.

Description

Method, device, and computer-readable storage medium for evaluating a production plan technical field

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.

Background technique

Every aspect associated with manufacturing activities consumes energy, from manufacturing, to maintaining the shop floor environment, transporting materials or products, to driving heavy machinery. Energy-efficient manufacturing and/or carbon-neutral production set higher standards for energy performance.

Usually hardware or software measures are recommended to achieve energy-efficient manufacturing. For example, from an energy management point of view, substituting energy-saving resources and installing energy recovery devices all contribute to energy-saving purposes and achieve energy efficiency. Additionally, improved equipment efficiency, advance planning and evaluation of manufacturing processes can also improve energy performance in manufacturing. Production scheduling has long been an important topic in production operations, with the goal of balancing resources, operations, and processes to achieve maximum productivity and profitability.

However, none of the current energy efficiency improvement methods can be directly used to evaluate production activities, let alone improve production activities.

Contents of the invention

In order to solve the above problems, 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:

Obtain production data related to the production plan of the production line;

Acquiring equipment-level energy consumption data of the production line;

determining overall energy consumption prediction data of the production plan based on the production data and the equipment-level energy consumption data;

The production plan is evaluated based on the overall energy consumption forecast data.

It can be seen that 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.

In one embodiment, 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:

Establishing an overall energy consumption prediction model of the production line;

inputting the production data and the device-level energy consumption data into the overall energy consumption prediction model;

The overall energy consumption prediction data of the production plan is output from the overall energy consumption prediction model.

Therefore, by introducing a prediction model, the overall energy consumption data can be predicted conveniently.

In one embodiment, the establishment of the overall energy consumption prediction model of the production line includes:

selecting 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 of each device and the production attribute 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.

Therefore, the overall energy consumption prediction model of the production line can be constructed through the model of each equipment.

In one embodiment, the establishment of the overall energy consumption prediction model of the production line includes:

Selecting a production line model closest to the production line from a preset model library;

Based on the production line, adjust the model of the equipment in the production line model and/or the connection relationship between the models of the equipment, wherein the model of each equipment includes the energy consumption attribute of each equipment and the energy consumption attribute of each equipment production attributes.

Therefore, the overall energy consumption prediction model of the production line can be conveniently constructed through the existing production line model.

In one embodiment, also include:

Obtain the production history data of the equipment;

Acquiring historical energy consumption data of the device;

The model of the equipment is updated based on the historical production data and the historical energy consumption data.

It can be seen that the device model can also be calibrated based on historical data to improve the accuracy of the device model.

In one embodiment, also include:

determining production constraints from said production data;

Determine overall energy consumption constraints;

When the overall energy consumption prediction data of the production plan does not comply with the overall energy consumption constraints, adjust the production plan so that the adjusted production plan meets the production constraints and the overall energy consumption of the adjusted production plan The energy consumption forecast data conforms to the overall energy consumption constraint; 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.

Optimization for production planning is thus also enabled by the overall energy consumption forecast data.

In one embodiment, 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.

It can be seen that by obtaining production data and equipment-level energy consumption data from various data sources, it has good scalability.

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.

It can be seen that 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.

In one embodiment, 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.

Therefore, by introducing a prediction model, the overall energy consumption data can be predicted conveniently.

In one embodiment, 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.

Therefore, the overall energy consumption prediction model of the production line can be constructed through the model of each equipment.

In one embodiment, 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.

Therefore, the overall energy consumption prediction model of the production line can be conveniently constructed through the existing production line model.

In one embodiment, 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.

It can be seen that the device model can also be calibrated based on historical data to improve the accuracy of the device model.

In one embodiment, also include:

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.

Optimization for production planning is thus also enabled by the overall energy consumption forecast data.

In one embodiment, 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.

It can be seen that by obtaining production data and equipment-level energy consumption data from various data sources, it has good scalability.

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.

Therefore, 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.

It can be seen that 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.

Description of drawings

Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, so that those of ordinary skill in the art will be more aware of the above-mentioned and other features and advantages of the present invention. In the accompanying drawings:

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.

Wherein, the reference signs are as follows:

label	meaning
100	Evaluation method of production plan
101～104	step
20	Evaluation and optimization of production plans
twenty one	database
twenty two	Predictive Model Configuration Handling
twenty three	KPI visualization
twenty four	predictive processing
25	optimization
26	Northbound API
27	Southbound Data Connector
211	Equipment Library
212	model library
213	historical database
31	Production Data Measurement
32	Device Model Calibration
33	energy consumption measurement
34	Update device model
41～46	equipment
51～56	step
61	production constraints

62	current production plan
600	Evaluation device for production planning
601	first acquisition module
602	Second acquisition module
603	Determine the module
604	assessment module
605	optimization module
701	Energy Management System/Asset Management System
702	production system
800	Evaluation device for production planning
801	processor
802	memory

Detailed ways

In order to make the purpose, technical solution and advantages of the present invention clearer, the following examples are given to further describe the present invention in detail.

For the sake of brevity and intuition in description, the solution of the present invention is described below by describing several representative implementation manners. Numerous details in the embodiments are only used to help the understanding of the solutions of the present invention. But obviously, the technical solutions of the present invention may not be limited to these details when implemented. In order to avoid unnecessarily obscuring the solution of the present invention, some embodiments are not described in detail, but only a framework is given. Hereinafter, "including" means "including but not limited to", and "according to..." means "at least according to, but not limited to only based on...". Due to the language habits of Chinese, when the quantity of a component is not specifically indicated below, it means that the component can be one or more, or can be understood as at least one.

The applicant found that: 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. The applicant made further research and found that the causes of the defect include at least:

(1) For the optimization of production plans, 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.

(2) Energy planning should consider the potential impact of resources, operations, and process adjustments, which requires two-way communication between production systems and energy management systems. However, the production system and the energy management system in the prior art are independent and lack communication interaction.

Considering the above reasons, 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.

As shown in Figure 1, 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.

Corresponding to the selected equipment in the production line, 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., the production line can be planned One or more production plans.

For example, suppose 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. Assume that the line requires at least one optional piece of equipment.

(1) When selecting equipment 2 and not selecting equipment 3 from the optional 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.

(2) When selecting equipment 3 and not selecting equipment 2 from the optional equipment, 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.

(3) When selecting equipment 2 and equipment 3 from the optional equipment, 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.

In one embodiment, in step 101, 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).

The above exemplarily describes a typical example of obtaining production data, and those skilled in the art may realize that this description is only exemplary and is not intended to limit the scope of protection of the embodiments of the present invention.

Step 102: Obtain equipment-level energy consumption data of the production line.

Here, the meaning of 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. For example, 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.

In one embodiment, in step 102, 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).

The above exemplarily describes a typical example of obtaining production data, and those skilled in the art can realize that this description is only exemplary and is not intended to limit the protection scope of the embodiments of the present invention

Step 103: Based on the production data and the equipment-level energy consumption data, determine overall energy consumption prediction data of the production plan.

In one embodiment, based on the production data and equipment-level energy consumption data, 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. Specifically, 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 . Among them, 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 .

In the establishment process of the overall energy consumption prediction model: first, select the respective models of equipment 41, equipment 42, equipment 43, equipment 44, equipment 45 and equipment 46 in the production line from the preset equipment library, in which equipment 41, equipment 42. 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.

Next, 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.

And, the production data related to the production plan of the production line is acquired from the production system of the production line. For example: 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.

For example, 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 power consumption of equipment 42 during planning; based on the working hours of equipment 45 and the unit power consumption of equipment 45, determine the power consumption of equipment 45 when the production plan is completed; based on the working hours of equipment 46 and the unit power consumption of equipment 46 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. Then, 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.

The above exemplarily describes the schematic diagram of the overall energy consumption prediction model of the production line. Those skilled in the art can appreciate that this description is only exemplary, and is not intended to limit the protection scope of the embodiments of the present invention.

Step 104: Evaluate the production plan based on the overall energy consumption prediction data.

Here, 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.

In one embodiment, 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. In FIG. 3 , 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 . 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.

In addition to evaluating the production plan, the embodiments of the present invention can also optimize the production plan.

In one embodiment, 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.

As shown in Figure 5, 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. Wherein, 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 .

Based on the above analysis, 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.

In FIG. 2 , 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.). Moreover, device-to-device interconnections can be built manually or imported from other systems or simulation software (such as SCADA, Plant Simulation, Preactor, etc.). After the overall energy consumption prediction model is constructed, the device model is calibrated using the historical data stored in the historical database 213 . If it is found that the model of a specific device does not exist in the device library 211, a corresponding new device model is constructed according to the energy consumption attribute and production attribute of the specific device, and the new device model is calibrated using the historical data of the specific device , the new device model can then be saved in the device library for future use.

In 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.

In 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.

As shown in FIG. 6 , 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.

In one embodiment, 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.

In one embodiment, 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.

In one embodiment, 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.

In one embodiment, 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.

In one embodiment, 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.

In one embodiment, 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.

In FIG. 7 , 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. Wherein, 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. For example, 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.

The embodiment of the present invention also proposes a state monitoring device for a frequency converter with a processor-memory architecture. 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.

As shown in Figure 8, 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. When the computer program is executed by the processor 801, any of the above The evaluation method of the production plan.

Wherein, 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. Specifically, the central processing unit or central processing unit core may be implemented as a CPU or MCU or DSP, and so on.

It should be noted that not all steps and modules in the above-mentioned processes and structure diagrams are necessary, and some steps or modules can be ignored according to actual needs. The execution order of each step is not fixed and can be adjusted as needed. The division of each module is only to facilitate the description of the functional division adopted. In actual implementation, one module can be divided into multiple modules, and the functions of multiple modules can also be realized by the same module. These modules can be located in the same device. , or on a different device.

The hardware modules in the various embodiments may be implemented mechanically or electronically. For example, 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. As for implementing the hardware module in a mechanical way, using a dedicated permanent circuit, or using a temporarily configured circuit (such as configured by software) to realize the hardware module, it can be decided according to cost and time considerations.

The above descriptions are only preferred implementation modes of the present invention, and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (16)

1. A method (100) for evaluating a production plan, characterized by comprising:

   Obtain production data related to the production plan of the production line (101);

   Acquiring equipment-level energy consumption data of the production line (102);

   Determine overall energy consumption prediction data of the production plan based on the production data and the equipment-level energy consumption data (103);

   The production plan is evaluated based on the overall energy consumption forecast data (104).
2. The method (100) according to claim 1, characterized in that,

   The determining the overall energy consumption prediction data of the production plan based on the production data and the equipment-level energy consumption data (103) includes:

   Establishing an overall energy consumption prediction model of the production line;

   inputting the production data and the device-level energy consumption data into the overall energy consumption prediction model;

   The overall energy consumption prediction data of the production plan is output from the overall energy consumption prediction model.
3. The method (100) according to claim 2, wherein said establishing an overall energy consumption prediction model of a production line comprises:

   selecting 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 of each device and the production attribute 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.
4. The method (100) according to claim 2, wherein said establishing an overall energy consumption prediction model of a production line comprises:

   Selecting a production line model closest to the production line from a preset model library;

   Based on the production line, adjust the model of the equipment in the production line model and/or the connection relationship between the models of the equipment, wherein the model of each equipment includes the energy consumption attribute of each equipment and the energy consumption attribute of each equipment production attributes.
5. The method (100) according to claim 3 or 4, further comprising:

   Obtain the production history data of the equipment;

   Acquiring historical energy consumption data of the device;

   The model of the equipment is updated based on the historical production data and the historical energy consumption data.
6. The method (100) according to claim 1, further comprising:

   determining production constraints from said production data;

   Determine overall energy consumption constraints;

   When the overall energy consumption prediction data of the production plan does not comply with the overall energy consumption constraints, adjust the production plan so that the adjusted production plan meets the production constraints and the overall energy consumption of the adjusted production plan The energy consumption forecast data conforms to the overall energy consumption constraint; 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.
7. The method (100) according to claim 1, characterized in that,

   The acquisition of production data (101) related to the production plan of the production line includes at least one of the following:

   obtaining said production data from an enterprise resource planning system;

   obtaining said production data from an advanced planning and scheduling system;

   obtaining said production data from a manufacturing execution system;

   The acquiring the equipment-level energy consumption data of the production line (102) includes: acquiring the energy consumption data of each equipment in the production line from an energy management system or an asset management system.
8. An evaluation device (600) for a production plan, characterized in that it includes:

   A first acquisition module (601), configured to acquire production data related to the production plan of the production line;

   A second acquisition module (602), configured to acquire equipment-level energy consumption data of the production line;

   A determination module (603), 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 (604), configured to evaluate the production plan based on the overall energy consumption prediction data.
9. The device (600) according to claim 8, characterized in that,

   The determination module (603) 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 model outputs the overall energy consumption prediction data of the production plan.
10. The device (600) according to claim 9, characterized in that,

    The determining module (603), 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 of each device and the The production attribute of the equipment; based on the operation sequence of the production line, the models of each equipment are sequentially connected to form an overall energy consumption prediction model of the production line.
11. The device (600) according to claim 9, characterized in that,

    The determination module (603) 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 of the equipment in the production line model and/or one of the models of the equipment The connection relationship between each device, wherein the model of each device includes the energy consumption attribute of each device and the production attribute of each device.
12. The device (600) according to claim 10 or 11, characterized in that,

    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 .
13. The device (600) according to claim 8, further comprising:

    An optimization module (605), configured to determine production constraints from the production data; determine overall energy consumption constraints; and adjust the overall energy consumption constraints when the overall energy consumption forecast data of the production plan does not meet the overall energy consumption constraints The production plan is adjusted 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.
14. The device (600) according to claim 8, characterized in that,

    The first obtaining module (601) 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 Production Data;

    The second obtaining module (602) is configured to obtain energy consumption data of each device in the production line from an energy management system or an asset management system.
15. A production plan optimization device (800), characterized by comprising a processor (801) and a memory (802);

    An application program executable by the processor (801) is stored in the memory (802), for enabling the processor (801) to execute the production plan according to any one of claims 1 to 7. Evaluation Methods (100).
16. A computer-readable storage medium, characterized in that computer-readable instructions are stored therein, and the computer-readable instructions are used to execute the production plan evaluation method (100) according to any one of claims 1-7.

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