Method, device and storage medium for energy consumption attribution and apportioning for multi-level production structures

Abstract

The application discloses a multi-level production structure-oriented energy consumption attribution and allocation method, equipment and storage medium, and the method firstly acquires data such as an organizational structure and a process route of a production system, and constructs a multi-level production relationship model containing organizational levels, process levels and physical and logical attribution relationships of equipment. Then, according to the model, equipment-level energy consumption is determined as three types of special energy consumption, public energy consumption or shared energy consumption, and the special energy consumption is directly attributed. For the public and shared energy consumption, preset rules are used for allocation calculation. Finally, the attributed and allocated energy consumption is collected level by level based on the level relationship, and process-level, unit-level and production line-level energy consumption results are generated. The application realizes accurate mapping and reasonable allocation of equipment-level energy consumption to production object-level energy consumption, solves the problems of unclear energy consumption attribution and unreasonable allocation in a complex production structure, and provides a reliable basis for fine energy consumption management, cost accounting and energy saving optimization.

Description

Technical Field

[0001] This invention relates to the field of industrial energy management and energy consumption analysis technology, and in particular to energy consumption attribution and allocation methods, equipment and storage media for multi-level production structures. Background Technology

[0002] As industrial enterprises continue to improve their digital and refined management, energy consumption analysis has evolved from traditional total statistics to equipment-level monitoring, process-level accounting, and production object-level evaluation. In typical industrial scenarios such as equipment manufacturing, machining, and painting, various metering instruments and industrial control acquisition systems deployed by enterprises can acquire equipment energy consumption data and achieve equipment-level energy consumption analysis through technologies such as energy consumption decomposition and status identification. However, existing energy consumption data remains at the single equipment level and cannot be mapped to the process, unit, or production line level. This results in a disconnect between energy consumption results and the actual production organization methods of enterprises, making it difficult to meet management needs such as cost accounting, process benchmarking, accountability, and energy-saving optimization.

[0003] In actual production, the organizational hierarchy of "production line-unit-process" is deeply coupled with the technological hierarchy of "process route-process-step," and equipment and various production objects generally have multi-dimensional mapping relationships. On the one hand, the same equipment may serve multiple processes or multiple production objects; on the other hand, the same process may also be completed collaboratively by multiple pieces of equipment, and the physical affiliation of equipment is not always consistent with the logical affiliation in the system. For complex production structures, existing energy consumption analysis methods lack a unified affiliation determination mechanism, cannot accurately distinguish between dedicated energy consumption, public energy consumption, and shared energy consumption, and cannot reasonably allocate energy consumption based on object relationships, leading to duplicate calculations, omissions, or aggregation biases in energy consumption results.

[0004] Furthermore, industrial sites commonly contain shared energy-consuming systems such as air compressor stations, circulating cooling systems, and centralized dust removal systems. These systems serve multiple production objects, making it difficult to directly attribute them to a single piece of equipment, process, or production line. Some equipment may switch between different tasks, batches, or process stages, resulting in shared energy consumption over time. For this type of energy consumption, simply using averages, fixed ratios, or empirical rules for allocation fails to accurately reflect the actual occupancy and energy contribution of each production object, leading to allocation results that lack interpretability and calculability.

[0005] In summary, existing technologies urgently need an energy consumption attribution and allocation method for multi-level production structures to realize the attribution, allocation, and transfer of equipment-level energy consumption to process-level, unit-level, and production line-level energy consumption, complete the transformation from "equipment values" to "production semantics," and provide industrial enterprises with an interpretable, traceable, and accountable energy consumption management foundation. Summary of the Invention

[0006] The purpose of this invention is to provide a method, device, and storage medium for energy consumption attribution and allocation in multi-level production structures. Based on the energy consumption decomposition results at the equipment level, combined with the production organization level, process route level, and the physical and logical attribution relationships between equipment and production objects, the invention determines the attribution of different types of energy consumption, calculates the allocation, and summarizes the results at the hierarchical level, ultimately forming process-level, unit-level, and production line-level energy consumption results, thus completing the transformation of energy consumption from the equipment dimension to the production semantic dimension.

[0007] The technical solution adopted in this invention is:

[0008] An energy consumption attribution and allocation method for multi-level production structures includes the following steps:

[0009] To construct a multi-level production relationship model, acquire organizational structure data, process route data, equipment association data, and equipment-level energy consumption data from the production system. The multi-level production relationship model defines at least the hierarchical relationship of production organization, the hierarchical relationship of process, and the physical and logical affiliation relationships between equipment and production objects.

[0010] Based on the multi-level production relationship model, equipment-level energy consumption data is classified into dedicated energy consumption, public energy consumption, or shared energy consumption, and dedicated energy consumption is directly assigned to the production object of the corresponding unique service.

[0011] Based on the preset allocation rules, calculate the energy consumption data of public energy consumption and shared energy consumption, and calculate the allocation results to each related production object.

[0012] Based on the hierarchical relationship of production organization and / or process hierarchy, the energy consumption allocation results of dedicated energy consumption, public energy consumption and shared energy consumption are summarized upwards level by level to generate energy consumption results at the process level, unit level and / or production line level.

[0013] Furthermore, the hierarchical relationship of production organization includes the subordinate relationship between production lines and production units, the subordinate relationship between production units and processes, and the mapping relationship between equipment and processes, production units, or production lines.

[0014] Furthermore, the process hierarchy includes the sequential relationships between process routes, operations, and steps.

[0015] Furthermore, physical attribution refers to the static attribution of equipment in terms of space or administration; logical attribution refers to the dynamic association of equipment with production objects based on production tasks, orders, or process paths. Furthermore, the physical or logical attribution relationship between equipment and production objects includes one-to-one, many-to-one, one-to-many, and cross-level mapping relationships.

[0016] Furthermore, dedicated energy consumption refers to the energy consumption generated by equipment serving only a single production object within the statistical period;

[0017] Public energy consumption refers to energy consumption that serves multiple production objects and cannot be directly and uniquely attributed to any one object.

[0018] Shared energy consumption refers to the energy consumption of the same equipment within a statistical period due to serving different tasks, processes, or production objects.

[0019] Furthermore, the preset allocation rules include at least one of the following: allocation by processing time, allocation by equipment occupancy time, allocation by output, allocation by number of workpieces, allocation by rated power weight, allocation by process energy consumption coefficient, allocation by task load ratio, and allocation by energy use contribution.

[0020] Furthermore, the allocation calculation is achieved through the following formula:

[0021] ;

[0022] in, To allocate the energy consumption to the i-th production object, This refers to the total amount of public or shared energy consumption to be allocated. The allocated weight is the weight corresponding to the i-th production object. This is the sum of the weights of all production objects participating in the allocation. The total number of production objects participating in the apportionment.

[0023] Furthermore, when the physical and logical ownership of equipment points to different production objects, the energy consumption ownership is determined according to preset priority rules.

[0024] Furthermore, the preset priority rule is: energy consumption determination and attribution are based on logical attribution relationships first.

[0025] Furthermore, the implementation of hierarchical aggregation includes: aggregating equipment-level energy consumption results to their respective processes to obtain process-level energy consumption results; aggregating process-level energy consumption results belonging to the same production unit to obtain unit-level energy consumption results; and aggregating unit-level energy consumption results belonging to the same production line to obtain production line-level energy consumption results.

[0026] Furthermore, the present invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the energy consumption attribution and allocation method for multi-level production structures.

[0027] Furthermore, the present invention also discloses a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the energy consumption attribution and allocation method for multi-level production structures.

[0028] The present invention adopts the above technical solution and has the following advantages compared with the prior art:

[0029] (1) The production organization level, process level, and physical and logical attribution relationship between equipment and production objects are jointly modeled to form a two-level coupling relationship network, realizing the effective transmission of equipment-level energy consumption to the production business level and the accurate association between energy consumption data and production organization, breaking through the limitations of the single equipment tree structure of the existing technology. (2) Adopting the logic of "first type identification, then allocation calculation", the energy consumption is first clarified as dedicated, public or shared type, and different processing methods are adopted for different types of energy consumption - dedicated energy consumption is directly assigned, and public energy consumption and shared energy consumption are allocated as needed, solving the long-standing pain point of difficult attribution of public energy consumption in industrial sites. (3) This invention strengthens the production business semantics of energy consumption results through the full-chain hierarchical energy consumption transmission and summary of "equipment - process - unit - production line - process route - product", meeting the energy consumption refined management needs of multi-level production structures, and breaking through the limitation of the simple energy consumption summary of "equipment to workshop" in the existing technology.

[0030] This invention is applicable to industrial scenarios with complex production hierarchies, such as equipment manufacturing, machining, assembly, painting, and heat treatment. It has strong versatility and high engineering application value and promotion prospects. Attached Figure Description

[0031] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments;

[0032] Figure 1 This is a schematic diagram of the overall process of the energy consumption attribution and allocation method for multi-level production structures described in this invention;

[0033] Figure 2 This is a schematic diagram of the process for constructing the multi-level production relationship model and determining energy consumption attribution as described in this invention;

[0034] Figure 3 This is a schematic diagram of the calculation process for the allocation of public and shared energy consumption as described in this invention;

[0035] Figure 4 This is a schematic diagram illustrating the hierarchical transmission and summarization of energy consumption results as described in this invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0037] The energy consumption attribution and allocation method for multi-level production structures provided by this invention is applicable to industrial scenarios with deep coupling between organizational and process levels, complex mapping relationships between equipment and production objects, and the coexistence of public and shared energy consumption. Figure 1 As shown, this method is based on the energy consumption decomposition results at the equipment level. It combines production organization relationships, process relationships, and equipment ownership rules to determine the ownership of energy consumption, calculate the allocation, and summarize the results at different levels, such as process level, unit level, and production line level. The specific execution steps are explained in detail in each example.

[0038] like Figures 1 to 4 As shown in any of the accompanying drawings, this invention discloses a method for energy consumption attribution and allocation in a multi-level production structure, comprising the following steps:

[0039] To construct a multi-level production relationship model, the organization structure data, process route data, equipment association data, and equipment-level energy consumption data in the production system are acquired. The multi-level production relationship model defines at least the production organization hierarchy, process hierarchy, and the physical and logical affiliation relationships between equipment and production objects. Among them, one-to-many, many-to-one, and cross-level mapping relationships are allowed between equipment and production objects to adapt to equipment sharing, process switching, and cross-unit collaborative production in complex industrial scenarios.

[0040] Based on the multi-level production relationship model, equipment-level energy consumption data is classified into dedicated energy consumption, public energy consumption, or shared energy consumption, and dedicated energy consumption is directly assigned to the production object of the corresponding unique service.

[0041] Based on the preset allocation rules, calculate the energy consumption data of public energy consumption and shared energy consumption, and calculate the allocation results to each related production object.

[0042] Based on the hierarchical relationship of production organization and / or process hierarchy, the energy consumption allocation results of dedicated energy consumption, public energy consumption and shared energy consumption are summarized upwards level by level to generate energy consumption results at the process level, unit level and / or production line level.

[0043] The steps of the energy consumption attribution and allocation method of the present invention are executed sequentially and closely related to each other, ensuring the accuracy of energy consumption attribution and the rationality of allocation.

[0044] Furthermore, the hierarchical relationship of production organization includes core objects such as production lines, production units, and processes, and the hierarchical subordinate relationships formed between these objects. Specifically, this includes the subordinate relationship between production lines and production units, the subordinate relationship between production units and processes, and the mapping relationship between equipment and processes, production units, or production lines.

[0045] Furthermore, the process hierarchy includes core objects such as process routes, procedures, and steps. The hierarchical relationships between these objects follow the process execution logic, specifically including the sequential relationships between process routes, procedures, and steps.

[0046] Furthermore, physical affiliation refers to the static affiliation of equipment in terms of space or administration; logical affiliation refers to the dynamic association of equipment with production objects based on production tasks, orders, or process paths.

[0047] Furthermore, the above mapping relationships cover one-to-many and many-to-one mapping relationships between equipment and processes, units, and production lines, realizing the coupling and association between the production organization level and the process level.

[0048] Furthermore, the energy consumption described in this invention is divided into three categories based on its service object and attribution characteristics: dedicated energy consumption, public energy consumption, and shared energy consumption, as specifically defined below:

[0049] Dedicated energy consumption: refers to energy consumption that serves only a single production object, such as a process, unit, or production line, and its attribution is unique;

[0050] Public energy consumption refers to energy consumption that is used by multiple production objects and cannot be directly and uniquely attributed to a single production object; its service objects are universal.

[0051] Shared energy consumption refers to the energy consumption generated when equipment or energy resources are alternately occupied by multiple production objects in the time or task dimension within a statistical period. The attribution relationship changes dynamically with task switching.

[0052] Furthermore, the preset allocation rules include at least one of the following: allocation by processing time, allocation by equipment occupancy time, allocation by output, allocation by number of workpieces, allocation by rated power weight, allocation by process energy consumption coefficient, allocation by task load ratio, and allocation by energy use contribution.

[0053] Furthermore, the allocation calculation is achieved through the following formula:

[0054] ;

[0055] in, To allocate the energy consumption to the i-th production object, This refers to the total amount of public or shared energy consumption to be allocated. The allocated weight is the weight corresponding to the i-th production object. This is the sum of the weights of all production objects participating in the allocation. The total number of production objects participating in the apportionment.

[0056] Furthermore, when the physical and logical ownership of equipment points to different production objects, the energy consumption ownership is determined according to preset priority rules.

[0057] Furthermore, the preset priority rule is: energy consumption determination and attribution are based on logical attribution relationships first.

[0058] Furthermore, the implementation of hierarchical aggregation includes: aggregating equipment-level energy consumption results to their respective processes to obtain process-level energy consumption results; aggregating process-level energy consumption results belonging to the same production unit to obtain unit-level energy consumption results; and aggregating unit-level energy consumption results belonging to the same production line to obtain production line-level energy consumption results.

[0059] Specifically, based on the constructed multi-level production relationship model, the dedicated energy consumption results after attribution determination and the calculated allocated energy consumption results are summarized and transmitted level by level, ultimately generating energy consumption results at the process level, unit level, production line level, and process-related levels. Specific summarization paths include: summarizing equipment-level energy consumption to the process level, process-level energy consumption to the unit level, and unit-level energy consumption to the production line level. Simultaneously, energy consumption aggregation along the process route can be achieved. The final output energy consumption results through hierarchical summarization and transmission include, but are not limited to: process energy consumption, unit energy consumption, production line energy consumption, process path energy consumption, product-related energy consumption, and order-related energy consumption, achieving precise matching of energy consumption results with production business semantics.

[0060] Furthermore, the present invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the energy consumption attribution and allocation method for multi-level production structures.

[0061] Furthermore, the present invention also discloses a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the energy consumption attribution and allocation method for multi-level production structures.

[0062] The working principle of this invention will be explained in detail below in different application scenarios:

[0063] Example 1: This example focuses on a dedicated energy consumption scenario, specifically the energy consumption of a dedicated CNC machine tool in a certain processing unit. This CNC machine tool only serves the "finishing process" and has not been switched to other processes or any other production objects during the statistical period. The specific execution steps are as follows:

[0064] S1 constructs a multi-level production relationship model: such as Figure 2As shown, the organizational structure data, process route data, CNC machine tool ledger data, and production execution data of the processing unit are obtained. A multi-level production relationship model is established to clarify the physical affiliation between the CNC machine tool and the finishing process, as well as the organizational hierarchy between the finishing process and its production unit and production line. Simultaneously, the equipment-level energy consumption decomposition results are obtained to clarify the total energy consumption data within the statistical period.

[0065] S2 determines the energy consumption attribution: Based on the constructed multi-level production relationship model, the operating status and task execution records of the CNC machine tool are analyzed to confirm that it only serves the finishing process within the statistical period and has a unique correspondence with this process. Therefore, all the energy consumption of the CNC machine tool is determined to be dedicated energy consumption and directly attributed to the finishing process.

[0066] S3 execution hierarchical summary: such as Figure 4 As shown, according to the production hierarchy, the energy consumption data of the finishing process is summarized to its respective production unit, and then summarized by the production unit to the corresponding production line, finally forming the process-level, unit-level and production line-level energy consumption results.

[0067] This example demonstrates that for equipment energy consumption that serves only a single production object, the present invention can directly complete the attribution determination and hierarchical summary through the above steps, without the need for allocation calculation, effectively avoiding unnecessary splitting of dedicated energy consumption and improving the efficiency and accuracy of energy consumption attribution.

[0068] Example 2: This example addresses a common energy consumption scenario, specifically applying it to the energy consumption allocation of a centralized air compressor system in a workshop. This centralized air compressor system supplies air to multiple processes and production units within the workshop simultaneously, and its energy consumption cannot be directly attributed to a single piece of equipment or a single process. The specific execution steps are as follows:

[0069] S1 constructs a multi-level production relationship model: such as Figure 2 As shown, the organizational structure data (production line, unit, process), process route data, and equipment ledger data of the centralized air compressor system of the workshop were obtained. A multi-level production relationship model was established to clarify the service relationship between the centralized air compressor system and each process and unit, as well as the hierarchical relationship between each process and unit and production line. At the same time, the equipment-level energy consumption decomposition results were obtained to obtain the total energy consumption decomposition results of the system, that is, the total public energy consumption to be allocated. .

[0070] S2 determines energy consumption attribution: Based on the multi-level production relationship model, it is identified that the centralized air compressor system serves multiple production objects simultaneously and has no unique correspondence with each production object. Therefore, the energy consumption of this system is determined to be public energy consumption.

[0071] S3 calculates the allocation of public energy consumption: such as Figure 3As shown, the gas consumption duration and output data for each process within the collection and statistical period are combined according to a preset ratio to form the allocated weight for each process. Let the total public energy consumption of the centralized air compressor system be... The following formula is used to complete the allocation calculation:

[0072] ;

[0073] in, To be allocated to the first Energy consumption of each process This represents the total number of processes involved in the cost-sharing.

[0074] S4 execution hierarchical summary: such as Figure 4 As shown, the common energy consumption allocated to each process is summarized to its respective production unit, and then summarized by the production unit to the corresponding production line, forming process-level, unit-level and production line-level energy consumption results.

[0075] Through the above steps, the public energy consumption of the centralized air compressor system can be reasonably allocated to each actual benefiting process, effectively avoiding the problem of result distortion caused by simple average allocation, and enabling public energy consumption to accurately participate in process-level accounting and unit-level summarization, providing support for refined energy consumption management.

[0076] Example 3: This example addresses a shared energy consumption scenario, specifically applied to energy allocation in a processing center. This processing center processes multiple batches of different products within a statistical period, corresponding to different work processes. Logically, these processes are alternately occupied by multiple work processes. The specific execution steps are as follows:

[0077] S1 constructs a multi-level production relationship model: such as Figure 2 As shown, the organizational structure data, process route data, equipment ledger data, and production execution data of the workshop to which the machining center belongs are obtained. A multi-level production relationship model is established to clarify the logical affiliation between the machining center and each process and each product batch, as well as the hierarchical relationship between each process and unit / production line. Simultaneously, the equipment-level energy consumption decomposition results are obtained to determine the total shared energy consumption of the equipment. .

[0078] S2 determines energy consumption attribution: Based on the multi-level production relationship model and combined with the task execution record and process switching record of the processing center, it is identified that the center is occupied alternately by multiple processes within the statistical period, indicating task switching behavior. Therefore, the energy consumption of the processing center is determined to be shared energy consumption.

[0079] S3 calculates the shared energy consumption allocation: such as Figure 3 As shown, the execution records of each product batch and each process task in the processing center are collected, the time period of equipment occupation for each task is extracted, and the occupation duration of each task is calculated. The allocation weight is determined based on the duration of occupation, and the total shared energy consumption of the processing center is set as follows: The following formula is used to complete the allocation calculation:

[0080] ;

[0081] in, To be allocated to the first Shared energy consumption of each task or corresponding process The total number of tasks involved in the sharing.

[0082] S4 execution hierarchical summary: such as Figure 4 As shown, the shared energy consumption obtained from each task and process is aggregated to the corresponding production unit and production line to form process-level, unit-level and production line-level energy consumption results.

[0083] In this example, through the above steps, the energy consumption of shared equipment is dynamically allocated according to the actual occupancy, which can truly reflect the energy consumption contribution of equipment in different production tasks and improve the rationality and interpretability of energy consumption results.

[0084] Example 4: This example addresses a scenario where the physical and logical attribution of equipment are inconsistent. Specifically, it applies to the energy consumption attribution and allocation of a drying equipment in a coating line. This drying equipment is physically installed in production unit A, but is shared by units A and B in terms of operational functionality. The specific execution steps are as follows:

[0085] S1 constructs a multi-level production relationship model: such as Figure 2 As shown, the organizational structure data, process route data, drying equipment ledger data, and task scheduling data of the coating line were obtained to establish a multi-level production relationship model. Simultaneously, the physical affiliation (belonging to production unit A) and logical affiliation (associated with the process tasks of units A and B) of the drying equipment were clarified, as well as the hierarchical relationship between units A and B and their corresponding production lines. At the same time, the equipment-level energy consumption decomposition results were obtained to obtain the total energy consumption of the equipment. .

[0086] S2 performs energy consumption attribution determination: Based on the multi-level production relationship model, the task execution records of the drying equipment are analyzed to confirm that its physical attribution and logical attribution are inconsistent. Part of the energy consumption corresponds to the process task of unit A and can be directly attributed to unit A; the other part of the energy consumption corresponds to the scheduling task of unit B and cannot be directly and uniquely attributed, so it needs to be allocated.

[0087] S3 calculates the allocation of energy consumption not directly attributed to it: such as Figure 3As shown, the execution time, number of task batches, and equipment load rate data of the corresponding process tasks in units A and B are collected, and the weights are synthesized according to preset rules. The energy consumption that is not directly assigned is then allocated to units A and B according to the weights.

[0088] S4 execution hierarchical summary: such as Figure 4 As shown, the energy consumption directly assigned to Unit A is combined with the energy consumption allocated to it, while the energy consumption allocated to Unit B is counted separately. Then, the energy consumption of the two units is summarized to the corresponding production line to form unit-level and production line-level energy consumption results.

[0089] This example, through the steps described above, reflects both the physical installation attributes of the equipment and its actual business usage, effectively solving the problem of energy consumption attribution bias caused by inconsistencies between physical and logical attribution, and further improving the accuracy and interpretability of energy consumption attribution.

[0090] In summary, combining Figures 1 to 4 As shown, the four examples above cover various typical industrial scenarios such as dedicated energy consumption, public energy consumption, shared energy consumption, and inconsistencies between the physical and logical affiliations of equipment. Each example elaborates on the specific execution steps of the method of the present invention and the corresponding diagram associations, fully demonstrating that the present invention can achieve accurate mapping and hierarchical transmission of equipment-level energy consumption results to process-level, unit-level, and production line-level results, effectively solving the shortcomings of existing technologies and meeting the needs of refined energy consumption management for industrial enterprises.

[0091] The present invention adopts the above technical solution and has the following advantages compared with the prior art:

[0092] (1) The production organization level, process level, and physical and logical attribution relationship between equipment and production objects are jointly modeled to form a two-level coupling relationship network, realizing the effective transmission of equipment-level energy consumption to the production business level and the accurate association between energy consumption data and production organization, breaking through the limitations of the single equipment tree structure of the existing technology. (2) Adopting the logic of "first type identification, then allocation calculation", the energy consumption is first clarified as dedicated, public or shared type, and different processing methods are adopted for different types of energy consumption - dedicated energy consumption is directly assigned, and public energy consumption and shared energy consumption are allocated as needed, solving the long-standing pain point of difficult attribution of public energy consumption in industrial sites. (3) This invention strengthens the production business semantics of energy consumption results through the full-chain hierarchical energy consumption transmission and summary of "equipment - process - unit - production line - process route - product", meeting the energy consumption refined management needs of multi-level production structures, and breaking through the limitation of the simple energy consumption summary of "equipment to workshop" in the existing technology.

[0093] This invention is applicable to industrial scenarios with complex production hierarchies, such as equipment manufacturing, machining, assembly, painting, and heat treatment. It has strong versatility and high engineering application value and promotion prospects.

[0094] Obviously, the described embodiments are only a part of the embodiments of this application, not all of them. Without conflict, the embodiments and features in the embodiments of this application can be combined with each other. The components of the embodiments of this application described and illustrated herein can generally be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of this application is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

Claims

1. An energy consumption attribution and allocation method for multi-level production structures, characterized in that, Includes the following steps: To construct a multi-level production relationship model, acquire organizational structure data, process route data, equipment association data, and equipment-level energy consumption data from the production system. The multi-level production relationship model defines at least the hierarchical relationship of production organization, the hierarchical relationship of process, and the physical and logical affiliation relationships between equipment and production objects. Based on the multi-level production relationship model, equipment-level energy consumption data is classified into dedicated energy consumption, public energy consumption, or shared energy consumption, and dedicated energy consumption is directly assigned to the production object of the corresponding unique service. Based on the preset allocation rules, calculate the energy consumption data of public energy consumption and shared energy consumption, and calculate the allocation results to each related production object. Based on the hierarchical relationship of production organization and / or process hierarchy, the energy consumption allocation results of dedicated energy consumption, public energy consumption and shared energy consumption are summarized upwards level by level to generate energy consumption results at the process level, unit level and / or production line level.

2. The energy consumption attribution and allocation method for multi-level production structures according to claim 1, characterized in that, The hierarchical relationship of production organization includes the subordinate relationship between production lines and production units, the subordinate relationship between production units and processes, and the mapping relationship between equipment and processes, production units or production lines; the hierarchical relationship of process includes the sequential relationship between process routes, processes and steps; the physical affiliation relationship refers to the static affiliation relationship of equipment in space or administration; the logical affiliation relationship refers to the relationship of equipment dynamically associated with production objects according to production tasks, orders or process paths.

3. The energy consumption attribution and allocation method for multi-level production structures according to claim 1, characterized in that, Furthermore, dedicated energy consumption refers to the energy consumption generated by equipment serving only a single production object within the statistical period; Public energy consumption refers to energy consumption that serves multiple production objects and cannot be directly and uniquely attributed to any one object. Shared energy consumption refers to the energy consumption of the same equipment within a statistical period due to serving different tasks, processes, or production objects.

4. The energy consumption attribution and allocation method for multi-level production structures according to claim 1, characterized in that, The preset allocation rules include at least one of the following: allocation by processing time, allocation by equipment occupancy time, allocation by output, allocation by number of workpieces, allocation by rated power weight, allocation by process energy consumption coefficient, allocation by task load ratio, and allocation by energy use contribution.

5. The energy consumption attribution and allocation method for multi-level production structures according to claim 1, characterized in that, The allocation calculation is achieved using the following formula: ； in, To allocate the energy consumption to the i-th production object, This refers to the total amount of public or shared energy consumption to be allocated. The allocated weight is the weight corresponding to the i-th production object. The sum of the weights of all production objects participating in the allocation; The total number of production objects participating in the apportionment.

6. The energy consumption attribution and allocation method for multi-level production structures according to claim 1, characterized in that, When the physical and logical ownership of a device points to different production objects, the energy consumption ownership is determined according to a preset priority rule.

7. The energy consumption attribution and allocation method for multi-level production structures according to claim 6, characterized in that, The preset priority rule is: energy consumption determination and attribution are based on logical attribution relationships first.

8. The energy consumption attribution and allocation method for multi-level production structures according to claim 1, characterized in that, The implementation of hierarchical aggregation includes: aggregating equipment-level energy consumption results to their respective processes to obtain process-level energy consumption results; aggregating process-level energy consumption results belonging to the same production unit to obtain unit-level energy consumption results; and aggregating unit-level energy consumption results belonging to the same production line to obtain production line-level energy consumption results.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of the energy consumption attribution and allocation method for multi-level production structures as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the energy consumption attribution and allocation method for multi-level production structures as described in any one of claims 1 to 8.

Images