Sand casting enterprise low-carbon production scheduling method
By building a low-carbon production scheduling model, reasonably arranging the processing processes and equipment of castings, and optimizing decision-making variables, the problem of high carbon emissions of sand casting enterprises is solved, and production efficiency is improved and carbon emissions are reduced.
Patent Information
- Application Number
- CN202510280795.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-11
- Publication Date
- 2025-07-04
AI Technical Summary
In the prior art, the carbon emissions of sand casting enterprises have not been effectively evaluated and controlled, resulting in inefficient production efficiency and waste of resources. The existing scheduling model lacks consideration for carbon emissions.
Build a low-carbon production scheduling model, determine the target process and equipment of castings in the entire production scheduling process as decision variables, optimize the decision variables to reasonably arrange the processing process and equipment, build objective functions, constraints and batch rules, and use multi-objective genetic algorithm for optimization.
It has realized low-carbon production scheduling of sand casting enterprises, improved production efficiency and reduced carbon emissions, and met the needs of the actual production scenarios of the enterprises.
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Abstract
Description
Technical Field
[0001] This application belongs to the technical field of carbon emission and production scheduling, and more specifically, relates to a low-carbon production scheduling method for sand casting enterprises. Background Art
[0002] As the foundation of the manufacturing industry, sand casting enterprises will inevitably generate a large amount of carbon emissions. How to measure the carbon emissions of sand casting enterprises and conduct research on carbon reduction and emission reduction is of guiding significance for their green transformation.
[0003] At the current stage, the measurement of carbon emissions in sand casting pays more attention to the overall enterprise, lacking the evaluation of the carbon emissions per casting. At the same time, during the production process of casting enterprises, it is necessary to arrange the production plan for castings. Manually arranging the production plan will inevitably cause problems such as low production efficiency and resource waste in the enterprise, resulting in high carbon emissions in the enterprise. Summary of the Invention
[0004] Aiming at the deficiencies of the prior art, the purpose of this application is to provide a low-carbon production scheduling method for sand casting enterprises, aiming to solve the problem of high carbon emissions in the prior art.
[0005] To achieve the above purpose, in the first aspect, this application provides a low-carbon production scheduling method for sand casting enterprises, including: Determine a low-carbon production scheduling model with the entire production scheduling process of casting castings in sand casting enterprises as the scheduling object and the decision variables being whether the casting is in the target process of the entire production scheduling process and whether the casting is processed on the target equipment in the target process; Optimize the decision variables in the low-carbon production scheduling model to determine the optimized decision variables; According to the optimized decision variables, determine the entire low-carbon production scheduling process of casting castings in sand casting enterprises.
[0006] In some embodiments, determining a low-carbon production scheduling model with the entire production scheduling process of casting castings in sand casting enterprises as the scheduling object and the decision variables being whether the casting is in the target process of the entire production scheduling process and whether the casting is processed on the target equipment in the target process includes: According to the scheduling object and decision variables, determine the objective function, constraint conditions, and batching rules in the low-carbon production scheduling model; According to the objective function, constraint conditions, and batching rules, determine the low-carbon production scheduling model.
[0007] In some embodiments, according to the scheduling object and decision variables, determining the objective function in the low-carbon production scheduling model includes: Determine the first objective function with the minimum of the maximum completion time of the castings as the goal according to the completion time of the castings determined by the scheduling object and decision variables; Determine the second objective function with the minimum of the early or late delivery time of the castings as the goal according to the early or late delivery penalty factor of the castings, the total processing time of the castings determined by the scheduling object and decision variables, and the time from the castings to the delivery date; Determine the third objective function with the minimum of the carbon emission value of the castings as the goal according to the scheduling object and decision variables; Determine the objective function according to the first objective function, the second objective function and the third objective function.
[0008] In some embodiments, according to the scheduling object and decision variables, the constraints in the low-carbon production scheduling model are determined as follows: Determine the capacity constraint conditions that the batch processing process of the castings in the whole process of production scheduling should meet and the processing constraint conditions that the castings in the whole process of production scheduling should meet according to the scheduling object and decision variables; Determine the constraints according to the capacity constraint conditions and the processing constraint conditions.
[0009] In some embodiments, according to the scheduling object and decision variables, the batch forming rules in the low-carbon production scheduling model are determined as follows: According to the time from the castings to the delivery date, perform melting batch forming processing on the castings, quantify the first overall similarity of the castings in the melting batch forming processing based on the casting material and pouring temperature, and determine the first batch forming rule with the maximization of the first overall similarity and the maximization of the total mass of the castings in the melting batch forming processing. The time from the castings to the delivery date is determined by the scheduling object and decision variables; According to the time from the castings to the delivery date, perform heat treatment batch forming processing on the castings, quantify the second overall similarity of the castings in the heat treatment batch forming processing based on the cooling method and heat treatment temperature, and determine the second batch forming rule with the maximization of the second overall similarity and the maximization of the total mass of the castings in the heat treatment batch forming processing; Determine the batch forming rules according to the first batch forming rule and the second batch forming rule.
[0010] In some embodiments, the whole process of production scheduling includes: Batch processing process and single-piece processing process.
[0011] In a second aspect, the present application provides a low-carbon production scheduling device for a sand casting enterprise, including: A first determination module, configured to determine a low-carbon production scheduling model with the whole process of production scheduling of casting castings by a sand casting enterprise as the scheduling object and whether the casting is in the target process in the whole process of production scheduling and whether the casting is processed on the target equipment in the target process as decision variables; An optimization module, configured to optimize decision variables in the low-carbon production scheduling model and determine the optimized decision variables; A second determination module, configured to determine the entire low-carbon production scheduling process for casting castings by a sand casting enterprise according to the optimized decision variables.
[0012] In a third aspect, the present application provides an electronic device, including: at least one memory for storing a program; at least one processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or any of some embodiments of the first aspect.
[0013] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program. When the computer program runs on a processor, the processor is caused to execute the method described in the first aspect or any of some embodiments of the first aspect.
[0014] In a fifth aspect, the present application provides a computer program product. When the computer program product runs on a processor, the processor is caused to execute the method described in the first aspect or any of some embodiments of the first aspect.
[0015] Generally speaking, compared with the prior art by the above technical solutions conceived by the present application, the following beneficial effects are achieved: The low-carbon production scheduling method for a sand casting enterprise provided by the present application aims at the problem of insufficient consideration of carbon emissions in the existing scheduling model. Taking the entire production scheduling process of casting castings by a sand casting enterprise as the scheduling object and the processing procedures of the castings and the processing equipment of the processing procedures where the castings are located as decision variables, a low-carbon production scheduling model is constructed, and the decision variables are optimized to obtain the entire low-carbon production scheduling process for casting castings by a sand casting enterprise. By reasonably arranging the processing procedures and processing equipment of casting castings by the enterprise under the entire production scheduling process of casting castings by a sand casting enterprise, the present application obtains the entire low-carbon production scheduling process, which helps to improve the production efficiency and reduce carbon emissions of the sand casting enterprise. Description of the Drawings
[0016] Figure 1 is one of the schematic flowcharts of the low-carbon production scheduling method for a sand casting enterprise provided by an embodiment of the present application; Figure 2 is another schematic flowchart of the low-carbon production scheduling method for a sand casting enterprise provided by an embodiment of the present application; Figure 3 is the schematic diagram of Batch-HFSP(QM) provided by an embodiment of the present application; Figure 4 is the schematic diagram of the carbon emission measurement boundary of a sand casting enterprise provided by an embodiment of the present application; Figure 5 It is a schematic structural diagram of a low-carbon production scheduling device for a sand casting enterprise provided by an embodiment of the present application; Figure 6 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners
[0017] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0018] The term "and / or" in this article is an association relationship describing associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The symbol " / " in this article represents an "or" relationship between associated objects. For example, A / B represents A or B.
[0019] The terms "first", "second", etc. in the specification and claims of this article are used to distinguish different objects, rather than to describe a specific order of objects. For example, the first batch rule and the second batch rule are used to distinguish different batch rules, rather than to describe the specific order of batch rules.
[0020] In the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, using words such as "exemplary" or "for example" aims to present relevant concepts in a specific manner.
[0021] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" refers to two or more.
[0022] In view of the problem of high corporate carbon emissions in related technologies, it is necessary to perform full-process intelligent scheduling in combination with an information management system. Intelligent scheduling can bring about savings in corporate resources, but most studies only focus on reducing the total processing time and do not combine intelligent scheduling with corporate carbon reduction and emission reduction.
[0023] Based on this, the embodiments of the present application provide a low-carbon production scheduling method for a sand casting enterprise, which is specifically implemented as follows. The embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application.
[0024] Please refer to Figure 1 , the embodiments of the present application provide a low-carbon production scheduling method for a sand casting enterprise, including: step 110, step 120, and step 130.
[0025] Step 110 determines a low-carbon production scheduling model with the entire production scheduling process of casting parts by a sand casting enterprise as the scheduling object, and the decision variables being whether the casting part is in the target process of the entire production scheduling process and whether the casting part is processed on the target equipment of the target process. Step 120 optimizes the decision variables in the low-carbon production scheduling model to determine the optimized decision variables. Step 130 determines the entire low-carbon production scheduling process of casting parts by the sand casting enterprise according to the optimized decision variables.
[0026] In the embodiment of the present application, based on the sand casting production process, the scheduling object and its decision variables of the low-carbon production scheduling model are determined.
[0027] Please further refer to Figure 2 , to construct a low-carbon production scheduling model, it is necessary to determine the scheduling object. The present application targets the entire production scheduling process of casting parts by a sand casting enterprise, including two batch processing processes of melting and heat treatment and single-piece processing processes such as cutting and grinding.
[0028] Specifically, the production scheduling problem in the sand casting workshop is close to the Hybrid FlowShop Scheduling Problem (HFSP). The scheduling object of the low-carbon production scheduling model is the entire production scheduling process, where the melting and heat treatment processes are batch processing processes, and multiple casting parts form a batch for processing. The melting processing time is proportional to the quality of the casting parts in the batch, and the heat treatment processing time depends on the casting part with the largest quality in the batch. At the same time, each process is equipped with different numbers of parallel machines, and the processing time of the same casting part on each parallel machine is different. Therefore, its scheduling problem can be further defined as the Batch-HFSP(Qm).
[0029] Taking whether the casting part is in the target process of the entire production scheduling process and whether the casting part is processed on the target equipment of the target process as decision variables, the casting part and each equipment parameter are determined to optimize the entire production scheduling process. In the embodiment of the present application, the target process is a certain process in the entire production scheduling process, and the target equipment is a certain equipment of a certain process. Based on the multi-objective genetic algorithm (NSGA-III), the above low-carbon production scheduling model is solved to optimize the decision variables and obtain the optimized decision variables.
[0030] Please further refer to Figure 3 , the square boxes represent the equipment that can be selected for each process, mxy represents the y th xA device, the number of devices for different processes can be different (i.e., the number of boxes in each column can be different), and the processing time of the same workpiece on different devices is different. The dashed box indicates the processing process in the batch processing process of this column, which needs to be grouped. Starting from the processing, it goes through y processes to complete the processing.
[0031] According to the optimized decision variables, it can be determined whether the casting is in a certain process and whether the casting is on a certain device in a certain process, so as to reasonably arrange the processing processes and processing devices of the castings in the sand casting enterprise, and obtain the full process of low-carbon production scheduling.
[0032] The low-carbon production scheduling method for sand casting enterprises provided by the embodiments of the present application aims at the problem of insufficient consideration of carbon emissions in the existing scheduling model. Taking the full process of production scheduling of castings in sand casting enterprises as the scheduling object, and taking the processing process where the casting is located and the processing device of the processing process where the casting is located as decision variables, a low-carbon production scheduling model is constructed, and the decision variables are optimized to obtain the full process of low-carbon production scheduling of castings in sand casting enterprises. Through the full process of production scheduling of castings in sand casting enterprises, the present application reasonably arranges the processing processes and processing devices of the castings in the enterprise, obtains the full process of low-carbon production scheduling, and helps to improve the production efficiency and reduce carbon emissions of sand casting enterprises.
[0033] Further, in some embodiments, in the above steps, the full process of production scheduling includes: Batch processing process and single-piece processing process.
[0034] In the embodiments of the present application, the full process of production scheduling can be specifically divided into a batch processing process and a single-piece processing process. Among them, the batch processing process includes two batch processing processes of melting and batch processing, and the single-piece processing process includes processes such as cutting and grinding.
[0035] Further, in some embodiments, in step 110, the low-carbon production scheduling model determined with the full process of production scheduling of castings in sand casting enterprises as the scheduling object and whether the casting is in the target process in the full process of production scheduling and whether the casting is processed on the target device in the target process as decision variables includes: According to the scheduling object and decision variables, determine the objective function, constraint conditions and batch grouping rules in the low-carbon production scheduling model; According to the objective function, constraint conditions and batch grouping rules, determine the low-carbon production scheduling model.
[0036] Please continue to refer to Figure 2 , aiming at the actual situation of casting production in sand casting enterprises, a low-carbon production scheduling model is constructed, which includes an objective function, constraint conditions and batch grouping rules.
[0037] For the entire production scheduling process and decision variables, construct the objective function and constraints. The specific steps are as follows: Construct the objective function: First, the makespan is an indicator to measure the quality of the scheduling plan. Optimizing this objective can improve the production efficiency of the enterprise. Second, sand casting enterprises schedule production according to the delivery date during production. Early or late delivery of castings will affect the casting enterprise. Therefore, add penalties for early and late delivery to the objective function. Finally, according to the constructed carbon emission measurement model, construct an objective function for optimizing the carbon emissions of castings to achieve the goal of carbon reduction and emission reduction.
[0038] Determine the constraints: Castings need to be subject to various restrictions during the production process, which are the constraints. In the embodiments of this application, the logic of scheduling optimization is realized under the constraints.
[0039] Formulate the lot-sizing rules: During the production of castings, the lot-sizing process in the melting and heat treatment links involves the use of various resources. Different lot-sizing methods will result in different carbon emissions. In the embodiments of this application, it is necessary to formulate lot-sizing rules for the melting and heat treatment processes.
[0040] Based on the above constructed objective function, constraints, and formulated lot-sizing rules, obtain a low-carbon production scheduling model.
[0041] Furthermore, in some embodiments, in the above steps, according to the scheduling object and decision variables, the objective function in the low-carbon production scheduling model includes: Determine the first objective function with the minimum makespan of the casting as the goal according to the completion time of the casting determined by the scheduling object and decision variables; Determine the second objective function with the minimum early or late time of the casting as the goal according to the early or late delivery penalty factor of the casting, the total processing time of the casting determined by the scheduling object and decision variables, and the time of the casting from the delivery date; Determine the third objective function with the minimum carbon emission value of the casting as the goal according to the scheduling object and decision variables; Determine the objective function according to the first objective function, the second objective function, and the third objective function.
[0042] In the embodiments of this application, determine the objective function with the minimum makespan of the casting as the goal according to the completion time of the casting determined by the scheduling object and decision variables, that is, the first objective function.
[0043] Specifically, the makespan of the casting represents the production efficiency of the enterprise's scheduling plan. By reasonably arranging the processing sequence and processing equipment of the castings, reducing the idle waiting time of each workpiece, and taking the minimization of the makespan of the casting as the objective function, the formula is as follows:
[0044] In the formula, is the first objective function, represents the completion time of the casting, which is determined by the scheduling object and decision variables, and represents the total number of castings.
[0045] In the embodiments of the present application, the decision variables all adopt binary decision variables. For example, : represents whether the casting is in the single-piece processing process; : represents whether the casting is processed on the equipment in the single-piece processing process ; : represents the processing time of the casting in the single-piece processing process ; : represents whether the casting is in the batch processing process; : represents whether the casting is assigned to the melting batch in the melting process ; : represents whether the melting batch in the melting process is processed on the equipment ; : represents whether the casting is assigned to the heat treatment batch in the heat treatment process ; : represents whether the heat treatment batch is processed on the equipment ; : represents the material difference between the casting and the casting ; : represents the cooling method difference between the casting and the casting .
[0046] Combined with the penalty factor for early or late delivery of the casting, the total processing time of the casting determined by the scheduling object and decision variables, and the time from the casting to the delivery date, calculate the objective function with the minimum of the early or late time of the casting as the goal, that is, the second objective function.
[0047] Specifically, the proximity of the casting to the delivery date determines the production scheduling of the entire production system, and all castings should be processed as close to the delivery date as possible. Completing the processing of castings after the delivery date will reduce the enterprise's reputation, and completing the processing before the delivery date will bring pressure on the enterprise's inventory and maintenance costs. Therefore, the number of days advanced or postponed from the delivery date is added to the objective function, and the formula is as follows:
[0048] In the formula, represents the casting penalty factor for early or late delivery, represents the casting total processing time, represents the casting time from the delivery date, which is determined by the scheduling object and decision variables. Different production scheduling processes and different values of decision variables will affect the value, represents the second objective function.
[0049] Based on the scheduling object and decision variables, calculate the objective function with the minimum carbon emission value of the casting as the goal, that is, the third objective function.
[0050] Specifically, according to the decision variables and the entire production scheduling process, combined with the constructed casting carbon emission measurement model, construct the carbon emission objective function corresponding to the casting carbon emission value, and the formula is as follows:
[0051] In the formula, represents the third objective function, represents the resource consumption emission factor required for producing a unit mass of casting. represents the electricity consumption emission factor. represents the fuel consumption emission factor. represents the casting mass. takes a value of 0 or 1, which is a binary decision variable, indicating whether the casting is in the single-piece processing process. takes a value of 0 or 1, which is a binary decision variable, indicating whether the casting is in the single-piece processing process on the equipment for processing. represents the equipment power, represents the equipment power. represents the casting in the single-piece processing process processing time. Taking values of 0 or 1, it is a binary decision variable representing the casting whether it is in the batch processing operation. Taking values of 0 or 1, it is a binary decision variable representing the casting whether it is assigned to the melting process in the melting batch . Taking values of 0 or 1, it is a binary decision variable representing the melting batch in the melting process whether it is processed on the equipment . Represents the time required for melting a unit mass of the casting. Taking values of 0 or 1, it is a binary decision variable representing the casting whether it is assigned to the heat treatment process in the heat treatment batch . Taking values of 0 or 1, it is a binary decision variable representing the heat treatment batch whether it is processed on the equipment . Represents the fuel consumed by the heat treatment process per unit time. Represents the time used for the heat treatment process of a unit mass of the casting.
[0052] Furthermore, in some embodiments, in the above steps, according to the scheduling object and decision variables, the constraint conditions in the low-carbon production scheduling model include: According to the scheduling object and decision variables, determine the capacity constraint conditions that the batch processing operation of the casting in the entire production scheduling process should satisfy and the processing constraint conditions that the casting in the entire production scheduling process should satisfy; According to the capacity constraint conditions and processing constraint conditions, determine the constraint conditions.
[0053] In specific implementation, the casting should satisfy the capacity constraints of the melting furnace and heat treatment furnace during the batch formation process, load as much as possible without exceeding the limit bearing capacity, and at the same time not less than the minimum startup capacity of the equipment. Based on this, the capacity constraint conditions that the batch processing operation of the casting in the entire production scheduling process should satisfy are obtained as follows:
[0054] Among them, represents the startup capacity of the equipment . represents the maximum bearing capacity of the equipment .
[0055]
[0056] Among them, represents the starting capacity of the device of the device. represents the maximum load capacity of the device of the device.
[0057] During the processing of the casting in the single-piece processing process, one process can only be processed on one device, and after processing, it enters the next process. Based on this, the processing constraint conditions that the processing equipment in the single-piece processing process of the casting in the entire production scheduling process needs to meet are as follows:
[0058] During the processing of the casting in the batch processing process, one batch can only be processed on one device, and after processing, it enters the next process. Based on this, the processing constraint conditions that the batch processing process of the casting in the entire production scheduling process needs to meet are as follows:
[0059]
[0060] In addition, the technological sequence of the casting cannot be changed after initial generation. Based on this, the processing constraint conditions corresponding to the processing sequence of the casting in the single-piece processing process are as follows:
[0061]
[0062] Among them, represents the casting at the start processing time of the process , represents the casting at the start processing time of the process . represents the casting at the end processing time of the process .
[0063] Furthermore, in some embodiments, according to the scheduling object and decision variables, the lot-sizing rules in the low-carbon production scheduling model include: According to the time of the casting from the delivery date, the castings are subjected to melting lot-sizing processing. Based on the casting material and pouring temperature, the first overall similarity of the castings in the melting lot-sizing processing is quantified, and the first lot-sizing rule with the maximization of the first overall similarity and the maximization of the total mass of the castings in the melting lot-sizing processing as the goals is determined. The time of the casting from the delivery date is determined by the scheduling object and decision variables; According to the time of the casting from the delivery date, the castings are subjected to heat treatment batch processing, and the second overall similarity of the castings in the heat treatment batch processing is quantified based on the cooling method and heat treatment temperature, and the second batch rule is determined with the goal of maximizing the second overall similarity and the total mass of the castings in the heat treatment batch processing; According to the first batch rule and the second batch rule, the batch rule is determined.
[0064] In the embodiment of the present application, the objective function of the melting batch processing gives priority to the time of the casting from the delivery date, and the castings with a shorter time from the delivery date are preferentially batched. The melting similarity between the castings in the melting batch processing is quantified based on the casting material and pouring temperature. When performing the melting batch processing, it is necessary to maximize the overall similarity (i.e., the first overall similarity) of the castings within the batch, and at the same time, the total mass of the castings within the batch is maximized as much as possible.
[0065] Normalize the delivery date of the casting so that is between [0, 1], The larger the value, the more urgent the time of the casting from the delivery date, and the higher the priority of the casting. The normalization formula is as follows:
[0066] Among them, represents the casting delivery date priority, represents the time of the casting with the farthest delivery date from the delivery date among all castings, represents the time of the casting with the nearest delivery date from the delivery date among all castings.
[0067] Quantify the melting similarity of the castings based on the casting material and pouring temperature. The similarity calculation formula is as follows:
[0068] Among them, represents the melting similarity of the casting and the casting in the melting batch processing. takes a value of 0 or 1, which is a binary decision variable, indicating the material difference between the casting and the casting in the melting batch processing. represents the pouring temperature of the casting in the melting process represents the melting process in the melting batch The overall similarity (i.e., the first overall similarity) of the castings within the batch (i.e., the castings in the melting batch processing). represents the melting process In the melting batch The number of castings inside
[0069] Determine the batch grouping rule (i.e., the first batch grouping rule) aiming at maximizing the first overall similarity and the casting quality in the melting batch grouping process, as follows:
[0070] The heat treatment batch grouping is similar to the melting batch grouping, considering giving priority to the distance to the delivery date, high similarity first, and maximizing the total quality of the castings within the batch. At the same time, since the processing time in the heat treatment link is related to the casting with the maximum quality within the batch, the quality deviation of the castings within the batch needs to be considered.
[0071] In the specific implementation, normalize the remaining delivery date of the castings to obtain the delivery date priority in the heat treatment link, as follows:
[0072] Among them, represents the process number before the heat treatment process in the whole production scheduling process, represents the number of the remaining processes before the heat treatment process in the whole production scheduling process, represents the casting in the process processing time.
[0073] Quantify the heat treatment similarity of the castings based on the cooling method and heat treatment temperature. Castings with different cooling methods cannot be placed in the same batch, as follows:
[0074] Among them, represents the castings in the heat treatment batch grouping and the casting heat treatment similarity. takes a value of 0 or 1, which is a binary decision variable, indicating the difference in the cooling method between the casting and the casting Cooling method difference. represents the casting holding temperature in the heat treatment link. represents the heat treatment batch the overall similarity of the castings inside (i.e., the castings in the heat treatment batch grouping), that is, the second overall similarity. represents the heat treatment batch The number of castings inside.
[0075] In the heat treatment process, the processing time of a batch is the processing time of the largest-quality casting in the furnace. Therefore, in the actual heat treatment batch-forming process, the smaller the quality deviation of the castings within a batch, the less waste of processing time for the same batch. The standard deviation is used to define the quality deviation amount of the castings within a batch, and the calculation formula is as follows:
[0076] Wherein, represents the quality deviation amount of the castings within the heat treatment batch
[0077] Determine the batch-forming rule (i.e., the second batch-forming rule) aiming at maximizing the second overall similarity and maximizing the total quality of the castings in the heat treatment batch-forming process, as follows:
[0078] In the embodiments of the present application, the batch-forming rules of the low-carbon production scheduling model include the above-mentioned first batch-forming rule and the above-mentioned second batch-forming rule.
[0079] Use a multi-objective genetic algorithm (such as NSGA-III) to solve the low-carbon production scheduling model, optimize the decision variables, and obtain the full process of low-carbon production scheduling for casting castings in a sand casting enterprise according to the optimized decision variables.
[0080] According to the optimized decision variables, calculate the third objective function corresponding to the carbon emission value of the casting, and compare it with the carbon emission value of the casting calculated by the carbon emission measurement model. The results show that the carbon emission value of the casting calculated by the production scheduling method of the sand casting enterprise provided in the embodiments of the present application is lower than the carbon emission value of the casting calculated by the carbon emission measurement model.
[0081] In the embodiments of the present application, the construction method of the carbon emission measurement model is as follows: Based on the boundary of the sand casting enterprise and the types of carbon emissions, construct a carbon emission measurement model for sand castings; further, the steps for obtaining the carbon emission model are as follows.
[0082] S1: According to the actual production process flow of the sand casting enterprise, determine the carbon emission measurement boundary of the sand casting enterprise. The boundary does not include the extraction and transportation of raw materials, human activities, etc., but only includes the carbon emissions brought by the processes in the casting production process; the measurement model is used to calculate the carbon emissions brought by the processes in the casting production process.
[0083] Please refer further to Figure 4 , divide the full process of casting production scheduling in a sand casting enterprise into a pouring stage and a post-treatment stage. The square boxes represent the processing steps of the full production scheduling process, the diamond boxes represent substances, the solid lines represent the flow direction of substances, and the dashed lines represent the input of energy (electricity, fuel, etc.). The construction of the carbon emission model is carried out inFigure 4 It is carried out under the full process shown in
[0084] S2: According to the material and energy structure of foundry enterprises, classify the carbon emission types of sand casting enterprises. Three carbon emission types of sand casting enterprises are proposed, namely raw material emission carbon source, energy emission carbon source and fuel emission carbon source; S3: According to the boundary and carbon emission types, construct a carbon emission measurement model for casting parts of sand casting enterprises. Using the activity level method, construct measurement models for three carbon emission types (raw material emission carbon source, energy emission carbon source and fuel emission carbon source).
[0085] Specifically, the activity level method is calculated based on output and default carbon emission factors. By obtaining the activity factors of foundry enterprises, the carbon emission value is obtained. The specific calculation formula is as follows.
[0086]
[0087] Among them, represents the greenhouse gas emissions of the casting . represents the activity data of the casting , that is, the output. represents the emission factor of the casting , that is, the default carbon emission factor. (Global warming potential) represents the global warming potential. When emitting CO2, GWP is 1.
[0088] According to the three types of carbon emission models, the carbon emission measurement models corresponding to the raw material emission carbon source, energy emission carbon source and fuel emission carbon source are constructed as follows:
[0089] Among them, represents the carbon emission measurement model corresponding to the raw material emission carbon source, represents the carbon emission measurement model corresponding to the energy emission carbon source, represents the carbon emission measurement model corresponding to the fuel emission carbon source, represents the ( = 1, 2... ) kind of production material consumption (unit: ton, cubic meter). represents the ( = 1, 2… ) kind of auxiliary material consumption (unit: ton, cubic meter). represents the casting quality (unit: ton). / / respectively represent the th production material / the th auxiliary material / the carbon dioxide emission factor of the casting (unit: , ). represents the solar power generation of the enterprise within a time period (unit: ). represents the purchased electricity of the enterprise within a time period (unit: ). represents the ( = 1, 2… )th equipment power (unit: ). represents the th equipment power factor ( ). t represents the equipment usage time (unit: hours). represents the self-produced steam volume of the enterprise (unit: cubic meters). represents the purchased steam volume of the enterprise (unit: cubic meters). represents the steam usage volume in the ( = 1, 2, … )th process of the single-piece production process ( ). / represents the carbon dioxide emission factor of electricity / steam ( , ). represents the ( = 1, 2… )th fuel consumption (unit: tons, cubic meters). represents the th fuel lower calorific value ( , ). represents the th fuel carbon content per unit calorific value ( ). represents the th fuel carbon oxidation rate ( ).
[0090] The low-carbon production scheduling method for sand casting enterprises provided by the embodiments of the present application proposes the batch rationality of two batch processing procedures, namely melting and heat treatment, for the lack of existing batch rules, and formulates specific batch rules, making the scheduling model more in line with the actual production scenario of the enterprise.
[0091] The low-carbon production scheduling device for sand casting enterprises provided by the present application will be described below. The low-carbon production scheduling device for sand casting enterprises described below can be correspondingly referred to the low-carbon production scheduling method for sand casting enterprises described above.
[0092] Please refer to Figure 5 , an embodiment of the present application provides a low-carbon production scheduling device for sand casting enterprises, including: a first determination module 510, an optimization module 520, and a second determination module 530.
[0093] The first determination module 510 is configured to determine a low-carbon production scheduling model with the entire production scheduling process of casting castings in a sand casting enterprise as the scheduling object and the casting being in the target process of the entire production scheduling process and whether the casting is processed on the target equipment of the target process as decision variables; The optimization module 520 is configured to optimize the decision variables in the low-carbon production scheduling model to determine the optimized decision variables; The second determination module 530 is configured to determine the entire low-carbon production scheduling process of casting castings in a sand casting enterprise according to the optimized decision variables.
[0094] The low-carbon production scheduling device for sand casting enterprises provided by the embodiment of the present application aims at the problem of insufficient consideration of carbon emissions in the existing scheduling model. With the entire production scheduling process of casting castings in a sand casting enterprise as the scheduling object and the processing process where the casting is located and the processing equipment of the processing process where the casting is located as decision variables, a low-carbon production scheduling model is constructed, and the decision variables are optimized to obtain the entire low-carbon production scheduling process of casting castings in a sand casting enterprise. By reasonably arranging the processing processes and processing equipment of casting castings in a sand casting enterprise under the entire production scheduling process, the present application obtains the entire low-carbon production scheduling process, which helps improve the production efficiency and reduce carbon emissions of sand casting enterprises.
[0095] It can be understood that the detailed function implementation of the above-mentioned each unit / module can refer to the introduction in the foregoing method embodiment, and will not be elaborated here.
[0096] It should be understood that the above-mentioned device is used to execute the method in the above-mentioned embodiment. For the corresponding program module in the device, its implementation principle and technical effect are similar to the description in the above-mentioned method. The working process of the device can refer to the corresponding process in the above-mentioned method, and will not be elaborated here.
[0097] Based on the method in the above-mentioned embodiment, an embodiment of the present application provides an electronic device. Please refer to Figure 6, the electronic device may include: a processor 610, a communications interface 620, a memory 630, and a communication bus 640. Among them, the processor 610, the communications interface 620, and the memory 630 communicate with each other through the communication bus 640. The processor 610 can call the logic instructions in the memory 630 to execute the methods in the above embodiments.
[0098] In addition, when the logic instructions in the above-mentioned memory 630 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application.
[0099] Based on the method in the above embodiments, an embodiment of this application provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program runs on a processor, it causes the processor to execute the method in the above embodiments.
[0100] Based on the method in the above embodiments, an embodiment of this application provides a computer program product. When the computer program product runs on a processor, it causes the processor to execute the method in the above embodiments.
[0101] It can be understood that the processor in the embodiments of this application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.
[0102] The method steps in the embodiments of this application can be implemented in a hardware manner or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in a random access memory (RAM), flash memory, read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), registers, hard disks, removable hard disks, CD-ROMs, or any other form of storage medium well-known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.
[0103] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or a wireless manner (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)), etc.
[0104] It can be understood that the various numerical numbers involved in the embodiments of this application are only for convenience of description and are not used to limit the scope of the embodiments of this application.
[0105] Those skilled in the art can easily understand that the above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims
1. A low-carbon production scheduling method for sand casting enterprises, characterized in that, Including: Determining a low-carbon production scheduling model with the entire production scheduling process of casting parts by a sand casting enterprise as the scheduling object, and using whether the casting part is in the target process of the entire production scheduling process and whether the casting part is processed on the target equipment of the target process as decision variables; Optimizing the decision variables in the low-carbon production scheduling model to determine the optimized decision variables; Determining the entire low-carbon production scheduling process of casting parts by the sand casting enterprise according to the optimized decision variables.
2. The low-carbon production scheduling method for sand casting enterprises according to claim 1, wherein The determining of the low-carbon production scheduling model with the entire production scheduling process of casting parts by a sand casting enterprise as the scheduling object, and using whether the casting part is in the target process of the entire production scheduling process and whether the casting part is processed on the target equipment of the target process as decision variables includes: Determining the objective function, constraint conditions and lot-sizing rules in the low-carbon production scheduling model according to the scheduling object and the decision variables; Determining the low-carbon production scheduling model according to the objective function, the constraint conditions and the lot-sizing rules.
3. The low-carbon production scheduling method for sand casting enterprises according to claim 2, characterized in that, The determining of the objective function in the low-carbon production scheduling model according to the scheduling object and the decision variables includes: Determining a first objective function with the minimum of the maximum completion time of the casting part as the objective according to the completion time of the casting part determined by the scheduling object and the decision variables; Determining a second objective function with the minimum of the early or late delivery time of the casting part as the objective according to the penalty factor for early or late delivery of the casting part, the total processing time of the casting part determined by the scheduling object and the decision variables, and the time from the casting part to the delivery date; Determining a third objective function with the minimum of the carbon emission value of the casting part as the objective according to the scheduling object and the decision variables; Determining the objective function according to the first objective function, the second objective function and the third objective function.
4. The low-carbon production scheduling method for sand casting enterprises according to claim 2, wherein The determining of the constraint conditions in the low-carbon production scheduling model according to the scheduling object and the decision variables includes: Determining the capacity constraint conditions that the batch processing process of the casting part in the entire production scheduling process should satisfy and the processing constraint conditions that the casting part in the entire production scheduling process should satisfy according to the scheduling object and the decision variables; Determining the constraint conditions according to the capacity constraint conditions and the processing constraint conditions.
5. The low-carbon production scheduling method for sand casting enterprises according to claim 2, wherein, The determining of the lot-sizing rules in the low-carbon production scheduling model according to the scheduling object and the decision variables includes: Performing melting batch processing on the casting parts according to the time from the casting parts to the delivery date, quantifying the first overall similarity of the casting parts in the melting batch processing based on the material and pouring temperature of the casting parts, and determining a first lot-sizing rule with the maximization of the first overall similarity and the maximization of the total mass of the casting parts in the melting batch processing as the objectives, where the time from the casting parts to the delivery date is determined by the scheduling object and the decision variables; Based on the time from the casting to the delivery date, heat treatment batch processing is performed on the castings, and the second overall similarity of the castings in the heat treatment batch processing is quantified based on the cooling method and heat treatment temperature, and a second batch rule is determined with the maximization of the second overall similarity and the maximization of the total mass of the castings in the heat treatment batch processing as the objectives; Based on the first batch rule and the second batch rule, the batch rule is determined.
6. The low-carbon production scheduling method for sand casting enterprises according to any one of claims 1-5, characterized in that, The entire production scheduling process includes: Batch processing operations and single-piece processing operations.
7. A low-carbon production scheduling device for a sand casting enterprise, characterized in that, It includes: A first determination module, configured to determine a low-carbon production scheduling model with the entire production scheduling process of casting castings by a sand casting enterprise as the scheduling object and with whether the casting is in the target process in the entire production scheduling process and whether the casting is processed by the target equipment in the target process as decision variables; An optimization module, configured to optimize the decision variables in the low-carbon production scheduling model to determine the optimized decision variables; A second determination module, configured to determine the entire low-carbon production scheduling process of casting castings by the sand casting enterprise according to the optimized decision variables.
8. An electronic device, characterized in that, It includes: At least one memory for storing a computer program; At least one processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 1-6.
9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program runs on the processor, the processor is caused to execute the method according to any one of claims 1-6.
10. A computer program product, characterized in that, When the computer program product runs on the processor, the processor is caused to execute the method according to any one of claims 1-6.