Batch-aggregation-based sintering furnace intelligent scheduling optimization method and system

Abstract

The application provides a sintering furnace intelligent scheduling optimization method and system based on batch aggregation, which comprises the following steps: compatibility matching based on the equipment attribute information of each sintering furnace and the process attribute information of each to-be-scheduled production order, determining a candidate sintering furnace, and determining a target sintering furnace corresponding to a target program number based on the equipment idle time of each candidate sintering furnace; batch aggregation based on the first constraint information of the target sintering furnace and the first product information of the target production order corresponding to the target program number, obtaining a target aggregated furnace batch; determining a first production order corresponding to a dynamic event and a second production order affected by the target aggregated furnace batch; local aggregation of the target aggregated furnace batch based on the second constraint information of the target sintering furnace and the second product information corresponding to the first production order and the second production order, obtaining a final aggregated furnace batch. The application guarantees the continuity and efficiency of sintering production.

Description

Technical Field

[0001] This invention relates to the field of production manufacturing and automated scheduling technology, and in particular to a method and system for intelligent scheduling optimization of sintering furnaces based on batch polymerization. Background Technology

[0002] The sintering process is a critical step in manufacturing. Its scheduling must simultaneously meet multiple complex constraints, including single-furnace capacity constraints, program number consistency requirements, upper and lower limit furnace loading ratios, tooling quantity and capacity limitations, and downtime windows. The rationality of the scheduling plan directly affects production efficiency, equipment utilization, and delivery time stability. Among existing technologies, the most widely used method is the general multi-objective optimization scheduling method based on genetic algorithms. This method constructs a weighted summation model that includes multiple objectives such as equipment utilization and delivery time achievement rate, and uses the evolutionary search mechanism of genetic algorithms to solve for the global scheduling solution.

[0003] However, the method lacks sufficient adaptability to the needs of program number aggregation and dynamic event response in sintering furnace scheduling scenarios. This leads to the need for global recalculation when events such as dynamic order insertion and window expiration occur. The recalculation is inefficient and prone to causing scheduling plan oscillations, failing to guarantee rapid adjustment and stable execution of the plan. Specifically, this method uses all processes in the entire workshop as optimization units and does not design targeted optimization logic for the characteristics of sintering furnace batches. When a dynamic event occurs, the entire evolutionary process of the genetic algorithm needs to be restarted to solve the global plan. This not only consumes a lot of computing resources, but the recalculation time is usually on the order of hours, making it difficult to meet the rapid response requirements for dynamic events in sintering production. At the same time, global recalculation can easily cause locked reasonable furnace batches to be split, resulting in plan oscillations and affecting the continuity and stability of on-site production. Summary of the Invention

[0004] This invention provides a method and system for intelligent scheduling optimization of sintering furnaces based on batch polymerization, aiming to solve the problem that existing methods are prone to plan oscillations when dynamic events occur, achieve rapid response to dynamic events and stable execution of scheduling plans, and ensure the continuity and efficiency of sintering production.

[0005] In a first aspect, the present invention provides a method for intelligent scheduling optimization of sintering furnaces based on batch polymerization, comprising: Based on the equipment attribute information of each sintering furnace and the process attribute information of each work order to be scheduled, compatibility matching is performed to determine candidate sintering furnaces, and the target sintering furnace corresponding to the target program number is determined based on the equipment idle time of each candidate sintering furnace; the target program number is the program number corresponding to the largest number of work orders to be scheduled. Batch aggregation is performed based on the first constraint information of the target sintering furnace and the first product information of the target production schedule corresponding to the target program number to obtain the target aggregation furnace sub-batch. Responding to dynamic events during the execution of the target polymerization furnace batch, determine the first production scheduling work order corresponding to the dynamic event and the second production scheduling work order that affects the target polymerization furnace batch; Based on the second constraint information of the target sintering furnace and the second product information corresponding to the first production schedule and the second production schedule respectively, the target polymerization furnace batch is partially polymerized to obtain the final polymerized furnace batch.

[0006] In a second aspect, the present invention also provides a batch polymerization-based intelligent scheduling optimization system for sintering furnaces, used to implement the batch polymerization-based intelligent scheduling optimization method for sintering furnaces as described in the first aspect; the batch polymerization-based intelligent scheduling optimization system for sintering furnaces includes: The sintering furnace matching module is used to perform compatibility matching based on the equipment attribute information of each sintering furnace and the process attribute information of each work order to be scheduled, to determine the candidate sintering furnaces, and to determine the target sintering furnace corresponding to the target program number based on the equipment idle time of each candidate sintering furnace; the target program number is the program number corresponding to the largest number of work orders to be scheduled. The batch aggregation module is used to perform batch aggregation based on the constraint information of the target sintering furnace and the first product information of the target production schedule corresponding to the target program number, so as to obtain the target aggregation furnace sub-batch. The dynamic event response module is used to respond to dynamic events during the execution of the target polymerization furnace batch, and to determine the first production scheduling work order corresponding to the dynamic event and the second production scheduling work order that affects the target polymerization furnace batch. The local polymerization module is used to perform local polymerization on the target polymerization furnace batch based on the second constraint information of the target sintering furnace and the second product information corresponding to the first production scheduling order and the second production scheduling order, respectively, to obtain the final polymerization furnace batch.

[0007] Thirdly, the present invention also provides an electronic device, comprising: a memory for storing computer software programs; and a processor for reading and executing the computer software programs, thereby realizing the intelligent scheduling optimization method for sintering furnaces based on batch polymerization as described above.

[0008] Fourthly, the present invention also provides a non-transitory computer-readable storage medium storing a computer software program, which, when executed by a processor, implements the intelligent scheduling optimization method for sintering furnaces based on batch polymerization as described above.

[0009] Fifthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the intelligent scheduling optimization method for sintering furnaces based on batch polymerization as described above.

[0010] The intelligent scheduling optimization method for sintering furnaces based on batch aggregation provided in this invention identifies the target program number with the largest number of pending work orders and determines the target sintering furnace by combining the equipment idle time of candidate sintering furnaces. This achieves precise matching between the target program number and equipment resources, and prioritizes scheduling for the program number with the largest number of work orders, thereby improving overall scheduling efficiency. Batch aggregation is performed using the first constraint information of the target sintering furnace and the first product information of the target production work order to form the target aggregation furnace batch. This achieves targeted aggregation of work orders with the same program number, ensuring the rationality of furnace batches. When responding to dynamic events, instead of triggering a global work order review, the system precisely locates the first production scheduling work order corresponding to the dynamic event and the second production scheduling work order affected by it. This clarifies the scope of local adjustments, avoiding the plan oscillation problem caused by global recalculation under dynamic events. Then, by using the second constraint information of the target sintering furnace and the second product information of the first and second production scheduling work orders for local aggregation, adjustments are made only to the affected furnace batches, without interfering with unaffected executed or locked furnace batches. Therefore, there is no need to restart the global optimization process, significantly shortening the rescheduling time. Thus, this invention solves the problem of low rescheduling efficiency under dynamic events and avoids scheduling plan oscillations caused by global recalculation, ultimately achieving rapid response to dynamic events and stable execution of the scheduling plan, ensuring the continuity and efficiency of sintering production. Attached Figure Description

[0011] Figure 1 This is a flowchart illustrating the intelligent scheduling optimization method for sintering furnaces based on batch polymerization provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the intelligent scheduling optimization system for sintering furnaces based on batch polymerization provided in an embodiment of the present invention; Figure 3 An embodiment diagram of the electronic device provided in this invention; Figure 4 An embodiment diagram of a computer-readable storage medium provided in accordance with the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0014] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0015] Optionally, see Figure 1 , Figure 1 This is a flowchart illustrating the intelligent scheduling optimization method for sintering furnaces based on batch polymerization provided by the present invention. In this embodiment, the executing entity of the intelligent scheduling optimization method for sintering furnaces based on batch polymerization is the scheduling optimization system. Therefore, the intelligent scheduling optimization method for sintering furnaces based on batch polymerization includes: Step 10: Perform compatibility matching based on the equipment attribute information of each sintering furnace and the process attribute information of each production order to be scheduled, determine the candidate sintering furnace, and determine the target sintering furnace corresponding to the target program number based on the equipment idle time of each candidate sintering furnace.

[0016] Optionally, the scheduling optimization system receives and verifies the equipment attribute information of each sintering furnace. This equipment attribute information refers to data that clearly defines the type, structural characteristics, and operational constraints of the sintering furnace, specifically including the furnace type (vertical, vertical tooling, horizontal), equipment group, total equipment area, furnace depth, equipment calendar (recording scheduled production tasks and idle periods), lower limit ratio of furnace loading area, and upper limit ratio of furnace loading area. Simultaneously, the scheduling optimization system receives and verifies the process attribute information of each production order to be scheduled. This process attribute information refers to key data related to the production process of the work order and used to match the sintering furnace equipment, specifically including the work order's corresponding program number, individual product area, product height, work order quantity, previous process completion time, downtime, delivery date, and delivery priority.

[0017] Furthermore, the scheduling optimization system performs compatibility matching with the target program number as the core. The target program number refers to the program number with the most corresponding work orders among the pending production work orders. If there are multiple program numbers with the same number of work orders, and all of them have the most, the system will make a decision based on the proximity of the work order's validity window and the urgency of the delivery date, and finally determine a unique target program number. The validity window refers to the latest time range within which the work order needs to complete the sintering process. The proximity of the window is the distance between the current time and the latest time. The closer the distance, the higher the proximity. The urgency of the delivery date refers to the urgency of the work order's required completion time. The earlier the required completion time, the higher the urgency.

[0018] Furthermore, the scheduling optimization system compares the equipment attribute information of each sintering furnace one by one according to the process requirements corresponding to the target program number, and filters out sintering furnaces whose equipment type, operating parameters, etc. are compatible with the process requirements of the target program number, forming candidate sintering furnaces. A candidate sintering furnace refers to a sintering furnace whose equipment attribute information is compatible with the process requirements of the target program number and has the capacity to undertake the corresponding work order production.

[0019] Furthermore, the scheduling optimization system queries the equipment idle time of each candidate sintering furnace. The equipment idle time refers to the time period in the equipment calendar during which the sintering furnace is not occupied by scheduled production tasks. In this embodiment of the invention, the sintering furnace with the earliest start of equipment idle time is selected from the candidate sintering furnace set according to the "earliest available" principle, and is used as the target sintering furnace corresponding to the target program number.

[0020] Furthermore, if multiple candidate sintering furnaces have the same earliest available time, the scheduling optimization system will further refer to the historical operating efficiency of the equipment and select the sintering furnace with better historical operating efficiency as the target sintering furnace. Here, historical operating efficiency refers to the comprehensive performance of the equipment, such as the average time and loading utilization rate of the equipment in the past to complete the production tasks of similar work orders.

[0021] In one embodiment, in a certain production scenario, the work orders to be scheduled include three program numbers: program number 1, program number 2, and program number 3. There are 15 work orders corresponding to program number 1, 12 work orders corresponding to program number 2, and 15 work orders corresponding to program number 3. At this time, program number 1 and program number 3 have the same number of work orders, and both are the maximum. Further verification of the proximity of their validity windows and the urgency of their delivery dates is conducted: the work order corresponding to program number 1 has a validity window with 2 days remaining and a delivery date of 5 days later; the work order corresponding to program number 3 has a validity window with 1 day remaining and a delivery date of 3 days later. Since program number 3 has a higher proximity of its validity window and a more urgent delivery date, program number 3 is determined as the target program number.

[0022] Furthermore, the scheduling optimization system queries the equipment attribute information of all sintering furnaces. Sintering furnace A is horizontal, sintering furnace B is vertical, and sintering furnace C has vertical tooling. The process requirements corresponding to target program number 3 need to be adapted to a horizontal sintering furnace, so sintering furnace A is selected as a candidate sintering furnace. The available time of sintering furnace A is checked, and its earliest available time is 18:00 on the same day (the current time is 10:00 on the same day). Therefore, sintering furnace A is determined to be the target sintering furnace corresponding to target program number 3.

[0023] Step 20: Based on the first constraint information of the target sintering furnace and the first product information of the target production schedule corresponding to the target program number, batch aggregation is performed to obtain the target polymerization furnace sub-batch.

[0024] Optionally, the scheduling optimization system performs batch polymerization operations based on the first constraint information of the target sintering furnace and the first product information of the target production order corresponding to the target program number, to obtain the next batch of the target polymerization furnace, as described in steps 201 to 202. The first constraint information includes the maximum furnace loading area of ​​the target sintering furnace, the maximum number of tooling units available, the number of products that can be loaded onto a single tooling unit, the upper limit of the furnace loading area, and the lower limit of the furnace loading area. The first product information includes the area of ​​a single product corresponding to the target production order.

[0025] Step 30: Respond to dynamic events during the execution of the target polymerization furnace batch, and determine the first production scheduling work order corresponding to the dynamic event and the second production scheduling work order that affects the target polymerization furnace batch.

[0026] Optionally, the scheduling optimization system monitors the execution process of the target polymerization furnace batch in real time and continuously captures potential dynamic events. Dynamic events refer to various events that occur suddenly during the execution of the furnace batch and affect the normal progress of the original production schedule, specifically including window expiration events and order insertion events.

[0027] When a window expiration event is detected, it means that the validity window of a certain production scheduling work order has reached the latest time node. If it is not included in the furnace batch to perform the sintering process, it will face the risk of being overdue. Identify the production scheduling work order corresponding to the event and determine it as a window expiration production scheduling work order.

[0028] When an interruption event is detected, it refers to a new event in the production process that needs to be inserted into the current production schedule for priority or timely execution of a production work order. The new production work order is then determined.

[0029] The first production scheduling work order in this embodiment of the invention includes a window-expiring production scheduling work order and a newly added production scheduling work order.

[0030] Furthermore, the scheduling optimization system analyzes the impact range of the aforementioned first production scheduling work order (window-expiring production scheduling work order or newly added production scheduling work order) on the target polymerization furnace batch. The impact range refers to the relevant production scheduling work orders in the original target polymerization furnace batch that may require adjustments to the production sequence and reallocation of production resources due to the insertion or emergency processing of the first production scheduling work order. This embodiment of the invention determines the affected production scheduling work orders by comparing key information such as the program number, earliest possible furnace loading time, and product specifications of the first production scheduling work order with the corresponding information of each production scheduling work order in the target polymerization furnace batch, thus obtaining the second production scheduling work order. Therefore, the second production scheduling work order refers to the production scheduling work order that needs adjustment in the original production plan due to the occurrence of the first production scheduling work order.

[0031] In one embodiment, the target polymerization furnace batch includes work orders A, B, and C, all corresponding to program number 3, and are planned to be executed sequentially in sintering furnace A (the target sintering furnace). During monitoring, it was found that the validity window of work order D had reached its latest time node (window expiration event). The program number corresponding to work order D is also 3, and the earliest possible furnace loading time overlaps with the execution period of the target polymerization furnace batch. If not handled in time, there will be a risk of overdue. Therefore, work order D is identified as the first production scheduling work order (window expired production scheduling work order). Analysis of the impact of work order D on the target polymerization furnace batch: Work order D has the same program number as work orders A, B, and C, and the required production resources (furnace loading area of ​​sintering furnace A, tooling, etc.) are related. After inserting work order D, the production sequence and loading plan of work orders A, B, and C need to be readjusted. Therefore, work orders A, B, and C are marked as the second production scheduling work orders.

[0032] In another embodiment, a new production scheduling order E (insertion event) is received. Order E has a program number of 3, a tight delivery deadline, and needs to be inserted into the next batch of the current target polymerization furnace for execution. Order E is then designated as the first production scheduling order (new production scheduling order). Analysis shows that the earliest possible furnace loading time for order E conflicts with the execution time of order B, and the furnace loading area occupied by order E will affect the loading arrangements of order B and order C. Therefore, order B and order C are marked as the second production scheduling orders.

[0033] Step 40: Based on the second constraint information of the target sintering furnace and combined with the second product information corresponding to the first and second production orders, perform partial polymerization on the target polymerization furnace batch to obtain the final polymerization furnace batch.

[0034] Optionally, the scheduling optimization system, based on the second constraint information of the target sintering furnace and combined with the second product information corresponding to the first and second production orders, performs partial polymerization operations on the target polymerization furnace batch to obtain the final post-polymerization furnace batch, as described in steps 401 to 408. The second constraint information includes the maximum furnace loading area of ​​the target sintering furnace, the maximum number of tooling available, the upper limit of the furnace loading area, and the lower limit of the furnace loading area. The second product information includes the product quantity, individual product area, and earliest possible loading time corresponding to the first and second production orders, respectively. The earliest possible loading time is calculated based on the completion time and dwell time of the previous process in the corresponding work order.

[0035] The embodiments of the present invention solve the problem of low rescheduling efficiency under dynamic events and avoid scheduling plan oscillations caused by global recalculation. Ultimately, it achieves rapid response to dynamic events and stable execution of scheduling plans, ensuring the continuity and efficiency of sintering production.

[0036] Optionally, the process of steps 201 to 202 includes: Step 201: Based on the maximum furnace loading area of ​​the target sintering furnace, the maximum number of tooling available, and the number of products that can be loaded per tooling, batch polymerization is carried out in combination with the single product area of ​​the target production schedule corresponding to the target program number to obtain the initial polymerization furnace batch.

[0037] Optionally, the scheduling optimization system determines the equipment type of the target sintering furnace, which includes three types: vertical, vertical tooling, and horizontal. The batch aggregation calculation logic is different for different equipment types. In this embodiment of the invention, the corresponding aggregation operation is performed according to the determined equipment type.

[0038] Optionally, if the target sintering furnace is vertical, the scheduling optimization system calculates the occupied area of ​​each target production order corresponding to the target program number. The occupied area of ​​a single target production order is calculated by multiplying the product quantity of that order by the area of ​​each product. Then, the scheduling optimization system accumulates the occupied areas of each target production order in descending order of delivery priority. Delivery priority refers to the urgency of the required completion time; the earlier the required completion time, the higher the urgency. During the accumulation process, the total occupied area is continuously monitored. When the total occupied area reaches or approaches the maximum loading area of ​​the target sintering furnace, but does not exceed the reasonable range corresponding to the maximum loading area, the accumulation operation stops, and the accumulated target production orders are combined into an initial polymerization furnace batch. The reasonable range refers to a buffer zone set based on production practice to avoid loading failure due to unforeseen circumstances, typically 95%-98% of the maximum loading area.

[0039] If there are still target production orders that have not been included in the initial polymerization furnace batch, repeat the above accumulation process to generate a new initial polymerization furnace batch until all target production orders have completed polymerization.

[0040] Optionally, if the target sintering furnace is a vertical fixture, the scheduling optimization system calculates the number of available fixtures for each target production order. The number of available fixtures is calculated by taking the smaller of two values. The first value is the number of products in the target production order divided by the number of products that can be installed in a single fixture (the result is rounded down, which means discarding the decimal part of the calculation result and keeping only the integer part). The second value is the maximum number of available fixtures for the target sintering furnace.

[0041] Furthermore, the scheduling optimization system calculates the occupied area of ​​the target production order. The occupied area is calculated by multiplying the area of ​​a single product by the number of available tooling. The occupied areas of each target production order are accumulated in descending order of delivery priority, while the tooling occupancy table is updated in real time (the tooling occupancy table is a dynamic table that records the usage status, occupied quantity, and remaining available quantity of tooling). When the total occupied area after accumulation approaches the maximum loading area of ​​the target sintering furnace, and the remaining tooling quantity cannot meet the minimum tooling requirement of the next target production order (the minimum tooling requirement is the minimum number of tooling required to complete the production of the target production order, calculated by dividing the number of products in the target production order by the number of products that can be loaded by a single tooling, and rounding up the result, which means that regardless of whether the decimal part of the calculation result is greater than 0, it is always rounded up to the integer part), the accumulation stops, and the accumulated target production orders are combined to form an initial polymerization furnace batch.

[0042] For target production orders with a large number of products that cannot be accommodated in a single batch, the scheduling optimization system automatically splits them into multiple parts and incorporates them into different initial polymerization furnace batches. During the splitting process, it ensures that the number of products in each part matches the corresponding number of tooling used.

[0043] Optionally, if the target sintering furnace is horizontal, the scheduling optimization system first calculates the number of products that can be loaded into each sleeve. The calculation method for the number of products that can be loaded into each sleeve is to divide the furnace depth of the target sintering furnace by the product height of the target production order (rounding down). Then, it calculates the number of sleeves required for each target production order. The calculation method for the number of sleeves required is to divide the number of products in the target production order by the number of products that can be loaded into each sleeve (rounding up). After that, the scheduling optimization system calculates the occupied area of ​​the target production order. The occupied area is calculated by multiplying the number of sleeves required by the area of ​​a single product. The occupied areas of each target production order are accumulated in descending order of delivery priority.

[0044] When the total occupied area after accumulation approaches the maximum loading area of ​​the target sintering furnace, and the remaining sleeve capacity (the remaining sleeve capacity refers to the total area of ​​products that can be loaded after subtracting the number of occupied sleeves from the total number of sleeves that the target sintering furnace can provide) cannot meet the occupied area requirements of the next target production schedule, the accumulation stops, and the accumulated target production schedules are combined into an initial polymerization furnace batch.

[0045] Step 202: Based on the upper limit and lower limit of the furnace loading area of ​​the target sintering furnace, the capacity of the initial polymerization furnace batch is verified to obtain the target polymerization furnace batch.

[0046] Optionally, the scheduling optimization system obtains the lower limit and upper limit of the furnace loading area of ​​the target sintering furnace. The lower limit of the furnace loading area refers to the minimum area that the target sintering furnace can occupy during one sintering production, which is usually set as a certain percentage of the maximum furnace loading area (e.g., 60% of the maximum furnace loading area). The upper limit of the furnace loading area refers to the maximum area that the target sintering furnace can occupy during one sintering production, which is usually equal to or slightly lower than the maximum furnace loading area (e.g., 98% of the maximum furnace loading area).

[0047] Furthermore, for each initial polymerization furnace batch, the actual total occupied area of ​​that batch is calculated, and the actual total occupied area is compared and verified with the lower limit and upper limit of the furnace loading area.

[0048] If the actual total area occupied by the initial polymerization furnace batch is between the lower limit and the upper limit of the furnace loading area, then the initial polymerization furnace batch meets the capacity constraint requirements and is determined as the target polymerization furnace batch.

[0049] If the actual total occupied area of ​​the initial polymerization furnace batch is lower than the lower limit of the furnace loading area, the work orders that are compatible with the target program number (compatible work orders are those whose program number and target program number can be produced in the same furnace and have the same sintering time) will be selected from the target production schedule work orders to be scheduled (target production schedule work orders that have not been included in any initial polymerization furnace batch). The occupied area of ​​these work orders will be added to the initial polymerization furnace batch in descending order of delivery priority, until the actual total occupied area of ​​the batch reaches the lower limit of the furnace loading area. At this time, the updated batch is determined as the target polymerization furnace batch.

[0050] If there are no compatible production orders to be scheduled, or if the minimum furnace area cannot be reached after accumulating all compatible production orders to be scheduled, the scheduling optimization system will merge the initial polymerization furnace batch with other initial polymerization furnace batches (the merged batch must meet the upper limit requirement of furnace area). The batch that meets the capacity constraint after merging will be determined as the target polymerization furnace batch.

[0051] If the minimum furnace area cannot be reached after merging, the situation will be marked as abnormal, and an early warning will be issued to the production management personnel, who will then manually intervene to make adjustments (e.g., delaying production and waiting for more compatible work orders).

[0052] If the actual total occupied area of ​​the initial polymerization furnace batch is higher than the upper limit of the furnace loading area, some target production schedules in the batch are removed in order of delivery priority from low to high. After each removal, the actual total occupied area of ​​the batch is recalculated until the actual total occupied area drops below the upper limit of the furnace loading area and is not lower than the lower limit of the furnace loading area. At this time, the updated batch is determined as the target polymerization furnace batch.

[0053] If, when only one target production order remains, the actual total occupied area is still higher than the upper limit of the furnace loading area, the scheduling optimization system will split the target production order into multiple parts to ensure that the occupied area of ​​each part is between the lower limit and the upper limit of the furnace loading area. Each split part will form a target polymerization furnace batch.

[0054] This invention provides differentiated initial polymerization logic for different types of target sintering furnaces, including vertical, vertical tooling, and horizontal furnaces. This ensures precise matching between the polymerization process and equipment structural characteristics, avoiding unreasonable loading issues caused by equipment type differences. During the initial polymerization stage, work orders are accumulated according to delivery date priority, ensuring that urgent work orders are prioritized for inclusion in the production plan and reducing the risk of late delivery. The capacity verification stage uses dual constraints of upper and lower limits for furnace loading area to avoid wasted equipment utilization due to insufficient area occupied in a single furnace, while preventing production safety hazards or equipment overload caused by excessive area occupied. For batches that do not reach the lower limit of furnace loading area, adjustments are made by supplementing compatible work orders or merging batches. For batches that exceed the upper limit of furnace loading area, optimization is achieved by removing low-priority work orders or splitting work orders, ensuring that each target polymerization furnace batch meets production constraints.

[0055] Optionally, the processes of steps 401 to 404 include: Step 401: If the dynamic event is an order insertion event, then based on the first earliest available furnace loading time corresponding to the first production work order and the second earliest available furnace loading time corresponding to each second production work order, determine the furnace loading time matching result between the first production work order and each second production work order, and filter out candidate matching pairs of the first production work order and the second production work order with no conflict in furnace loading time based on the time matching result.

[0056] Optionally, the scheduling optimization system obtains the first earliest available furnace loading time for the first production order and the second earliest available furnace loading time for each second production order. The first earliest available furnace loading time refers to the earliest time at which the furnace loading operation can be performed for the first production order (newly added production order) based on the completion time and dwell time of its previous process. The second earliest available furnace loading time refers to the earliest time at which the furnace loading operation can be performed for each second production order based on the completion time and dwell time of its previous process.

[0057] Furthermore, the scheduling optimization system determines the planned loading time period for the target sintering furnace for the second batch of production orders. This loading time period is the time interval originally allocated to the second batch of production orders within the target polymerization furnace's next batch, from the start to the end of loading. It should be noted that the starting point of the loading time period for the second batch of production orders must not be earlier than its second earliest possible loading time.

[0058] Furthermore, the scheduling optimization system jointly compares the earliest available furnace loading time of the first production schedule with the second earliest available furnace loading time of each second production schedule, as well as the planned furnace loading time period, to determine the furnace loading time matching result. The furnace loading time matching result refers to the judgment result that comprehensively judges whether the earliest available furnace loading times of the first and second production schedules meet the process sequence requirements, whether there is a time conflict between the furnace loading operations of the two, and whether they can be executed compatiblely within the planned furnace loading time period.

[0059] The specific comparison logic is as follows: First, confirm whether the first earliest possible furnace loading time is not earlier than the second earliest possible furnace loading time (if the process requires the second production order to start furnace loading first, then this condition must be met; if the process allows both to start furnace loading simultaneously, then the first earliest possible furnace loading time can be the same as the second earliest possible furnace loading time); second, determine whether the total furnace loading operation time of the first production order and the second production order does not exceed the total time of the planned furnace loading time period after the furnace loading operation corresponding to the first earliest possible furnace loading time is started, and whether the furnace loading operations of the two do not overlap or conflict within this time period (or the overlapping part does not affect their respective normal furnace loading).

[0060] If both of the above conditions are met, it is determined that there is no conflict between the first production order and the second production order in terms of furnace loading time; otherwise, if the earliest first furnace loading time is earlier than the earliest second furnace loading time and does not meet the process requirements, or if the total furnace loading operation time of the two exceeds the planned furnace loading time period, or if there is an incompatible time overlap, it is determined that there is a conflict in the furnace loading time.

[0061] Furthermore, the scheduling optimization system filters out all combinations of first and second production schedules with no conflicting furnace loading times, forming candidate matching pairs. A candidate matching pair refers to a combination of a first production schedule and a single second production schedule that has no conflicting furnace loading times and is feasible for aggregation.

[0062] Step 402: Based on the single area and quantity of the first product corresponding to the first production order, obtain the first total furnace area of ​​the first production order; and based on the single area and quantity of the second product corresponding to each second production order in the candidate matching pair, obtain the second total furnace area of ​​each second production order.

[0063] Optionally, the scheduling optimization system calculates the first total furnace loading area for the first production order. The first total furnace loading area refers to the total furnace loading area required by the first production order, calculated by multiplying the area of ​​the first product's individual area by the quantity of the first product. Here, the area of ​​the first product's individual area refers to the furnace loading area occupied by a single product corresponding to the first production order; the quantity of the first product refers to the total number of products included in the first production order. Simultaneously, for each candidate matching pair's second production order, the scheduling optimization system calculates its second total furnace loading area. The second total furnace loading area refers to the total furnace loading area required by the second production order, calculated by multiplying the area of ​​the second product's individual area by the quantity of the second product. Here, the area of ​​the second product's individual area refers to the furnace loading area occupied by a single product corresponding to the second production order; the quantity of the second product refers to the total number of products included in the second production order.

[0064] Step 403: Based on the lower limit and upper limit of the furnace loading area of ​​the target sintering furnace, and combined with the second total furnace loading area of ​​each second row of production work orders in the candidate matching, the furnace loading area range of the pre-set split part of the first row of production work orders that can be accommodated by each second row of production work orders is obtained.

[0065] Optionally, for the second production order in each candidate matching pair, the scheduling optimization system calculates the difference between the second total furnace loading area and the upper limit of the furnace loading area of ​​the second production order. This difference is the maximum additional furnace loading area that can be accommodated during the furnace loading time period of the second production order. Then, the system calculates the difference between the lower limit of the furnace loading area and the second total furnace loading area of ​​the second production order.

[0066] If the difference is negative, the minimum additional furnace area that can be accommodated is 0 (that is, no additional area is needed to meet the minimum furnace area requirement).

[0067] If the difference is positive, then the difference is the minimum additional furnace area that needs to be added during the furnace loading period of the second production order (to ensure that the total furnace loading area is not lower than the lower limit of the furnace loading area).

[0068] Furthermore, based on the above calculation results, the scheduling optimization system determines the range of furnace loading area for the pre-defined portion of the first production order that can be accommodated by each second production order. The furnace loading area range refers to the interval within which the furnace loading area corresponding to the additional portion of the first production order that can be accommodated during the furnace loading time period of a single second production order. The lower limit of this interval is the minimum additional furnace loading area that can be accommodated, and the upper limit is the maximum additional furnace loading area that can be accommodated. The pre-defined portion refers to the several parts formed by splitting the first production order according to the furnace loading area to accommodate the furnace loading area range that the second production order can accommodate.

[0069] Step 404: Based on the range of furnace loading area that each second production order can accommodate and the first total furnace loading area of ​​the first production order, perform local aggregation to obtain the final aggregated furnace batch.

[0070] Optionally, the scheduling optimization system performs local aggregation based on the range of furnace loading area that each second production order can accommodate and the first total furnace loading area of ​​the first production order to obtain the final aggregated furnace batch, as described in steps 4041 to 4044.

[0071] The embodiments of the present invention replace global rescheduling with local adjustments, which not only improves the response speed and adjustment accuracy of the scheduling plan to dynamic order insertion events, but also minimizes the disturbance to the original production schedule, ensuring the continuity and efficiency of sintering production.

[0072] Optionally, the processes of steps 4041 to 4044 include: Step 4041: Based on the first total furnace loading area of ​​the first production work order and the range of furnace loading area that each second production work order can accommodate, determine the work order splitting strategy for the first production work order.

[0073] Optionally, the scheduling optimization system summarizes the range of furnace loading area that the second production order can accommodate in all candidate matching pairs, and determines the lower and upper limits of the additional furnace loading area that each second production order can accommodate.

[0074] Furthermore, the scheduling optimization system compares the first total furnace loading area with the sum of the furnace loading areas that can be accommodated by all second-row production orders. If the first total furnace loading area is less than or equal to the sum of the furnace loading areas that can be accommodated by all second-row production orders, the system allocates the furnace loading area share of the first-row production orders to each second-row production order in turn, according to the principle of "prioritizing filling the upper limit of the capacity of a single second-row production order," ensuring that each allocated share does not exceed the furnace loading area range that the corresponding second-row production order can accommodate. If the first total furnace loading area is greater than the sum of the furnace loading areas that can be accommodated by all second-row production orders, the system first fills the furnace loading area range that can be accommodated by all second-row production orders, and the first-row production orders corresponding to the remaining furnace loading area need to be generated as new furnace batches separately (the new furnace batches need to meet the upper and lower limit requirements of the furnace loading area of ​​the target sintering furnace).

[0075] Furthermore, a work order splitting strategy is determined based on the above allocation logic. The work order splitting strategy refers to clarifying how many parts the first production work order needs to be split into, the specific value of the furnace loading area corresponding to each part, and the specific plan for the matching second production work order for each part. This strategy must ensure that the sum of the furnace loading areas of all parts equals the first total furnace loading area, and that the furnace loading area of ​​each part is within the furnace loading area that can be accommodated by the corresponding second production work order.

[0076] Step 4042: Based on the single area of ​​the first product in the first production work order and the furnace loading area of ​​each split part in the work order splitting strategy, obtain the product quantity corresponding to each split part, and perform entity splitting on the first production work order based on the product quantity of each split part to obtain multiple first split entity parts.

[0077] Optionally, the scheduling optimization system obtains the single area of ​​the first product in the first production order, that is, the furnace loading area occupied by a single product corresponding to the first production order.

[0078] For each split portion determined in the work order splitting strategy, the scheduling optimization system calculates the number of products corresponding to that split portion. The calculation method is to divide the furnace loading area of ​​that split portion by the area of ​​a single first product, and round the result up to ensure that the number of products is an integer and can cover the furnace loading area requirement of that split portion.

[0079] Furthermore, the scheduling optimization system performs entity splitting on the first production order based on the calculated product quantities corresponding to each split portion. Entity splitting refers to dividing the physical products corresponding to the first production order into several independent production units according to quantity, with each production unit being a first split entity portion. Each first split entity portion must retain the core process information of the original first production order (such as program number, sintering time, delivery requirements, etc.), while clearly indicating its own product quantity and corresponding furnace loading area.

[0080] Step 4043: Based on the furnace loading area of ​​each first split entity in the work order splitting strategy and the second total furnace loading area of ​​the corresponding second production work order, calculate the combined furnace loading area corresponding to the initial work order combination.

[0081] Optionally, for each candidate matching pair, the scheduling optimization system retrieves the furnace loading area of ​​the corresponding first split entity (determined by the work order splitting strategy) and the second total furnace loading area of ​​the second production work order in the candidate matching pair (i.e., the total furnace loading area required by the second production work order).

[0082] Furthermore, the scheduling optimization system calculates the combined furnace loading area of ​​the initial work order combination corresponding to each candidate matching pair. The initial work order combination refers to the work order combination consisting of a single second production work order and the matched first split entity part; the combined furnace loading area refers to the sum of the second total furnace loading area of ​​the second production work order and the furnace loading area of ​​the corresponding first split entity part in the initial work order combination.

[0083] Step 4044: Based on the combined furnace loading area corresponding to each initial work order combination, combined with the upper limit and lower limit of the furnace loading area, local aggregation is performed to obtain the final aggregated furnace batch.

[0084] Optionally, the scheduling optimization system performs local aggregation based on the combined furnace loading area corresponding to each initial work order combination, combined with the upper limit and lower limit of the furnace loading area, to obtain the final aggregated furnace batch, as described in steps 40441 to 40444.

[0085] The embodiments of the present invention ensure the timely insertion of new production scheduling orders (first production scheduling orders) through local aggregation, while maximizing the stability of the original production scheduling plan (second production scheduling orders), and reducing the disturbance of dynamic order insertion to the production rhythm, thus ensuring the continuity of sintering production.

[0086] Optionally, the processes of steps 40441 to 40444 include: Step 40441: Using the upper limit and lower limit of the furnace loading area as area constraints, select the target work order combination that meets the area constraints based on the combined furnace loading area corresponding to each initial work order combination.

[0087] Optionally, the scheduling optimization system uses the lower and upper limits of the target sintering furnace's loading area as area constraints, comparing the combined loading area of ​​each initial work order combination with the lower and upper limits. If the combined loading area is greater than or equal to the lower limit and less than or equal to the upper limit, the initial work order combination meets the area constraint requirements; if the combined loading area is lower than the lower limit or higher than the upper limit, it does not meet the area constraint requirements.

[0088] Therefore, the scheduling optimization system selects all initial work order combinations that meet the area constraints and identifies them as target work order combinations. Target work order combinations refer to those that are feasible to aggregate in terms of furnace loading area.

[0089] Step 40442: Calculate the total number of products corresponding to the target work order combination based on the number of products corresponding to the first split entity part and the number of second products corresponding to the second production scheduling work order in each target work order combination.

[0090] Optionally, for each target work order combination, the scheduling optimization system obtains the product quantity corresponding to the first split entity portion and the second product quantity corresponding to the second production work order. The product quantity corresponding to the first split entity portion refers to the total number of products from the first production work order included in that portion after entity splitting; the second product quantity refers to the total number of products included in the second production work order. The total product quantity for each target work order combination is calculated as the sum of the product quantity corresponding to the first split entity portion and the second product quantity in that target work order combination.

[0091] Step 40443: Based on the maximum available quantity of tooling and the total number of products corresponding to each target work order combination, the work order combination is filtered to obtain the final work order combination. Based on the earliest available furnace loading time of the first split entity part and the earliest available furnace loading time of the second production schedule work order corresponding to each final work order combination, the actual furnace loading time is determined.

[0092] Optionally, the scheduling optimization system obtains the maximum number of tooling available for the target sintering furnace. The maximum number of tooling available refers to the total number of tooling that can be put into use in the target sintering furnace during the current production period.

[0093] For each target work order combination, the scheduling optimization system calculates the required tooling quantity based on the total number of products and the number of products that can be loaded into a single tooling (the number of products that can be loaded into a single tooling). The calculation method is to divide the total number of products by the number of products that can be loaded into a single tooling, and round the result up. If the required tooling quantity is less than or equal to the maximum available tooling quantity, the target work order combination meets the tooling constraint requirements; if the required tooling quantity is greater than the maximum available tooling quantity, it does not meet the tooling constraint requirements. Further, the scheduling optimization system selects target work order combinations that simultaneously meet both area and tooling constraints, and determines these as the final work order combinations. The final work order combination refers to a work order combination that has satisfied all core production constraints and can be directly included in the furnace batch.

[0094] For each final work order combination, the scheduling optimization system retrieves the earliest possible furnace loading time for the first split entity and the earliest possible furnace loading time for the second production work order within that combination. The later of these two earliest possible furnace loading times is determined as the actual furnace loading time for that final work order combination. The actual furnace loading time refers to the time when the final work order combination actually starts the furnace loading operation on the target sintering furnace. This time setting ensures that both the first split entity and the second production work order meet their own process requirements for the earliest possible furnace loading.

[0095] Step 40444: Based on the actual furnace loading time of each final work order combination, the final work order combinations are divided into time periods and classified, and the final work order combinations of each time period after classification are determined as the final furnace batch after polymerization.

[0096] Optionally, the scheduling optimization system categorizes all final work order combinations by time period based on their actual furnace loading times. Time period categorization means grouping final work order combinations whose actual furnace loading times fall within the same continuous production time period into one category. Final work order combinations of the same category will share the same production cycle of the target sintering furnace, forming an independent furnace batch. Further, the scheduling optimization system determines the final work order combinations of each categorized time period as the final post-polymerization furnace batch. In this embodiment of the invention, each final post-polymerization furnace batch must clearly indicate all work order information (numbers of the first split entity and the second production schedule work order, product quantity, furnace loading area, etc.), actual furnace loading time, required tooling quantity, and combined furnace loading area.

[0097] The embodiments of this invention comprehensively cover production constraints of area, tooling, and time, while ensuring the orderly integration of new production schedules with existing production schedules. This minimizes the disruption to the production plan caused by dynamic order insertions, improves the compliance, accuracy, and executability of the scheduling plan, and at the same time ensures the efficient utilization of sintering production resources and the continuity of the production process.

[0098] Optionally, steps 405 to 408 include: Step 405: If the dynamic event is a window expiration event, then based on the earliest possible furnace loading time corresponding to the first production schedule, determine the priority furnace loading time window to be prioritized, and filter out conflicting production schedules in the second production schedule where the earliest possible furnace loading time overlaps with the priority furnace loading time window. The earliest possible furnace loading time is the window expiration time of the first production schedule.

[0099] Optionally, in the window expiration event scenario, the earliest possible furnace loading time is the window expiration time of the first production order (window expiration production order). The window expiration time refers to the latest time node at which the first production order must complete the sintering process. Exceeding this time node will face the risk of overdue.

[0100] Optionally, the scheduling optimization system determines the priority loading time window based on the window expiration time of the first production order. The priority loading time window refers to the time interval for which production resources are allocated to ensure that the first production order completes the sintering process before the window expiration time. The end point of this time window is the window expiration time of the first production order, and the start point is the earliest start time between the current time and the window expiration time that can accommodate the complete sintering process (including loading, sintering, and unloading) of the first production order.

[0101] Furthermore, the scheduling optimization system retrieves the second earliest possible loading time for all second-row production orders, as well as the planned loading time slots for the target sintering furnace for the second-row production orders. It then compares the second earliest possible loading time and the planned loading time slot for each second-row production order with the priority loading time window to determine if there are any overlaps or conflicts. An overlap or conflict occurs when the planned loading time slot for the second-row production order overlaps with the priority loading time window, and this overlap prevents the first-row production order from successfully completing its loading operation within the priority loading time window.

[0102] Furthermore, the scheduling optimization system filters out all second production schedules that have the aforementioned overlapping conflicts and identifies them as conflicting production schedules. A conflicting production schedule refers to a second production schedule that requires scheduling adjustments because it conflicts with the priority furnace loading time window guaranteed by the first production schedule.

[0103] Step 406: Based on the single area and quantity of the first product corresponding to the first production scheduling work order, calculate the first total furnace area of ​​the first production scheduling work order, and based on the single area and quantity of the second product corresponding to each conflicting production scheduling work order, calculate the second total furnace area of ​​each conflicting production scheduling work order.

[0104] Optionally, the scheduling optimization system calculates the first total furnace loading area for the first production order. The first total furnace loading area refers to the total furnace loading area required by the first production order, calculated by multiplying the area of ​​the first product's individual area by the quantity of the first product. Here, the area of ​​the first product's individual area refers to the furnace loading area occupied by a single product corresponding to the first production order; the quantity of the first product refers to the total number of products included in the first production order. Simultaneously, for each conflicting production order, the scheduling optimization system calculates its second total furnace loading area. The second total furnace loading area refers to the total furnace loading area required by the conflicting production orders, calculated by multiplying the area of ​​the second product's individual area by the quantity of the second product in that conflicting production order. Here, the area of ​​the second product's individual area refers to the furnace loading area occupied by a single product corresponding to the conflicting production order; the quantity of the second product refers to the total number of products included in the conflicting production order.

[0105] Step 407: Based on the upper limit of the furnace loading area and the maximum number of tooling available within the priority furnace loading time window, and combined with the first total furnace loading area and the first product quantity of the first production order, determine the maximum furnace loading area and the maximum product quantity that can be accommodated within the priority furnace loading time window.

[0106] Optionally, the scheduling optimization system obtains the maximum number of tooling available within the priority charging time window. The maximum number of tooling available within the priority charging time window refers to the total number of tooling that can be put into use in the target sintering furnace during the production period corresponding to the priority charging time window. Based on the upper limit of the charging area, the system determines the maximum charging area that can be accommodated within the priority charging time window. This maximum charging area is the upper limit of the charging area of ​​the target sintering furnace (ensuring that the equipment capacity constraint is not exceeded).

[0107] Furthermore, the scheduling optimization system combines the maximum number of available toolings within the priority loading time window and the number of products that can be loaded per tooling (the number of products that can be loaded per tooling refers to the number of products that a single tooling can carry) to calculate the maximum number of products that can be accommodated within the priority loading time window. The calculation method is to multiply the maximum number of available toolings within the priority loading time window by the number of products that can be loaded per tooling.

[0108] Furthermore, the scheduling optimization system verifies the total furnace area and the quantity of the first product in the first production order: ensuring that the total furnace area of ​​the first production order does not exceed the maximum furnace area that can be accommodated within the priority furnace loading time window, and that the quantity of the first product does not exceed the maximum quantity of products that can be accommodated within the priority furnace loading time window. If the relevant parameters of the first production order exceed the above maximum capacity, the scheduling optimization system splits the first production order, specifically as shown in step 4042, ensuring that the portion included in the priority furnace loading time window after splitting meets the maximum capacity requirement, and the remaining portion is arranged according to the subsequent production schedule.

[0109] Furthermore, the scheduling optimization system integrates furnace loading area constraints and tooling constraints to determine the maximum furnace loading area and maximum product quantity that can be accommodated within the priority furnace loading time window.

[0110] Step 408: Based on the second total furnace loading area of ​​each conflicting production schedule, combined with the maximum furnace loading area and the maximum product quantity that can be accommodated within the priority furnace loading time window, local aggregation is performed to obtain the final aggregated furnace batch.

[0111] Optionally, the scheduling optimization system performs local aggregation based on the second total furnace loading area of ​​each conflicting production order, combined with the maximum furnace loading area and the maximum product quantity that can be accommodated within the priority furnace loading time window, to obtain the final aggregated furnace batch, as described in steps 4081 to 4084.

[0112] This invention replaces global rescheduling with local adjustments, improving the scheduling plan's response speed and assurance capability to emergencies, while also taking into account the compliance of production constraints and the continuity of production processes. This effectively reduces the risk of work orders being overdue and enhances the stability of the scheduling plan.

[0113] Optionally, the process of steps 4081 to 4084 includes: Step 4081: Based on the additional maximum furnace area and maximum product quantity that can be accommodated within the priority furnace loading time window, compare the second total furnace area and second product quantity in each conflicting production schedule to select suitable production schedules that can be loaded into the furnace together with the first production schedule within the priority furnace loading time window.

[0114] Optionally, the scheduling optimization system calculates the additional maximum furnace area that can be accommodated within the priority furnace charging time window. The additional maximum furnace area refers to the difference between the maximum furnace area that can be accommodated within the priority furnace charging time window and the first total furnace area of ​​the first production order. This difference represents the upper limit of the additional furnace area that can be accommodated within the priority furnace charging time window, provided that the first production order is successfully charged.

[0115] Furthermore, the scheduling optimization system calculates the maximum additional product quantity that can be accommodated within the priority loading time window. The maximum additional product quantity refers to the difference between the maximum product quantity that can be accommodated within the priority loading time window and the first product quantity of the first production order. This represents the upper limit of the additional product quantity that can be accepted after the first production order is loaded.

[0116] Furthermore, the scheduling optimization system retrieves the second total furnace loading area and the second product quantity for each conflicting production order and compares them with the additional maximum furnace loading area and the additional maximum product quantity. If the second total furnace loading area of ​​the conflicting production order is less than or equal to the additional maximum furnace loading area, and the second product quantity is less than or equal to the additional maximum product quantity, then the conflicting production order meets the condition of being loaded into the furnace together with the first production order within the priority loading time window; otherwise, it does not meet this condition.

[0117] Furthermore, the scheduling optimization system filters out all conflicting production schedules that meet the conditions for joint furnace loading and identifies them as suitable production schedules. A suitable production schedule is one that is compatible with the first production schedule in terms of capacity constraints and can be loaded into the furnace together within the priority furnace loading time window.

[0118] Step 4082: Based on the first total furnace loading area of ​​the first production schedule, the total furnace loading area of ​​each compatible production schedule, and the furnace loading area constraint, determine whether the first production schedule needs to be split.

[0119] Optionally, for each suitable production scheduling work order, the scheduling optimization system calculates the total furnace loading area after combining the first production scheduling work order with the suitable production scheduling work order. The calculation method is to add the first total furnace loading area of ​​the first production scheduling work order to the second total furnace loading area of ​​the suitable production scheduling work order. Further, the combined total furnace loading area is compared with the furnace loading area constraint: if there is at least one suitable production scheduling work order whose total furnace loading area after combining with the first production scheduling work order is between the lower limit and the upper limit of the furnace loading area, then it is determined that the first production scheduling work order does not need to be split; if the total furnace loading area after combining with all suitable production scheduling work orders and the first production scheduling work order exceeds the upper limit of the furnace loading area or is lower than the lower limit of the furnace loading area, then it is determined that the first production scheduling work order needs to be split.

[0120] Step 4083: If the total furnace loading area after combining the first production work order with each matching production work order exceeds the upper limit of the furnace loading area or is lower than the lower limit of the furnace loading area, then based on the accommodating area of ​​each matching production work order, determine the number of parts to be split in the first production work order and the furnace loading area of ​​each split part.

[0121] Optionally, the scheduling optimization system calculates the accommodating area for each suitable production work order. The accommodating area refers to the range of furnace area that the suitable production work order can accommodate after combining with the first production work order, provided that it does not exceed the upper limit of the furnace area and is not lower than the lower limit of the furnace area. The calculation method is as follows: the upper limit of the furnace area minus the second total furnace area of ​​the suitable production work order gives the maximum furnace area that the suitable production work order can accommodate; the lower limit of the furnace area minus the second total furnace area of ​​the suitable production work order (if the result is negative, then take 0) gives the minimum furnace area that the suitable production work order can accommodate. The two constitute the accommodating area range of the suitable production work order.

[0122] Furthermore, the scheduling optimization system aggregates the accommodating area range of all suitable production scheduling orders and, combined with the first total furnace loading area of ​​the first production scheduling order, determines the number of parts to be split in the first production scheduling order. The number of parts refers to the number of independent parts required to ensure that each part of the first production scheduling order can be combined with different suitable production scheduling orders to meet the furnace loading area constraints. The number of parts must satisfy the condition that the sum of the furnace loading areas of all parts equals the first total furnace loading area, and that the furnace loading area of ​​each part is within the accommodating area range of the corresponding suitable production scheduling order.

[0123] Furthermore, the scheduling optimization system allocates a corresponding furnace loading area to each split part based on the number of split parts and the accommodating area range of each suitable production work order, ensuring that the furnace loading area of ​​each split part is within the accommodating area range of the corresponding suitable production work order, and that the sum of the furnace loading areas of all split parts is equal to the first total furnace loading area, thus forming a complete splitting scheme.

[0124] Step 4084: Based on the single area of ​​the first product in the first production order and the furnace loading area of ​​each split part, perform local polymerization to obtain the final batch after polymerization.

[0125] Optionally, the scheduling optimization system performs local aggregation based on the single area of ​​the first product in the first production order and the furnace loading area of ​​each split part to obtain the final aggregated furnace batch, as described in steps 40841 to 40843.

[0126] The embodiments of the present invention provide emergency support for the first production scheduling work order (the production scheduling work order with the window due date), while maximizing the use of production resources, reducing the adjustment disturbance to the original adapted production scheduling work orders, effectively improving the emergency response capability of the scheduling plan, and ensuring the continuity of sintering production and the timeliness of work order delivery.

[0127] Optionally, the processes of steps 40841 to 40843 include: Step 40841: Based on the single area of ​​the first product in the first production order and the furnace loading area of ​​each split part, calculate the product quantity of each split part, and perform entity splitting on the first production order based on the product quantity of each split part to obtain multiple second split entity parts.

[0128] Optionally, for each segment, the scheduling optimization system calculates the number of products corresponding to that segment. The calculation method is to divide the furnace loading area of ​​the segment by the area of ​​a single first product, and round the result up to ensure that the number of products is an integer and can completely cover the furnace loading area requirement of the segment.

[0129] Furthermore, the scheduling optimization system performs entity splitting on the first production order based on the calculated product quantities corresponding to each split portion. Entity splitting refers to dividing the physical products corresponding to the first production order into several independent production units according to quantity, with each production unit being a second split entity portion. Each second split entity portion must retain the core process information of the original first production order (such as program number, sintering time, delivery requirements, etc.), while clearly indicating its own product quantity and corresponding furnace loading area.

[0130] Step 40842: Combine each second split entity part with each matching production scheduling work order, calculate the total furnace area and total product quantity of each initial combination, and select the preferred combination from the initial combination whose total furnace area meets the upper limit and lower limit of furnace area and whose total product quantity does not exceed the maximum available quantity of tooling.

[0131] Optionally, the scheduling optimization system pairs each second-part split entity with its corresponding suitable production scheduling work order, forming multiple initial combinations. An initial combination refers to a work order combination consisting of a single second-part split entity and a single suitable production scheduling work order. For each initial combination, the scheduling optimization system calculates its total furnace loading area and total product quantity. The total furnace loading area is calculated by adding the furnace loading area of ​​the second-part split entity in the combination to the second total furnace loading area of ​​the suitable production scheduling work order; the total product quantity is calculated by adding the product quantity of the second-part split entity in the combination to the second product quantity of the suitable production scheduling work order.

[0132] Optionally, the screening constraints in this embodiment of the invention are: the total furnace loading area is between the lower and upper limits of the target sintering furnace loading area; the total number of products must not exceed the maximum available quantity of tooling within the priority loading time window. The scheduling optimization system filters all initial combinations based on the above constraints, determining the initial combinations that simultaneously meet the constraints as priority combinations. Priority combinations refer to work order combinations that can be compliantly loaded within the priority loading time window.

[0133] Step 40843: The priority combination is added to the priority furnace loading time window to form a priority furnace batch. For the remaining work orders in the conflict scheduling work orders that are not included in the matching scheduling work orders, the furnace loading time is reallocated based on their earliest available furnace loading time to form subsequent furnace batches. The priority furnace batch and the subsequent furnace batches constitute the final aggregated furnace batch.

[0134] Optionally, the scheduling optimization system incorporates all priority combinations into the priority furnace loading time window, forming priority furnace batches. A priority furnace batch refers to a furnace batch executed within the priority furnace loading time window that includes the second split entity portion and the corresponding production schedule. This batch must clearly indicate core information such as the furnace loading time, total furnace loading area, and total product quantity for each combination, ensuring that all second split entity portions of the first production schedule can be sintered before the window expires.

[0135] Furthermore, for the remaining work orders in the conflicting production work orders that were not selected as suitable production work orders, the scheduling optimization system retrieves their second earliest furnace loading time (the second earliest furnace loading time refers to the earliest time that the remaining work order can perform furnace loading operation based on the completion time and dwell time of its previous process).

[0136] Furthermore, the scheduling optimization system, based on the second earliest available loading time for the remaining work orders and combined with the target sintering furnace's equipment calendar (which records the equipment's scheduled production tasks and idle periods), reallocates loading time slots for each remaining work order. This ensures that the reallocated loading time slots do not conflict with the time of the priority furnace batch and meet the process requirements and delivery constraints of the remaining work order. The remaining work orders after the reallocation of loading time slots are then categorized by time slot to form subsequent furnace batches. Subsequent furnace batches refer to furnace batches executed after the priority furnace batches that include remaining work orders from conflicting production schedules.

[0137] Furthermore, the scheduling optimization system integrates the priority furnace batch with the subsequent furnace batches to jointly determine the final post-polymerization furnace batch. The final post-polymerization furnace batch must completely cover the remaining work orders in the first production schedule, the matching production schedule, and the conflicting production schedule, and all sub-batches must meet the production constraints.

[0138] This invention prioritizes the formation of priority furnace batches to ensure timely delivery of work orders with expiring windows. At the same time, it reallocates time slots for remaining conflicting work orders to form subsequent furnace batches, minimizing disruption to the original production schedule and ensuring the continuity of sintering production.

[0139] Furthermore, the intelligent scheduling optimization system for sintering furnaces based on batch polymerization provided by the present invention will be described below. The intelligent scheduling optimization system for sintering furnaces based on batch polymerization described below can be referred to in correspondence with the intelligent scheduling optimization method for sintering furnaces based on batch polymerization described above.

[0140] Optionally, refer to Figure 2 , Figure 2 This is a schematic diagram of the intelligent scheduling optimization system for sintering furnaces based on batch polymerization provided by the present invention. The intelligent scheduling optimization system for sintering furnaces based on batch polymerization includes: The sintering furnace matching module 210 is used to perform compatibility matching based on the equipment attribute information of each sintering furnace and the process attribute information of each work order to be scheduled, to determine the candidate sintering furnace, and to determine the target sintering furnace corresponding to the target program number based on the equipment idle time of each candidate sintering furnace; the target program number is the program number corresponding to the largest number of work orders to be scheduled. Batch aggregation module 220 is used to perform batch aggregation based on the constraint information of the target sintering furnace and the first product information of the target production schedule corresponding to the target program number, so as to obtain the target aggregation furnace sub-batch. The dynamic event response module 230 is used to respond to dynamic events during the execution of the second batch of the target polymerization furnace, and to determine the first production schedule corresponding to the dynamic event and the second production schedule that affects the second batch of the target polymerization furnace. The local polymerization module 240 is used to perform local polymerization on the target polymerization furnace batch based on the second constraint information of the target sintering furnace and the second product information corresponding to the first production order and the second production order, respectively, to obtain the final polymerization furnace batch.

[0141] The embodiments of the present invention solve the problem of low rescheduling efficiency under dynamic events and avoid scheduling plan oscillations caused by global recalculation. Ultimately, it achieves rapid response to dynamic events and stable execution of scheduling plans, ensuring the continuity and efficiency of sintering production.

[0142] Please see Figure 3 , Figure 3 An embodiment diagram of an electronic device provided in accordance with the present invention. For example... Figure 3 As shown, an embodiment of the present invention provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, it implements the processes of steps 10 to 40.

[0143] Please see Figure 4 , Figure 4 An embodiment diagram of a computer-readable storage medium provided in accordance with an embodiment of the present invention is shown. Figure 4 As shown, this embodiment provides a computer-readable storage medium 400 on which a computer program 311 is stored. When the computer program 311 is executed by a processor, it implements the processes of steps 10 to 40.

[0144] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the intelligent scheduling optimization method for sintering furnace based on batch polymerization provided by the above methods, which includes steps 10 to 40.

[0145] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0146] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent scheduling optimization of a batch-based sintering furnace based on aggregation, characterized in that, include: Based on the equipment attribute information of each sintering furnace and the process attribute information of each work order to be scheduled, compatibility matching is performed to determine candidate sintering furnaces, and the target sintering furnace corresponding to the target program number is determined based on the equipment idle time of each candidate sintering furnace; the target program number is the program number corresponding to the largest number of work orders to be scheduled. Batch aggregation is performed based on the first constraint information of the target sintering furnace and the first product information of the target production schedule corresponding to the target program number to obtain the target aggregation furnace sub-batch. Responding to dynamic events during the execution of the target polymerization furnace batch, determine the first production scheduling work order corresponding to the dynamic event and the second production scheduling work order that affects the target polymerization furnace batch; Based on the second constraint information of the target sintering furnace and the second product information corresponding to the first and second production schedules, partial polymerization is performed on the target polymerization furnace batch to obtain the final polymerization furnace batch, specifically including: If the dynamic event is an order insertion event, then based on the first earliest furnace loading time corresponding to the first production scheduling work order and the second earliest furnace loading time corresponding to each second production scheduling work order, the furnace loading time matching result of the first production scheduling work order and each second production scheduling work order is determined, and candidate matching pairs of the first production scheduling work order and the second production scheduling work order with no conflict in furnace loading time are selected based on the time matching result. Based on the single area and quantity of the first product corresponding to the first production order, the first total furnace area of ​​the first production order is obtained, and based on the single area and quantity of the second product corresponding to each second production order in the candidate matching pair, the second total furnace area of ​​each second production order is obtained. Based on the lower limit and upper limit of the furnace loading area of ​​the target sintering furnace, and combined with the second total furnace loading area of ​​each second row of production work orders in the candidate matching, the furnace loading area range of the split preset part of the first row of production work orders that can be accommodated by each second row of production work orders is obtained. Based on the range of furnace loading area that each second production order can accommodate and the first total furnace loading area of ​​the first production order, partial aggregation is performed to obtain the final aggregated furnace batch.

2. The method of claim 1, wherein, The constraint information includes the maximum furnace loading area, the maximum number of tooling available, the number of products that can be loaded into a single tooling, the upper limit of the furnace loading area, and the lower limit of the furnace loading area; the product information includes the number of products, the area of ​​a single product, and the earliest time that can be loaded into the furnace; the earliest time that can be loaded into the furnace is determined based on the completion time of the previous process and the dwell time.

3. The method of claim 2, wherein, The partial aggregation based on the furnace loading area range that each second production order can accommodate and the first total furnace loading area of ​​the first production order, to obtain the final aggregated furnace batch, includes: Based on the first total furnace loading area of ​​the first production schedule and the range of furnace loading areas that each second production schedule can accommodate, a work order splitting strategy for the first production schedule is determined; the work order splitting strategy indicates each split part of the first production schedule and the furnace loading area corresponding to each split part. Based on the single area of ​​the first product in the first production scheduling work order and the furnace loading area of ​​each split part in the work order splitting strategy, the product quantity corresponding to each split part is obtained, and the first production scheduling work order is physically split based on the product quantity of each split part to obtain multiple first splitting entity parts. Based on the furnace loading area of ​​each first split entity in the work order splitting strategy and the second total furnace loading area of ​​the corresponding second production work order, calculate the combined furnace loading area corresponding to each initial work order combination. Based on the combined furnace loading area corresponding to each initial work order combination, combined with the upper limit and lower limit of the furnace loading area, local aggregation is performed to obtain the final aggregated furnace batch.

4. The method of claim 3, wherein, The process of locally aggregating the combined furnace loading area corresponding to each initial work order combination, along with the upper and lower limits of the furnace loading area, to obtain the final aggregated furnace batch includes: Using the upper and lower limits of the furnace loading area as area constraints, target work order combinations that meet the area constraints are selected based on the combined furnace loading area corresponding to each initial work order combination. Based on the number of products corresponding to the first split entity part and the number of second products corresponding to the second production scheduling work order in each target work order combination, calculate the total number of products corresponding to each target work order combination. Based on the maximum available quantity of tooling and the total number of products corresponding to each target work order combination, the work order combination is screened to obtain the final work order combination. Based on the earliest available furnace loading time of the first split entity part and the earliest available furnace loading time of the second production schedule work order corresponding to each final work order combination, the actual furnace loading time is determined. Based on the actual furnace loading time of each final work order combination, the final work order combinations are divided into time periods and categorized, and the final work order combinations of each time period after categorization are determined as the final batch of furnaces after polymerization.

5. The method of claim 2, wherein, The steps for obtaining the final batch after partial polymerization include: If the dynamic event is a window expiration event, then based on the earliest available furnace loading time corresponding to the first production scheduling work order, the priority furnace loading time window to be prioritized is determined, and conflicting production scheduling work orders in the second production scheduling work order that have overlapping conflicts with the earliest available furnace loading time and the priority furnace loading time window are screened out. Based on the single area and quantity of the first product corresponding to the first production scheduling work order, calculate the first total furnace area of ​​the first production scheduling work order, and based on the single area and quantity of the second product corresponding to each conflicting production scheduling work order, calculate the second total furnace area of ​​each conflicting production scheduling work order. Based on the upper limit of furnace loading area and the maximum number of tooling available within the priority furnace loading time window, and combined with the first total furnace loading area and the first product quantity of the first production order, determine the maximum furnace loading area and the maximum product quantity that can be accommodated within the priority furnace loading time window. Based on the second total furnace area of ​​each conflicting production schedule, combined with the maximum furnace area that can be accommodated within the priority furnace loading time window and the maximum number of products, local aggregation is performed to obtain the final aggregated furnace batch.

6. The method of claim 5, wherein, The partial aggregation based on the second total furnace loading area of ​​each conflicting production schedule, combined with the maximum furnace loading area and maximum product quantity that can be accommodated within the priority furnace loading time window, yields the final aggregated furnace batch, including: Based on the maximum additional furnace area and maximum product quantity that can be accommodated within the priority furnace loading time window, compare the second total furnace area and second product quantity in each conflicting production schedule to select suitable production schedules that can be loaded together with the first production schedule within the priority furnace loading time window. Based on the first total furnace area of ​​the first production scheduling work order, the total furnace area of ​​each compatible production scheduling work order, and the furnace area constraint, determine whether the first production scheduling work order needs to be split. If the total furnace loading area after combining the first production schedule with each matching production schedule exceeds the upper limit of the furnace loading area or is lower than the lower limit of the furnace loading area, then the number of parts of the first production schedule and the furnace loading area of ​​each part are determined based on the accommodating area of ​​each matching production schedule. Based on the single area of ​​the first product and the furnace loading area of ​​each split part in the first production schedule, local polymerization is performed to obtain the final batch of the polymerized furnace.

7. The method of claim 6, wherein, The partial aggregation based on the single area of ​​the first product and the furnace loading area of ​​each segmented part of the first production schedule to obtain the final aggregated furnace batch includes: Based on the single area of ​​the first product in the first production schedule and the furnace loading area of ​​each split part, calculate the product quantity of each split part, and perform entity splitting on the first production schedule based on the product quantity of each split part to obtain multiple second split entity parts. Each second split entity is combined with each matching production scheduling work order. The total furnace area and total product quantity of each initial combination are calculated. In the initial combination, the preferred combination is selected where the total furnace area meets the upper limit and lower limit of the furnace area and the total product quantity does not exceed the maximum available quantity of tooling. Priority combinations are added to the priority loading time window to form priority loading batches. For the remaining work orders in the conflicting production schedule that are not included in the matching production schedule, the loading time is reallocated based on the earliest available loading time to form subsequent loading batches. Priority loading batches and subsequent loading batches constitute the final aggregated loading batch.

8. The method of claim 2, wherein, The batch aggregation based on the first constraint information of the target sintering furnace and the first product information of the target production schedule corresponding to the target program number is performed to obtain the target polymerization furnace sub-batch, including: Based on the maximum furnace loading area of ​​the target sintering furnace, the maximum number of tooling available, and the number of products that can be loaded per tooling, batch polymerization is carried out in combination with the single product area of ​​the target production schedule work order corresponding to the target program number to obtain the initial polymerization furnace batch. The initial batch of polymerization furnaces is capacity-verified based on the upper and lower limits of the furnace loading area of ​​the target sintering furnace to obtain the target batch of polymerization furnaces.

9. A batch-based, sintering furnace, intelligent scheduling optimization system, comprising: Used to implement the intelligent scheduling optimization method for sintering furnaces based on batch polymerization as described in any one of claims 1 to 8; The intelligent scheduling optimization system for sintering furnaces based on batch polymerization includes: The sintering furnace matching module is used to perform compatibility matching based on the equipment attribute information of each sintering furnace and the process attribute information of each work order to be scheduled, to determine the candidate sintering furnaces, and to determine the target sintering furnace corresponding to the target program number based on the equipment idle time of each candidate sintering furnace; the target program number is the program number corresponding to the largest number of work orders to be scheduled. The batch aggregation module is used to perform batch aggregation based on the constraint information of the target sintering furnace and the first product information of the target production schedule corresponding to the target program number, so as to obtain the target aggregation furnace sub-batch. The dynamic event response module is used to respond to dynamic events during the execution of the target polymerization furnace batch, and to determine the first production scheduling work order corresponding to the dynamic event and the second production scheduling work order that affects the target polymerization furnace batch. The local polymerization module is used to perform local polymerization on the target polymerization furnace batch based on the second constraint information of the target sintering furnace and the second product information corresponding to the first production scheduling order and the second production scheduling order, respectively, to obtain the final polymerization furnace batch.

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