Production scheduling rescheduling method, device, equipment and system

Abstract

Embodiments of the present application provide a production scheduling rescheduling method, device, equipment and system. It relates to the technical field of vehicle production management. The production scheduling rescheduling method comprises: obtaining order information of an uncompleted order in a vehicle order; determining a dynamic risk threshold corresponding to the uncompleted order based on a station sequence; determining a risk level of the uncompleted order based on a remaining delivery time, the dynamic risk threshold and a standard working time of a to-be-executed station in the station sequence; if the risk level meets a preset rescheduling condition, generating a plurality of candidate scheduling schemes; calculating a rescheduling impact index of each candidate scheduling scheme based on a production efficiency dimension and a material completeness dimension, and executing the candidate scheduling scheme with the smallest rescheduling impact index. The present application is used to improve the delivery security of vehicle orders.

Description

Technical Field

[0001] This application relates to the field of vehicle production management technology, and in particular to a production scheduling rescheduling method, apparatus, equipment and system. Background Technology

[0002] In the direct sales model, automakers sell vehicles directly to end users. Users are highly sensitive to delivery time, and the fulfillment of delivery commitments directly affects user satisfaction, brand reputation, and order conversion rate.

[0003] In related technologies, vehicle production scheduling aims to maximize capacity and is based on production cycle time, material availability, and process constraints within the workshop. However, this approach cannot guarantee timely order delivery, resulting in poor order fulfillment assurance. Summary of the Invention

[0004] This application provides a production scheduling rescheduling method, apparatus, equipment, and system to improve the reliability of vehicle order delivery.

[0005] In a first aspect, embodiments of this application provide a production scheduling rescheduling method, including:

[0006] Retrieve order information for incomplete orders in the vehicle order list. The order information includes the remaining delivery time and workstation sequence, and the workstation sequence includes at least one workstation to be executed.

[0007] Based on the workstation sequence, determine the dynamic risk threshold corresponding to uncompleted orders;

[0008] The risk level of unfinished orders is determined based on the remaining delivery time, dynamic risk threshold, and standard working hours of pending workstations in the workstation sequence.

[0009] If the risk level meets the preset rescheduling conditions, multiple candidate scheduling schemes will be generated.

[0010] Based on the dimensions of production efficiency and material availability, the rescheduling impact index of each candidate scheduling scheme is calculated, and the candidate scheduling scheme with the smallest rescheduling impact index is executed.

[0011] In one possible implementation, the workstation sequence further includes executed workstations. Based on the workstation sequence, a dynamic risk threshold corresponding to incomplete orders is determined, including:

[0012] Obtain the production load factor of the production line and the buffer time for unfulfilled orders, where the buffer time is used to characterize the duration reserved for potential risks during the production process;

[0013] The production stage coefficient for incomplete orders is determined based on the ratio of completed workstations to the sum of pending and completed workstations.

[0014] The complexity of unfinished orders is determined based on the total number of workstations in the workstation sequence.

[0015] The product of the production stage coefficient, complexity, production load coefficient, and buffer time is used as the dynamic risk threshold for unfinished orders.

[0016] In one possible implementation, the rescheduling impact index of each candidate scheduling scheme is calculated based on the dimensions of production efficiency and material availability, including:

[0017] Based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme, calculate the production efficiency impact value of the candidate scheduling scheme;

[0018] Based on the differences in material requirements between the candidate scheduling scheme and the current scheduling scheme, the material availability impact value of the candidate scheduling scheme is calculated.

[0019] The rescheduling impact index of candidate scheduling schemes is obtained by weighting the impact values ​​of production efficiency and material availability.

[0020] In one possible implementation, based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme, the production efficiency impact value of the candidate scheduling scheme is calculated, including:

[0021] The difference between the number of times the processing type of the candidate scheduling scheme changes at each workstation and the number of times the processing type of the current scheduling scheme changes at each workstation is taken as the line change impact of the candidate scheduling scheme.

[0022] The difference between the production cycle time in the candidate scheduling scheme and the standard cycle time of the production line is taken as the cycle time impact of the candidate scheduling scheme.

[0023] The difference between the standard deviation of equipment load in the candidate scheduling scheme and the standard deviation of equipment load in the current scheduling scheme is taken as the load impact of the candidate scheduling scheme.

[0024] The production efficiency impact values ​​of the candidate scheduling schemes are obtained by summing up the line changeover impact, cycle time impact, and load impact.

[0025] In one possible implementation, the material availability impact value is calculated based on the difference in material requirements between the candidate scheduling scheme and the current scheduling scheme, including:

[0026] The difference between the number of material requirement changes in the candidate scheduling scheme within the preset window and the number of material requirement changes in the current scheduling scheme within the preset window is taken as the material impact of the candidate scheduling scheme.

[0027] The number of changes in the work-in-process flow path between the candidate scheduling scheme and the current scheduling scheme is taken as the path impact of the candidate scheduling scheme.

[0028] Based on the candidate scheduling schemes, the number of material items that need to be expedited is determined, and the supply impact is obtained;

[0029] The material availability impact value of the candidate scheduling scheme is obtained by summing up the material impact, path impact and supply impact.

[0030] In one possible implementation, the risk level of unfinished orders is determined based on the remaining delivery time, a dynamic risk threshold, and the standard working hours of pending workstations within the workstation sequence, including:

[0031] The sum of the standard working hours of the workstations to be executed is taken as the remaining production time for unfinished orders;

[0032] If the remaining delivery time is greater than or equal to the sum of the remaining production time and the dynamic risk threshold, the risk level is determined to be no risk.

[0033] If the remaining delivery time is greater than or equal to the sum of the remaining production time and the weighted dynamic risk threshold, and less than the sum of the remaining production time and the dynamic risk threshold, the risk level is determined to be low risk, where the weighted dynamic risk threshold is equal to the product of the risk weight and the dynamic risk threshold.

[0034] If the remaining delivery time is greater than or equal to the standard working hours, and less than the sum of the remaining production time and the weighted dynamic risk threshold, the risk level is determined to be medium risk.

[0035] If the remaining delivery time is less than the remaining production time, the risk level is determined to be high risk.

[0036] In one possible implementation, multiple candidate scheduling schemes are generated, including:

[0037] Obtain the scheduling priority of unfinished orders and the proportion of unfinished orders in each pending workstation. The proportion of time is used to represent the time obtained by allocating the remaining delivery time according to the ratio of the standard time of each pending workstation to the remaining production time. The scheduling priority is used to indicate the priority of unfinished orders when generating candidate scheduling schemes.

[0038] Based on the scheduling priority and proportional working hours of unfinished orders, the current scheduling scheme is adjusted through at least one of the following methods: partial adjustment, workstation reorganization, and cycle time adjustment, resulting in multiple candidate scheduling schemes.

[0039] In one possible implementation, the scheduling priority of incomplete orders is obtained in the following way:

[0040] The minimum value between the quotient of the remaining production time of an unfinished order divided by the remaining delivery time and the preset first weight threshold is used as the base weight of the unfinished order.

[0041] Determine the customer level coefficient for incomplete orders based on customer information.

[0042] Based on the risk level, the risk level coefficient of the incomplete orders is determined through a risk level coefficient mapping table;

[0043] The product of the baseline weight, customer level coefficient, and risk level coefficient is used as the priority weight for incomplete orders.

[0044] Secondly, embodiments of this application provide a production scheduling rescheduling device, comprising:

[0045] The acquisition module is used to acquire order information for unfinished orders in the vehicle order list. The order information includes the remaining delivery time and workstation sequence, and the workstation sequence includes at least one workstation to be executed.

[0046] The processing module is used to determine the dynamic risk threshold corresponding to the unfinished orders based on the workstation sequence; determine the risk level of the unfinished orders based on the remaining delivery time, the dynamic risk threshold, and the standard working hours of the workstations to be executed in the workstation sequence; generate multiple candidate scheduling schemes if the risk level meets the preset rescheduling conditions; calculate the rescheduling impact index of each candidate scheduling scheme based on the production efficiency dimension and the material completeness dimension, and execute the candidate scheduling scheme with the smallest rescheduling impact index.

[0047] In one possible implementation, the workstation sequence also includes executed workstations. A processing module is specifically used to: obtain the production load coefficient of the production line and the buffer time for unfinished orders, wherein the buffer time is used to characterize the time reserved for potential risks during the production process; determine the production stage coefficient of unfinished orders based on the ratio of executed workstations to the sum of unexecuted and executed workstations; determine the complexity of unfinished orders based on the total number of workstations in the workstation sequence; and use the product of the production stage coefficient, complexity, production load coefficient, and buffer time as the dynamic risk threshold corresponding to the unfinished orders.

[0048] In one possible implementation, the processing module is specifically used to: calculate the production efficiency impact value of the candidate scheduling scheme based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme; calculate the material availability impact value of the candidate scheduling scheme based on the difference in material demand indicators between the candidate scheduling scheme and the current scheduling scheme; and obtain the rescheduling impact index of the candidate scheduling scheme based on the weighted sum of the production efficiency impact value and the material availability impact value.

[0049] In one possible implementation, the processing module is further configured to: take the difference between the number of times the processing type is switched at each workstation in the candidate scheduling scheme and the number of times the processing type is switched at each workstation in the current scheduling scheme as the line changeover impact of the candidate scheduling scheme; take the difference between the production cycle time in the candidate scheduling scheme and the standard cycle time of the production line as the cycle time impact of the candidate scheduling scheme; take the difference between the equipment load standard deviation of the candidate scheduling scheme and the equipment load standard deviation of the current scheduling scheme as the load impact of the candidate scheduling scheme; and sum the line changeover impact, cycle time impact, and load impact to obtain the production efficiency impact value of the candidate scheduling scheme.

[0050] In one possible implementation, the processing module is further configured to: take the difference between the number of material requirement changes in the candidate scheduling scheme within a preset window and the number of material requirement changes in the current scheduling scheme within the preset window as the material impact of the candidate scheduling scheme; take the number of changes in the work-in-process flow path between the candidate scheduling scheme and the current scheduling scheme as the path impact of the candidate scheduling scheme; determine the number of material items that need to be expedited based on the candidate scheduling scheme to obtain the supply impact; and sum the material impact, path impact, and supply impact to obtain the material kitting impact value of the candidate scheduling scheme.

[0051] In one possible implementation, the processing module is specifically configured to: take the sum of the standard working hours of the workstations to be executed as the remaining production time for unfinished orders; if the remaining delivery time is greater than or equal to the sum of the remaining production time and the dynamic risk threshold, determine the risk level as no risk; if the remaining delivery time is greater than or equal to the sum of the remaining production time and the weighted dynamic risk threshold, and less than the sum of the remaining production time and the dynamic risk threshold, determine the risk level as low risk, wherein the weighted dynamic risk threshold is equal to the product of the risk weight and the dynamic risk threshold; if the remaining delivery time is greater than or equal to the standard working hours, and less than the sum of the remaining production time and the weighted dynamic risk threshold, determine the risk level as medium risk; if the remaining delivery time is less than the remaining production time, determine the risk level as high risk.

[0052] In one possible implementation, the processing module is specifically used to: obtain the scheduling priority of unfinished orders and the proportional working hours of unfinished orders in each pending workstation, wherein the proportional working hours are used to characterize the time obtained by allocating the remaining delivery time according to the ratio of the standard time of each pending workstation to the remaining production time, and the scheduling priority is used to indicate the priority of unfinished orders when generating candidate scheduling schemes; based on the scheduling priority and proportional working hours of unfinished orders, the current scheduling scheme is adjusted through at least one of local adjustment, workstation reorganization and takt adjustment to obtain multiple candidate scheduling schemes.

[0053] In one possible implementation, the processing module is further configured to obtain the scheduling priority of unfinished orders by: using the minimum value between the quotient of the remaining production time of the unfinished order divided by the remaining delivery time and a preset first weight threshold as the base weight of the unfinished order; determining the customer level coefficient of the unfinished order based on the customer information of the unfinished order; determining the risk level coefficient of the unfinished order based on the risk level through a risk level coefficient mapping table; and using the product of the base weight, the customer level coefficient, and the risk level coefficient as the priority weight of the unfinished order.

[0054] Thirdly, embodiments of this application provide a production scheduling rescheduling device, including: a memory and a processor;

[0055] The memory stores instructions that the computer executes;

[0056] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0057] Fourthly, embodiments of this application provide a production scheduling rescheduling system, including production scheduling rescheduling equipment and workshop equipment as described in the third aspect and / or various possible implementations of the third aspect, wherein: the production scheduling rescheduling equipment is used to determine a target scheduling plan based on order information of incomplete orders and to issue the target scheduling plan to the workshop equipment; the workshop equipment is used to receive and execute the target scheduling plan issued by the production scheduling rescheduling equipment, and to perform operations according to the production tasks and delivery times allocated to each workstation in the target scheduling plan.

[0058] Fifthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0059] In a sixth aspect, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0060] The production scheduling rescheduling method, apparatus, equipment, and system provided in this application obtain order information for incomplete orders and determine the order risk level by combining the remaining delivery time, the dynamic risk threshold corresponding to the order, and the standard working hours of the workstation to be executed. This enables more accurate identification of orders with delivery delay risks during the production process, thereby improving the timeliness of early warning for delivery anomalies and the delivery guarantee capability, ensuring the timely delivery of vehicle orders. Simultaneously, when the risk level meets preset rescheduling conditions, multiple candidate scheduling schemes are generated, and the rescheduling impact index of each candidate scheduling scheme is calculated based on production efficiency and material availability dimensions. This allows for a quantitative assessment of the impact of scheduling adjustments on production operations while meeting rescheduling requirements, and then the candidate scheduling scheme with the smallest rescheduling impact index is executed, reducing the impact of scheduling adjustments on production line efficiency and material organization, and improving the stability of vehicle production. Attached Figure Description

[0061] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0062] Figure 1 A schematic diagram illustrating a scenario for the production scheduling rescheduling method provided in this application embodiment;

[0063] Figure 2 A flowchart illustrating a production scheduling rescheduling method provided in an embodiment of this application;

[0064] Figure 3 A flowchart illustrating a production scheduling rescheduling method provided in an embodiment of this application;

[0065] Figure 4 A schematic diagram of the structure of the production scheduling rescheduling device provided in the embodiments of this application;

[0066] Figure 5 A schematic diagram of the production scheduling rescheduling equipment provided in this application embodiment.

[0067] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0068] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application.

[0069] This application relates to production scheduling rescheduling technology in vehicle manufacturing, applicable to manufacturing execution and scheduling control scenarios in a direct-sales, order-based production environment for new energy vehicles. Manufacturing execution and scheduling control scenarios typically involve collaborative operation of business systems such as order management, production execution, and supply chain coordination, continuously receiving order delivery information, workstation status information, and material status information at the production line scheduling layer.

[0070] In related technologies, the production process of new energy vehicles through direct sales and make-to-order manufacturing typically revolves around capacity utilization, production cycle time, equipment status, material supply, and process constraints. Orders are allocated to various workstations according to a preset sequence, and scheduling personnel make local adjustments based on experience after anomalies occur. The focus of this approach is maintaining continuous production line operation, but the commitment to final delivery is not considered a core constraint in scheduling decisions, and there is no direct correlation between the remaining delivery time of unfinished orders and the subsequent workstation sequence. When equipment failures, material delays, or order changes occur, risk identification relies heavily on manual inspections, post-event statistics, or delayed warnings, making it difficult to promptly determine which orders are approaching delivery risk boundaries. Furthermore, situations can easily arise where delivery timeliness and production stability are mutually constrained, preventing highly sensitive orders from being prioritized.

[0071] The production scheduling rescheduling method provided in this application adopts a rescheduling approach that links the remaining delivery time of unfinished orders with the workstation sequence for judgment. This directly places delivery pressure on the workstations to be executed, first identifying the time risk of orders in the current production stage before deciding whether to enter the rescheduling process. A dynamic risk threshold is used to adapt to changes in risk boundaries under different workstation sequences and production line states. After candidate scheduling schemes are generated, they are assessed for impact based on production efficiency and material availability dimensions, facilitating the selection of the scheme with less disruption to the production line from multiple adjustment results. Simultaneously, continuous data flow is maintained between order data, workstation status, and order execution status feedback. Order information, workstation status, and execution results can be updated in a closed loop. The risk level of unfinished orders and scheduling results can be adjusted synchronously with production line changes, improving delivery assurance capabilities and reducing the impact of scheduling adjustments on production operations.

[0072] Figure 1 This is a schematic diagram illustrating a scenario of the production scheduling rescheduling method provided in the embodiments of this application, such as... Figure 1As shown, the specific application scenarios of this application embodiment include: direct-operation terminal 11, workshop equipment 12, and processing center 13, wherein:

[0073] The processing center 13 is connected to the workshop equipment 12, and the direct terminal 11 is connected to the processing center 13.

[0074] Processing center 13 obtains vehicle orders within direct-sales terminal 11 through a communication connection with the direct-sales terminal 11. Processing center 13 manages production within workshop equipment 12 through a communication connection with workshop equipment 12, enabling workshop equipment 12 to produce vehicle orders within direct-sales terminal 11.

[0075] Meanwhile, the processing center 12 can also obtain the production status of the workshop equipment 12 to obtain the order information of unfinished orders in the vehicle order, and manage and schedule the production schedule of the workshop equipment 12 through the production scheduling rescheduling method.

[0076] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0077] Figure 2 This is a flowchart illustrating a production scheduling rescheduling method provided in an embodiment of this application. Figure 2 As shown, the production scheduling rescheduling method includes:

[0078] S201. Obtain order information for incomplete orders in the vehicle order list. The order information includes the remaining delivery time and workstation sequence. The workstation sequence includes at least one workstation to be executed.

[0079] Order information carries scheduling data for incomplete orders, serving as input for risk identification of vehicle delivery risks and production scheduling adjustments. Remaining delivery time represents the amount of time remaining before the order's delivery milestone. Workstation sequence describes the workstations that incomplete orders must pass through and the order in which they are passed. Workstations awaiting execution represent the workstations in incomplete orders that have not yet been processed; these are the targets of scheduling adjustments.

[0080] Specifically, the order information for each vehicle order is obtained. This order information includes at least the order identifier, delivery commitment time, current production status, and process route information. Then, the remaining delivery time for unfinished orders is determined based on the difference between the current time and the delivery commitment time.

[0081] Based on the process route in the order information, the sequence of workstations for incomplete orders is determined. Simultaneously, workstations in the process route that are not yet completed and still require execution are designated as workstations to be executed.

[0082] Optionally, the workstation sequence can also be associated with the standard working hours of each workstation to be executed. For example, if an order has completed the preceding workstations but still needs to execute multiple subsequent workstations, then the workstation sequence of the order will at least include the aforementioned workstations to be executed. These workstations to be executed are written into the order information object in the order of process sequence, and the standard working hours corresponding to each workstation are recorded to obtain the workstation sequence.

[0083] Based on the above data organization method, by associating the remaining delivery time and workstation sequence, the delivery time of vehicle orders can be directly linked to the production chain of vehicle orders, so that the time status and workstation status of unfinished orders can be uniformly expressed in the same data structure, thereby providing a basis for subsequent rescheduling around order delivery risks.

[0084] S202. Based on the workstation sequence, determine the dynamic risk threshold corresponding to the unfinished orders.

[0085] The dynamic risk threshold is used to measure the risk boundary of unfinished orders in the current production state. The value of the dynamic risk threshold is not fixed, but changes with the composition and progress of the workstations to be executed in the workstation sequence.

[0086] The number, sequence, and standard working hours of the workstations to be executed can reflect the changes in the subsequent processing pressure of the order.

[0087] In practice, the risk threshold of the corresponding order can be dynamically determined by combining the characteristics of the workstation represented by the workstation sequence, and the determined dynamic risk threshold can be used as a comparison benchmark for subsequent risk level determination.

[0088] For example, if there are many workstations to be executed and / or the total number of workstations in the workstation sequence is small, the dynamic risk threshold will be adjusted accordingly by reducing it.

[0089] For example, if there are few workstations to be executed, a large total number of workstations in the workstation sequence, and / or a large load on the workstations to be executed, the dynamic risk threshold will be increased accordingly.

[0090] For example, if the ratio of the workstation to be executed to the total number of workstations in the workstation sequence is small, that is, the order is about to be completed, the dynamic risk threshold will decrease accordingly.

[0091] For example, if the ratio of the workstation to be executed to the total number of workstations in the workstation sequence is large, that is, the order has just started production, the dynamic risk threshold will increase accordingly.

[0092] By combining the workstation characteristics represented by the workstation sequence, the risk assessment boundary represented by the dynamic risk threshold can be matched with the actual production progress. Furthermore, after the dynamic risk threshold is determined, the order information of the corresponding order can be written back for association.

[0093] By incorporating information from the workstation sequence into the determination of risk boundaries represented by dynamic risk thresholds, the risk thresholds can change synchronously with the actual production stage of unfinished orders, rather than using a single fixed time limit for judgment. This allows delivery pressure to be mapped onto the workstation chain to be executed, improving the timeliness and consistency of subsequent risk identification.

[0094] S203. Determine the risk level of unfinished orders based on the remaining delivery time, dynamic risk threshold, and standard working hours of pending workstations within the workstation sequence.

[0095] Standard working hours represent the production time required to perform processing at a workstation. The remaining delivery time, dynamic risk threshold, and standard working hours of pending workstations within the workstation sequence collectively determine whether an order faces delivery risk. Risk level is used to classify incomplete orders, characterizing whether an order faces delivery risk. Furthermore, the risk level can serve as a basis for triggering rescheduling.

[0096] Specifically, for each incomplete order, the risk level of the order is determined by reading the remaining delivery time, dynamic risk threshold, and standard working hours of the pending workstations.

[0097] For example, a lower risk level can be identified when the remaining delivery time is sufficient to reflect the subsequent processing pressure relative to the dynamic risk threshold and the standard working hours of the workstations to be executed.

[0098] For example, a higher risk level can be identified when the remaining delivery time is tight relative to subsequent processing pressure.

[0099] Optionally, the determined risk level can be generated into a structured label and associated with the order information.

[0100] By combining the delivery time boundary, represented by the remaining delivery time, with the time load of the standard working hours of the workstations to be executed within the workstation sequence, and providing quantifiable risk stratification for incomplete orders based on dynamic risk thresholds, highly sensitive orders can be identified before they become obviously overdue, providing a unified criterion for whether to initiate rescheduling.

[0101] S204. If the risk level meets the preset rescheduling conditions, generate multiple candidate scheduling schemes.

[0102] Preset rescheduling conditions are used to specify the risk levels under which scheduling adjustments will be initiated. The risk level meeting the preset rescheduling conditions can be specifically set to trigger rescheduling when a predetermined risk level is reached. Optionally, the preset rescheduling conditions are considered met when the risk level is higher than medium risk.

[0103] Candidate scheduling schemes are used to characterize the multiple executable adjustments provided after a rescheduling is triggered.

[0104] If an order meets the preset rescheduling conditions, it will enter the candidate scheduling scheme generation process. The candidate scheduling scheme generation is centered on the workstation link to be executed for this order, and is adjusted in combination with the scheduling results of other orders in the same production line and the same time window, thereby forming multiple different schemes.

[0105] Optionally, candidate scheduling schemes can be obtained by adjusting the start time of orders in the current scheduling scheme at the workstation to be executed, by adjusting the execution order of orders in the current scheduling scheme and other orders at one or more workstations, or by adjusting the cycle interval of orders in the current scheduling scheme entering the workstation to be executed.

[0106] Furthermore, to ensure the feasibility of candidate scheduling schemes, during the generation of candidate scheduling schemes, constraints on process sequence, capacity of the same workstation, equipment availability time, and the constraint that locked work orders cannot be changed are verified. Any combination that violates the constraints is eliminated during the generation stage of candidate scheduling schemes.

[0107] Based on the above analysis, it can be seen that this step is not a single forced modification of the current scheduling plan, but rather the formation of multiple adjustment paths under the premise of meeting manufacturing constraints. This allows subsequent choices to be based on a set of executable solutions, thereby providing a unified basis for comparison between ensuring the delivery of urgent orders and production line stability.

[0108] S205. Based on the dimensions of production efficiency and material availability, calculate the rescheduling impact index of each candidate scheduling scheme, and execute the candidate scheduling scheme with the smallest rescheduling impact index.

[0109] The production efficiency dimension measures the impact of candidate scheduling schemes from the perspectives of production cycle time and resource utilization. The material completeness dimension measures the impact of candidate scheduling schemes from the perspectives of material supply and work-in-process. The rescheduling impact index is used to comprehensively characterize the magnitude of the impact of each candidate scheduling scheme on the production system. Executing the candidate scheduling scheme with the smallest rescheduling impact index means that the scheme with the smaller overall disturbance will be issued and the current schedule will be updated.

[0110] Specifically, each candidate scheduling scheme is evaluated from the dimensions of production efficiency and material availability to obtain the rescheduling impact index of the corresponding candidate scheduling scheme. Multiple candidate scheduling schemes are compared, and the candidate scheduling scheme with the smallest rescheduling impact index that meets the delivery requirements is selected as the target execution scheme.

[0111] Once the target execution plan is determined, the start time, end time, and sequential position of relevant orders at each workstation can be updated via the scheduling interface. After the target execution plan is executed, the updated order information, workstation status, and execution results are collected again, and the risk identification process is re-entered, thus forming a closed-loop rescheduling.

[0112] By uniformly quantifying the impact of candidate scheduling schemes on production efficiency and material availability, multiple candidate scheduling schemes can be compared on the same scale, thereby selecting the adjustment result that causes less disruption to the production line and meets delivery requirements.

[0113] This application provides a production scheduling rescheduling method. By directly linking the remaining delivery time of incomplete orders with subsequent workstation links, and connecting dynamic risk thresholds, risk level determination, candidate scheduling scheme generation, and impact index assessment into a continuous processing flow, the scheduling layer can first identify the time risk of orders in the current production stage, then reschedule orders that meet the conditions, and select the scheme with the smallest overall disturbance from multiple adjustment results, thereby achieving closed-loop scheduling control around the delivery target. By obtaining the order information of incomplete orders and combining the remaining delivery time, the dynamic risk threshold corresponding to the order, and the standard working hours of the workstation to be executed to determine the order risk level, it is possible to more accurately identify orders with delivery delay risks in the production process, thereby improving the timeliness of early warning of delivery anomalies and the delivery guarantee capability, and ensuring the delivery timeliness of vehicle orders.

[0114] Figure 3 This is a flowchart illustrating a production scheduling rescheduling method provided in an embodiment of this application. Figure 3 As shown, in this embodiment... Figure 2 Based on the embodiments, the production scheduling rescheduling method is described in detail, which includes:

[0115] In one possible implementation, the workstation sequence also includes completed workstations, and step S202 may further include:

[0116] S2021. Obtain the production load factor of the production line and the buffer time for unfinished orders, wherein the buffer time is used to characterize the duration reserved for potential risks in the production process.

[0117] First, read the current production load factor of the production line. The production load factor is used to characterize the busyness of the production line.

[0118] Optionally, when the production line load rate is less than or equal to 70%, the production load factor is 0.9. When the production line load rate is greater than 70% and less than or equal to 85%, the production load factor is 1. When the production line load rate is greater than 85%, the production load factor is 1.2.

[0119] Simultaneously, based on the pre-set risk reservation strategy for orders, a buffer time is obtained for unfinished orders. This buffer time is used to cover the additional time required to cover various unexpected disturbances that may occur during the production process.

[0120] Optionally, the buffer time is determined based on the vehicle configuration in the uncompleted orders, that is, different buffer times are configured for different vehicle models.

[0121] Optionally, the buffer time is determined based on customer information in incomplete orders, that is, different buffer times are set for different customers.

[0122] Optionally, the buffer time is determined based on the remaining delivery time of the unfinished orders, with a longer buffer time set for orders with a longer remaining delivery time and a shorter buffer time set for orders with a shorter remaining delivery time.

[0123] Optionally, the buffer time can range from 4 hours to 8 hours.

[0124] S2022. Based on the ratio of executed workstations to the sum of unexecuted workstations and executed workstations, determine the production stage coefficient for incomplete orders.

[0125] By statistically analyzing the number of executed and pending workstations in the workstation sequence of incomplete orders, the sum of pending and executed workstations is calculated. Then, the production stage coefficient is determined by the proportion of executed workstations to the sum of pending and executed workstations.

[0126] The design logic of the production stage coefficient is as follows: when an order is in the later stage of production (i.e., the proportion of executed workstations to the sum of unexecuted workstations and executed workstations is relatively low), the production stage coefficient will decrease accordingly; when an order is in the earlier stage of production (i.e., the proportion of executed workstations to the sum of unexecuted workstations and executed workstations is relatively large), the production stage coefficient will increase accordingly, so as to avoid unnecessary rescheduling triggered by minor fluctuations.

[0127] Optionally, if the proportion of executed workstations to the sum of unexecuted workstations and executed workstations is less than or equal to 30%, then the production stage coefficient is set to 1.5.

[0128] If the proportion of executed workstations to the sum of pending and executed workstations is greater than 30% and less than or equal to 70%, then the production stage coefficient is determined to be 1.2.

[0129] If the proportion of executed workstations to the sum of pending and executed workstations is greater than 70%, then the production stage coefficient is set to 1.

[0130] S2023. Determine the complexity of unfinished orders based on the total number of workstations in the workstation sequence.

[0131] Optionally, the total number of workstations within a workstation sequence can be used as a complexity parameter. The more workstations there are, the more complex the production processes involved in the order, and the more potential anomalies there are. Therefore, the complexity parameter is positively correlated with the total number of workstations, which can be used to quantify the impact of the process chain length on execution risk.

[0132] Optionally, based on the total number of workstations within the workstation sequence, incomplete orders are divided into: standard configuration models, medium configuration models, and high-complexity customized models. Then, the complexity of the standard configuration model is set to 1.0, the complexity of the medium configuration model to 1.2, and the complexity of the high-complexity customized model to 1.5.

[0133] S2024. The product of the production stage coefficient, complexity, production load coefficient, and buffer time is used as the dynamic risk threshold for uncompleted orders.

[0134] The dynamic risk threshold for the unfinished order is obtained by multiplying the four parameters: production stage coefficient, complexity, production load coefficient, and buffer time.

[0135] Optionally, the dynamic risk threshold can be associated with the order information of incomplete orders, which can be called later when jointly determining the risk level with the remaining delivery time and the standard working hours of the pending workstations.

[0136] By adopting the above method, the dynamic risk threshold is simultaneously associated with the production stage, workstation complexity, production line load, and risk reservation time. The dynamic risk threshold can be adjusted according to changes in the production line status, thereby making the risk assessment and rescheduling trigger conditions for unfinished orders more targeted, and providing a consistent threshold basis for the generation of subsequent candidate scheduling schemes and impact assessment.

[0137] In one possible implementation, step S205 may further include:

[0138] S2051. Based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme, calculate the production efficiency impact value of the candidate scheduling scheme.

[0139] After generating candidate scheduling schemes, extract the workstation sequence, workstation start time, and workstation processing time corresponding to the candidate scheduling scheme and the currently executing scheduling scheme.

[0140] Next, the deviation of the candidate scheduling scheme from the current scheduling scheme in terms of production efficiency is quantified from multiple dimensions to obtain the impact values ​​of the candidate scheduling scheme and the current scheduling scheme in different dimensions. Then, the impact values ​​in different dimensions are normalized, multiplied by preset weighting coefficients, and summed to obtain the production efficiency impact value of the candidate scheduling scheme. Optionally, the multiple dimensions include at least two of the following: changeover times, production cycle time, and production line load.

[0141] The larger the impact value on production efficiency, the greater the disturbance to production efficiency caused by the candidate solution.

[0142] S2052. Based on the difference in material requirements between the candidate scheduling scheme and the current scheduling scheme, calculate the material availability impact value of the candidate scheduling scheme.

[0143] After generating candidate scheduling schemes, extract the required quantity, current material arrival status, and planned arrival time of each material corresponding to the candidate scheduling scheme and the currently executed scheduling scheme.

[0144] Next, the degree of material variation between the candidate scheduling scheme and the current scheduling scheme is quantified from multiple dimensions to obtain the impact values ​​of the candidate scheduling scheme and the current scheduling scheme in different dimensions. Then, the impact values ​​in different dimensions are normalized, multiplied by preset weighting coefficients, and summed to obtain the material availability impact value of the candidate scheduling scheme. Optionally, the multiple dimensions include at least two of the following: material availability rate, shortage quantity, and critical material timing.

[0145] For example, if the arrival time of key materials in the candidate scheduling plan cannot meet the workstation start-up requirements of the candidate scheduling plan compared to the current scheduling plan being executed, then the impact value of the key material dimension will increase accordingly.

[0146] S2053. Based on the weighted sum of the production efficiency impact value and the material completeness impact value, the rescheduling impact index of the candidate scheduling scheme is obtained.

[0147] After standardizing the dimensions of the production efficiency impact value and the material availability impact value, they are linearly weighted and summed according to preset weights. The resulting weighted sum is the rescheduling impact index of the candidate scheduling scheme. The weights of the production efficiency impact value and the material availability impact value are set based on the current production stability requirements and material support requirements of the production line. Consistency in weight configuration can be maintained for the same production line or the same order type. Optionally, the weights of both the production efficiency impact value and the material availability impact value are 0.5.

[0148] By employing the weighted summation method described above, comparable quantitative evaluation results can be generated for different candidate scheduling schemes. A smaller rescheduling impact index indicates less overall disturbance to both production efficiency and material availability dimensions, making it more suitable as the final rescheduling implementation plan. This approach ensures that scheduling adjustments maintain production continuity while simultaneously constraining changes in material availability, providing a clear quantitative basis for selecting the optimal rescheduling scheme.

[0149] In one possible implementation, based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme, the production efficiency impact value of the candidate scheduling scheme is calculated, including: taking the difference between the number of processing type switching times at each workstation in the candidate scheduling scheme and the number of processing type switching times at each workstation in the current scheduling scheme as the line changeover impact of the candidate scheduling scheme; taking the difference between the production cycle time in the candidate scheduling scheme and the standard cycle time of the production line as the cycle time impact of the candidate scheduling scheme; taking the difference between the equipment load standard deviation of the candidate scheduling scheme and the equipment load standard deviation of the current scheduling scheme as the load impact of the candidate scheduling scheme; and summing the line changeover impact, cycle time impact, and load impact to obtain the production efficiency impact value of the candidate scheduling scheme.

[0150] After receiving the candidate scheduling scheme and the current scheduling scheme, the processing type sequence corresponding to each workstation is first counted, and the number of switching operations is calculated based on whether adjacent processing types have changed. Then, the difference between the switching operations corresponding to the two scheduling schemes is used to obtain the number of line changes. Next, the number of line changes is multiplied by the line change impact value generated by each line change to obtain the line change impact. The line change impact value is 5.

[0151] Next, the baseline cycle time of the current scheduling scheme is obtained by multiplying the production cycle time of each workstation in the current scheduling scheme by the total number of parts processed at each workstation within a preset time window. Simultaneously, the candidate cycle times of the candidate scheduling scheme are obtained by multiplying the production cycle time of each workstation in the candidate scheduling scheme by the total number of parts processed at each workstation within a preset time window. The difference between the candidate cycle times and the baseline cycle times is used to obtain the cycle time loss. Then, the cycle time loss is multiplied by the cycle time impact value per unit time to obtain the cycle time impact. The cycle time impact value is 0.5, and the unit time is minutes.

[0152] Subsequently, the load balancing deviation is obtained by comparing the standard deviation between the load rate of each device under the candidate scheduling scheme and the load rate under the current scheduling scheme within the statistical period. Then, the load balancing deviation is multiplied by the load surge value generated per percentage point change to obtain the load surge. The cycle surge value is 2 per percentage point.

[0153] Then, the line changeover impact, cycle time impact, and load impact are summed to obtain the production efficiency impact value.

[0154] The production efficiency impact value, as a unified evaluation metric for candidate scheduling schemes in terms of production efficiency, is used together with the material availability impact to form the rescheduling impact index, thus participating in the selection of candidate scheduling schemes. Adopting this approach allows for the unified mapping of frequent line changes, cycle time deviations, and equipment load fluctuations into comparable values, facilitating consistent evaluation of different candidate schemes in rescheduling scenarios.

[0155] In one possible implementation, the material availability impact value is calculated based on the difference in material demand indicators between the candidate scheduling scheme and the current scheduling scheme. This includes: taking the difference between the number of material demand changes in the candidate scheduling scheme within a preset window and the number of material demand changes in the current scheduling scheme within a preset window as the material impact of the candidate scheduling scheme; taking the number of changes in the work-in-process flow path between the candidate scheduling scheme and the current scheduling scheme as the path impact of the candidate scheduling scheme; determining the number of material items requiring expedited supply based on the candidate scheduling scheme to obtain the supply impact; and summing the material impact, path impact, and supply impact to obtain the material availability impact value of the candidate scheduling scheme.

[0156] First, the number of material types for which material requirements change within a preset time window (e.g., the next 4 hours) in the candidate scheduling scheme is compared with the number of material types for which material requirements change within the same time window in the current scheduling scheme. The difference between the two is taken as the number of material changes in the candidate scheduling scheme. Then, the number of material changes is multiplied by the material shock value to obtain the material shock. Optionally, the material shock value is 3.

[0157] Next, the candidate scheduling scheme is compared with the current scheduling scheme, and the number of changes in the work-in-process (WIP) flow path is counted. This number is taken as the path change count for the candidate scheduling scheme. A WIP flow path change refers to a WIP being adjusted to a different workstation sequence in the candidate scheme compared to the original scheme. Then, the path change count is multiplied by the path impact value to obtain the path impact. Optionally, the path impact value is 2.

[0158] Subsequently, based on the candidate scheduling schemes, the number of material items requiring urgent supplier response or expedited delivery is counted, and this number is taken as the number of urgent response items in the candidate scheduling scheme. Specifically, if the demand time for a material is brought forward to a range that cannot be covered by its normal procurement lead time, or if the demand for that material in the candidate scheme exceeds the sum of current available inventory and normal arrival quantity, then that material is marked as requiring urgent supplier response. Then, the number of urgent response items is multiplied by the supply shock value to obtain the supply shock. Optionally, the supply shock value is 4.

[0159] Then, the material shock, path shock, and supply shock are summed to obtain the material availability shock value of the candidate scheduling scheme.

[0160] By adopting the above method, changes in material demand, disturbances in work-in-process paths, and pressure for expedited supply can be uniformly mapped to a single impact value. This allows for a quantitative characterization of the material availability impact of candidate scheduling schemes, facilitating their participation in scheme selection along with production efficiency impacts and reducing additional disturbances to the material support chain during rescheduling.

[0161] In one possible implementation, step S203 may further include:

[0162] S2031. The sum of the standard working hours of the workstations to be executed shall be used as the remaining production time for unfinished orders.

[0163] Simultaneously, the standard working hours of all pending workstations in the workstation sequence of the incomplete order are summed to obtain the remaining production time for that incomplete order. The remaining production time reflects the pure production hours still required to complete the order under ideal conditions, and serves as the basic reference value for subsequent risk level determination.

[0164] S2032. If the remaining delivery time is greater than or equal to the sum of the remaining production time and the dynamic risk threshold, the risk level is determined to be no risk.

[0165] Compare the remaining delivery time with the sum of the remaining production time and the dynamic risk threshold.

[0166] If the remaining delivery time is greater than or equal to the sum of the remaining production time and the dynamic risk threshold, it indicates that even considering comprehensive risk factors such as production line load, workstation complexity, production stage, and buffer reserves, the current remaining delivery time is still sufficient. The order can still be completed on schedule after normal execution and reasonable risk margin is included. Therefore, the risk level is determined to be risk-free.

[0167] S2033. If the remaining delivery time is greater than or equal to the sum of the remaining production time and the weighted dynamic risk threshold, and less than the sum of the remaining production time and the dynamic risk threshold, the risk level is determined to be low risk, where the weighted dynamic risk threshold is equal to the product of the risk weight and the dynamic risk threshold.

[0168] If the remaining delivery time is greater than or equal to the sum of the remaining production time and the weighted dynamic risk threshold, and less than the sum of the remaining production time and the dynamic risk threshold, it indicates that although the remaining delivery time is narrower than the risk-free state, it can still be managed by appropriately compressing the risk reserve or slightly adjusting the pace. Therefore, the risk level is determined to be low risk.

[0169] Optionally, the risk weight is a predefined weight less than 1. For example, the risk weight is 0.5.

[0170] S2034. If the remaining delivery time is greater than or equal to the standard working hours, and less than the sum of the remaining production time and the weighted dynamic risk threshold, the risk level is determined to be medium risk.

[0171] If the remaining delivery time is greater than or equal to the standard working hours, but less than the sum of the remaining production time and the weighted dynamic risk threshold, it indicates that simply compressing risk reserves is insufficient to guarantee on-time delivery, and the order is already facing significant pressure to delay. In this case, if the remaining delivery time is still not less than the standard working hours corresponding to the order (i.e., the shortest necessary length calculated based on ideal pure production working hours), it means that even with extreme compression of non-production time, or in the event of a rescheduling, there is still a theoretical possibility of on-time delivery. However, more proactive intervention measures are required, and therefore the risk level is determined to be medium risk.

[0172] S2035. If the remaining delivery time is less than the remaining production time, the risk level is determined to be high risk.

[0173] When the remaining delivery time is less than the remaining production time, it means that even if all risk factors are completely eliminated and the operation is carried out at the most ideal pure production efficiency, the remaining time cannot meet the pure production time requirements of the order. Theoretically, it is no longer feasible to complete the order on time. Therefore, the risk level is determined to be high risk, and rescheduling or emergency response measures should be triggered accordingly.

[0174] Through the aforementioned hierarchical judgment mechanism, dynamic risk thresholds and their weighted forms are used as interval boundaries to establish a quantitative correspondence between order delivery pressure and workstation execution progress. Risk levels can directly serve as input for whether to trigger rescheduling, enabling the identification of orders approaching delivery boundaries and providing a basis for generating subsequent candidate scheduling solutions, thereby ensuring that risk assessment results remain dynamically consistent with the current production rhythm.

[0175] In one possible implementation, step S204 may further include:

[0176] S2041. Obtain the scheduling priority of unfinished orders and the proportion of unfinished orders in each pending workstation, wherein the proportion of time is used to represent the time obtained by allocating the remaining delivery time according to the ratio of the standard time of each pending workstation to the remaining production time, and the scheduling priority is used to indicate the priority of unfinished orders when generating candidate scheduling schemes.

[0177] Scheduling priority is used to indicate the order in which each order is processed when generating candidate scheduling schemes, so that orders with high delivery pressure or high importance can obtain favorable scheduling positions first.

[0178] The remaining delivery time of the order is allocated according to the ratio of the standard time of each workstation to the remaining production time, so as to obtain the proportional working hours corresponding to each workstation. The proportional working hours limit the time allocation boundary of each workstation in the candidate scheduling scheme, ensuring that the time allocation between workstations matches the actual working hour requirements of the order.

[0179] Scheduling priority and proportional working hours together constitute the constraints for generating candidate scheduling schemes, enabling scheduling adjustments to revolve around the remaining delivery time and limiting the adjustment effect to the controllable range of the current scheduling scheme.

[0180] S2042. Based on the scheduling priority and proportional working hours of unfinished orders, the current scheduling scheme is adjusted through at least one of the following methods: partial adjustment, workstation reorganization, and cycle time adjustment, to obtain multiple candidate scheduling schemes.

[0181] Based on the obtained scheduling priority and proportional working hours, at least one of the following methods—local adjustment, workstation reorganization, and cycle time adjustment—is used to make multi-directional adjustments to the current scheduling scheme.

[0182] Local adjustment method: This method involves swapping, inserting, or reversing the order of certain workstations in the current scheduling plan to create candidate plans with local adjustments. Local adjustment focuses on optimizing the execution order of workstations within a smaller scope, reducing efficiency losses caused by unreasonable local arrangements.

[0183] Workstation reorganization: This method recombines multiple workstations to be executed into a new execution sequence, forming candidate solutions after workstation reorganization. Workstation reorganization adjusts the execution logic relationships between workstations at a more macro-level and is suitable for scenarios requiring a complete restructuring of the overall workstation process.

[0184] Cycle time adjustment method: Based on proportional working hours, the production interval and cycle time spacing between adjacent workstations are compressed or widened to form candidate solutions after cycle time adjustment. The cycle time adjustment method makes the scheduling plan more suitable for the constraints of the remaining delivery time in the time dimension by adjusting the time rhythm between workstations.

[0185] The above adjustment methods can be used individually or in combination to generate multiple candidate scheduling schemes with different structures but all satisfying the constraints. Scheduling priority ensures that high-priority orders are more likely to be placed in favorable scheduling positions, while proportional time ensures that the time allocation for each workstation does not exceed reasonable boundaries. The resulting multiple candidate scheduling schemes provide diverse alternatives for subsequent impact index evaluation, enabling the final rescheduling decision to select the best option from multiple feasible solutions, thereby improving the match between the rescheduling results and delivery constraints.

[0186] In one possible implementation, the scheduling priority of unfinished orders is obtained as follows: the minimum value between the quotient of the remaining production time of the unfinished order divided by the remaining delivery time and a preset first weight threshold is used as the base weight of the unfinished order; the customer level coefficient of the unfinished order is determined based on the customer information of the unfinished order; the risk level coefficient of the unfinished order is determined based on the risk level through a risk level coefficient mapping table; and the product of the base weight, the customer level coefficient, and the risk level coefficient is used as the priority weight of the unfinished order.

[0187] The remaining production time for unfinished orders can be obtained by adding up the standard working hours of the workstations where the order is pending.

[0188] Dividing the remaining production time by the remaining delivery time yields the time urgency ratio. The smaller value between this ratio and a preset first weight threshold is then used to obtain the baseline weight. This preset first weight threshold is used to prevent the baseline weight from becoming excessively amplified when the remaining delivery time approaches zero, as priority weights tend to approach infinity. It prevents high-priority orders from excessively monopolizing scheduling resources due to extreme weight values, thus compromising the rationality and feasibility of the overall scheduling plan. By setting an upper limit on the baseline weight, the preset first weight threshold ensures that even under extremely tight delivery times, the baseline weight remains within a controllable range, maintaining stability in the candidate scheduling plan generation process and preventing the scheduling result from deviating from the global optimum due to the extreme weight of a single order.

[0189] The baseline weight reflects the time sufficiency of an order at its current progress. A baseline weight greater than 1 indicates time constraints and potential delivery risks. A baseline weight less than 1 indicates that the remaining allowable processing time is greater than the theoretically required time, meaning the order has ample time. A higher baseline weight tends to give the order a higher priority.

[0190] The customer tier coefficient is determined by the order management system after retrieving customer files based on customer codes. Optionally, customer tiers include Ordinary, Important, and Special. Specifically, the customer tier coefficient for Ordinary customers is 1; for Important customers, it is 1.1; and for Special customers, it is 1.2.

[0191] The risk level coefficient mapping table can be stored in the scheduling parameter library, with its key-value items corresponding to risk levels such as no risk, low risk, medium risk, and high risk. Risk level coefficients can be set to different positive weights to give high-risk orders higher priority under the same conditions. Optionally, risk levels include no risk, low risk, medium risk, and high risk. Specifically, the risk level coefficient for no risk is 1; for low risk, it is 1.1; for medium risk, it is 1.3; and for high risk, it is 1.5.

[0192] Then, the baseline weight, customer level coefficient, and risk level coefficient are multiplied together to output the priority weight of incomplete orders.

[0193] This priority weighting is formed by the combined effect of time urgency, customer attribute differences, and risk sensitivity to form a comprehensive ranking basis. This enables scheduling control to incorporate delivery pressure, customer level, and risk status into the calculation, and directly use the results to determine the rescheduling priority of incomplete orders. This ensures that the generation and screening of subsequent candidate scheduling schemes are based on a consistent priority scale.

[0194] After adopting the above method, the sorting results of incomplete orders no longer rely solely on a single time indicator, but simultaneously reflect the remaining production time, remaining delivery time, customer information, and risk level. The differentiation of scheduling priorities is more explicit, and changes in priority weights can be updated synchronously with the order status, thereby improving the identification accuracy of highly sensitive orders during rescheduling.

[0195] Figure 4 A schematic diagram of the structure of the production scheduling rescheduling device provided in the embodiments of this application is shown below. Figure 4 As shown, the production scheduling rescheduling device 40 provided in this embodiment includes:

[0196] The acquisition module 401 is used to acquire the order information of unfinished orders in the vehicle order. The order information includes the remaining delivery time and workstation sequence, and the workstation sequence includes at least one workstation to be executed.

[0197] The processing module 402 is used to determine the dynamic risk threshold corresponding to the unfinished order based on the workstation sequence; determine the risk level of the unfinished order based on the remaining delivery time, the dynamic risk threshold, and the standard working hours of the workstations to be executed in the workstation sequence; generate multiple candidate scheduling schemes if the risk level meets the preset rescheduling conditions; calculate the rescheduling impact index of each candidate scheduling scheme based on the production efficiency dimension and the material completeness dimension, and execute the candidate scheduling scheme with the smallest rescheduling impact index.

[0198] In one possible implementation, the workstation sequence also includes executed workstations. The processing module 402 is specifically used to: obtain the production load coefficient of the production line and the buffer time for unfinished orders, wherein the buffer time is used to characterize the time reserved for potential risks during the production process; determine the production stage coefficient of unfinished orders based on the ratio of executed workstations to the sum of unexecuted workstations and executed workstations; determine the complexity of unfinished orders based on the total number of workstations in the workstation sequence; and use the product of the production stage coefficient, complexity, production load coefficient, and buffer time as the dynamic risk threshold corresponding to the unfinished orders.

[0199] In one possible implementation, the processing module 402 is specifically used to: calculate the production efficiency impact value of the candidate scheduling scheme based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme; calculate the material availability impact value of the candidate scheduling scheme based on the difference in material demand indicators between the candidate scheduling scheme and the current scheduling scheme; and obtain the rescheduling impact index of the candidate scheduling scheme based on the weighted sum of the production efficiency impact value and the material availability impact value.

[0200] In one possible implementation, the processing module 402 is further configured to: take the difference between the number of times the processing type is switched at each workstation in the candidate scheduling scheme and the number of times the processing type is switched at each workstation in the current scheduling scheme as the line changeover impact of the candidate scheduling scheme; take the difference between the production cycle time in the candidate scheduling scheme and the standard cycle time of the production line as the cycle time impact of the candidate scheduling scheme; take the difference between the equipment load standard deviation of the candidate scheduling scheme and the equipment load standard deviation of the current scheduling scheme as the load impact of the candidate scheduling scheme; and sum the line changeover impact, cycle time impact, and load impact to obtain the production efficiency impact value of the candidate scheduling scheme.

[0201] In one possible implementation, the processing module 402 is further configured to: take the difference between the number of material demand changes in the candidate scheduling scheme within a preset window and the number of material demand changes in the current scheduling scheme within the preset window as the material impact of the candidate scheduling scheme; take the number of changes in the work-in-process flow path between the candidate scheduling scheme and the current scheduling scheme as the path impact of the candidate scheduling scheme; determine the number of material items that need to be expedited based on the candidate scheduling scheme to obtain the supply impact; and sum the material impact, path impact, and supply impact to obtain the material kitting impact value of the candidate scheduling scheme.

[0202] In one possible implementation, the processing module 402 is specifically configured to: take the sum of the standard working hours of the workstations to be executed as the remaining production time for unfinished orders; if the remaining delivery time is greater than or equal to the sum of the remaining production time and the dynamic risk threshold, determine the risk level as no risk; if the remaining delivery time is greater than or equal to the sum of the remaining production time and the weighted dynamic risk threshold, and less than the sum of the remaining production time and the dynamic risk threshold, determine the risk level as low risk, wherein the weighted dynamic risk threshold is equal to the product of the risk weight and the dynamic risk threshold; if the remaining delivery time is greater than or equal to the standard working hours, and less than the sum of the remaining production time and the weighted dynamic risk threshold, determine the risk level as medium risk; if the remaining delivery time is less than the remaining production time, determine the risk level as high risk.

[0203] In one possible implementation, the processing module 402 is specifically used to: obtain the scheduling priority of unfinished orders and the proportional working hours of unfinished orders in each pending workstation, wherein the proportional working hours are used to characterize the time obtained by allocating the remaining delivery time according to the ratio of the standard time of each pending workstation to the remaining production time, and the scheduling priority is used to indicate the priority of unfinished orders when generating candidate scheduling schemes; based on the scheduling priority and proportional working hours of unfinished orders, the current scheduling scheme is adjusted through at least one of local adjustment, workstation reorganization and takt adjustment to obtain multiple candidate scheduling schemes.

[0204] In one possible implementation, the processing module 402 is further configured to obtain the scheduling priority of unfinished orders by: using the minimum value between the quotient of the remaining production time of the unfinished order divided by the remaining delivery time and a preset first weight threshold as the base weight of the unfinished order; determining the customer level coefficient of the unfinished order based on the customer information of the unfinished order; determining the risk level coefficient of the unfinished order based on the risk level through a risk level coefficient mapping table; and using the product of the base weight, the customer level coefficient, and the risk level coefficient as the priority weight of the unfinished order.

[0205] The production scheduling rescheduling device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0206] Figure 5 A schematic diagram of the production scheduling rescheduling equipment provided in this embodiment of the application. Figure 5 As shown, the production scheduling rescheduling device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the production scheduling rescheduling device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0207] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0208] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0209] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0210] A production scheduling rescheduling system includes the production scheduling rescheduling equipment and workshop equipment provided above, wherein: the production scheduling rescheduling equipment is used to determine a target scheduling plan based on the order information of unfinished orders and to send the target scheduling plan to the workshop equipment; the workshop equipment is used to receive and execute the target scheduling plan sent by the production scheduling rescheduling equipment and to perform operations according to the production tasks and delivery times allocated to each workstation in the target scheduling plan.

[0211] Production scheduling rescheduling equipment combines order information from incomplete orders to generate target scheduling plans. This ensures that scheduling decisions directly address remaining order delivery pressure and workshop execution resources, thus implementing delivery constraints in the task allocation of each workstation. Workshop equipment receives and executes the issued target scheduling plans, enabling each workstation to collaborate around its corresponding production tasks and delivery times, thereby reducing cycle time disruptions caused by manual adjustments. Therefore, the system can maintain consistency between scheduling and execution in the event of order changes, equipment malfunctions, or material fluctuations, thereby improving the ability to guarantee time-sensitive orders and reducing the impact on continuous production line operation.

[0212] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0213] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0214] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0215] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0216] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0217] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0218] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0219] 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0220] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0221] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0222] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0223] Finally, it should be noted that other embodiments of this application will readily conceive of by those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes may be made without departing from its scope.

Claims

1. A production scheduling rescheduling method, characterized in that, include: Obtain order information for uncompleted orders in the vehicle order list. The order information includes the remaining delivery time and workstation sequence, and the workstation sequence includes at least one workstation to be executed. Based on the workstation sequence, determine the dynamic risk threshold corresponding to the unfinished order; The risk level of the unfinished order is determined based on the remaining delivery time, the dynamic risk threshold, and the standard working hours of the workstations to be executed in the workstation sequence. If the risk level meets the preset rescheduling conditions, multiple candidate scheduling schemes are generated. Based on the dimensions of production efficiency and material availability, the rescheduling impact index of each candidate scheduling scheme is calculated, and the candidate scheduling scheme with the smallest rescheduling impact index is executed.

2. The production scheduling rescheduling method according to claim 1, characterized in that, The workstation sequence also includes executed workstations. Determining the dynamic risk threshold corresponding to the unfinished order based on the workstation sequence includes: Obtain the production load factor of the production line and the buffer time for the unfinished orders, wherein the buffer time is used to characterize the duration reserved for potential risks during the production process; The production stage coefficient of the unfinished order is determined based on the ratio of the executed workstations to the sum of the pending workstations and the executed workstations. The complexity of the unfinished order is determined based on the total number of workstations in the workstation sequence. The product of the production stage coefficient, the complexity, the production load coefficient, and the buffer time is used as the dynamic risk threshold corresponding to the unfinished order.

3. The production scheduling rescheduling method according to claim 1, characterized in that, The rescheduling impact index of each candidate scheduling scheme is calculated based on the dimensions of production efficiency and material completeness, including: Based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme, the production efficiency impact value of the candidate scheduling scheme is calculated. Based on the difference in material requirement indicators between the candidate scheduling scheme and the current scheduling scheme, the material availability impact value of the candidate scheduling scheme is calculated. The rescheduling impact index of the candidate scheduling scheme is obtained by weighting the production efficiency impact value and the material completeness impact value.

4. The production scheduling rescheduling method according to claim 3, characterized in that, The step of calculating the production efficiency impact value of the candidate scheduling scheme based on the difference in production efficiency indicators between the candidate scheduling scheme and the current scheduling scheme includes: The difference between the number of times the processing type is switched at each workstation in the candidate scheduling scheme and the number of times the processing type is switched at each workstation in the current scheduling scheme is taken as the line change impact of the candidate scheduling scheme. The difference between the production cycle time in the candidate scheduling scheme and the standard cycle time of the production line is taken as the cycle time impact of the candidate scheduling scheme. The difference between the equipment load standard deviation of the candidate scheduling scheme and the equipment load standard deviation of the current scheduling scheme is taken as the load impact of the candidate scheduling scheme. The production efficiency impact value of the candidate scheduling scheme is obtained by summing the line change impact, the cycle time impact, and the load impact.

5. The production scheduling rescheduling method according to claim 3, characterized in that, The calculation of the material availability impact value based on the difference in material demand indicators between the candidate scheduling scheme and the current scheduling scheme includes: The difference between the number of material requirement changes in the candidate scheduling scheme within a preset window and the number of material requirement changes in the current scheduling scheme within a preset window is taken as the material impact of the candidate scheduling scheme. The number of changes in the work-in-process flow path between the candidate scheduling scheme and the current scheduling scheme is taken as the path impact of the candidate scheduling scheme. Based on the candidate scheduling schemes, the number of material items requiring expedited supply is determined, thus obtaining the supply shock; The material impact, the path impact, and the supply impact are summed to obtain the material kitting impact value of the candidate scheduling scheme.

6. The production scheduling rescheduling method according to any one of claims 1 to 5, characterized in that, The determination of the risk level of the unfinished order based on the remaining delivery time, the dynamic risk threshold, and the standard working hours of the pending workstations in the workstation sequence includes: The sum of the standard working hours of the workstations to be executed shall be taken as the remaining production time for the unfinished orders; If the remaining delivery time is greater than or equal to the sum of the remaining production time and the dynamic risk threshold, the risk level is determined to be risk-free. If the remaining delivery time is greater than or equal to the sum of the remaining production time and the weighted dynamic risk threshold, and less than the sum of the remaining production time and the dynamic risk threshold, the risk level is determined to be low risk, wherein the weighted dynamic risk threshold is equal to the product of the risk weight and the dynamic risk threshold; If the remaining delivery time is greater than or equal to the standard working hours, and less than the sum of the remaining production time and the weighted dynamic risk threshold, the risk level is determined to be medium risk. If the remaining delivery time is less than the remaining production time, the risk level is determined to be high risk.

7. The production scheduling rescheduling method according to any one of claims 1 to 5, characterized in that, The generation of multiple candidate scheduling schemes includes: The scheduling priority of the unfinished orders and the proportional working hours of the unfinished orders in each pending workstation are obtained, wherein the proportional working hours are used to characterize the time obtained by allocating the remaining delivery time according to the ratio of the standard time of each pending workstation to the remaining production time, and the scheduling priority is used to indicate the priority of the unfinished orders when generating the candidate scheduling scheme. Based on the scheduling priority of the unfinished orders and the proportional working hours, the current scheduling scheme is adjusted through at least one of the following methods: local adjustment, workstation reorganization, and cycle time adjustment, to obtain multiple candidate scheduling schemes.

8. The production scheduling rescheduling method according to claim 7, characterized in that, The scheduling priority of the incomplete orders is obtained in the following way: The minimum value between the quotient of the remaining production time of the unfinished order divided by the remaining delivery time and a preset first weight threshold is used as the base weight of the unfinished order. Based on the customer information of the uncompleted orders, determine the customer level coefficient of the uncompleted orders; Based on the risk level, the risk level coefficient of the uncompleted order is determined through a risk level coefficient mapping table; The product of the baseline weight, the customer level coefficient, and the risk level coefficient is used as the priority weight for the incomplete order.

9. A production scheduling rescheduling device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1 to 8.

10. A production scheduling rescheduling system, characterized in that, Includes the production scheduling rescheduling equipment and workshop equipment as described in claim 9, wherein: The production scheduling rescheduling equipment is used to determine a target scheduling plan based on the order information of unfinished orders, and to send the target scheduling plan to the workshop equipment; The workshop equipment is used to receive and execute the target scheduling plan issued by the production scheduling rescheduling equipment, and to perform operations according to the production tasks and delivery times allocated to each workstation in the target scheduling plan.

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