Process route scheduling progress synchronization method and system based on key process anchoring

Abstract

This invention relates to the field of production scheduling and optimization technology, and provides a method and system for synchronizing process route scheduling progress based on key process anchoring. The method includes the following steps: acquiring process route data for the target product and identifying key process anchoring steps; constructing the progress influence function of each key process anchoring step and the inter-process influence function between adjacent process sections; establishing a process route progress synchronization model; solving the process route progress synchronization model to obtain the time adjustment amount for non-key processes within each process section; and updating the scheduling plan for non-key processes based on the time adjustment amount. This invention quantitatively models the cumulative impact of schedule deviations, ensuring that the progress of non-key processes within each process section remains synchronized with the progress of key process anchoring steps. This effectively suppresses the step-by-step amplification and chain transmission of schedule deviations in the process route, and is suitable for dynamic scheduling adjustments in multi-variety, small-batch discrete manufacturing scenarios.

Description

Technical Field

[0001] This invention belongs to the field of production scheduling and optimization technology, and particularly relates to a method and system for synchronizing process route scheduling progress based on key process anchoring. Background Technology

[0002] As the manufacturing industry shifts towards a production model characterized by diverse product types, small batches, and short lead times, traditional manual scheduling, reliant on planner experience, suffers from low efficiency, delayed response, and inefficient resource allocation. Advanced Planning and Scheduling (APS) systems, as advanced planning and scheduling tools based on supply chain management and constraint theory, have been widely applied in production planning and scheduling within manufacturing enterprises. Existing APS systems typically utilize intelligent algorithms such as genetic algorithms and constraint theory to automatically generate production scheduling plans under multiple constraints, including equipment capacity, material supply, and process sequence.

[0003] However, existing APS scheduling technology still has the following shortcomings in synchronizing process route progress and needs improvement: Current scheduling systems treat all processes in the process route as equally weighted nodes for unified scheduling, without distinguishing the criticality of processes. In a process route containing dozens of processes, the schedule deviation of non-critical processes has a negligible impact on overall delivery, while even a small deviation in critical processes (such as bottleneck processes or long-cycle processes) can lead to delays in the delivery of the entire order. Existing technologies lack mechanisms for identifying and anchoring critical processes in the process route, resulting in significant waste of computational resources and low response speed. Summary of the Invention

[0004] The purpose of this invention is to provide a method for synchronizing process route scheduling based on key process anchoring, in order to solve the above-mentioned technical problems.

[0005] This invention is implemented as follows: a method for synchronizing process route scheduling based on key process anchoring, comprising the following steps:

[0006] Obtain the process route data of the target product and identify key process anchor points to obtain anchoring base data;

[0007] Based on the deviation between the planned and actual execution progress of each key process anchor point, a progress influence function for each key process anchor point and an inter-process segment influence function are constructed. The progress influence function is used to quantitatively describe the cumulative impact of a single process progress deviation on non-key processes within its process segment. The inter-process segment influence function is used to quantitatively describe the mutual transmission of progress deviations between adjacent process segments.

[0008] Using the aforementioned schedule impact function and inter-process segment impact function as optimization objectives, a schedule synchronization model for the process route is established. The schedule synchronization model takes minimizing the sum of the schedule impact of all critical process anchor point operations and the sum of the inter-process segment impact of all adjacent process segments as its objective function, and uses the time adjustment amount of non-critical operations within each process segment as the decision variable.

[0009] Solve the aforementioned schedule synchronization model to obtain the time adjustment amount for non-critical processes within each process section;

[0010] The scheduling plan for non-critical processes is updated based on the time adjustment amount, so that the progress of non-critical processes in each process section is synchronized with the progress of the corresponding critical process anchor point processes.

[0011] Furthermore, the process route data includes information on all processes that make up the process route and the sequential constraints between each process; the steps of acquiring the process route data of the target product and identifying key process anchor points to obtain anchored basic data specifically include:

[0012] Calculate the comprehensive criticality index for each process step; the comprehensive criticality index is obtained by weighted summation of the processing time weight, resource exclusivity weight, and topological position weight before and after the process step;

[0013] Processes whose comprehensive criticality index exceeds a preset threshold are marked as candidate critical processes, and non-adjacent processes are selected from the candidate critical processes according to the process route sequence as critical process anchor points.

[0014] Based on each key process anchor point, the process route is divided into several process sections to obtain anchoring foundation data.

[0015] Furthermore, the method for dividing the process segments is as follows: each critical process anchor point is used as the anchor point of the process segment, and all non-critical processes between two adjacent critical process anchor point processes are divided into the same process segment. The first and last process segments are respectively bounded by the first critical process anchor point process and the last critical process anchor point process.

[0016] Furthermore, the method for constructing the schedule impact function is as follows: obtain the schedule deviation value of the i-th critical process anchor point. Construct the schedule impact function of the i-th critical process anchor point according to the following formula. :

[0017] ;

[0018] in, The influence coefficient is positively correlated with the number of non-critical processes in the process section where the i-th critical process anchor point process is located and the planned working hours of that process. The influence coefficient has a non-linear variation characteristic: when the absolute value of the schedule deviation exceeds the preset linear zone threshold, the influence coefficient increases non-linearly with the increase of the schedule deviation value.

[0019] Furthermore, the schedule deviation value is calculated based on the difference between the planned and actual working hours and the planned and actual end times of the corresponding process.

[0020] Furthermore, the method for constructing the inter-process segment influence function is as follows: The inter-segment influence function between the i-th process segment and the (i+1)-th process segment is constructed according to the following formula. :

[0021] ;

[0022] in, and These are the schedule deviation values ​​for the i-th and (i+1)-th critical process anchor points, respectively; The coupling influence coefficient is determined based on the process connection strength between two adjacent key process anchor points.

[0023] Furthermore, the method for constructing the progress synchronization model is as follows:

[0024] The time adjustment amount of non-critical processes within each process section is used as the decision variable;

[0025] A schedule synchronization model is constructed with the objective function of minimizing the sum of the schedule impact of all key process anchor points and the sum of the inter-segment impact of all adjacent sections.

[0026] The objective function is expressed as:

[0027] ;

[0028] in, Let be the decision variable, representing the time adjustment amount for the j-th non-critical process; M is the total number of critical process anchor points; A i Let be the set of non-critical processes within the process segment containing the i-th critical process anchor point; and let be the time adjustment amount for each non-critical process. Set upper and lower limit constraints, and set a total linkage constraint for the sum of time adjustments of all non-critical processes in each process section.

[0029] Furthermore, the method for solving the progress synchronization model is as follows: the progress synchronization model is transformed into an optimization problem with convex function properties, and an iterative optimization algorithm is used to solve the objective function. In each iteration, the descent direction of the objective function is calculated based on the current solution, and the time adjustment amount of each non-critical process is updated along the descent direction until the difference between the objective function values ​​of two adjacent iterations is less than a preset convergence threshold, at which point the iteration terminates, and the current solution is output as the time adjustment amount of each non-critical process.

[0030] Another object of the present invention is to provide a process route scheduling schedule synchronization system based on critical process anchoring, for implementing the above-mentioned process route scheduling schedule synchronization method based on critical process anchoring, including:

[0031] The data acquisition and identification module is used to acquire the process route data of the target product and identify key process anchor points to obtain anchoring base data.

[0032] The function construction module is used to construct the schedule impact function of each key process anchor process and the inter-process segment impact function between adjacent process segments based on the deviation between the planned and actual execution progress of each key process anchor process. The schedule impact function is used to quantitatively describe the cumulative impact of a single process schedule deviation on non-key processes within its process segment. The inter-process segment impact function is used to quantitatively describe the mutual transmission impact of schedule deviations between adjacent process segments.

[0033] The model building module is used to establish a schedule synchronization model of the process route with the schedule impact function and the process segment impact function as optimization objectives. The schedule synchronization model takes minimizing the sum of the schedule impact of all key process anchor points and the sum of the process segment impact of all adjacent process segments as the objective function, and the time adjustment amount of non-key processes within each process segment as the decision variable.

[0034] The model solving module is used to solve the progress synchronization model to obtain the time adjustment amount of non-critical processes in each process section.

[0035] The synchronization update module is used to update the scheduling plan of non-critical processes according to the time adjustment amount, so that the progress of non-critical processes in each process section is synchronized with the progress of the corresponding critical process anchor point processes.

[0036] Furthermore, the data acquisition and recognition module specifically includes:

[0037] The indicator calculation unit is used to calculate the comprehensive criticality index of each process; the comprehensive criticality index is obtained by weighted summation of the processing time weight, resource exclusivity weight and topological position weight before and after the process.

[0038] The critical process determination unit is used to mark processes whose comprehensive criticality index exceeds a preset threshold as candidate critical processes, and select non-adjacent processes from the candidate critical processes according to the process route sequence as critical process anchor point processes.

[0039] The segmentation unit is used to divide the process route into several process segments based on each key process anchor point process, so as to obtain anchoring base data;

[0040] The model building module specifically includes:

[0041] The variable determination unit is used to determine the decision variables based on the time adjustment amount of non-critical processes within each process section.

[0042] The objective function determination unit is used to construct a schedule synchronization model with the objective function of minimizing the sum of the schedule impact of all key process anchor point operations and the sum of the inter-segment impact of all adjacent segments.

[0043] The present invention provides a process route scheduling synchronization method based on key process anchoring, which quantitatively models the cumulative impact of schedule deviations, ensuring that the progress of non-critical processes within each process segment is synchronized with the progress of key process anchor points. This effectively suppresses the gradual amplification and chain transmission of schedule deviations along the process route, and is suitable for dynamic scheduling adjustments in multi-variety, small-batch discrete manufacturing scenarios. Specifically, the present invention identifies key process anchor points and constructs a schedule influence function to nonlinearly and quantitatively characterize the cumulative impact of single-process schedule deviations, accurately reflecting actual production patterns and avoiding the problems of over-adjustment of small deviations or underestimation of large deviations in traditional linear methods. In addition, the present invention incorporates the deviation differences between adjacent segments into the optimization objective by constructing an influence function between process segments, effectively suppressing the chain transmission effect of local deviations amplifying along the process route and improving the robustness of the overall scheduling. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the process route scheduling and progress synchronization method based on key process anchoring provided in an embodiment of the present invention.

[0045] Figure 2 This is a flowchart illustrating step S100 in the process route scheduling and progress synchronization method based on key process anchoring provided in an embodiment of the present invention.

[0046] Figure 3 A flowchart illustrating the method for constructing a progress synchronization model provided in an embodiment of the present invention.

[0047] Figure 4 This is a schematic diagram of the process route scheduling and progress synchronization system based on key process anchoring provided in an embodiment of the present invention.

[0048] Figure 5 This is a schematic diagram of the data acquisition and recognition module provided in an embodiment of the present invention.

[0049] Figure 6 This is a schematic diagram of the model building module structure provided in an embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0051] like Figure 1 As shown, in one embodiment of the present invention, a method for synchronizing process route scheduling based on key process anchoring is provided, comprising the following steps:

[0052] S100. Obtain the process route data of the target product and identify key process anchor points to obtain anchoring base data.

[0053] S200. Based on the deviation between the planned and actual execution progress of each key process anchor point, construct the progress influence function of each key process anchor point and the inter-process segment influence function between adjacent process segments; the progress influence function is used to quantitatively describe the cumulative impact of single-process progress deviation on non-key processes within its process segment; the inter-process segment influence function is used to quantitatively describe the mutual transmission influence of progress deviations between adjacent process segments.

[0054] S300. Using the aforementioned schedule impact function and the inter-process segment impact function as optimization objectives, a schedule synchronization model for the process route is established. The schedule synchronization model takes minimizing the sum of the schedule impact of all critical process anchor point operations and the sum of the inter-process segment impact of all adjacent process segments as its objective function, and uses the time adjustment amount of non-critical operations within each process segment as the decision variable.

[0055] S400. Solve the progress synchronization model to obtain the time adjustment amount of non-critical processes in each process section;

[0056] S500. Update the scheduling plan of non-critical processes according to the time adjustment amount, so that the progress of non-critical processes in each process section is synchronized with the progress of the corresponding critical process anchor point processes.

[0057] In practical applications, the controller reads the complete process route data of the target product from the Manufacturing Execution System (MES) database. The process route data includes information on all processes that make up the route and the sequential constraints between them. For example, the process route may contain 25 processes, denoted as OP-01 to OP-25. Each process includes: process number, process name, processing equipment, planned time, and dependencies between preceding and subsequent processes. Specifically, the sequential constraints between processes are as follows: OP-02 can only begin after OP-01 is completed, OP-03 can only begin after OP-02 is completed, and so on, forming a complete sequential constraint network. The controller can identify several key processes as anchor processes from the 25 processes according to preset key process anchor point identification rules. For example, in this embodiment, four key process anchor processes are identified: OP-05, OP-10, OP-16, and OP-22. After identification, the controller outputs these four anchor processes and their position information in the process route as anchoring base data for subsequent steps.

[0058] like Figure 2 As shown, in a preferred embodiment of the present invention, the step of obtaining the process route data of the target product and identifying key process anchor points to obtain anchored basic data, namely step S100, specifically includes:

[0059] S110. Calculate the comprehensive criticality index for each process; the comprehensive criticality index is obtained by weighted summation of the processing time weight, resource exclusivity weight, and topological position weight before and after the process.

[0060] Specifically, the method for determining the weight of processing time is as follows: The planned time for each process step is read from the process route data. Find the maximum planned working hours for all processes. and minimum value For the j-th process, calculate its processing time weight using the following formula. :

[0061] ;

[0062] The method for determining resource exclusivity weights is as follows: Identify the resources used in each process, such as equipment, tooling, fixtures, and operators; for resource r used in the j-th process, its scarcity is defined as the reciprocal of the number of resources available in the workshop (i.e., the number of usable resources); for resource r, its competitiveness is defined as the proportion of processes using that resource to the total number of processes; define the resource exclusivity index as the product of scarcity and competitiveness, reflecting the scarcity and competitiveness of the resource; for the j-th process, determine the maximum value of each resource exclusivity index (the maximum value is taken because a process is usually constrained by its scarcest resource); perform minimum-maximum normalization on the maximum values ​​of the resource exclusivity indices of all processes, mapping them to the 0-1 interval to obtain the resource exclusivity weights. .

[0063] The topological position weights before and after a process are used to measure the importance of a process position in the process route network structure. Processes located at the center of the process route and with a large number of preceding and following processes have a wider impact on schedule deviations and therefore higher weights. In this embodiment, the method for determining the topological position weights before and after a process is as follows: Construct a directed graph model of the process route; treat each process as a node in the graph, and treat the sequential constraints between processes as directed edges (from the preceding process to the following process); calculate the number of preceding and following nodes for each process; the number of preceding nodes refers to the number of all processes that must be completed directly or indirectly before the j-th process; the number of following nodes refers to the number of processes that must be started directly or indirectly after the j-th process; define the topological position index as the product of the number of preceding and following nodes. The larger the product, the stronger the mediating role of the process in the process network, indicating that a large number of preceding processes depend on it (wide upstream influence) and a large number of following processes are affected by it (wide downstream impact); perform min-max normalization on the topological position indices of all processes, mapping them to the 0-1 interval, to obtain the topological position weights before and after the process. ;

[0064] Then, the comprehensive keyness index The calculation formula is as follows:

[0065] ;

[0066] In the formula, , , The preset weighting coefficients, with the sum of the three being 1, can be determined using an expert-based assignment method, such as... , , However, it is not limited to this.

[0067] S120. Mark the process with the comprehensive criticality index exceeding the preset threshold as a candidate critical process, and select non-adjacent processes from the candidate critical processes according to the process route sequence as critical process anchor point processes.

[0068] In practical applications, the threshold can be set to 0.7, but is not limited to this; any process with a comprehensive criticality index exceeding 0.7 is marked as a candidate critical process; from the candidate critical processes, processes that are not adjacent to each other are selected as the final critical process anchor processes in the order of the process route from front to back; it should be noted that non-adjacent means that there is at least one non-critical process between any two critical process anchor processes.

[0069] S130. Based on each key process anchor point, the process route is divided into several process sections to obtain anchoring foundation data;

[0070] Specifically, the method for dividing process sections is as follows: each critical process anchor point is used as the anchor point of the process section, and all non-critical processes between two adjacent critical process anchor point processes are divided into the same process section. The first and last process sections are respectively bounded by the first critical process anchor point process and the last critical process anchor point process.

[0071] In practical applications, taking the four key process anchor points OP-05, OP-10, OP-16, and OP-22 as examples, the 25 processes are divided into four process segments, as detailed below:

[0072] The first process section: with OP-05 as the anchor point, the starting boundary of the process route OP-01 as the starting boundary, and OP-05 as the ending boundary, it includes 5 processes: OP-01, OP-02, OP-03, OP-04, and OP-05. Among them, the non-critical processes are OP-01, OP-02, OP-03, and OP-04, which are 4 non-critical processes.

[0073] The second process section: with OP-10 as the anchor point, OP-06 as the first process after OP-05 as the starting boundary, and OP-10 as the ending boundary, it includes 5 processes: OP-06, OP-07, OP-08, OP-09, and OP-10. Among them, the non-critical processes are OP-06, OP-07, OP-08, and OP-09, which are a total of 4 non-critical processes.

[0074] The third process section: with OP-16 as the anchor point, OP-11 as the first process after OP-10 as the starting boundary, and OP-16 as the ending boundary, it includes 6 processes: OP-11, OP-12, OP-13, OP-14, OP-15, and OP-16. Among them, the non-critical processes are OP-11, OP-12, OP-13, OP-14, and OP-15, totaling 5 non-critical processes.

[0075] The fourth process section: with OP-22 as the anchor point, OP-17 as the first process after OP-16 as the starting boundary, and OP-25 as the ending boundary of the process route, it includes 9 processes: OP-17, OP-18, OP-19, OP-20, OP-21, OP-22, OP-23, OP-24, and OP-25. Among them, the non-critical processes are OP-17, OP-18, OP-19, OP-20, OP-21, OP-23, OP-24, and OP-25, totaling 8 non-critical processes.

[0076] The division results of the above four process sections are stored and output as part of the anchoring base data.

[0077] In this embodiment of the invention, by introducing a comprehensive criticality index mechanism with three dimensions of processing time, resource exclusivity, and topological location, the critical processes that have the greatest impact on the overall scheduling can be objectively and quantitatively selected from many processes as anchor points, avoiding the arbitrariness and inaccuracy of subjective judgment based on human experience.

[0078] In a preferred embodiment of the present invention, the method for constructing the schedule impact function is as follows: obtaining the schedule deviation value of the i-th critical process anchor point. Construct the schedule impact function of the i-th critical process anchor point according to the following formula. :

[0079] ;

[0080] in, The influence coefficient is positively correlated with the number of non-critical processes in the process section where the i-th critical process anchor point process is located and the planned working hours of that process. The influence coefficient has a non-linear variation characteristic: when the absolute value of the schedule deviation exceeds the preset linear zone threshold, the influence coefficient increases non-linearly with the increase of the schedule deviation value.

[0081] Specifically, the schedule deviation value is calculated based on the differences between the planned and actual working hours of the corresponding process and the planned and actual end times. In practical applications, the planned working hours of each key process anchor point process i are first read from the manufacturing execution system. Actual working hours Planned end time Compared with the actual end time It should be noted that for processes that have not yet started or been completed, the forward-looking forecast values ​​of the manufacturing execution system are used as the basis; the weights are determined based on an empirical assignment method. and ,like , The formula for calculating the schedule deviation is as follows:

[0082] .

[0083] In addition, the influence coefficient This coefficient is used to quantitatively characterize the impact of a unit schedule deviation of the i-th critical process anchor point on all non-critical processes within its process segment. A larger coefficient indicates a greater schedule impact for the same deviation magnitude, meaning it is more sensitive to deviations in that process. Specifically, the influence coefficient... The calculation formula is as follows:

[0084] ;

[0085] ;

[0086] in, The baseline influence coefficient; This is a global impact adjustment factor, typically ranging from 0.2 to 0.8. It can be determined by fitting historical data or by assigning a value based on expert experience. In this embodiment, the value is 0.6, which is used to scale the magnitude of the overall impact coefficient. The number of non-critical processes within the process section where the i-th critical process anchor point process is located; The arithmetic mean of the planned man-hours for all key process anchor points; The deviation linear zone threshold for the i-th critical process anchor point is usually set to 10%-20% (e.g., 15%) of the planned man-hours for that process. This is the nonlinear gain coefficient, which is usually set to 0.5-2, and in this embodiment, it is set to 1.

[0087] In this embodiment of the invention, by constructing a schedule influence function and an inter-process segment influence function, the originally abstract schedule deviation is transformed into a quantifiable and calculable influence value, providing accurate mathematical input for the establishment of a subsequent synchronous optimization model. At the same time, the introduction of the inter-process segment influence function ensures that the deviation difference between adjacent segments can also be quantified and optimized, avoiding neglecting one aspect for another. In this invention, the progress impact function is constructed using a quadratic function similar to the principle of elastic potential energy calculation. This ensures that the impact of progress deviations on non-critical processes within a process segment increases quadratically with the magnitude of the deviation, accurately depicting the actual production pattern of "limited impact from small deviations and severe impact from large deviations." Secondly, the impact coefficient is positively correlated with the number of non-critical processes and planned working hours within the process segment. The more processes and the longer the working hours within the segment, the larger the range of influence of the deviation and the higher the impact coefficient, thus achieving differentiated measurement of impact. Furthermore, by using a piecewise calculation method on both sides of the linear region threshold, the impact coefficient remains constant with small deviations and increases non-linearly with the increase of deviations with large deviations. This avoids over-adjustment caused by small deviations and ensures that large deviations receive sufficient intervention priority.

[0088] In a preferred embodiment of the present invention, the method for constructing the inter-process segment influence function is as follows: The inter-segment influence function between the i-th process segment and the (i+1)-th process segment is constructed according to the following formula. :

[0089] ;

[0090] in, and These are the schedule deviation values ​​for the i-th and (i+1)-th critical process anchor points, respectively; This is the coupling influence coefficient; the coupling influence coefficient is determined based on the process connection strength between two adjacent key process anchor points.

[0091] Specifically, the method for determining the coupling influence coefficient is as follows:

[0092] First, determine the global coupling scaling factor. The same value is taken for all adjacent process sections, and its determination method is the same as... Similarly, a calibration method or an empirical setting method can be used; for example, in this embodiment, the value is set to 0.4.

[0093] Next, we count the number of direct processes between the i-th critical process anchor process and the (i+1)-th critical process anchor process (i.e., the number of non-critical processes between them). The more direct processes there are, the stronger the dependency between upstream and downstream processes. By performing min-max normalization on the number of direct processes and mapping it to the 0-1 interval, we can obtain the direct process connectivity index. ;

[0094] Assess the dependence of the output of the i-th critical process anchor step on the input of the (i+1)-th critical process anchor step: If the (i+1)-th anchor step must completely depend on the output of the i-th anchor step to start, then define a material dependence strength index. The value is 1; if there is only partial dependence or substitutable supply, then the material dependence strength index is defined. The value is 0.2-0.8 (e.g., 0.5); if there is no dependence at all, then the material dependence strength index is defined. The value is 0; in this embodiment, the degree of dependence can be determined based on the actual bill of materials and process requirements, and the corresponding material dependence strength index is 0. This can be determined by looking up a table;

[0095] Assess whether two process sections use the same bottleneck resources: If two critical process anchor points use the same critical equipment, resource competition exists, and schedule deviations will be further propagated through resource contention; define a resource competition index. This is the ratio of the number of identical resources used in the two processes to the average total number of resources; where the average total number of resources is equal to half the sum of the total number of resources used in the i-th critical process anchor process and the total number of resources used in the (i+1)-th critical process anchor process.

[0096] Then, based on the direct process connection index Material Dependence Strength Index Resource competition index Determine the process connection strength The calculation formula is as follows:

[0097] ;

[0098] in, , , These are preset weighting coefficients, the sum of which is 1. These can be set according to the priorities of time-based workshop management; for example, in this embodiment, we take... , , 2.

[0099] Finally, the global coupling scaling factor Connection strength with process Multiplying them together yields the coupling influence coefficient.

[0100] like Figure 3 As shown, in a preferred embodiment of the present invention, the method for constructing the progress synchronization model is as follows:

[0101] S310. Use the time adjustment amount of non-critical processes in each process section as the decision variable;

[0102] S320. A schedule synchronization model is constructed with the objective function of minimizing the sum of the schedule impact of all key process anchor points and the sum of the inter-segment impact of all adjacent sections.

[0103] The objective function is expressed as:

[0104] ;

[0105] in, Let be the decision variable, representing the time adjustment amount for the j-th non-critical process; M is the total number of critical process anchor points; A i Let be the set of non-critical processes within the process segment containing the i-th critical process anchor point; and let be the time adjustment amount for each non-critical process. Set upper and lower limit constraints, and set a total linkage constraint for the sum of time adjustments of all non-critical processes in each process section.

[0106] Specifically, the upper limit U j The upward adjustment limit (i.e., shifting backward) is related to the available buffer time for non-critical processes: For example, for OP-03, its planned start time is 08:30, and the planned start time of the subsequent process OP-04 is 08:50, with a 20-minute buffer between them. Therefore, the upper limit for upward adjustment is set to U3 = 20 minutes. The lower limit Lj (downward adjustment, i.e., advancing forward) is limited by the completion time of the preceding process: For example, the planned completion time of the preceding process OP-02 is 08:25, and the planned start time of OP-03 is 08:30, with only a 5-minute advance margin. Therefore, the lower limit for downward adjustment is set to L3 = -5 minutes. Upper and lower limit constraints are set according to this rule for each non-critical process as one of the constraints of the model.

[0107] In addition, a total time adjustment constraint is set for the sum of all non-critical processes in each process segment. That is, the sum of time adjustments must be less than or equal to the allowable total adjustment threshold (determined according to the actual situation, such as 40 minutes). This serves as another constraint on the model to prevent the adjustments in the segment from canceling each other out or excessively accumulating, which could lead to the overall schedule going out of control.

[0108] In a preferred embodiment of the present invention, the method for solving the progress synchronization model is as follows: the progress synchronization model is transformed into an optimization problem with convex function properties, and an iterative optimization algorithm is used to solve the objective function. In each iteration, the descent direction of the objective function is calculated based on the current solution, and the time adjustment amount of each non-critical process is updated along the descent direction until the difference between the objective function values ​​of two adjacent iterations is less than a preset convergence threshold, at which point the iteration is terminated, and the current solution is output as the time adjustment amount of each non-critical process.

[0109] Specifically, the solution steps of the iterative optimization algorithm are as follows:

[0110] Initialization Phase: All decision variables are initialized to 0, meaning the initial solution is to not adjust any non-critical processes. At this point, the initial value of the objective function is the sum of the original schedule impact of all critical process anchor processes and the sum of the original inter-process impact of all adjacent process sections.

[0111] Iterative update phase: In the t-th iteration, the controller calculates the current solution x. (t) The partial derivatives of the objective function with respect to each decision variable are used to form a gradient vector; the negative direction of the gradient vector is the direction in which the objective function decreases the fastest; the values ​​of each decision variable are updated along this descent direction; after each update, it is checked whether the updated solution satisfies the upper and lower limit constraints and the total linkage constraints set above. If it does not satisfy them, the part exceeding the constraints is truncated to the constraint boundary value.

[0112] Convergence determination phase: After each iteration, the difference between the objective function values ​​of two adjacent iterations is calculated. When the difference is less than the preset convergence threshold or the preset number of iterations is reached, the iteration is terminated.

[0113] In step S500, the original scheduled time for each non-critical process is added to the corresponding time adjustment amount to obtain the updated scheduled time.

[0114] like Figure 4 As shown, in another embodiment of the present invention, a process route scheduling progress synchronization system based on critical process anchoring is provided to implement the above-mentioned process route scheduling progress synchronization method based on critical process anchoring, including:

[0115] The data acquisition and identification module 10 is used to acquire the process route data of the target product and identify key process anchor points to obtain anchoring base data.

[0116] The function construction module 20 is used to construct the progress influence function of each key process anchor process and the inter-process segment influence function between adjacent process segments based on the deviation between the planned and actual execution progress of each key process anchor process. The progress influence function is used to quantitatively describe the cumulative impact of the progress deviation of a single process on the non-key processes within its process segment. The inter-process segment influence function is used to quantitatively describe the mutual transmission influence of progress deviations between adjacent process segments.

[0117] The model building module 30 is used to establish a progress synchronization model of the process route with the progress influence function and the process segment influence function as optimization objectives. The progress synchronization model takes minimizing the sum of the progress influence of all key process anchor point operations and the sum of the process segment influence of all adjacent process segments as the objective function, and takes the time adjustment amount of non-key operations in each process segment as the decision variable.

[0118] The model solving module 40 is used to solve the progress synchronization model to obtain the time adjustment amount of non-critical processes in each process section.

[0119] The synchronization update module 50 is used to update the scheduling plan of non-critical processes according to the time adjustment amount, so that the progress of non-critical processes in each process section is synchronized with the progress of the corresponding critical process anchor point process.

[0120] like Figure 5 As shown, in a preferred embodiment of the present invention, the data acquisition and identification module 10 specifically includes:

[0121] The index calculation unit 11 is used to calculate the comprehensive criticality index of each process; the comprehensive criticality index is obtained by weighted summation of the processing time weight, resource exclusivity weight and topological position weight before and after the process.

[0122] The key process determination unit 12 is used to mark processes whose comprehensive criticality index exceeds a preset threshold as candidate key processes, and select non-adjacent processes from the candidate key processes according to the process route sequence as key process anchor point processes.

[0123] The segment division unit 13 is used to divide the process route into several process segments based on each key process anchor point process to obtain anchoring base data.

[0124] like Figure 6 As shown, in a preferred embodiment of the present invention, the model building module 30 specifically includes:

[0125] Variable determination unit 31 is used to determine the time adjustment amount of non-critical processes in each process section as the decision variable;

[0126] Objective function determination unit 32 is used to construct a schedule synchronization model with the objective function of minimizing the sum of the schedule impact of all critical process anchor point operations and the sum of the inter-segment impact of all adjacent segments.

[0127] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0128] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods.

[0129] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for synchronizing the progress of process route scheduling based on key process anchoring, characterized in that, Includes the following steps: Obtain the process route data of the target product and identify key process anchor points to obtain anchoring base data; Based on the deviation between the planned and actual execution progress of each key process anchor point, a progress influence function for each key process anchor point and an inter-process segment influence function are constructed. The progress influence function is used to quantitatively describe the cumulative impact of a single process progress deviation on non-key processes within its process segment. The inter-process segment influence function is used to quantitatively describe the mutual transmission of progress deviations between adjacent process segments. Using the aforementioned schedule impact function and inter-process segment impact function as optimization objectives, a schedule synchronization model for the process route is established. The schedule synchronization model takes minimizing the sum of the schedule impact of all critical process anchor point operations and the sum of the inter-process segment impact of all adjacent process segments as its objective function, and uses the time adjustment amount of non-critical operations within each process segment as the decision variable. Solve the aforementioned schedule synchronization model to obtain the time adjustment amount for non-critical processes within each process section; The scheduling plan for non-critical processes is updated based on the time adjustment amount, so that the progress of non-critical processes in each process section is synchronized with the progress of the corresponding critical process anchor point processes.

2. The method for synchronizing process route scheduling based on key process anchoring according to claim 1, characterized in that, The process route data includes information on all the processes that make up the process route and the sequential constraints between each process. The steps to obtain the process route data for the target product and identify key process anchor points to obtain anchored basic data include: Calculate the comprehensive criticality index for each process step; the comprehensive criticality index is obtained by weighted summation of the processing time weight, resource exclusivity weight, and topological position weight before and after the process step; Processes whose comprehensive criticality index exceeds a preset threshold are marked as candidate critical processes, and non-adjacent processes are selected from the candidate critical processes according to the process route sequence as critical process anchor points. Based on each key process anchor point, the process route is divided into several process sections to obtain anchoring foundation data.

3. The method for synchronizing process route scheduling based on key process anchoring according to claim 2, characterized in that, The specific method for dividing the process sections is as follows: each critical process anchor point is used as the anchor point of the process section, and all non-critical processes between two adjacent critical process anchor point processes are divided into the same process section. The first and last process sections are respectively bounded by the first critical process anchor point process and the last critical process anchor point process.

4. The method for synchronizing process route scheduling based on key process anchoring according to claim 1, characterized in that, The method for constructing the schedule impact function is as follows: obtain the schedule deviation value of the i-th critical process anchor point. Construct the schedule impact function of the i-th critical process anchor point according to the following formula. : ； in, The influence coefficient is positively correlated with the number of non-critical processes in the process section where the i-th critical process anchor point process is located and the planned working hours of that process. The influence coefficient has a non-linear variation characteristic: when the absolute value of the schedule deviation exceeds the preset linear zone threshold, the influence coefficient increases non-linearly with the increase of the schedule deviation value.

5. The method for synchronizing process route scheduling based on key process anchoring according to claim 4, characterized in that, The schedule deviation value is calculated based on the difference between the planned and actual working hours and the planned and actual end times of the corresponding process.

6. The method for synchronizing process route scheduling based on key process anchoring according to claim 4, characterized in that, The method for constructing the inter-segment influence function is as follows: The inter-segment influence function between the i-th process segment and the (i+1)-th process segment is constructed according to the following formula. : ； in, and These are the schedule deviation values ​​for the i-th and (i+1)-th critical process anchor points, respectively; The coupling influence coefficient is determined based on the process connection strength between two adjacent key process anchor points.

7. The method for synchronizing process route scheduling based on key process anchoring according to claim 6, characterized in that, The method for constructing the progress synchronization model is as follows: The time adjustment amount of non-critical processes within each process section is used as the decision variable; A schedule synchronization model is constructed with the objective function of minimizing the sum of the schedule impact of all key process anchor points and the sum of the inter-segment impact of all adjacent sections. The objective function is expressed as: ； in, Let be the decision variable, representing the time adjustment amount for the j-th non-critical process; M is the total number of critical process anchor points; A i Let be the set of non-critical processes within the process segment containing the i-th critical process anchor point; and let be the time adjustment amount for each non-critical process. Set upper and lower limit constraints, and set a total linkage constraint for the sum of time adjustments of all non-critical processes in each process section.

8. The method for synchronizing process route scheduling based on key process anchoring according to claim 7, characterized in that, The method for solving the progress synchronization model is as follows: the progress synchronization model is transformed into an optimization problem with convex function properties, and an iterative optimization algorithm is used to solve the objective function. In each iteration, the descent direction of the objective function is calculated based on the current solution, and the time adjustment amount of each non-critical process is updated along the descent direction until the difference between the objective function values ​​of two adjacent iterations is less than a preset convergence threshold, at which point the iteration terminates, and the current solution is output as the time adjustment amount of each non-critical process.

9. A process route scheduling and progress synchronization system based on critical process anchoring, used to implement the process route scheduling and progress synchronization method based on critical process anchoring as described in any one of claims 1-8, characterized in that, include: The data acquisition and identification module is used to acquire the process route data of the target product and identify key process anchor points to obtain anchoring base data. The function construction module is used to construct the schedule impact function of each key process anchor process and the inter-process segment impact function between adjacent process segments based on the deviation between the planned and actual execution progress of each key process anchor process. The schedule impact function is used to quantitatively describe the cumulative impact of a single process schedule deviation on non-key processes within its process segment. The inter-process segment impact function is used to quantitatively describe the mutual transmission impact of schedule deviations between adjacent process segments. The model building module is used to establish a schedule synchronization model of the process route with the schedule impact function and the process segment impact function as optimization objectives. The schedule synchronization model takes minimizing the sum of the schedule impact of all key process anchor points and the sum of the process segment impact of all adjacent process segments as the objective function, and the time adjustment amount of non-key processes within each process segment as the decision variable. The model solving module is used to solve the progress synchronization model to obtain the time adjustment amount of non-critical processes in each process section. The synchronization update module is used to update the scheduling plan of non-critical processes according to the time adjustment amount, so that the progress of non-critical processes in each process section is synchronized with the progress of the corresponding critical process anchor point processes.

10. The method for synchronizing process route scheduling based on key process anchoring according to claim 9, characterized in that, The data acquisition and recognition module specifically includes: The indicator calculation unit is used to calculate the comprehensive criticality index of each process; the comprehensive criticality index is obtained by weighted summation of the processing time weight, resource exclusivity weight and topological position weight before and after the process. The critical process determination unit is used to mark processes whose comprehensive criticality index exceeds a preset threshold as candidate critical processes, and select non-adjacent processes from the candidate critical processes according to the process route sequence as critical process anchor point processes. The segmentation unit is used to divide the process route into several process segments based on each key process anchor point process, so as to obtain anchoring base data; The model building module specifically includes: The variable determination unit is used to determine the decision variables based on the time adjustment amount of non-critical processes within each process section. The objective function determination unit is used to construct a schedule synchronization model with the objective function of minimizing the sum of the schedule impact of all key process anchor point operations and the sum of the inter-segment impact of all adjacent segments.

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