A machining production planning management method and system

Abstract

The present application relates to the technical field of machining production management, in particular to a machining production plan management method and system, comprising the following steps: extracting time sequence limits to establish a part flow path diagram, matching available slots and idle spindles to generate machine mapping assignment spectrum, performing postponement and replacement scheduling for tool occupancy exceeding quota items to obtain reconstruction sequence, generating clamping turnover distribution list according to tray idle identification, and judging limit out-of-bound conditions to transmit start-up level to trigger chain. In the present application, equipment assignment is implemented based on path constraints and machine tool resource distribution, which twists the production capacity mismatch caused by subjective experience scheduling, deeply checks tool occupancy capacity and pre-selects out-of-limit processes, implements postponement and replacement scheduling action to recast production sequence, avoids material flow lag and equipment change downtime hazards, compares scheduling operation time limit to strip out-of-bound dispatching nodes, and directly issues non-conflict instructions to the bottom layer to ensure close flow in the workshop.

Description

Technical Field

[0001] This invention relates to the field of machining production management technology, and in particular to a machining production planning management method and system. Background Technology

[0002] The field of machining production management technology mainly involves the overall planning and control of various elements and processes in the machining and manufacturing process. Its core matters cover order demand processing, capacity planning of machine tools such as lathes and milling machines, raw material supply chain coordination, and personnel scheduling. By systematically controlling the manufacturing physical resources and processing procedures in the workshop, it ensures that the cutting and processing activities of various parts and finished products can be carried out in an orderly manner. Traditional machining production planning management methods refer to the scheduling of daily machining tasks and process operations in the manufacturing workshop. The planning personnel estimate the time required for each process, such as roughing, finishing, and drilling, based on the delivery dates and purchase quantities in the company's internal spreadsheets and their experience. They then compare these with the detailed machine tool list and employee schedule recorded in the paper ledgers. They manually fill out forms or write simple formulas to specify the types of machine tools to be processed and the amount of raw materials to be used each day. At the same time, the workshop scheduler conducts regular inspections on the production site to record the operating status and number of completed parts for each machine tool. When machine tools are damaged or the machine is stopped due to lack of materials, the on-site personnel notify the management personnel through walkie-talkies or by submitting paper abnormality reports. The subsequent processing sequence and material transfer orders are then manually changed in the spreadsheets.

[0003] Traditional machining workshops rely on manual experience to estimate the time required for process flow and manually assign machine tasks according to paper ledgers. This subjective scheduling is prone to conflicts such as equipment idleness and stacking of processing tasks. The production process relies solely on personnel to conduct regular inspections to obtain the operating status of machine tools. The delayed information feedback makes it difficult to respond quickly to tool breakage and machine downtime due to material shortages. In the event of sudden abnormalities, manual intervention and manual rescheduling of subsequent work orders are still required, which greatly exacerbates the sluggishness of abnormal handling on the manufacturing site, seriously disrupts the continuity of the overall production plan execution, and leads to a long-term imbalance in the workshop's capacity allocation. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a machining production planning management method, comprising the following steps: S1: Collect order delivery dates and blank process dwell positions, extract the flow sequence boundaries between adjacent blank process dwell positions, arrange them in sequence, and establish a part flow path diagram; S2: Obtain the available slots of the CNC milling machine in the workshop and the idle spindle codes of the turning center, match the stop position of each blank process in the workpiece flow path diagram with the corresponding available slots and idle spindle codes, and obtain the machine tool mapping assignment spectrum. S3: Extract the machine tool magazine slot quota and cutting tool occupancy items, compare the size of the cutting tool occupancy items built into the machine tool mapping assignment spectrum with the machine tool magazine slot quota, filter the blank process dwell positions corresponding to the cutting tool occupancy items that exceed the machine tool magazine slot quota, perform the sequential arrangement action for the blank process dwell positions, and fill the vacant positions with alternative processing positions to obtain the parallel scheduling reconstruction sequence; S4: Collect the idle indicators of the pallets at the changing workstation, assign corresponding idle indicators to adjacent alternative processing positions within the parallel scheduling reconstruction sequence, remove alternative processing positions with unmatched idle indicators, and generate a clamping turnover distribution column. S5: Extract the workshop shift operation deadline boundary, determine the boundary status of each dispatch node built into the clamping turnover distribution column, transmit the corresponding start level of the node after removing the boundary item to the production line main control console, and obtain the dispatch execution trigger chain.

[0005] As a further embodiment of the present invention, the part flow path diagram includes a transfer vector, a transport directed edge, and a topology; the machine mapping assignment spectrum includes an allocation matrix, a binding index, and a scheduling block; the parallel scheduling reconstruction sequence includes an adjustment time window, a substitute processing array, and a heavy-load work order chain; the clamping and turnover distribution column includes a transfer batch, a mounting queue, and a cache stack; and the work dispatch execution trigger chain includes an activation pulse, a start / stop control word, and a work instruction set.

[0006] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Collect order delivery date nodes and blank process dwell positions, extract the timestamp reference value at the delivery date node, record the trigger time of the blank process dwell position, calculate the time difference data item between the reference value and the trigger time, filter the dwell position information corresponding to the positive value at the time difference data item and compile it into the data vector group, extract the boundary values ​​of the node values ​​at both ends of the data vector group, and establish the process flow time sequence interval. S102: Call the process flow time interval, read the time tag quantity within the interval, perform position swapping operation on the blank process dwell position according to the time tag quantity and ascending order criterion, extract the sequence feature after the swapping operation, project the blank process dwell position onto the two-dimensional plane according to the sequence feature, connect adjacent blank process dwell position nodes in the two-dimensional plane with directed line segments, and obtain the part flow path diagram.

[0007] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Obtain the available slots of the CNC milling machine in the workshop and the idle spindle codes of the turning center. Extract the available slot numbers and spindle code characters. Concatenate the numbers and characters into a device resource vector. Calculate the node load values ​​in the device resource vector. Compare the load values ​​with the device load threshold. Remove nodes whose load values ​​exceed the device load threshold to obtain the set of idle machine resources. S202: Call the machine idle resource set and the part flow path diagram, extract the coordinates of the blank process stop position in the part flow path diagram, calculate the position difference between the stop position coordinates and the node coordinates of the machine idle resource set, retrieve the node item where the position difference is equal to the minimum value, perform corresponding association between the stop position and the node item at the minimum value and write it into the binary matrix to obtain the machine mapping assignment spectrum.

[0008] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Collect the machine tool magazine slot quota and cutting tool occupancy item, call the machine mapping assignment spectrum, extract the built-in cutting tool occupancy item value, calculate the difference between the occupancy item value and the machine tool magazine slot quota, compare the difference with the quota limit benchmark value, record the slot coordinates where the difference exceeds the quota limit benchmark value, add the slot coordinates to the tensor, and obtain the slot over-limit index cluster; S302: Based on the slot over-limit index cluster, extract the built-in slot coordinates, call the stop position coordinates in the part flow path diagram, calculate the distance difference between the slot coordinates and the stop position coordinates, compare the distance difference with the position reference value, remove the stop items where the distance difference exceeds the position reference value, extract the remaining stop position nodes, and perform the head-tail connection and arrangement action on the stop position nodes to obtain the over-limit stop queue. S303: For the over-limit stay queue, extract the timestamp of the node in the queue, add a delay constant after the timestamp, rearrange the second position of the node according to the delay constant and perform the ranking extension action, locate the coordinate empty item derived from the ranking extension action, collect the available slot configuration next to the empty item and combine it into the alternative processing position feature, fill the coordinate empty item with the alternative processing position feature, and establish a parallel scheduling reconstruction sequence.

[0009] As a further aspect of the present invention, the two-dimensional coordinate data of the machine corresponding to the location where the difference is greater than the quota limit benchmark value is used as the slot coordinate. Construct an initial data structure as a tensor, and write the slot coordinates into the empty element positions of the tensor in the order of coordinate acquisition. Combine tensors with written records to form a slot over-limit index cluster.

[0010] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: Collect the idle status indicator of the pallet of the changing workstation, read the built-in status parameter of the idle status indicator, call the parallel scheduling reconstruction sequence, extract the coordinates of the replacement processing position node, calculate the Euclidean distance between the node coordinates and the coordinates of the workstation origin, serialize and reorganize the Euclidean distance according to the ascending order rule, arrange the replacement processing position nodes according to the serialization and reorganization results, and obtain the processing position order set. S402: Extract the sequence nodes in the processing position sequence set, call the idle identifier of the changing workstation pallet, perform a connection mapping action between the idle identifier of the changing workstation pallet and the sequence nodes in the processing position sequence set, extract the mapping action-derived pairing values, compare the pairing values ​​with the set matching benchmark constant, extract the pairing items where the pairing values ​​are equal to the matching benchmark constant, and obtain the pallet association matrix. S403: For the pallet association matrix, read the pairing items, detect the built-in status feature identifier of the pairing items, compare the status feature identifier with the preset empty feature constant, remove the unmatched nodes where the status feature identifier deviates from the preset empty feature constant, collect the position coordinates of the remaining matching nodes, arrange and combine the position coordinates in the order of time evolution, and generate the clamping turnover distribution column.

[0011] As a further aspect of the present invention, the horizontal and vertical coordinate values ​​of the alternative processing station node coordinates are extracted, and the reference horizontal and vertical coordinate values ​​of the workstation origin coordinates are extracted. Calculate the sum of squares of the differences between the horizontal and vertical coordinate values ​​and the corresponding baseline horizontal and vertical coordinate values, and then take the square root to obtain the Euclidean distance. The arrangement of the replacement processing node coordinates is adjusted according to the Euclidean distance values ​​from smallest to largest to complete the serialization and recombination.

[0012] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: Extract the workshop shift operation deadline boundary, call the clamping turnover distribution column, collect the timestamp values ​​of each built-in dispatch node, calculate the time difference parameter between the timestamp value and the operation deadline boundary, compare the time difference parameter with the boundary reference constant, record the dispatch node index where the time difference parameter exceeds the boundary reference constant, encode the node index into a single-dimensional vector, and obtain the boundary dispatch index cluster. S502: Based on the out-of-bounds dispatch index cluster, call the built-in full dispatch nodes of the clamping turnover distribution column, retrieve the mapping correspondence between the dispatch nodes and the built-in index items of the out-of-bounds dispatch index cluster, remove the node items where there is a mapping correspondence, extract the parameters of the remaining dispatch nodes where there is no mapping correspondence, and reorganize and arrange the parameters according to the time evolution order to obtain the compliant dispatch sequence. S503: For the compliant dispatch sequence, collect the level trigger signal of the dispatch node built into the sequence, detect the value of the start flag bit in the level trigger signal, transmit the node information where the start flag bit value is equal to the trigger level to the main control port of the production line, read the confirmation handshake code returned by the port, connect the node information and the confirmation handshake code to form a communication combination, and establish a dispatch execution trigger chain.

[0013] A machining production planning and management system, comprising: The planning module collects order delivery dates and blank process dwell positions, extracts the flow sequence boundaries between adjacent blank process dwell positions, arranges them in sequence, and establishes a part flow path diagram. The resource scheduling module obtains the available slots of CNC milling machines in the workshop and the idle spindle codes of the turning center, matches the stop position of each blank process in the workpiece flow path diagram with the corresponding available slots and idle spindle codes, and obtains the machine tool mapping assignment spectrum. The exception handling module extracts the machine tool magazine slot quota and cutting tool occupancy items, compares the size of the cutting tool occupancy items built into the machine tool mapping assignment spectrum with the machine tool magazine slot quota, filters the blank process dwell positions corresponding to the cutting tool occupancy items that exceed the machine tool magazine slot quota, performs a sequential arrangement action for the blank process dwell positions, and fills the vacant positions with alternative machining positions to obtain the parallel scheduling reconstruction sequence. The turnover distribution module collects the idle indicators of the pallets at the changing workstation, assigns corresponding idle indicators to adjacent alternative processing positions within the parallel scheduling reconstruction sequence, removes alternative processing positions corresponding to unmatched idle indicators of pallets, and generates a clamping turnover distribution column. The progress monitoring module extracts the end-of-shift boundary of the workshop, determines whether the deadline of each dispatch node in the clamping and turnover distribution column exceeds the boundary, transmits the start-up level of the node to be retained after removing the out-of-bounds item to the main control console of the production line, and obtains the dispatch execution trigger chain.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by combining delivery nodes and flow sequence boundaries to construct underlying path constraints, equipment allocation is carried out based on the distribution of idle spindles and available resources of machine tools on site. This completely reverses the capacity mismatch caused by subjective experience-based assignment, deeply analyzes the occupancy of cutting tools and pre-screens over-allocated tasks, and reshapes the processing sequence by automatically executing follow-up and replacement actions. This eliminates the risk of sudden downtime caused by tool over-allocation, filters invalid assignment nodes by linking idle pallet markers at the workstation, avoids the risk of material flow and clamping process interruptions, comprehensively compares shift deadlines to eliminate out-of-bounds tasks, and directly issues conflict-free equipment triggering commands to the underlying main control console, ensuring the compact and continuous operation of the workshop cutting manufacturing process. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] Please see Figure 1 This invention provides a machining production planning management method, comprising the following steps: S1: Collect order delivery nodes and blank process dwell positions, extract the flow sequence boundaries between adjacent blank process dwell positions, arrange them in sequence according to the flow sequence boundaries, and establish a part flow path diagram. S2: Based on the part flow path diagram, obtain the available slots of the CNC milling machine in the workshop and the idle spindle codes of the turning center, match the stop position of each blank process in the part flow path diagram with the corresponding available slots and idle spindle codes, and obtain the machine tool mapping assignment spectrum. S3: For the machine tool mapping assignment spectrum, extract the machine tool magazine slot quota and cutting tool occupancy items, compare the size of the cutting tool occupancy items built into the machine tool mapping assignment spectrum with the machine tool magazine slot quota, filter the blank process dwell positions corresponding to the cutting tool occupancy items that exceed the machine tool magazine slot quota, perform the sequential arrangement action for the blank process dwell positions, and fill the vacant positions with alternative machining positions to obtain the parallel scheduling reconstruction sequence; S4: Collect the idle status of the pallets at the changing workstation, assign corresponding idle status to adjacent alternative processing positions within the parallel scheduling reconstruction sequence, remove alternative processing positions with unmatched idle status, and generate a clamping turnover distribution column. S5: Based on the clamping and turnover distribution column, extract the workshop shift operation deadline boundary, determine the boundary status of each dispatch node built into the clamping and turnover distribution column, and based on the judgment conclusion, transmit the corresponding start-up level of the retained node after removing the boundary item to the production line main control console to obtain the dispatch execution trigger chain. The part flow path diagram includes transfer vectors, transport directed edges, and topology; the machine mapping assignment spectrum includes allocation matrix, binding index, and scheduling block; the parallel scheduling refactoring sequence includes adjusting time window, substitute processing array, and heavy-load work order chain; the clamping and turnover distribution column includes transfer batch, mounting queue, and cache stack; and the work dispatch execution trigger chain includes activation pulse, start / stop control word, and work instruction set.

[0020] Please see Figure 2 The specific steps of S1 are as follows: S101: Collect order delivery date nodes and blank process dwell positions, extract the timestamp reference value at the delivery date node, record the trigger time of the blank process dwell position, calculate the time difference data item between the reference value and the trigger time, filter the dwell position information corresponding to the positive value at the time difference data item and compile it into the data vector group, extract the boundary values ​​of the node values ​​at both ends of the data vector group, and establish the process flow time sequence interval. Through a data platform based on cloud-native architecture-deployed industrial application software, the system collects order delivery dates from the internal storage of workshop production management equipment and the dwell positions of blank processes within workshop logistics records. It extracts the timestamp baseline values ​​corresponding to these delivery dates and records the trigger moments when the blank process dwell positions shift. Using the stream processing engine within the industrial application software, it calculates the time difference between the timestamp baseline value and the trigger moment by performing a subtraction operation. Then, it filters out the dwell position information corresponding to positive time difference values ​​and incorporates them into a data vector group. Further, it extracts the boundary values ​​of the nodes at both ends of this data vector group, thereby establishing the process flow time sequence interval. By calling the delivery deadlines of each order under a specific production batch through the enterprise resource planning (ERP) equipment port, for three production orders of a certain model of aerospace aluminum alloy parts, the system obtains their delivery dates and converts them into a standard timestamp format. The extracted timestamp baseline values ​​are 1715300000, 1715400000, and 1715500000, respectively. By deploying RFID readers at various workstations in the workshop, the positions of the workpiece at different processing stages were collected, and the trigger time was recorded when the workpiece entered the corresponding position. The trigger time values ​​for three workpiece positions were collected as 1715200000, 1715450000, and 1715480000. Using the above timestamp reference value as the minuend and the trigger time value as the subtrahend, the two values ​​were subtracted to obtain the time difference data item. The advantage of this calculation logic is that direct timestamp subtraction can accurately quantify the buffer time margin between each process and the final delivery date. Substituting the first delivery timestamp base value of 1715300000 and the first trigger time value of 1715200000 into the subtraction logic, the time difference data item is obtained as 100000. Similarly, the second set of data 1715400000 minus 1715450000 yields -50000, and the third set of data 1715500000 minus 1715480000 yields 20000. After obtaining all time difference data items, each time difference data item is sequentially checked for being greater than 0. Negative values ​​less than or equal to 0 are eliminated, and the time difference data items 100000 and 20000, which are greater than 0 in the above calculation results, are selected. The blank process dwell information corresponding to these two positive values ​​is extracted, and the information identified as workstation A and workstation C is incorporated into a one-dimensional data vector group.For this data vector group, the timestamp time difference items stored inside are read sequentially. The maximum and minimum values ​​are identified through comparison operations. The maximum value of 100000 is set as the upper limit boundary, and the minimum value of 20000 is set as the lower limit boundary. The numerical boundary quantities of the two nodes are extracted to construct a process flow time interval with a span of 80000 seconds. The maximum and minimum values ​​are combined and encapsulated to generate interval parameters containing the two endpoints of 20000 and 100000, thus completing the interval establishment operation.

[0021] S102: Call the process flow time interval, read the time tag quantity within the interval, perform position swapping operation on the blank process dwell position according to the time tag quantity and ascending order criterion, extract the sequence feature after the swapping operation, project the blank process dwell position onto the two-dimensional plane according to the sequence feature, connect adjacent blank process dwell position nodes in the two-dimensional plane with directed line segments, and obtain the part flow path diagram. Based on the time stamp values, all extracted blank process dwell positions are swapped in ascending order. The resulting sequence features are then extracted, and using the embedded 2D visualization rendering engine in the industrial application software, each blank process dwell position is projected onto a 2D plane. Finally, directed line segments connect adjacent blank process dwell position nodes in this 2D plane to obtain a complete part flow path diagram. Time stamp values ​​associated with each dwell position are extracted from the process flow time interval. These time stamp values, derived from the trigger time value, characterize the specific order in which the part arrives at each process. The extracted time stamp values ​​for four blank process dwell positions are 400, 100, 300, and 200, respectively. The time stamps are swapped using a sorting logic. First, the first time stamp (400) is compared to the second (100). Since 400 is greater than 100, their positions are swapped. Then, 400 is compared to 300 and swapped, and so on. After multiple rounds of comparison and swapping of adjacent elements, a sequence of time stamps in ascending order is obtained: 100, 200, 300, and 400. As the time stamps are sorted, the corresponding workpiece processing stops also change position synchronously, generating a sequence characteristic reflecting the actual processing order, resulting in the processing order of stops B, D, C, and A. The dimensional scale parameters of the actual workshop layout are extracted, and a two-dimensional Cartesian coordinate system with the workshop entrance as the origin is established. Based on the actual physical coordinates of each stop within the workshop, the sorted workpiece processing stops are projected one by one onto this two-dimensional plane. The coordinates of stop B are 10 and 20, and the coordinates of stop D are 30 and 40. After projection is completed, according to the flow direction established in the sequence features, a line segment with a directional arrow is used to start from the first stop node in the sequence and connect to the next stop node that follows. A straight line is drawn from coordinates 10 and 20 to coordinates 30 and 40, and a directional arrow is added at the end point. This process is repeated to connect all nodes projected in the two-dimensional plane to generate the part flow path diagram.

[0022] Please see Figure 3 The specific steps of S2 are as follows: S201: Obtain the available slots of the CNC milling machine in the workshop and the idle spindle codes of the turning center. Extract the available slot numbers and spindle code characters. Concatenate the numbers and characters into a device resource vector. Calculate the node load values ​​in the device resource vector. Compare the load values ​​with the device load threshold. Remove nodes whose load values ​​exceed the device load threshold to obtain the set of idle machine resources. The available slot numbers and spindle codes are extracted and concatenated into a device resource vector. Historical operating parameters of the equipment are collected, and the load values ​​of each node within the device resource vector are calculated. These load values ​​are compared with a pre-set equipment load threshold, and nodes exceeding the threshold are removed, leaving only the remaining nodes to obtain the idle machine resource set. The physical status parameters of multiple CNC machines are retrieved in real time through the data interface of the workshop manufacturing execution equipment. The available slot numbers of CNC milling machines marked as idle are extracted, yielding slot numbers 5 and 8. Simultaneously, the idle spindle codes of the turning center in a no-cutting-task state are obtained, yielding codes 2 and 4. The extracted slot numbers and codes are concatenated into strings. Slot number 5 and code 2 are concatenated into string 52 as the first node, and slot number 8 and code 4 are concatenated into string 84 as the second node. These concatenated strings are then arranged sequentially to form the device resource vector. By reading the real-time current feedback value and rated current value of the servo motors inside each device, the node load value is calculated by dividing the two. The advantage of this calculation logic is that the current ratio directly reflects the current mechanical stress level of the machine. When the real-time current feedback value is 15 amps and the rated current value is 20 amps, the ratio is 0.75. Converting this ratio to a percentage gives the node load value as 75. Based on historical equipment failure and maintenance data, statistical analysis is performed to determine the average load threshold point when the equipment failure rate suddenly increases. This threshold point is then lowered by 10 percentage points as a preset equipment load threshold. For example, if the statistically determined failure surge threshold is 80, then 70 is set as the equipment load threshold. The calculated node load value is compared one by one with the equipment load threshold of 70. The load value of the first node is 75, and the load value of the second node is 60. If the comparison result shows that 75 is greater than 70, then the first node is determined to exceed the equipment load threshold and is removed from the equipment resource vector. For the second node, 60 is less than 70, it is retained. Summarize all the retained node parameters and package the idle resource item corresponding to number 84 into a machine idle resource set.

[0023] S202: Call the machine idle resource set and the part flow path diagram, extract the coordinates of the blank process stop position in the part flow path diagram, calculate the position difference between the stop position coordinates and the node coordinates of the machine idle resource set, retrieve the node item where the position difference is equal to the minimum value, perform corresponding association between the stop position and the node item at the minimum value and write it into the binary matrix, and obtain the machine mapping assignment spectrum. The calculation begins with the logistics optimization algorithm module of the industrial application software. It extracts the coordinates of each blanking process stop position within the part flow path diagram. Using a distance formula, it calculates the positional difference between the stop position coordinates and the coordinates of each node in the machine idle resource set. From all the positional difference results, it retrieves the node item whose value equals the minimum value. It then performs a corresponding association operation between this stop position and the retrieved minimum value node item, and writes this correspondence into a two-dimensional matrix data structure to obtain the machine mapping assignment spectrum. The horizontal and vertical coordinate parameters of each blanking process position are extracted one by one from the part flow path diagram. The coordinates of the first blanking process stop position are obtained as follows: horizontal axis 50, vertical axis 60. The fixed coordinates of each available equipment node are read from the machine idle resource set. Equipment node A has a horizontal axis of 55 and a vertical axis of 62, and equipment node B has a horizontal axis of 40 and a vertical axis of 80. The square root of the sum of the squares of the coordinate differences between the stop position coordinates and each equipment node coordinate is calculated to obtain the absolute positional difference between the two points. Substituting coordinates 50 and 60 with coordinates 55 and 62 of device node A into the calculation logic, first, the difference in the horizontal coordinates is calculated: 55 minus 50 equals 5, and the difference in the vertical coordinates is calculated: 62 minus 60 equals 2. Then, 5 squared (25) plus 2 squared (4) equals 29. Finally, the square root of 29 gives a position difference of approximately 5.385. Similarly, the position difference with device node B is calculated: the difference in the horizontal coordinates is 40 minus 50 equals -10, squared to 100; the difference in the vertical coordinates is 80 minus 60 equals 20, squared to 400. Adding these together gives 500, and the square root gives a position difference of approximately 22.360. Comparing all the obtained position differences, the minimum value of 5.385 is retrieved between 5.385 and 22.360, and the device node A corresponding to this minimum value is located. The current blank process dwell position is then linked with the retrieved device node A, generating a key-value pair-like association record. Create a blank binary matrix table with the number of rows equal to the number of dwell positions and two columns. Write the identifier of the dwell position as the data in the first column of the matrix, and write the equipment code of equipment node A as the data in the second column of the matrix in the same row of the matrix, thus completing the persistent storage of one associated record. Repeat the above operations of calculating the position difference and retrieving and writing the minimum value, traversing all the dwell positions of the blank process. After all the corresponding associations have been written into the matrix, the binary matrix constitutes the final machine mapping assignment spectrum.

[0024] Table 1: Equipment Status Distribution Table

[0025] Table 1 shows the real-time load parameters of some devices and the final availability status filtering results.

[0026] Please see Figure 4 The specific steps of S3 are as follows: S301: Collect the machine tool magazine slot quota and cutting tool occupancy items, call the machine mapping assignment spectrum, extract the built-in cutting tool occupancy item values, calculate the difference between the occupancy item values ​​and the machine tool magazine slot quota, compare the difference with the quota limit benchmark value, record the slot coordinates where the difference exceeds the quota limit benchmark value, add the slot coordinates to the tensor, and obtain the slot over-limit index cluster; By leveraging the virtual mapping and synchronization function of the digital twin module in the industrial application software in the cloud, the actual total quota of tool magazine slots inside the machine tool and the physical occupancy of the current cutting tools are collected. The machine tool mapping assignment spectrum generated in the previous steps is invoked, and the occupancy values ​​of the cutting tools built into the indicated equipment are extracted. A subtraction operation is performed to calculate the difference between the occupancy value and the machine tool magazine slot quota. The calculated difference is compared with a pre-set quota limit benchmark value, and the coordinates of specific slots where the difference exceeds the quota limit benchmark value are recorded. These recorded slot coordinates are added one by one into a one-dimensional tensor container to obtain the slot over-limit index cluster. The factory hardware parameters of each machine tool magazine are read through the machine tool data acquisition interface to determine the maximum number of slots that can accommodate tools, which is taken as the machine tool magazine slot quota. The tool magazine slot quota for a certain model of machining center is found to be 40 slots. Simultaneously, the built-in photoelectric sensor in the tool magazine senses the reflected signals from the tool holder shanks in each slot, and counts the number of slots currently occupied by actual tools as the cutting tool occupancy value. The count shows that 45 tools are currently occupied or waiting to be loaded into slots, resulting in a logical occupancy exceeding the limit. A subtraction operation is performed, using the cutting tool occupancy value of 45 as the minuend and the tool magazine slot quota of 40 as the subtrahend, resulting in a difference of 5. Based on the safety margin requirements of the tool magazine changing robot, the allowable limit overflow buffer is set as the quota limit benchmark value. Through multiple extreme pressure tests, the maximum safe overflow without tool jamming in the tool magazine is determined to be 2, so the quota limit benchmark value is set to 2. Comparing the calculated difference of 5 with the quota limit benchmark value of 2, it is found that 5 is greater than 2, therefore, the current tool magazine status is determined to exceed the quota limit. A positioning command is triggered, and the physical 3D coordinates of the temporary storage area or waiting slot where the 5 tools exceeding the quota are currently located are extracted using the internal coordinate mapping table of the machine tool control equipment. These slot coordinates are recorded, such as coordinate parameters 150, 200, and 350. A blank one-dimensional tensor data structure is initialized, and the extracted slot coordinates exceeding the limit are appended as elements into this tensor. After traversing and checking all the tool magazines of equipment listed in the machine tool mapping assignment spectrum in the workshop, and writing all the slot coordinates exceeding the limit into this tensor, the tensor generates a slot over-limit index cluster containing all problem points.

[0027] S302: Based on the slot over-limit index cluster, extract the built-in slot coordinates, call the stop position coordinates in the part flow path diagram, calculate the distance difference between the slot coordinates and the stop position coordinates, compare the distance difference with the position reference value, remove the stop items where the distance difference exceeds the position reference value, extract the remaining stop position nodes, and perform the head-tail connection and arrangement action on the stop position nodes to obtain the over-limit stop queue. The coordinates of each dwell position recorded in the part flow path diagram are called again to calculate the straight-line distance difference between the slot coordinates and the dwell position coordinates. This distance difference result is compared with the preset position reference value. Those dwell positions with distance differences exceeding the position reference value are eliminated, and the remaining dwell position nodes that meet the conditions are retained. Finally, these retained dwell position nodes are arranged by connecting the beginning and end to obtain the over-limit dwell queue composed of over-limit nodes. Elements are read line by line from the slot over-limit index cluster, and the coordinates of a slot that has over-limited are extracted as 150 on the horizontal axis and 200 on the vertical axis. Then, the coordinates of a blank process dwell position to be evaluated are extracted from the part flow path diagram as 160 on the horizontal axis and 210 on the vertical axis. Euclidean distance calculation is performed on these two sets of coordinates to calculate the distance difference between them. First, the difference of the horizontal coordinates is calculated to be 10, and the square of this is 10, which gives 100. The difference of the vertical coordinates is also calculated to be 10, which is 10, and the square of this is 10, which gives 200. Then, the square root of 200 is performed to obtain a distance difference of approximately 14.14 mm. The advantage of this calculation logic lies in its accurate assessment of the spatial proximity between the tool overflow point and the dwell point of the material to be processed. Based on the economic transport radius range of the automated guided vehicle (AGV) in a single fully loaded state, the upper limit of this economic transport radius value is set as the position reference value. By collecting material transport energy consumption data over the past six months, it is confirmed that the unit energy consumption will increase significantly when the transport radius exceeds 50 mm. Therefore, the position reference value is set to 50 mm. The calculated distance difference of 14.14 mm is compared with the position reference value of 50 mm. Since 14.14 is less than 50, the value does not exceed the position reference value. It is determined that the dwell item is spatially close enough to the over-limit slot and should be retained. The distance difference between the next dwell position's coordinates (horizontal axis 250 and vertical axis 300) and the over-limit slot is calculated. Similarly, the distance difference is calculated to be approximately 141.4 mm. The comparison shows that 141.4 is greater than 50. It is determined that the dwell item exceeds the position reference value, and a rejection operation is performed to remove it from the candidate list. After completing all comparison and elimination operations, the remaining nodes that meet the distance conditions are selected. The nodes are then linked to the head of the next node by pointer reference according to their original process flow time sequence, thus performing the head-tail connection arrangement action to obtain the over-limit stay queue.

[0028] S303: For the queue of overstaying, extract the timestamp of the node in the queue, add a delay constant after the timestamp, rearrange the second position of the node according to the delay constant and perform the ranking extension action, locate the coordinate empty item derived from the ranking extension action, collect the available slot configuration next to the empty item and combine it into the alternative processing position feature, fill the coordinate empty item with the alternative processing position feature, and establish a parallel scheduling reconstruction sequence. The pre-built parallel scheduling solver component within the industrial application software is activated. The original timestamps bound to each node in the queue are extracted. A fixed delay constant is appended to these timestamps. The node positions are rearranged based on the new value obtained after adding the delay constant, and a ranking extension action is performed. Then, the coordinate vacancy items derived from the ranking extension action on the original timeline are located. Available slot configurations next to these vacancy items are collected and combined into a substitute machining position feature. Finally, this substitute machining position feature is filled into the coordinate vacancy item, establishing a complete parallel scheduling reconstruction sequence. The attribute parameters of each node are sequentially extracted from the over-limit dwell queue. The timestamp parameter of the scheduled machining task for the first node is extracted as 3600 seconds. Based on the average debugging time required for tool re-clamping and equipment reset, this time value is set as the delay constant. By measuring the time required for a workshop technician to complete a standard tool change, the fixed time for this operation is determined to be 300 seconds; therefore, the delay constant is set to 300. Substituting the extracted timestamp 3600 and the delay constant 300 into the addition operation logic, the sum is used to obtain the updated time value of 3900 seconds. The advantage of this operation logic is that by forcibly introducing equipment buffer time, it can effectively avoid secondary congestion caused during tool changes. This addition operation is performed on all nodes in the queue to obtain a new set of time values. These new values ​​are compared and sorted in ascending order using a sorting algorithm, moving the nodes that originally occupied the 3600-second time slot to the 3900-second time slot, thus completing the ranking extension of the nodes in the queue. After the node extension, a blank area with no task assignment will appear in the original timeline interval from 3600 seconds to 3900 seconds. This empty coordinate item caused by the extension is accurately located through timeline scanning operations. The system initiates a device exploration command in the surrounding area, collects available slot configuration parameters for other idle machine tools within a 10-meter radius of the physical location of the empty slot, identifies a standby machining center with available slots, and determines that its spindle speed is 8000 rpm. The system then combines and packages the equipment number and coordinate parameters to establish a parallel scheduling refactoring sequence.

[0029] Please see Figure 5 The specific steps of S4 are as follows: S401: Collect the idle status flag of the pallet of the changing workstation, read the built-in status parameter of the idle status flag, call the parallel scheduling to reconstruct the order, extract the coordinates of the replacement processing position node, calculate the Euclidean distance between the node coordinates and the coordinates of the workstation origin, serialize and reconstruct the Euclidean distance according to the ascending order rule, arrange the replacement processing position nodes according to the serialization and reconstruction results, and obtain the processing position order set. By calling the microservice architecture interface in the industrial application software to achieve spatial logistics collaboration, the geographical coordinates of each alternative processing node in the reconfiguration sequence are extracted. The Euclidean distance between the node coordinates and the origin coordinates of the transshipment workstation is calculated. All the calculated Euclidean distances are serialized and recombined in ascending order. Based on the result of this serialization and recombination, all alternative processing nodes are rearranged to obtain a priority-based processing position order set. Gravity sensors and infrared detectors deployed in the pallet parking area of ​​the transshipment workstation collect electrical signals indicating whether materials are currently placed on each pallet slot. A low-level signal indicating no material coverage is received as an idle indicator. The status parameters built into the signal data packet are read, and the pallet number is parsed to be 12 with a load status parameter of 0 kg, confirming that the pallet is absolutely idle and available. The data set of the parallel scheduling reconfiguration sequence is called to extract the spatial location information of the processing nodes assigned as alternatives, obtaining the coordinates of the alternative processing nodes as 80° on the horizontal axis and 90° on the vertical axis. Obtain the fixed origin coordinates of the alternation workstation, with the origin coordinates being 10 on both the horizontal and vertical axes. Substitute the coordinates of the alternative processing station nodes and the workstation origin coordinates into the distance calculation logic. Calculate the difference between their horizontal axis coordinates: 80 minus 10 equals 70. Calculate the difference between their vertical axis coordinates: 90 minus 10 equals 80. Calculate the squares of these two values: 70 squared is 4900, and 80 squared is 6400. Add the two squared values ​​to obtain 11300. Take the square root of this value to obtain the Euclidean distance of approximately 106.3 mm. The advantage of this calculation logic is that it intuitively quantifies the transportation cost of moving an idle pallet to the alternative processing station. Perform this distance calculation on all alternative processing station nodes to obtain a set of Euclidean distance values, such as 106.3, 50.5, and 120.8. Use quicksort logic to compare and swap these distance values, arranging them in ascending order as 50.5, 106.3, and 120.8, completing the data serialization and reassembly. Extract the sorted index of the recombined distance values, and swap the positions of the originally scattered alternative processing position nodes according to the order corresponding to the index. Move the node with a distance of 50.5 to the first position, place the node with a distance of 106.3 in the second position, and place the node with a distance of 120.8 at the end to obtain the processing position order set.

[0030] S402: Extract the sequence nodes in the processing position sequence set, call the idle identifier of the changing workstation pallet, perform a connection mapping action between the idle identifier of the changing workstation pallet and the sequence nodes in the processing position sequence set, extract the mapping action-derived pairing values, compare the pairing values ​​with the set matching benchmark constant, extract the pairing items where the pairing values ​​are equal to the matching benchmark constant, and obtain the pallet association matrix. The process involves linking and mapping the idle status of the transshipment workstation pallet to the sequence nodes within the processing position sequence set. From this mapping, derived pairing values ​​are extracted and compared with the matching baseline constant set by the device. Pairing values ​​that are exactly equal to the matching baseline constant are selected and retained to obtain the final pallet association matrix used to guide clamping. Following the sorting result of the processing position sequence set, the parameters of each internal sequence node are extracted sequentially, starting from the first node. The first sequence node is extracted, with its resource requirement type parameter being the identifier number 1, representing a need for a light-duty load-bearing pallet. The idle status data of the transshipment workstation pallets confirmed to be idle is retrieved, obtaining pallet number 12, whose load-bearing capacity type parameter is the identifier number 1. In the device memory, a data structure linking and mapping operation is performed on these two parameters, comparing the resource requirement type parameter of the sequence node with the load-bearing capacity type parameter of the pallet idle status. The specific logic of this comparison operation is to perform an XOR logic judgment on the two parameter values. If the two type identifiers match, the pairing value corresponding to a high level is output; otherwise, the pairing value corresponding to a low level is output. The advantage of this operational logic is that it quickly filters out pallet resources whose load-bearing specifications perfectly match the processing requirements at the hardware interface level. Substituting the sequence node parameter 1 and pallet parameter 1 into the calculation, since their values ​​are completely identical, the output pairing value is 100. If inconsistent parameters, such as 1 and 2, are substituted, the output pairing value is 0. The device's preset ideal matching state reference value is obtained as the matching baseline constant, and this matching baseline constant is set to 100. A strict equality verification comparison is performed between the previously calculated pairing value of 100 and the matching baseline constant 100. Since the comparison result shows that the pairing value is exactly equal to the matching baseline constant, it indicates that the pallet perfectly matches the load-bearing requirements of the processing position. At this point, the combined data packet containing the pallet number 12 and the processing position node is extracted as a valid pairing item. If the comparison result is not equal, for example, the pairing value is 0, the combined data is discarded. After processing all sequence nodes and available pallets, all the selected valid pairs are written into a two-dimensional table data structure row by row. The first column stores the pallet number, and the second column stores the coordinates of the processing position node. The completed two-dimensional table constitutes the pallet association matrix.

[0031] S403: For the pallet association matrix, read the pairing items, detect the built-in status feature identifier of the pairing items, compare the status feature identifier with the preset empty feature constant, remove the unmatched nodes where the status feature identifier deviates from the preset empty feature constant, collect the position coordinates of the remaining matching nodes, arrange and combine the position coordinates according to the time evolution order, and generate the clamping turnover distribution column. The read status feature identifier is compared with a pre-set empty feature constant. Unmatched nodes whose status feature identifiers deviate from the pre-set empty feature constant are stripped and removed. Then, the three-dimensional coordinates of all remaining matching nodes are collected. Finally, these coordinates are arranged according to the expected time sequence of each process, generating a clamping and turnover distribution list that can be directly issued for execution. A paired item is read from the first row of the pallet association matrix. The data message transmitted in real-time via the IoT module is parsed, and the status feature identifier stored in a specific byte segment within the message is detected and extracted. The hexadecimal value of this status feature identifier is 01, indicating that the pallet is currently unobstructed and accessible to the robotic arm. A standard status code representing absolute pallet safety, pre-stored in the database, is extracted as a pre-set empty feature constant, also set to hexadecimal 01. An equivalence comparison is performed between the two. If the extracted status feature identifier equals the preset empty feature constant, the paired item is considered to be in good condition. If the extracted status feature identifier deviates from the baseline constant of 01 due to some sudden interference, such as dust accumulation on the sensor, the value becomes 02, triggering the exception handling logic. For the case where the comparison result is 02, deviating from the constant, the device activates the isolation mechanism, removing the data node containing the paired item from the tray association matrix to prevent the issuance of erroneous commands. For the normal case where the comparison result is 01, the node is retained, and the current precise physical position coordinates of the matched node are collected using the workshop indoor positioning device, obtaining the horizontal axis 110, the vertical axis 120, and the height 30. The position coordinate data of all remaining matched nodes after status cleaning are summarized, and their corresponding timestamp tags in the scheduling scheme are extracted. These coordinate data are then reorganized and concatenated according to the direction of the timestamp value from smallest to largest, i.e., the time evolution order. The arranged coordinate sequence is written into the execution memory area of ​​the programmable logic controller to generate the clamping and turnover distribution column.

[0032] Table 2: Pallet Matching Status Details

[0033] Table 2 lists the final status of each tray after the verification operation and whether it meets the matching criteria.

[0034] Please see Figure 6 The specific steps of S5 are as follows: S501: Extract the workshop shift's running deadline boundary, call the clamping and turnover distribution column, collect the timestamp values ​​of each built-in dispatch node, calculate the time difference parameter between the timestamp value and the running deadline boundary, compare the time difference parameter with the boundary-crossing benchmark constant, record the dispatch node index where the time difference parameter exceeds the boundary-crossing benchmark constant, encode the node index into a single-dimensional vector, and obtain the boundary-crossing dispatch index cluster. Calculate the time difference parameter between the timestamp value and the running deadline. Compare the calculated time difference parameter with the equipment's preset out-of-bounds reference constant. Record the unique index number of the dispatch node where the time difference parameter exceeds the out-of-bounds reference constant. Finally, encode these recorded node indices into a single-dimensional vector to obtain an out-of-bounds dispatch index cluster used to identify timeout risks. Log in to the workshop's manufacturing execution equipment server backend, read the current production shift's work schedule, and extract the absolute time point when all equipment is required to stop for shift handover as the shift's running deadline. Extract the corresponding Unix timestamp format data as 1715600000. Call the optimized clamping and turnover distribution queue, and sequentially obtain the estimated timestamp values ​​of each dispatch node scheduled to perform clamping or processing operations from the queue. The timestamp value of the first dispatch node is obtained as 1715598000. Perform a subtraction operation, using the shift's end-of-shift boundary value as the minuend and the dispatch node's timestamp value as the subtrahend, calculate the time difference parameter between the two, and accurately calculate the remaining available time window before each task must be stopped for handover through a countdown method, generating an out-of-bounds dispatch index cluster.

[0035] S502: Based on the out-of-bounds dispatch index cluster, call the built-in full dispatch nodes of the clamping turnover distribution column, retrieve the mapping correspondence between the dispatch nodes and the built-in index items of the out-of-bounds dispatch index cluster, remove the node items where there is a mapping correspondence, extract the parameters of the remaining dispatch nodes where there is no mapping correspondence, and reorganize and arrange the parameters according to the time evolution order to obtain the compliant dispatch sequence. The process involves retrieving the mapping between the dispatch node's identity sequence number and the built-in index entries of the out-of-bounds dispatch index cluster. For nodes with such mappings, a removal instruction is executed. All parameters of the remaining dispatch nodes without such mappings are extracted and retained. Finally, these retained parameters are strictly recombined and arranged according to the chronological order of time evolution to obtain a compliant dispatch sequence that fully complies with time constraints. The process also involves expanding the clamping and turnover distribution column, reading the full set of dispatch nodes contained within it, and extracting the unique identification sequence number of each node. The first node's sequence number is set to 1, and the second node's sequence number to 5. Simultaneously, the list of abnormal index entries stored within the out-of-bounds dispatch index cluster is read, revealing index entries 5 and 7. A traversal comparison algorithm is used to compare each dispatch node's sequence number with all index entries in the out-of-bounds dispatch index cluster. The advantage of this operation is that, through a simple set subtraction operation, all potential timeout risk items can be quickly and losslessly extracted from a large plan. Substituting node number 1 into the comparison, it is found that the index cluster does not contain the number 1, thus determining that there is no mapping relationship. Substituting node number 5 into the comparison, it is found that the index cluster contains the number 5, and the two values ​​are completely consistent, thus determining that there is a mapping relationship for this node. For nodes whose mapping relationship is confirmed by the comparison results, a memory clearing operation is triggered, removing them along with all associated coordinates, tool, and pallet parameters from the execution list. For the remaining dispatch nodes for which no matching items are found and no mapping relationship exists, such as node number 1 and its attribute parameters, they are truncated and retained. All parameters of the retained dispatch nodes are collected, their timestamp tags are extracted, and ascending sorting logic is applied again to ensure that these nodes are rearranged completely according to the chronological order, i.e., the order of time evolution, to generate a compliant dispatch sequence.

[0036] S503: For compliant dispatching sequences, collect the level trigger signal of the dispatching node built into the sequence, detect the value of the start flag bit in the level trigger signal, transmit the node information where the start flag bit value is equal to the level trigger signal to the main control port of the production line, read the confirmation handshake code returned by the port, connect the node information and the confirmation handshake code to form a communication combination, and establish a dispatching execution trigger chain. The system detects the specific value of the start-up flag bit contained within the level trigger signal and, relying on the underlying communication control protocol stack integrated into the industrial application software, transmits the node information where the start-up flag bit value is precisely equal to the trigger voltage level to the production line main control port via the industrial Ethernet network. It then reads the confirmation handshake code returned from this port, and connects the sent node information with the received confirmation handshake code to form a communication sequence, thereby establishing the dispatch execution trigger chain that ultimately drives the equipment operation. Status query polling commands are sent to the material sensors corresponding to each node in the compliant dispatch sequence, collecting the level trigger signal data packets returned by each sensor and parsing the start-up flag bit byte within the data packet that indicates whether the material is in place. The start-up flag bit value of the first node is extracted as binary 1. The standard start signal reference value defined in the underlying communication protocol of the equipment is obtained as the trigger voltage level. This standard defines that when the sensor collects a high level, it outputs a value of 1; therefore, the trigger voltage level is set to 1. A comparison logic is executed to compare the collected start-up flag bit value with the trigger voltage level for equality. The advantage of this logical operation is that, through strict hardware and software signal closed-loop verification, it ensures that the scheduling command is only released when the physical processing conditions are absolutely met. Substituting the numerical value 1 with the constant 1 for comparison, if the result is completely equal, it is determined that the material associated with this node has arrived at the designated workstation and is clamped. This triggers the network communication module, which encapsulates and packages the comprehensive information contained in the node, such as the machine tool number, machining program number, and cutting parameters, and transmits it to the production line main control console port at the workshop headquarters via the transmission control protocol port. After receiving the data packet and verifying its correctness, the main control console sends back a specific verification string as a confirmation handshake code to the original sender. Reading the content of this confirmation handshake code indicates that the command has been received. In the sender's memory, the previously transmitted node details and the confirmation handshake code string are concatenated and merged into a complete communication combination column, which serves as an electronic certificate of successful scheduling. This detection and communication operation is continuously looped along the timeline, sequentially connecting all successfully confirmed communication combination columns to establish a dispatch execution trigger chain.

[0037] Please see Figure 7 A machining production planning and management system, comprising: The planning module collects order delivery dates and blank process dwell positions, extracts the flow sequence boundaries between adjacent blank process dwell positions, arranges them in sequence, and establishes a part flow path diagram. The resource scheduling module obtains the available slots of CNC milling machines in the workshop and the idle spindle codes of the turning center, matches the stop position of each blank process in the part flow path diagram with the corresponding available slots and idle spindle codes, and obtains the machine tool mapping assignment spectrum. The exception handling module extracts the machine tool magazine slot quota and cutting tool occupancy items, compares the size of the cutting tool occupancy items built into the machine tool mapping assignment spectrum with the machine tool magazine slot quota, filters the blank process dwell positions corresponding to the cutting tool occupancy items that exceed the machine tool magazine slot quota, performs a sequential arrangement action for the blank process dwell positions, and fills the vacant positions with alternative machining positions to obtain the parallel scheduling reconstruction sequence. The turnover distribution module collects the idle indicators of the pallets at the changing workstation, assigns corresponding idle indicators to adjacent alternative processing positions within the parallel scheduling reconstruction sequence, removes alternative processing positions corresponding to unmatched idle indicators of pallets, and generates a clamping turnover distribution column. The progress monitoring module extracts the end-of-shift boundary of the workshop, determines whether the deadline of each work node in the clamping and turnover distribution column exceeds the boundary, transmits the start-up level of the node to be retained after removing the out-of-bounds item to the main control panel of the production line, and obtains the work execution trigger chain.

[0038] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of protection of the described technical solutions.

Claims

1. A method for managing machining production planning, characterized in that, Includes the following steps: S1: Collect order delivery dates and blank process dwell positions, extract the flow sequence boundaries between adjacent blank process dwell positions, arrange them in sequence, and establish a part flow path diagram; The specific steps of S1 are as follows: S101: Collect order delivery date nodes and blank process dwell positions, extract the timestamp reference value at the delivery date node, record the trigger time of the blank process dwell position, calculate the time difference data item between the reference value and the trigger time, filter the dwell position information corresponding to the positive value at the time difference data item and compile it into the data vector group, extract the boundary values ​​of the node values ​​at both ends of the data vector group, and establish the process flow time sequence interval. S102: Call the process flow time interval, read the time tag quantity in the interval, perform position swapping operation on the blank process dwell position according to the time tag quantity and the ascending order criterion, extract the sequence feature after the swapping operation, project the blank process dwell position onto the two-dimensional plane according to the sequence feature, connect adjacent blank process dwell position nodes in the two-dimensional plane with directed line segments, and obtain the part flow path diagram. S2: Obtain the available slots of the CNC milling machine in the workshop and the idle spindle codes of the turning center, match the stop position of each blank process in the workpiece flow path diagram with the corresponding available slots and idle spindle codes, and obtain the machine tool mapping assignment spectrum. The specific steps of S2 are as follows: S201: Obtain the available slots of the CNC milling machine in the workshop and the idle spindle codes of the turning center. Extract the available slot numbers and spindle code characters. Concatenate the numbers and characters into a device resource vector. Calculate the node load values ​​in the device resource vector. Compare the load values ​​with the device load threshold. Remove nodes whose load values ​​exceed the device load threshold to obtain the set of idle machine resources. S202: Call the machine idle resource set and the part flow path diagram, extract the coordinates of the blank process stop position in the part flow path diagram, calculate the position difference between the stop position coordinates and the node coordinates of the machine idle resource set, retrieve the node item where the position difference is equal to the minimum value, perform corresponding association between the stop position and the node item at the minimum value and write it into a binary matrix to obtain the machine mapping assignment spectrum. S3: Extract the machine tool magazine slot quota and cutting tool occupancy items, compare the size of the cutting tool occupancy items built into the machine tool mapping assignment spectrum with the machine tool magazine slot quota, filter the blank process dwell positions corresponding to the cutting tool occupancy items that exceed the machine tool magazine slot quota, perform the sequential arrangement action for the blank process dwell positions, and fill the vacant positions with alternative processing positions to obtain the parallel scheduling reconstruction sequence; The specific steps for S3 are as follows: S301: Collect the machine tool magazine slot quota and cutting tool occupancy item, call the machine mapping assignment spectrum, extract the built-in cutting tool occupancy item value, calculate the difference between the occupancy item value and the machine tool magazine slot quota, compare the difference with the quota limit benchmark value, record the slot coordinates where the difference exceeds the quota limit benchmark value, add the slot coordinates to the tensor, and obtain the slot over-limit index cluster; S302: Based on the slot over-limit index cluster, extract the built-in slot coordinates, call the stop position coordinates in the part flow path diagram, calculate the distance difference between the slot coordinates and the stop position coordinates, compare the distance difference with the position reference value, remove the stop items where the distance difference exceeds the position reference value, extract the remaining stop position nodes, and perform the head-tail connection and arrangement action on the stop position nodes to obtain the over-limit stop queue. S303: For the over-limit stay queue, extract the timestamp of the node in the queue, add a delay constant after the timestamp, rearrange the node position according to the delay constant and perform the ranking extension action, locate the coordinate empty item derived from the ranking extension action, collect the available slot configuration next to the empty item and combine it into the alternative processing position feature, fill the coordinate empty item with the alternative processing position feature, and establish a parallel scheduling reconstruction sequence. S4: Collect the idle indicators of the pallets at the changing workstation, assign corresponding idle indicators to adjacent alternative processing positions within the parallel scheduling reconstruction sequence, remove alternative processing positions with unmatched idle indicators, and generate a clamping turnover distribution column. The specific steps of S4 are as follows: S401: Collect the idle status indicator of the pallet of the changing workstation, read the built-in status parameter of the idle status indicator, call the parallel scheduling reconstruction sequence, extract the coordinates of the replacement processing position node, calculate the Euclidean distance between the node coordinates and the coordinates of the workstation origin, serialize and reorganize the Euclidean distance according to the ascending order rule, arrange the replacement processing position nodes according to the serialization and reorganization results, and obtain the processing position order set. S402: Extract the sequence nodes in the processing position sequence set, call the idle identifier of the changing workstation pallet, perform a connection mapping action between the idle identifier of the changing workstation pallet and the sequence nodes in the processing position sequence set, extract the mapping action-derived pairing values, compare the pairing values ​​with the set matching benchmark constant, extract the pairing items where the pairing values ​​are equal to the matching benchmark constant, and obtain the pallet association matrix. S403: For the pallet association matrix, read the pairing items, detect the built-in status feature identifier of the pairing items, compare the status feature identifier with the preset empty feature constant, remove the unmatched nodes where the status feature identifier deviates from the preset empty feature constant, collect the position coordinates of the remaining matching nodes, arrange and combine the position coordinates according to the time evolution order, and generate the clamping turnover distribution column. S5: Extract the workshop shift operation deadline boundary, determine the boundary status of each dispatch node built into the clamping turnover distribution column, transmit the corresponding start level of the node to be retained after removing the boundary item to the production line main control console, and obtain the dispatch execution trigger chain. The specific steps of S5 are as follows: S501: Extract the workshop shift operation deadline boundary, call the clamping turnover distribution column, collect the timestamp values ​​of each built-in dispatch node, calculate the time difference parameter between the timestamp value and the operation deadline boundary, compare the time difference parameter with the boundary reference constant, record the dispatch node index where the time difference parameter exceeds the boundary reference constant, encode the node index into a single-dimensional vector, and obtain the boundary dispatch index cluster. S502: Based on the out-of-bounds dispatch index cluster, call the built-in full dispatch nodes of the clamping turnover distribution column, retrieve the mapping correspondence between the dispatch nodes and the built-in index items of the out-of-bounds dispatch index cluster, remove the node items where there is a mapping correspondence, extract the parameters of the remaining dispatch nodes where there is no mapping correspondence, and reorganize and arrange the parameters according to the time evolution order to obtain the compliant dispatch sequence. S503: For the compliant dispatch sequence, collect the level trigger signal of the dispatch node built into the sequence, detect the value of the start flag bit in the level trigger signal, transmit the node information where the start flag bit value is equal to the trigger level to the main control port of the production line, read the confirmation handshake code returned by the port, connect the node information and the confirmation handshake code to form a communication combination, and establish a dispatch execution trigger chain.

2. The machining production planning management method according to claim 1, characterized in that, The part flow path diagram includes transfer vectors, transport directed edges, and topology; the machine mapping assignment spectrum includes allocation matrix, binding index, and scheduling block; the parallel scheduling reconstruction sequence includes adjustment time window, substitute processing array, and heavy-load work order chain; the clamping turnover distribution column includes transfer batch, mounting queue, and cache stack; and the dispatch execution trigger chain includes activation pulse, start / stop control word, and work instruction set.

3. The machining production planning management method according to claim 1, characterized in that, Use the two-dimensional coordinate data of the machine where the difference is greater than the quota limit benchmark value as the slot coordinate; Construct an initial data structure as a tensor, and write the slot coordinates into the empty element positions of the tensor in the order of coordinate acquisition. Combine tensors with written records to form a slot over-limit index cluster.

4. The machining production planning management method according to claim 1, characterized in that, Extract the horizontal and vertical coordinate values ​​of the replacement machining station node coordinates, and extract the reference horizontal and vertical coordinate values ​​of the workstation origin coordinates. Calculate the sum of squares of the differences between the horizontal and vertical coordinate values ​​and the corresponding baseline horizontal and vertical coordinate values, and then take the square root to obtain the Euclidean distance. The arrangement of the replacement processing node coordinates is adjusted according to the Euclidean distance values ​​from smallest to largest to complete the serialization and recombination.

5. A machining production planning and management system, characterized in that, The system is used to implement the machining production planning management method according to any one of claims 1-4, the system comprising: The planning module collects order delivery dates and blank process dwell positions, extracts the flow sequence boundaries between adjacent blank process dwell positions, arranges them in sequence, and establishes a part flow path diagram. The resource scheduling module obtains the available slots of CNC milling machines in the workshop and the idle spindle codes of the turning center, matches the stop position of each blank process in the workpiece flow path diagram with the corresponding available slots and idle spindle codes, and obtains the machine tool mapping assignment spectrum. The exception handling module extracts the machine tool magazine slot quota and cutting tool occupancy items, compares the size of the cutting tool occupancy items built into the machine tool mapping assignment spectrum with the machine tool magazine slot quota, filters the blank process dwell positions corresponding to the cutting tool occupancy items that exceed the machine tool magazine slot quota, performs a sequential arrangement action for the blank process dwell positions, and fills the vacant positions with alternative machining positions to obtain the parallel scheduling reconstruction sequence. The turnover distribution module collects the idle indicators of the pallets at the changing workstation, assigns corresponding idle indicators to adjacent alternative processing positions within the parallel scheduling reconstruction sequence, removes alternative processing positions corresponding to unmatched idle indicators of pallets, and generates a clamping turnover distribution column. The progress monitoring module extracts the end-of-shift boundary of the workshop, determines whether the deadline of each dispatch node in the clamping and turnover distribution column exceeds the boundary, transmits the start-up level of the node to be retained after removing the out-of-bounds item to the main control console of the production line, and obtains the dispatch execution trigger chain.

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