Product processing management method and system under comprehensive production line, and electronic equipment

Abstract

The invention provides a product processing management method and system under a comprehensive production line and electronic equipment, and relates to the technical field of production line control, and the method comprises the steps: mapping a plurality of key process feature sequences to an equipment parameter library, outputting a plurality of standard production control sequences, then carrying out the difference frequency analysis, and constructing a difference frequency control matrix; constructing a task execution sequence of the plurality of product processing tasks based on the difference frequency control matrix; and based on the task execution sequence, carrying out connection difference frequency control identification on the plurality of standard production control sequences, and constructing an equipment parameter control conversion sequence according to an identification result to carry out operation control management on the production line equipment group. The technical problem that in the prior art, when multiple cookware products are machined on a comprehensive production line, the production efficiency and the production stability are affected by machining task switching, and consequently the yield of cookware production is affected is solved. The technical effects of improving the task transition smoothness of processing task switching, improving the production efficiency and the production stability of the comprehensive production line and guaranteeing quality control are achieved.

Description

Technical Field

[0001] The present invention relates to the field of production line control technology, and in particular to a product processing management method, system and electronic equipment under an integrated production line. Background Art

[0002] Existing technologies typically rely on manual experience to pre-set fixed production sequences, lacking dynamic analysis of real-time equipment status, process constraints, and the coupling relationships between tasks. For example, when scheduling a mixed production of multiple types of pots (such as cast iron pots, stainless steel pots, and honeycomb non-stick pans), mold changes, equipment parameter adjustments, and process buffer interval settings are highly dependent on operator experience. This can easily lead to increased equipment idle time or process conflicts (such as starting mold removal before the stamping machine has completed pressure relief), resulting in unstable production line rhythms.

[0003] At the same time, different cookware production tasks require significantly different equipment parameters (such as stamping pressure, spray flow rate, and annealing temperature), and existing technologies lack systematic planning for the parameter switching process. For example, when switching from high-pressure cast iron pot production to low-pressure stainless steel pot production, a sudden drop in the stamping press pressure can easily cause hydraulic system fluctuations, resulting in dimensional deviations of the first product. Initiating the spraying process before the annealing furnace temperature stabilizes within the target range can result in substandard adhesion due to uneven coating curing.

[0004] In summary, the existing technology has a technical problem that when an integrated production line is used to process multiple cookware products, the switching of processing tasks affects production efficiency and production stability, thereby affecting the production qualification rate of cookware. Summary of the Invention

[0005] The present application provides a product processing management method, system and electronic equipment under an integrated production line, which is used to solve the technical problem in the prior art that when an integrated production line is used to process multiple cookware products, the switching of processing tasks affects production efficiency and production stability, thereby affecting the production qualification rate of cookware.

[0006] In view of the above problems, the present application provides a product processing management method, system and electronic equipment under an integrated production line.

[0007] The first aspect of the present application provides a product processing management method under an integrated production line, the method comprising: after receiving real-time order information, extracting multiple key process feature sequences of multiple product processing tasks from the real-time order information; mapping the multiple key process feature sequences to an equipment parameter library, and outputting multiple standard production control sequences; constructing a difference frequency control matrix by performing difference frequency analysis on the multiple standard production control sequences; constructing a task execution sequence for the multiple product processing tasks based on the difference frequency control matrix; performing connection difference frequency control identification on the multiple standard production control sequences based on the task execution sequence, and constructing an equipment parameter control conversion sequence according to the identification result; when executing the task execution sequence to a processing task switching node, performing operation control management on the production line equipment group according to the equipment parameter control conversion sequence.

[0008] The second aspect of the present application provides a product processing management system under an integrated production line, the system comprising: a process feature extraction unit for extracting multiple key process feature sequences of multiple product processing tasks from the real-time order information after receiving real-time order information; a process feature mapping unit for mapping the multiple key process feature sequences to an equipment parameter library and outputting multiple standard production control sequences; a difference frequency analysis unit for constructing a difference frequency control matrix by performing difference frequency analysis on the multiple standard production control sequences; an execution sequence construction unit for constructing a task execution sequence for the multiple product processing tasks based on the difference frequency control matrix; a difference frequency control identification unit for performing connection difference frequency control identification on the multiple standard production control sequences based on the task execution sequence, and constructing an equipment parameter control conversion sequence according to the identification result; an operation control management execution unit for performing operation control management on the production line equipment group according to the equipment parameter control conversion sequence when executing the task execution sequence to the processing task switching node.

[0009] The third aspect of the present application provides an electronic device, which includes: a processor; a memory for storing instructions executable by the processor; wherein the processor is used to execute a product processing management method under an integrated production line provided in the present application.

[0010] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0011] The method provided in the embodiment of the present application receives real-time order information, extracts multiple key process feature sequences of multiple product processing tasks from the real-time order information; maps the multiple key process feature sequences to the equipment parameter library, and outputs multiple standard production control sequences; constructs a difference frequency control matrix by performing difference frequency analysis on the multiple standard production control sequences; constructs a task execution sequence for the multiple product processing tasks based on the difference frequency control matrix; performs connection difference frequency control identification on the multiple standard production control sequences based on the task execution sequence, and constructs an equipment parameter control conversion sequence based on the identification result; when executing the task execution sequence to the processing task switching node, the production line equipment group is controlled and managed according to the equipment parameter control conversion sequence. The technical effect of improving the task transition smoothness of processing task switching, improving the comprehensive production line production efficiency and production stability, and ensuring quality control is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A flowchart of a product processing management method under a comprehensive production line provided in this application;

[0013] Figure 2 This is a structural diagram of a product processing management system under an integrated production line provided by this application;

[0014] Figure 3 This is a schematic diagram of the structure of an electronic device provided in this application.

[0015] Explanation of the accompanying symbols: process feature extraction unit 11, process feature mapping unit 12, difference frequency analysis unit 13, execution sequence construction unit 14, difference frequency control identification unit 15, operation control management execution unit 16, processor 21, memory 22, input device 23, output device 24. DETAILED DESCRIPTION

[0016] The present invention provides a product processing management method, system, and electronic device for an integrated production line. These methods address the existing technical problem of processing multiple cookware products on an integrated production line, where task switching impacts production efficiency and stability, thus affecting the yield rate of cookware production. This method improves the smoothness of task switching, enhances production efficiency and stability of the integrated production line, and ensures quality control.

[0017] Below, the technical solutions of the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments described herein. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention, rather than all, are shown in the accompanying drawings.

[0018] Example 1, as Figure 1 As shown, the present invention provides a product processing management method under an integrated production line, the method comprising:

[0019] A100: After receiving real-time order information, extract multiple key process feature sequences of multiple product processing tasks from the real-time order information.

[0020] In one embodiment, after receiving the real-time order information, multiple key process feature sequences of multiple product processing tasks are extracted from the real-time order information. Step A100 of the method provided by the present invention further includes:

[0021] A110: Obtain the real-time order information by receiving orders from multiple sources.

[0022] A120: Based on the process feature classification rules, use NPL technology to extract fields from the real-time order information to obtain multiple task-related fields for multiple production and processing tasks.

[0023] A130: Mapping process parameters based on the multiple task-related fields to obtain the multiple key process feature sequences.

[0024] In one embodiment, the task-related fields are composed of cookware material characteristics, cookware structure characteristics, and cookware coating requirements.

[0025] In one embodiment, process parameter mapping is performed based on the multiple task-related fields to obtain the multiple key process feature sequences. Step A130 of the method provided by the present invention further includes:

[0026] A131: Map process parameters based on the multiple task-related fields and output multiple process requirement characteristic parameter groups.

[0027] A132: Local call process dependency topology.

[0028] A133: Dynamically prioritize the multiple process requirement feature parameter groups based on the process dependency topology to obtain the multiple key process feature sequences.

[0029] Specifically, in this embodiment, order information from different order sending systems is integrated through a multi-source data interface to ensure data integrity and real-time performance. For example, a structured order form (including product model and batch quantity) is obtained from the ERP system, unstructured text (such as "urgent order for 200 honeycomb non-stick pans") is parsed from an email, and real-time order push from the e-commerce platform is received through an API. The system uses data cleaning and format conversion technology to unify heterogeneous data into standard data objects containing field labels (such as "material", "structure", and "coating"), eliminating data redundancy and format conflicts, and providing consistent input for subsequent feature extraction.

[0030] On the basis of obtaining the real-time order information, the order content is semantically parsed through natural language processing technology (NLP) to extract task feature fields that are strongly related to production.

[0031] Specifically, based on predefined process feature classification rules, an entity recognition algorithm is used to extract key information from the text of the real-time order information, and multiple task association fields of multiple production and processing tasks contained in the real-time order information are obtained, thereby converting the unstructured order description into a machine-understandable set of process feature fields.

[0032] It should be noted that the task-related fields are composed of the cookware material characteristics, the cookware structure characteristics and the cookware coating requirements.

[0033] For example, from "304 stainless steel honeycomb frying pan, three-layer ceramic coating", the material type ("304 stainless steel"), structural characteristics ("honeycomb texture", "diameter 32cm") and coating parameters ("three-layer ceramic", "thickness ≥75μm") are identified, and at the same time, the physical indicators are quantified through numerical analysis rules (such as mapping "diameter 32cm" to the stamping die number M32), and the process parameters are mapped according to the multiple task-related fields to obtain the multiple key process feature sequences. The purpose is to map each task-related field (such as material, structure, coating) to the control parameter set of the corresponding equipment, and generate a parameter group bound to the process steps.

[0034] Specific implementation includes:

[0035] Material feature mapping is performed for each task-related field. For example, the material "cast iron" is mapped to the pressure parameters of the stamping machine (950 tons, calculated based on the yield strength of cast iron and the projected area of the pot body), the heating rate of the annealing furnace (8°C / min), and the holding time (50 minutes). Structural feature mapping is performed for each task-related field. For example, the structure "honeycomb texture" is mapped to the power (180W), groove depth (0.2mm), and path planning template (honeycomb grid algorithm) of the laser notcher. Coating feature mapping is performed for each task-related field. For example, the coating "three-layer ceramic" is mapped to the spray gun movement speed (0.8m / s), single-layer spray thickness (25μm), and curing furnace temperature curve (200°C±5°C) of the spray machine.

[0036] Ultimately, each task-associated field independently generates an equipment parameter group (such as the coating parameter group contains sprayer and curing oven parameters), forming a discrete process requirement characteristic parameter group, providing atomic input for subsequent serialization.

[0037] The process dependency topology is called locally. The process dependency topology defines the execution sequence and process execution time interval of all cookware processing processes. The topology connects parameter groups (nodes) with directed edges to form a logical link for process execution (such as stamping → annealing → spraying), ensuring that the physical execution sequence of parameter groups is consistent with process requirements.

[0038] For example, the stamping process must be started after the mold is installed (depending on the mold in place signal), the spraying process must wait until annealing is completed and the temperature drops to the safety threshold (depending on the annealing furnace completion signal), the annealing furnace preheating must be triggered 30 seconds before the end of stamping, and the minimum interval from annealing completion to spraying start is 10 seconds.

[0039] By analyzing the process constraints and resource association rules in the process dependency topology, each process requirement characteristic parameter group (such as the stamping pressure parameter group, annealing temperature parameter group, and spraying speed parameter group of a stainless steel frying pan) is dynamically sorted into a unique corresponding key process feature sequence. Specifically, by identifying the independence and coupling between parameter groups, independent parameter groups that can be executed in parallel (such as mold preheating and annealing furnace cleaning of a honeycomb pot) are assigned to parallel time windows, while coupled parameter groups with strong dependencies (such as stamping pressure relief of a cast iron pot → mold disassembly → new mold press-in) are not. Serial execution links are generated in topological order. When a timing conflict is detected (for example, the deviation between the start time of non-stick pan spraying and the annealing completion signal exceeds 5 seconds), a buffer interval is dynamically inserted or an alternative parameter template is switched (for example, the spray flow rate is adjusted from 40mL / min to the target value in two stages). Finally, by combining the equipment timing alignment rules (for example, the annealing furnace preheating instruction must be triggered 30 seconds before the end of stamping) and safety interlock conditions (for example, the CO concentration in the ventilation system must be detected to be less than 50ppm before the coating is cured), the discrete parameter groups are arranged into an executable sequence strictly bound to the cookware type.

[0040] This embodiment achieves the technical effect of fully describing the whole process control logic of a cookware from raw materials to finished products in each key process feature sequence, realizing "one pot, one sequence" precise production control.

[0041] A200: Map the multiple key process feature sequences to the equipment parameter library and output multiple standard production control sequences.

[0042] In one embodiment, the multiple key process feature sequences are mapped to an equipment parameter library to output multiple standard production control sequences. Step A200 of the method provided by the present invention further includes:

[0043] A210: Map the multiple key process feature sequences to the equipment parameter library to obtain multiple benchmark production control sequences.

[0044] A220: Locally call multiple equipment status information sequences of multiple production line equipment sequences corresponding to the multiple benchmark production control sequences.

[0045] A230: Dynamically compensate the multiple baseline production control sequences based on the multiple equipment status information sequences, and output multiple compensated production control sequences.

[0046] A240: Perform collaborative optimization of the equipment beats of the multiple compensation production control sequences based on the process dependency topology, and output the multiple standard production control sequences.

[0047] Specifically, in this embodiment, according to the rules in the equipment parameter library (such as the pressure-material mapping table and the temperature-coating relationship curve), the parameter groups in the process feature sequence (such as the annealing temperature and spraying speed of the cast iron pot) are matched to the equipment control value range. For example, "cast iron material" is mapped to the stamping machine benchmark pressure of 950 tons (calculated according to the yield strength formula), and "three-layer ceramic coating" is mapped to the spray machine benchmark flow rate of 35mL / min (based on the coating thickness and spraying efficiency model). The initial benchmark control sequence is generated to clarify the equipment target parameters and execution window of each process.

[0048] The operating status data of production line equipment (such as the instantaneous fluctuation value of the hydraulic pressure of the stamping machine, the actual temperature distribution of each temperature zone of the annealing furnace, and the wear coefficient of the spray machine nozzle) are collected in real time and classified into status information sequences according to the equipment group. For example, the stamping machine status sequence includes the pressure sensor reading (1032 tons), oil temperature (65°C), and mold in-place signal (TRUE), providing real-time working condition input for dynamic compensation.

[0049] Dynamically correct baseline parameters based on equipment status data. For example, if a press hydraulic pressure fluctuation of +3% is detected, the target pressure is automatically increased by 2% to compensate for the deviation. If the spray gun positioning error accumulates to 0.5mm, the motion trajectory coordinates are adjusted in the opposite direction and the spray speed is reduced by 10% to maintain coating uniformity. Ultimately, a compensated control sequence is generated, ensuring that equipment parameters remain close to the process target despite dynamic disturbances.

[0050] Compensation sequences are time-aligned and resource co-optimized based on process-dependent topology. For example, during the press holding phase (which takes 30 seconds), the annealing furnace preheating process is started in parallel to shorten the total cycle time, or the sprayer start window is adjusted to avoid competing with the mold change process for conveyor belt resources. The final output standard production control sequence includes equipment parameters, coordinated beats, and tolerance rules.

[0051] This embodiment converts the process feature sequence into accurately executable equipment control instructions through rule matching and real-time status feedback of the equipment parameter library, achieving the technical effect of ensuring that the production parameters both meet the process requirements and adapt to the actual working conditions of the equipment.

[0052] A300: Construct a difference frequency control matrix by performing difference frequency analysis on the multiple standard production control sequences.

[0053] In one embodiment, by performing a difference frequency analysis on the plurality of standard production control sequences to construct a difference frequency control matrix, the method step A300 provided by the present invention further includes:

[0054] A310: Calculate the process timing deviations based on the combined enumeration results of the multiple standard production control sequences to obtain multiple groups of process timing deviations.

[0055] A320: Calculate the device parameter offsets based on the combined enumeration results of the multiple standard production control sequences to obtain multiple groups of device parameter offsets.

[0056] A330: Construct a task execution matrix based on the multiple product processing tasks.

[0057] A340: Fill the multiple groups of process timing deviations and multiple groups of equipment parameter offsets into the task execution matrix to complete the construction of the difference frequency control matrix.

[0058] Specifically, in this embodiment, by enumerating the combination arrangements of different standard production control sequences, the process timing deviations of each production task in actual execution are analyzed, and multiple possible task arrangements and combinations are generated (such as stainless steel wok → cast iron soup pot → honeycomb non-stick pan, cast iron soup pot → honeycomb non-stick pan → stainless steel wok, etc.), and the difference between the actual execution time and the theoretical time of each process combination is calculated.

[0059] For example, if a stamping process in a task combination theoretically takes 180 seconds but actually takes 190 seconds, then the timing deviation for that process is recorded as ΔT = +10 seconds. Similarly, by traversing all processes and combinations, multiple sets of timing deviation data are accumulated to identify process links and task combination patterns with high-frequency deviations, providing a quantitative basis for subsequent production sequence optimization.

[0060] This embodiment calculates the offset amplitude between the actual operating parameters of the equipment and the theoretical parameters for multiple standard production control sequence combinations generated by enumeration. Specifically, the equipment parameter execution records under each task combination (such as punching machine pressure, spray machine flow, annealing furnace temperature) are traversed, the difference between the theoretical set value and the actual feedback value is compared, and the offset is calculated by parameter type (pressure, flow, temperature, etc.). By counting the offset direction (positive / negative) and amplitude of each device under different combinations, high-frequency offset parameters and associated task combinations are identified to provide data support for equipment stability optimization.

[0061] For example, in a certain task combination, the theoretical flow rate of the sprayer is 40 mL / min, and the actual average flow rate is 38 mL / min. Then, the calculated equipment parameter offset Q = (38-40) / 40×100% = -5%.

[0062] A task execution matrix is constructed based on the multiple product processing tasks, wherein the horizontal and vertical dimensions of the matrix are both the multiple product processing tasks. The multiple sets of process timing deviations and multiple sets of equipment parameter offsets are filled into the task execution matrix to complete the construction of the difference frequency control matrix.

[0063] This embodiment achieves the technical effect of providing reliable reference data for subsequent task execution sequence analysis.

[0064] A400: Constructing a task execution sequence for the plurality of product processing tasks based on the difference frequency control matrix.

[0065] Specifically, in this embodiment, the horizontal and vertical dimensions of the differential frequency control matrix represent different product processing tasks, and the cells store data such as the task switching timing deviation ΔT, equipment parameter offset P, and mold compatibility. By analyzing the inter-task switching impact data quantitatively stored in the matrix, an optimized task execution sequence is dynamically constructed.

[0066] For example, if the timing deviation ΔT of task A→task B in the matrix is +20 seconds (the actual buffer time exceeds the theoretical value), the parameter offset P is +25% (the stamping pressure jump is large), and the mold compatibility is "incompatible", then avoid direct continuous scheduling of A→B and insert low-conflict task C instead (for example, ΔT of A→C in the matrix is +5 seconds, P is -10%, and the mold compatibility is "quick mold change") to generate the sequence [A→C→B]. At the same time, for high-frequency deviation task combinations (for example, ΔT frequency weight of B→D in the matrix is greater than 0.2), a grouped centralized scheduling strategy (such as [B×5→D×5]) is adopted to reduce the number of parameter switching times.

[0067] Driven by matrix data, a task execution sequence that takes into account both efficiency and stability is generated, such as cast iron pots × 5 (high-pressure group) → stainless steel pots × 10 (compatible mold group) → honeycomb pots × 8 (parameter smoothing group), to achieve equipment load balancing and production rhythm optimization under multi-task mixed production.

[0068] A500: Based on the task execution sequence, the plurality of standard production control sequences are subjected to connection difference frequency control identification, and an equipment parameter control conversion sequence is constructed according to the identification results.

[0069] In one embodiment, based on the task execution sequence, the plurality of standard production control sequences are subjected to connection difference frequency control identification, and an equipment parameter control conversion sequence is constructed according to the identification result. Step A500 of the method provided by the present invention further includes:

[0070] A510: Extract a first sequential processing task and a second sequential processing task from the task execution sequence.

[0071] A520: Extract a first standard production control sequence and a second standard production control sequence from the plurality of standard production control sequences according to the first and second time sequence processing tasks.

[0072] A530: Calculate the buffer deviation of the first standard production control sequence and the second standard production control sequence to obtain a first device parameter control conversion time window.

[0073] A540: Compare the first standard production control sequence and the second standard production control sequence to locate N parameter adjustment transition points.

[0074] A550: Based on the process dependency topology, perform equipment collaborative conversion judgment on the N parameter adjustment transition points and output the first equipment parameter control conversion instruction.

[0075] A560: Similarly, multiple device parameter control conversion time windows and multiple device parameter control conversion instructions are obtained.

[0076] A570: Connect the multiple device parameter control conversion time windows and the multiple device parameter control conversion instructions according to the task execution sequence, and output the device parameter control conversion sequence.

[0077] Specifically, in this embodiment, two adjacent processing tasks are extracted from a preset task execution sequence (for example, cast iron pot × 5 → stainless steel pot × 10 → honeycomb pot × 8 arranged by priority), namely, the first sequential processing task (such as cast iron pot production) and the second sequential processing task (such as stainless steel pot production) that follows it.

[0078] A first standard production control sequence and a second standard production control sequence are extracted from the plurality of standard production control sequences according to the first and second time sequence processing tasks.

[0079] The buffer deviation is calculated for the first standard production control sequence and the second standard production control sequence. By comparing the theoretical buffer time (30 seconds) of the final process of Task A (such as the completion of annealing of the cast iron pot) with the actual demand (45 seconds due to the heat dissipation delay of the annealing furnace), the buffer deviation ΔT = +15 seconds is obtained, thereby generating the equipment parameter control conversion time window (for example, the annealing furnace cooling instruction needs to be triggered 15 seconds in advance).

[0080] Subsequently, a full parameter comparison was performed on the first standard production control sequence and the second standard production control sequence to locate key parameter adjustment transition points. For example, the pressure of the stamping machine dropped sharply from 1300 tons to 1050 tons (ΔP=-19.2%), and the flow rate of the spray machine increased from 25mL / min to 35mL / min (ΔQ=+40%). Such transition points require special treatment due to the large amplitude of parameter mutation.

[0081] Finally, based on the equipment coordination rules defined in the process dependency topology (such as "press pressure reduction must be performed after mold disassembly"), the feasibility of each transition point is judged, and equipment parameter control conversion instructions are output (such as "press pressure is adjusted in two stages: 1300→1150→1050 tons, with an interval of 5 seconds between each stage") to ensure that parameter switching complies with the physical constraints of the equipment and process timing requirements, thereby maintaining production line stability and efficiency during task switching.

[0082] Similarly, based on all adjacent task pairs in the task execution sequence, the A510-A550 process is executed in sequence, and the corresponding equipment parameter control conversion time window (such as the annealing furnace cooling window, the mold replacement window) and the equipment parameter control conversion instruction (such as the stamping machine gradient pressure regulation step, the spray flow pre-calibration rule) are generated for each task switching point. According to the original order of the task execution sequence, all time windows and instructions are connected and assembled according to the timing constraints of the process dependency topology. For example, after the production of the cast iron pot is completed, the annealing furnace cooling time window is inserted and the stamping machine pressure reduction instruction is bound. When the production of the stainless steel pot is completed, the mold quick replacement window and the spray flow calibration instruction are triggered. Finally, the output is an equipment parameter control conversion sequence that is strictly aligned with the task execution sequence, ensuring that the start and stop timing, equipment parameter switching steps and buffer intervals of each production task comply with the process dependency rules, forming a complete and controllable multi-task switching control link.

[0083] A600: When executing the task execution sequence to the processing task switching node, the production line equipment group is operated and controlled according to the equipment parameter control conversion sequence.

[0084] Specifically, in this embodiment, when the task execution sequence reaches the processing task switching node (such as the end of cast iron pot production and the start of stainless steel pot production), the operating status of the production line equipment group is dynamically scheduled according to the predefined timing rules in the equipment parameter control conversion sequence (such as the annealing furnace cooling time window is triggered 15 seconds in advance) and the equipment coordination instructions (such as the staged adjustment of the press pressure, the interlocking conditions of the mold disassembly and installation), and ultimately achieve closed-loop operation and control management with seamless connection between multiple tasks, equipment load balancing and stable and controllable production rhythm.

[0085] Example 2 is based on the same inventive concept as the product processing management method under a comprehensive production line in the above embodiment. Figure 2 As shown, the present invention provides a product processing management system for an integrated production line, wherein the system includes:

[0086] The process feature extraction unit 11 is configured to extract a plurality of key process feature sequences of a plurality of product processing tasks from the real-time order information after receiving the real-time order information.

[0087] The process feature mapping unit 12 is used to map the multiple key process feature sequences to an equipment parameter library and output multiple standard production control sequences.

[0088] The difference frequency analysis unit 13 is configured to construct a difference frequency control matrix by performing difference frequency analysis on the plurality of standard production control sequences.

[0089] The execution sequence construction unit 14 is configured to construct a task execution sequence for the plurality of product processing tasks based on the difference frequency control matrix.

[0090] The frequency difference control identification unit 15 is used to perform connection frequency difference control identification on the multiple standard production control sequences based on the task execution sequence, and construct an equipment parameter control conversion sequence according to the identification result.

[0091] The operation control management execution unit 16 is used to perform operation control management on the production line equipment group according to the equipment parameter control conversion sequence when executing the task execution sequence to the processing task switching node.

[0092] In one embodiment, the process feature extraction unit 11 is further configured to:

[0093] The real-time order information is obtained by receiving orders from multiple sources; based on process feature classification rules, the real-time order information is subjected to field extraction using NPL technology to obtain multiple task-related fields for multiple production and processing tasks, wherein the task-related fields are composed of cookware material features, cookware structure features, and cookware coating requirements; process parameter mapping is performed based on the multiple task-related fields to obtain the multiple key process feature sequences.

[0094] In one embodiment, the process feature extraction unit 11 is further configured to:

[0095] Process parameter mapping is performed based on the multiple task association fields to output multiple process requirement feature parameter groups; process dependency topology is locally called; and the multiple process requirement feature parameter groups are dynamically prioritized based on the process dependency topology to obtain the multiple key process feature sequences.

[0096] In one embodiment, the difference frequency control identification unit 15 is further configured to:

[0097] Extract the first sequential processing task and the second sequential processing task from the task execution sequence; extract the first standard production control sequence and the second standard production control sequence from the multiple standard production control sequences based on the first sequential processing task and the second sequential processing task; perform buffer deviation calculation on the first standard production control sequence and the second standard production control sequence to obtain a first equipment parameter control conversion time window; compare the first standard production control sequence and the second standard production control sequence to locate N parameter adjustment transition points; perform equipment collaborative conversion judgment on the N parameter adjustment transition points based on the process dependency topology, and output a first equipment parameter control conversion instruction; and so on, obtain multiple equipment parameter control conversion time windows and multiple equipment parameter control conversion instructions; connect the multiple equipment parameter control conversion time windows and the multiple equipment parameter control conversion instructions based on the task execution sequence, and output the equipment parameter control conversion sequence.

[0098] In one embodiment, the process feature mapping unit 12 is further configured to:

[0099] The multiple key process feature sequences are mapped to the equipment parameter library to obtain multiple benchmark production control sequences; multiple equipment status information sequences of the multiple production line equipment sequences corresponding to the multiple benchmark production control sequences are locally called; the multiple benchmark production control sequences are dynamically compensated based on the multiple equipment status information sequences, and multiple compensated production control sequences are output; the equipment beat collaborative optimization of the multiple compensated production control sequences is performed according to the process dependency topology, and the multiple standard production control sequences are output.

[0100] In one embodiment, the difference frequency analysis unit 13 is further configured to:

[0101] According to the combined enumeration results of the multiple standard production control sequences, the process timing deviation is calculated to obtain multiple groups of process timing deviations; according to the combined enumeration results of the multiple standard production control sequences, the equipment parameter offset is calculated to obtain multiple groups of equipment parameter offsets; a task execution matrix is constructed based on the multiple product processing tasks; the multiple groups of process timing deviations and the multiple groups of equipment parameter offsets are filled into the task execution matrix to complete the construction of the difference frequency control matrix.

[0102] Example 3, Figure 3 This is a structural diagram of an electronic device provided in Example 3 of the present invention, and is a block diagram of an exemplary electronic device suitable for implementing an embodiment of the present invention. Figure 3 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0103] like Figure 3 As shown, the electronic device includes a processor 21, a memory 22, an input device 23 and an output device 24; the number of processors 21 in the electronic device can be one or more. Figure 2 Taking a processor 21 as an example, the processor 21, memory 22, input device 23 and output device 24 in the electronic device can be connected through a bus or other means. Figure 2 The bus connection is taken as an example.

[0104] Any of the methods or steps described above may be stored as computer instructions or programs in various types of computer memories, and the computer instructions or programs may be recognized by various types of computer processors to implement any of the methods or steps described above.

[0105] Based on the above specific embodiments of the present invention, any improvements and modifications made to the present invention by those skilled in the art without departing from the principles of the present invention shall fall within the scope of patent protection of the present invention.

Claims

1. A product processing management method under an integrated production line, characterized in that: The method comprises: After receiving the real-time order information, extracting a plurality of key process feature sequences of a plurality of product processing tasks from the real-time order information; Mapping the multiple key process feature sequences to an equipment parameter library and outputting multiple standard production control sequences; Constructing a difference frequency control matrix by performing difference frequency analysis on the plurality of standard production control sequences; constructing a task execution sequence for the plurality of product processing tasks based on the difference frequency control matrix; Based on the task execution sequence, the plurality of standard production control sequences are subjected to connection difference frequency control identification, and an equipment parameter control conversion sequence is constructed according to the identification result; When executing the task execution sequence to the processing task switching node, the production line equipment group is operated and controlled according to the equipment parameter control conversion sequence.

2. The product processing management method under the integrated production line according to claim 1, characterized in that: After receiving real-time order information, extracting multiple key process feature sequences of multiple product processing tasks from the real-time order information, the method includes: Obtaining the real-time order information by receiving orders from multiple sources; Based on the process feature classification rules, NPL technology is used to extract fields from the real-time order information to obtain multiple task-related fields of multiple production and processing tasks; Process parameter mapping is performed according to the multiple task association fields to obtain the multiple key process feature sequences.

3. The product processing management method under the integrated production line according to claim 2, characterized in that: Process parameter mapping is performed based on the multiple task-related fields to obtain the multiple key process feature sequences, the method comprising: Performing process parameter mapping according to the plurality of task-related fields, and outputting a plurality of process requirement characteristic parameter groups; Local call process dependency topology; The multiple process requirement feature parameter groups are dynamically prioritized according to the process dependency topology to obtain the multiple key process feature sequences.

4. The product processing management method under the integrated production line according to claim 3, characterized in that: Based on the task execution sequence, the plurality of standard production control sequences are subjected to connection difference frequency control identification, and an equipment parameter control conversion sequence is constructed according to the identification result. The method includes: extracting a first time-series processing task and a second time-series processing task from the task execution sequence; extracting a first standard production control sequence and a second standard production control sequence from the plurality of standard production control sequences according to the first time sequence processing task and the second time sequence processing task; Calculate the buffer deviation of the first standard production control sequence and the second standard production control sequence to obtain a first device parameter control conversion time window; Comparing the first standard production control sequence with the second standard production control sequence, locating N parameter adjustment transition points; According to the process dependency topology, performing equipment collaborative conversion judgment on the N parameter adjustment transition points, and outputting a first equipment parameter control conversion instruction; By analogy, multiple device parameter control conversion time windows and multiple device parameter control conversion instructions are obtained; The plurality of device parameter control conversion time windows and the plurality of device parameter control conversion instructions are connected according to the task execution sequence, and the device parameter control conversion sequence is output.

5. The product processing management method under the integrated production line according to claim 3, characterized in that: Mapping the multiple key process feature sequences to an equipment parameter library and outputting multiple standard production control sequences, the method includes: Mapping the multiple key process feature sequences to the equipment parameter library to obtain multiple benchmark production control sequences; locally calling a plurality of equipment status information sequences of a plurality of production line equipment sequences corresponding to the plurality of reference production control sequences; Dynamically compensating the multiple reference production control sequences based on the multiple equipment status information sequences, and outputting multiple compensated production control sequences; The equipment tact collaborative optimization of the multiple compensation production control sequences is performed according to the process dependency topology, and the multiple standard production control sequences are output.

6. The product processing management method under the integrated production line according to claim 2, characterized in that: The task-related fields are composed of the material characteristics of the cookware, the structural characteristics of the cookware, and the coating requirements of the cookware.

7. The product processing management method under the integrated production line according to claim 1, characterized in that: By performing a difference frequency analysis on the plurality of standard production control sequences, a difference frequency control matrix is constructed, the method comprising: Calculating process timing deviations based on the combined enumeration results of the plurality of standard production control sequences to obtain a plurality of groups of process timing deviations; Calculating device parameter offsets based on the combined enumeration results of the plurality of standard production control sequences to obtain a plurality of sets of device parameter offsets; constructing a task execution matrix based on the plurality of product processing tasks; The multiple groups of process timing deviations and multiple groups of equipment parameter offsets are filled into the task execution matrix to complete the construction of the difference frequency control matrix.

8. A product processing management system under an integrated production line, characterized in that: The steps for implementing the method according to any one of claims 1 to 7 include: A process feature extraction unit is configured to extract a plurality of key process feature sequences of a plurality of product processing tasks from the real-time order information after receiving the real-time order information; A process feature mapping unit, configured to map the plurality of key process feature sequences to an equipment parameter library and output a plurality of standard production control sequences; a difference frequency analysis unit, configured to construct a difference frequency control matrix by performing difference frequency analysis on the plurality of standard production control sequences; an execution sequence construction unit, configured to construct a task execution sequence for the plurality of product processing tasks based on the difference frequency control matrix; A frequency difference control identification unit is used to perform connection frequency difference control identification on the plurality of standard production control sequences based on the task execution sequence, and to construct an equipment parameter control conversion sequence according to the identification result; The operation control management execution unit is used to perform operation control management on the production line equipment group according to the equipment parameter control conversion sequence when executing the task execution sequence to the processing task switching node.

9. An electronic device, characterized in that: The electronic device comprises: a memory for storing executable instructions; The processor is configured to implement a product processing management method under an integrated production line according to any one of claims 1 to 7 when executing the executable instructions stored in the memory.

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