Intelligent scheduling system for finish machining and finish machining single station

Abstract

The invention provides an intelligent scheduling system for finish machining and finish machining single stations, the intelligent scheduling system comprises at least two finish machining single stations and a scheduling device, a finish machining process at least comprises two procedures, and at least one finish machining single station executes operation in any procedure; the number of the finish machining single stations corresponding to any working procedure is positively correlated with the machining implementation of the working procedure; and the scheduling device identifies the raw materials and matches the corresponding treatment process, and the number of finish machining single stations adopted in each procedure is matched according to the machining time of different procedures in the treatment process. The corresponding number of finish machining single stations are distributed according to the machining time of the working procedures in the machining technology, the machining efficiency of a production line can be improved, the modular single station design is utilized, technology development and market changes can be better adapted, meanwhile, the maintenance and upgrading processes are simplified, the overall efficiency of the system is improved, and the service life of the system is prolonged. The modular design not only reduces the long-term operation cost, but also provides convenience for future technical innovation and function extension.

Description

Technical Field

[0001] The present invention relates to the technical field of food processing, and in particular to an intelligent scheduling system and a single finishing station for finishing. Background Art

[0002] There are still many processes in the food deep processing industry that need to be completed manually, especially in the field of fine meat cutting. This field faces many challenges: the types, sizes, and postures of incoming food raw materials are diverse, and deep-processed products change rapidly with market demand, requiring factories to be flexible in changing models and lines. The fine cutting process is complex, and the quality requirements for finished product weight, size, appearance, etc. are high, and the utilization rate of meat raw material cutting is also high. It is difficult to recruit workers manually, the labor force is seriously aging, and the training cycle is long, the cost is high, and the high turnover rate leads to poor production stability. Traditional large-scale automated equipment lacks flexibility and is difficult to cope with a variety of incoming materials, and often leads to reduced raw material utilization.

[0003] Currently, manual cutting is the common method used in the market for fine processing. A small number of large-scale special equipment uses infrared scanning to identify the volume (length, width and height) of the raw materials, and uses flying knives in fixed positions to perform quantitative cutting of the raw materials and process them to the target volume.

[0004] In the prior art, a dedicated machine equipment must perform multiple processes during fine processing, and the equipment needs to be switched when performing different processes, which affects the processing efficiency and needs to be improved. Summary of the invention

[0005] In view of the defects in the prior art, the object of the present invention is to provide an intelligent scheduling system for fine machining and a fine machining single station.

[0006] According to the present invention, an intelligent scheduling system for fine machining includes at least two fine machining stations and a scheduling device. The fine machining process includes at least two processes, and at least one fine machining station performs the operation in any process.

[0007] The number of finishing stations corresponding to any process is positively correlated with the processing realization of the process;

[0008] The scheduling device identifies the raw materials and matches the corresponding processing technology, and matches the number of finishing stations used in each process according to the processing time of different processes in the processing technology.

[0009] Preferably, the processing process includes cutting the meat material;

[0010] The cutting process of meat materials includes:

[0011] First cut: The first cut is made from the top of the material to be processed and cuts into the material at an angle, and removes the excess height in the height cutting strategy and the excess length in the length cutting strategy in a continuous manner;

[0012] Second cut: The second cut is to cut into the material to be processed vertically, comprehensively removing the excess weight in the weight cutting strategy and the excess width in the width cutting strategy;

[0013] The time for finishing single station to execute the first cut is X times the time for executing the second cut, and the number of finishing single stations to execute the first cut is X times the number of finishing single stations to execute the second cut.

[0014] Preferably, the material processed in the previous process is conveyed to the next process for processing via a conveyor belt.

[0015] A single finishing station provided according to the present invention also includes:

[0016] Loading module: provides materials to be processed;

[0017] Transport module: transport the materials to be processed to the target location;

[0018] Identification and calculation module: collects data of the material to be processed, the data at least including: one or more of the type of the material to be processed, the weight of the material to be processed, the length of the material to be processed, the width of the material to be processed, and the height of the material to be processed;

[0019] Auxiliary processing module: adjust the posture of the material to be processed;

[0020] Execution module: Process the materials to be processed according to the instructions;

[0021] Unloading module: classify and unload the processed materials.

[0022] Preferably, the transport module comprises a turntable, and at least two loading stations are arranged on the turntable;

[0023] The feeding module includes an inductive grating and a feeding robot arm. The feeding robot arm places the material to be processed into a designated feeding position, and the inductive grating feedback data monitors the feeding status in real time.

[0024] Preferably, the turntable rotates to rotate the loading station to the designated loading position in sequence for loading, then rotates to the identification and calculation module to collect data of the material to be processed, then rotates to the auxiliary processing module to adjust the posture of the material to be processed, then rotates to the execution module to process the material to be processed according to the instructions, then rotates to the unloading module to classify and unload the processed materials, and then rotates to the loading position for loading.

[0025] Preferably, the recognition and calculation module includes a 3D camera. When the material to be processed moves to the bottom of the recognition and calculation module, the 3D camera takes a picture of the material to be processed below it and performs 3D recognition. The recognized data will be converted into volume and weight data through the segformer_b2 semantic segmentation model visual algorithm for calculation by the cutting model.

[0026] Preferably, the auxiliary processing module includes a rotating device to rotate the material tray of the loading station to adjust the posture of the processed material.

[0027] Preferably, the execution module comprises a multi-degree-of-freedom robot arm, a processing end and an auxiliary end, wherein the processing end is mounted on the multi-degree-of-freedom robot arm;

[0028] The auxiliary end contacts the material to be processed to fix the material to be processed, and the multi-degree-of-freedom robotic arm drives the processing end to execute the preset processing process on the material to be processed.

[0029] Preferably, a single finishing station for performing different processes in a process production line includes:

[0030] The finishing station in the initial process collects data on the material to be processed and generates an overall processing strategy. The finishing station in the subsequent process can execute the processing strategy of the corresponding process.

[0031] Or, the finishing station of any process collects data of the material to be processed, generates and executes the processing strategy of the process.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. The present invention helps to improve the processing efficiency of the production line by allocating a corresponding number of finishing stations according to the processing time of the process in the processing technology. The modular single-station design can better adapt to technological development and market changes, and greatly simplify the maintenance and upgrade process, thereby improving the overall efficiency and life of the system. This modular design not only reduces long-term operating costs, but also facilitates future technological innovation and functional expansion.

[0034] 2. The present invention can be flexibly spliced ​​through a single station, adapted to a variety of complex process flows, matched with existing manual and automated equipment, and formed into a variety of production lines to meet different product needs.

[0035] 3. The present invention improves the utilization rate of raw materials by simulating manual cutting, performs real-time dynamic identification and calculation according to different raw materials, processes the raw materials with the optimal solution, and ensures the maximum utilization rate of raw materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0037] Figure 1 This is a flow chart of the intelligent finishing method mainly embodied in the present invention;

[0038] Figure 2 This is a top view of the overall structure of the intelligent finishing single station mainly embodied in the present invention;

[0039] Figure 3 This is a schematic diagram of the overall structure of the feeding module mainly embodied in the present invention;

[0040] Figure 4 This is a schematic diagram of the overall structure of the identification and calculation module mainly embodied in the present invention;

[0041] Figure 5 This is a schematic diagram of the overall structure of the auxiliary processing module mainly embodied in the present invention;

[0042] Figure 6 This is a schematic diagram of the overall structure of the execution module mainly embodied in the present invention;

[0043] Figure 7 This is a schematic diagram of the overall structure of the blanking module mainly embodied in the present invention. DETAILED DESCRIPTION

[0044] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0045] Embodiment 1

[0046] like Figure 1 As shown, an intelligent finishing method according to the present invention comprises the following steps:

[0047] Step S1, transporting the material to be processed to the target location.

[0048] Step S2, collecting data of the material to be processed, the data at least including: one or more of the type of the material to be processed, the weight of the material to be processed, the length of the material to be processed, the width of the material to be processed, and the height of the material to be processed.

[0049] Step S3: Compare the collected data of the material to be processed with the target finished product index to generate a processing strategy.

[0050] Step S4: Process the material to be processed according to the generated processing strategy.

[0051] Step S5, compare the material processed in step S4 with the target finished product index. If the material meets the standard, the material is unloaded; if the material does not meet the standard, repeat steps S1 to S5.

[0052] It should be noted that the technical solution of the present application generates a processing strategy by comparing the data of the material to be processed with the target finished product indicators, and then processes the material to be processed according to the generated processing strategy to obtain the target finished product, thereby greatly reducing the dependence on skilled workers and reducing labor costs and training costs. Compared with manual labor, equipment can directly bring effective input-output and further reduce the factory's production costs.

[0053] It should be noted that the intelligent finishing method of the present application can be configured with different functions such as peeling, deboning, splitting, and trimming.

[0054] In a feasible implementation, for step S2, a deep learning algorithm is used to quickly identify meat materials of different types and shapes. The method includes the following sub-steps:

[0055] Sub-step S2.1, collect pictures of the materials to be processed at the target location, and use the semantic segmentation model to identify the raw materials. Specifically, the segformer_b2 semantic segmentation model is used to identify the raw materials.

[0056] Sub-step S2.2: converting the shape of the material to be processed into a virtual point cloud model.

[0057] Sub-step S2.3: Analyze the length, width and height of the material to be processed, and further calculate the volume of the material to be processed.

[0058] Sub-step S2.4: locating density data using an adaptive density algorithm.

[0059] Sub-step S2.5: Calculate the weight of the material to be processed according to the volume and density data of the material to be processed.

[0060] In a feasible implementation: Adaptive processing path planning: dynamically adjust the processing strategy according to the characteristics of the raw material, taking cutting as an example. Combine the visual system and force feedback data to plan the optimal cutting path in real time. For example, when encountering hard structures such as bones or fascia, the cutting angle and depth are automatically adjusted. For step S3:

[0061] The length of the material to be processed is compared with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a length cutting strategy is generated. If it meets the standard, no length cutting strategy is generated.

[0062] The height of the material to be processed is compared with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a height cutting strategy is generated. If it meets the standard, no height cutting strategy is generated.

[0063] The width of the material to be processed is compared with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a width cutting strategy is generated. If it meets the standard, no width cutting strategy is generated.

[0064] The weight of the material to be processed is compared with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a weight cutting strategy is generated. If it meets the standard, no weight cutting strategy is generated.

[0065] Initial cutting strategies include:

[0066] First cut: The first cut is made from the top of the material to be processed and cuts into the material at an angle, and removes the excess height in the height cutting strategy and the excess length in the length cutting strategy in a continuous manner;

[0067] Second cut: The second cut is to cut into the material to be processed vertically, comprehensively removing the excess weight in the weight cutting strategy and the excess width in the width cutting strategy.

[0068] Also included are optimized cutting strategies, including:

[0069] According to the information collected in step S2, the abnormal points on the cutting path that affect the cutting factors are determined, and the cutting path is adjusted to bypass the abnormal points that affect the cutting factors to form an optimized cutting path.

[0070] Step S4 further includes the following sub-steps:

[0071] Sub-step S4.1, the tool executes the cutting strategy generated in step S3 to cut the material to be processed;

[0072] Sub-step S4.2: During the cutting process, the force feedback data of the tool is monitored in real time. When the force feedback data is abnormal, one or more actions of the tool's cutting angle, cutting force, and cutting depth are adjusted, and the operation is repeated until the cutting is completed.

[0073] In summary: by comparing the volume and weight of the raw materials with the target data, the manual cutting model is simulated to plan the preliminary cutting path; through visual data, abnormal points such as bones, fascia, skin, etc. that may affect the cutting factors on the path are identified, and the final path is planned based on the abnormal points on the basis of the preliminary path, and the robotic arm is driven to cut; during the cutting process, the force feedback data is monitored in real time. If the force feedback data fluctuates significantly (touching abnormal points that affect the cutting), the algorithm will correct and adjust in real time along the force fluctuation path, adjust the cutting angle, force, depth and other actions in real time, and repeat this process until the end.

[0074] The technical solution of this application: To achieve accurate and smooth cutting action, a high-precision multi-joint force-controlled robotic arm is used to monitor the force changes during the cutting process in real time, and dynamically adjust the cutting force according to different meat quality and bone structure. The use of advanced algorithms such as force-position hybrid control makes the robotic arm have a certain degree of "flexibility" during the cutting process, similar to the flexibility of human hands, and can automatically adjust the movement trajectory according to the changes in meat quality to avoid excessive or insufficient cutting.

[0075] An intelligent finishing system provided according to the present invention comprises the following modules:

[0076] Module M1, used to transport the material to be processed to the target location;

[0077] Module M2, used for collecting data of materials to be processed, the data at least including: one or more of the type of materials to be processed, the weight of materials to be processed, the length of materials to be processed, the width of materials to be processed and the height of materials to be processed;

[0078] Module M3, used to compare the collected data of the material to be processed with the target finished product index to generate a cutting strategy;

[0079] Module M4 is used to cut the material to be processed according to the generated cutting strategy.

[0080] Preferably, for module M3, for step S3:

[0081] Compare the length of the material to be processed with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a length cutting strategy is generated. If it meets the standard, no length cutting strategy is generated;

[0082] Compare the height of the material to be processed with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a height cutting strategy is generated. If it meets the standard, no height cutting strategy is generated;

[0083] Compare the width of the material to be processed with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a width cutting strategy is generated. If it meets the standard, no width cutting strategy is generated.

[0084] Compare the weight of the material to be processed with the target finished product index data to determine whether it meets the standard. If it does not meet the standard, a weight cutting strategy is generated. If it meets the standard, no weight cutting strategy is generated;

[0085] Initial cutting strategies include:

[0086] First cut: The first cut is made from the top of the material to be processed and cuts into the material at an angle, and removes the excess height in the height cutting strategy and the excess length in the length cutting strategy in a continuous manner;

[0087] Second cut: The second cut is to cut into the material to be processed vertically, comprehensively removing the excess weight in the weight cutting strategy and the excess width in the width cutting strategy;

[0088] Also included are optimized cutting strategies, including:

[0089] The abnormal points on the cutting path that affect the cutting factors are determined based on the information collected in the module M2, and the cutting path is adjusted to bypass the abnormal points that affect the cutting factors to form an optimized cutting path.

[0090] Preferably, the module M4 further includes the following submodules:

[0091] Submodule M4.1 and tool execution module M3 generate cutting strategies to cut the material to be processed;

[0092] Submodule M4.2: During the cutting process, the force feedback data of the tool is monitored in real time. When the force feedback data is abnormal, one or more actions of the tool's cutting angle, cutting force, and cutting depth are adjusted, and the operation is repeated until the cutting is completed.

[0093] Preferably, the method further includes step M5, comparing the material cut in step M4 with the target finished product index;

[0094] If the material meets the standards, unloading is completed;

[0095] If the material does not meet the standards, repeat steps S1 to S5.

[0096] Embodiment 2

[0097] Based on Example 1, an intelligent finishing station provided according to the present invention is used to execute the intelligent finishing method in Example 1. It should be noted that the intelligent finishing station of the present application is integrated on a frame, and the bottom of the frame has universal wheels and telescopic support feet, which can realize the line rotation arrangement of the intelligent finishing station.

[0098] like Figure 2 , Figure 3 , Figure 4 , Figure 5 , Figure 6 as well as Figure 7 , also includes:

[0099] The loading module provides the materials to be processed. The transport module transports the materials to be processed to the target location. The identification and calculation module collects the data of the materials to be processed, and the data at least includes: one or more of the type of materials to be processed, the weight of the materials to be processed, the length of the materials to be processed, the width of the materials to be processed, and the height of the materials to be processed. The auxiliary processing module adjusts the posture of the materials to be processed. The execution module processes the materials to be processed according to the instructions. The unloading module classifies and unloads the processed materials.

[0100] Specifically, the transport module includes a turntable, and at least two loading stations are arranged on the turntable. In a specific embodiment, eight loading stations are arranged at equal intervals around the turntable, and each loading station is provided with a material tray for holding the material to be processed. It should be noted that the turntable of the present application can be driven to rotate by a drive member such as a motor in the prior art.

[0101] The turntable rotates to turn the loading station to the designated loading position in sequence for loading, then turns to the identification and calculation module to collect data of the material to be processed, then turns to the auxiliary processing module to adjust the posture of the material to be processed, then turns to the execution module to process the material to be processed according to the instructions, then turns to the unloading module to classify and unload the processed materials, and then turns to the loading position for loading.

[0102] The loading module includes an inductive grating and a loading robot. The loading robot puts the material to be processed into the designated loading position, and the inductive grating feedback data monitors the loading situation in real time. The loading robot grabs the material to be processed and puts it into the material tray on the loading station at the loading position. The loading situation is monitored in real time through the dual feedback data of vision and grating, and the equipment is intelligently controlled in real time through different loading states, such as: waiting, pausing, stopping or others.

[0103] The recognition and calculation module includes a 3D camera. When the material to be processed moves to the bottom of the recognition and calculation module, the 3D camera takes a picture of the material to be processed below it and performs 3D recognition. The recognized data will be converted into volume and weight data through the segformer_b2 semantic segmentation model visual algorithm for calculation by the cutting model.

[0104] The auxiliary processing module includes a rotating device that rotates the material tray of the loading station to adjust the posture of the material to be processed. The rotating device may include a clamp and a rotating motor. The clamp grasps the material tray downward, and the rotating motor drives the clamp and the material tray to rotate a certain angle together. It should be noted that the auxiliary processing module adjusts the posture of the material to be processed in advance, reduces the movement of the execution module robot, and improves the efficiency of the execution module robot. It should be noted that the auxiliary processing module can also integrate the function of simple pre-cutting of the material to be processed, as well as other simple auxiliary functions.

[0105] The execution module includes a multi-degree-of-freedom robot arm, a processing end and an auxiliary end. The processing end is installed on the multi-degree-of-freedom robot arm. The auxiliary end contacts the material to be processed to fix the material to be processed, and the multi-degree-of-freedom robot arm drives the processing end to perform the preset processing process on the material to be processed. The multi-degree-of-freedom robot arm has a force feedback module.

[0106] Specifically, when the raw materials are transferred to the main processing position, the free-degree-of-freedom robot arm will drive the processing end and the auxiliary end to process the materials to be processed. The single station will replace the processing end according to different raw materials: such as knives, scissors, rollers, etc. And auxiliary ends, such as fixed pressure plates, fixed needles, etc. The processing end cooperates with the auxiliary end to perform complex actions on the raw materials. For example, cutting, engraving, etc. The scraps generated during the processing will enter the collection tank from the funnel, and the processing scraps can be collected and reused. Because different SKU processing will produce different scraps, the system will intelligently determine the ownership of the scraps through the SKU being processed to maximize the utilization rate of raw materials.

[0107] When the system determines that the material processing is completed, the processed material is transported to the first unloading station, and the dial plate of the unloading module dials the processed material to the second unloading station. When the processed material is delivered to the second unloading station, the processed material is weighed and visually identified to determine the SKU of the finished product. After the system determines the SKU to which the finished product belongs by the weight and appearance of the material, it controls the dial plate to divert the finished product into the finished product trough for transportation to the subsequent process.

[0108] This application uses a modular single-station design to better adapt to technological development and market changes, while greatly simplifying the maintenance and upgrade process and improving the overall efficiency and life of the system. This modular design not only reduces long-term operating costs, but also facilitates future technological innovation and functional expansion.

[0109] Each module (such as the robot arm, vision system, cutting tool, etc.) is a relatively independent unit, and each module can be developed, tested and optimized separately without affecting the overall system. When technology advances or market demand changes, individual modules can be easily replaced or upgraded. For example, the appropriate cutting tool module can be selected for different types of meat processing, and a more advanced visual recognition module can be replaced without changing the entire system. The system can be quickly adjusted or reconfigured according to different production line requirements, for example, adding or reducing cutting stations, adjusting the conveyor speed, etc.

[0110] When a problem occurs in the system, the specific module can be quickly located and only the faulty module can be replaced or repaired, reducing downtime and repair costs. The control software can be modularly designed to facilitate updates for specific functions, and new functions can be easily added or algorithms optimized without affecting other parts.

[0111] Flexible response to a variety of incoming materials, improve equipment utilization, users can use a single station to create a variety of raw material product production lines, flexible and convenient, with high reuse rate. Single stations can be flexibly spliced, adapted to a variety of complex process flows, and matched with existing manual and automated equipment to form a variety of production lines to meet different product needs.

[0112] Simulate manual cutting to improve raw material utilization: This single station will perform real-time dynamic identification and calculation based on different raw materials, process the raw materials with the optimal solution, and ensure maximum raw material utilization.

[0113] High cutting quality: This single station will continuously optimize the processing technology through deep learning of artificial intelligence, so that the single station can reach the processing level of manual or even better than manual.

[0114] Small footprint, suitable for processing companies of all sizes: This single station only takes up the workspace of one person, but the output exceeds that of one person, further improving the efficiency of the factory.

[0115] Modular design, easy to operate, upgrade and maintain: The display screen is intuitive to operate, and the functions are convenient and simple, which reduces the cost of worker training. The control system warns of problems, monitors the operating status, and reasonably configures the process. It can also continuously optimize system operations through remote upgrades and conduct unified management and analysis of production data.

[0116] Scalability: It can start from a small scale in the early stage, and gradually expand the scale of production line as demand increases, so that enterprises can make gradual upgrades according to actual conditions and budgets. A single intelligent single station can adapt to different types of processing tasks by replacing tools or adjusting parameters, such as deboning and slicing for fish processing, slicing and shaping for cooked food processing, and decorating and cutting for pastry processing.

[0117] Embodiment 3

[0118] Based on the first and second embodiments, the present invention provides an intelligent scheduling system for finishing, including at least two finishing stations and a scheduling device, wherein the finishing process includes at least two procedures, and at least one finishing station performs the operation in any procedure. The number of finishing stations corresponding to any procedure is positively correlated with the processing realization of the procedure. The scheduling device identifies the raw material and matches the corresponding processing process, and matches the number of finishing stations used in each process according to the processing time of different procedures in the processing process.

[0119] The processing process includes cutting meat materials; the cutting process of meat materials includes: first cut: the first cut is cut into the material from the top of the material to be processed obliquely, and the excess height in the height cutting strategy and the excess length in the length cutting strategy are continuously removed; second cut: the second cut is cut into the material to be processed with a vertical cut, and the excess weight in the weight cutting strategy and the excess width in the width cutting strategy are comprehensively removed; the time for the finishing single station to execute the first cut is X times the time for executing the second cut, and the number of finishing single stations executing the first cut is X times the number of finishing single stations executing the second cut. X is an integer. For example, if the processing time of the first cut is 6S and the processing time of the second cut is 2S, then 3 finishing single stations need to be configured to execute the first cut, and 1 finishing single station needs to be configured to execute the second cut. For example, if the processing time of the first cut is 6S and the processing time of the second cut is 2S, then 3 finishing single stations need to be configured to execute the first cut, and 1 finishing single station needs to be configured to execute the second cut.

[0120] It should be noted that the cutting strategy for meat materials can be generated using the method in Example 1.

[0121] The materials processed by the previous process are conveyed to the next process through the conveyor belt for processing. For the finishing stations that perform different processes in a process production line, it includes: the finishing station located in the initial process collects the data of the materials to be processed and generates the overall processing strategy, and the finishing stations of the subsequent processes can execute the processing strategy of the corresponding process; or, the finishing stations of any process collect the data of the materials to be processed, generate the processing strategy of the process and execute it.

[0122] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0123] In the description of the present application, it should be understood that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0124] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An intelligent scheduling system for finishing, characterized in that: It includes at least two finishing stations and a dispatching device. The finishing process includes at least two processes. Each process is performed by at least one finishing station. The number of finishing stations corresponding to any process is positively correlated with the processing realization of the process; The scheduling device identifies the raw materials and matches the corresponding processing technology, and matches the number of finishing stations used in each process according to the processing time of different processes in the processing technology.

2. The intelligent scheduling system for finishing according to claim 1, characterized in that: The processing includes cutting of meat materials; The cutting process of meat materials includes: First cut: The first cut is made from the top of the material to be processed and cuts into the material at an angle, and removes the excess height in the height cutting strategy and the excess length in the length cutting strategy in a continuous manner; Second cut: The second cut is to cut into the material to be processed vertically, comprehensively removing the excess weight in the weight cutting strategy and the excess width in the width cutting strategy; The time for finishing single station to execute the first cut is X times the time for executing the second cut, and the number of finishing single stations to execute the first cut is X times the number of finishing single stations to execute the second cut.

3. The intelligent scheduling system for finishing according to claim 1, characterized in that: The materials processed in the previous process are transported to the next process for processing via conveyor belts.

4. A single finishing station, characterized in that: The intelligent scheduling system for finishing according to any one of claims 1 to 3, further comprising: Loading module: provides materials to be processed; Transport module: transport the materials to be processed to the target location; Identification and calculation module: collects data of the material to be processed, the data at least including: one or more of the type of the material to be processed, the weight of the material to be processed, the length of the material to be processed, the width of the material to be processed, and the height of the material to be processed; Auxiliary processing module: adjust the posture of the material to be processed; Execution module: Process the materials to be processed according to the instructions; Unloading module: classify and unload the processed materials.

5. The finishing station according to claim 4, characterized in that: The transport module comprises a turntable, on which at least two loading stations are arranged; The feeding module includes an inductive grating and a feeding robot arm. The feeding robot arm places the material to be processed into a designated feeding position, and the inductive grating feedback data monitors the feeding status in real time.

6. The finishing station according to claim 5, characterized in that: The turntable rotates to rotate the loading station to the designated loading position in sequence for loading, then rotates to the identification and calculation module to collect data of the material to be processed, then rotates to the auxiliary processing module to adjust the posture of the material to be processed, then rotates to the execution module to process the material to be processed according to the instructions, then rotates to the unloading module to classify and unload the processed materials, and then rotates to the loading position for loading.

7. The finishing station according to claim 4, characterized in that: The recognition and calculation module includes a 3D camera. When the material to be processed moves to the bottom of the recognition and calculation module, the 3D camera takes a picture of the material to be processed below it and performs 3D recognition. The recognized data will be converted into volume and weight data through the segformer_b2 semantic segmentation model visual algorithm for calculation by the cutting model.

8. The finishing station according to claim 4, characterized in that: The auxiliary processing module includes a rotating device to rotate the material tray of the loading station to adjust the posture of the processed material.

9. The finishing station according to claim 4, characterized in that: The execution module includes a multi-degree-of-freedom robot arm, a processing end, and an auxiliary end, wherein the processing end is installed on the multi-degree-of-freedom robot arm; The auxiliary end contacts the material to be processed to fix the material to be processed, and the multi-degree-of-freedom robotic arm drives the processing end to execute the preset processing process on the material to be processed.

10. The finishing station according to claim 4, characterized in that: A single finishing station for performing different processes in a process production line, including: The finishing station in the initial process collects data on the material to be processed and generates an overall processing strategy. The finishing station in the subsequent process can execute the processing strategy of the corresponding process. Or, the finishing station of any process collects data of the material to be processed, generates and executes the processing strategy of the process.

Images