Workstation control method, apparatus, device, medium, and product
By using digital twin 3D models to simulate and monitor workstation operations in real time, the inefficiency and safety hazards caused by the reliance on manual intervention in traditional workstations have been resolved, achieving efficient and reliable sample processing flow control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 蒙牛乳业(宁夏)有限公司
- Filing Date
- 2024-12-20
- Publication Date
- 2026-06-23
AI Technical Summary
Traditional workstations rely on manual intervention, resulting in low efficiency, error-proneness, inaccurate data, difficulty in achieving systematic and timely analysis, inability to respond to anomalies in real time, and increased security risks and quality hazards.
The system simulates workstation operation using a digital twin 3D model, monitors and generates control commands in real time, updates the model with real data, detects and reports anomalies, and displays abnormal situations using early warning messages and visualizations.
It improves the accuracy and reliability of workstation operation, reduces the risk of errors and malfunctions, and achieves efficient control and optimization of the sample processing flow.
Smart Images
Figure CN122260924A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of sample processing technology, and in particular to a workstation control method, apparatus, equipment, medium, and product. Background Technology
[0002] Currently, traditional workstations primarily rely on manual intervention for sample processing. From sample reception, labeling, and allocation to specific workstations, to task planning and execution, and finally to result recording and feedback, the entire process involves numerous manual steps, which is not only inefficient but also prone to errors. For example, manually recording sample information may lead to inaccurate or missing data; manually adjusting workstation environmental parameters and equipment operating status is difficult to guarantee accuracy and consistency; and the organization and analysis of historical sample processing data lacks systematicity and timeliness, making it difficult to effectively guide the optimization of subsequent processing tasks. Therefore, manual monitoring of the processing process struggles to respond to anomalies in real time, increasing safety risks and potential quality issues. Summary of the Invention
[0003] This invention provides a workstation control method to address the deficiencies in the prior art.
[0004] This invention provides a workstation control method, comprising: Receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation task that the workstation to be controlled needs to perform on the sample to be processed. The user input data is input into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; If it is determined that there is no abnormal simulation data in the simulation data, a control command corresponding to the user input data is generated and the control command is sent to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
[0005] According to a workstation control method provided by the present invention, after sending the control command to the workstation to be controlled corresponding to the second identifier, the method further includes: During the execution of the operation task of the workstation to be controlled corresponding to the second identifier, real data fed back by the workstation to be controlled corresponding to the second identifier is acquired in real time; wherein, the real data includes real workstation operating status data, real workstation operation process data, and real sample processing result data; Identify the target twin object in the digital twin 3D model that is related to the real data; Based on the real data, the state parameters of the target twin object in the digital twin 3D model are updated in real time.
[0006] According to a workstation control method provided by the present invention, the method further includes: If abnormal workstation simulation operation status data is found in the simulation data, a first anomaly analysis report corresponding to the abnormal workstation simulation operation status data is generated; wherein, the first anomaly analysis report includes a third identifier of the abnormal simulation device and the abnormal simulation type corresponding to the abnormal simulation device; The first warning message is output in the user interface of the digital twin platform, and the first anomaly analysis report is visualized.
[0007] According to a workstation control method provided by the present invention, the method further includes: The simulation data is determined to contain abnormal workstation simulation operation process data. Based on the digital twin 3D model, the simulation operation process video corresponding to the abnormal workstation simulation operation process data is obtained. The second warning message is output in the user interface of the digital twin platform, and the simulation operation process video is displayed visually.
[0008] According to a workstation control method provided by the present invention, the method further includes: If abnormal sample simulation processing result data is found in the simulation data, a second anomaly analysis report corresponding to the abnormal sample simulation processing result data is generated; wherein, the second anomaly analysis report includes a fourth identifier of the abnormal sample simulation processing step and the anomaly type corresponding to the abnormal sample simulation processing step; The third warning message is output in the user interface of the digital twin platform, and the second anomaly analysis report is visualized.
[0009] According to a workstation control method provided by the present invention, the method further includes: Real-time acquisition of real sensor data from the workstation mapped by the digital twin 3D model; Based on the real sensor data, the state values of the corresponding twin sensors in the digital twin 3D model are updated through a data synchronization mechanism.
[0010] The present invention also provides a workstation control device, the device comprising: The first workstation control module is used to receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation tasks that the workstation to be controlled needs to perform on the sample to be processed. The second workstation control module is used to input the user input data into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; The third workstation control module is used to determine that there is no abnormal simulation data in the simulation data, generate control instructions corresponding to the user input data, and send the control instructions to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
[0011] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the workstation control method described above.
[0012] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the workstation control method as described above.
[0013] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the workstation control method as described above.
[0014] The workstation control method provided by this invention receives user input data, including a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the required operational task. This data is then input into a digital twin 3D model constructed based on workstation physical layout parameters, equipment configuration parameters, and workflow parameters, enabling simulation of the operational task. By verifying that the simulation data does not contain abnormal simulation data, including abnormal workstation operating states, abnormal operation processes, and abnormal sample processing results, the effectiveness and safety of the operational task can be ensured. Corresponding control commands are then generated and sent to the designated workstation. This improves the accuracy and reliability of workstation operation, reduces the risk of errors or malfunctions in actual operation, and achieves efficient control and optimization of the sample processing flow. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0016] Figure 1 This is a flowchart illustrating the workstation control method provided by the present invention.
[0017] Figure 2 This is a schematic diagram of the workstation control device provided by the present invention.
[0018] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation
[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0020] Figure 1 This is one of the flowcharts illustrating the workstation control method provided by the present invention, such as... Figure 1 As shown, the method includes steps 110, 120 and 130.
[0021] Step 110: Receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation task to be performed by the workstation to be controlled on the sample to be processed. It should be noted that the workstation control method in this embodiment is applied to a digital twin platform, which provides a user interface that allows users to input the following user input data: The primary identifier of the sample to be processed: such as sample number, name, type, etc., used to identify a specific sample to be processed in the system.
[0022] The second identifier for the workstation to be controlled: such as workstation number, name, type, etc., refers to the identifier of the specific workstation that the user wishes to control or operate. It should be understood that in a smart sample laboratory, multiple workstations are responsible for different sample experimental tasks; therefore, the user needs to explicitly specify which workstation will perform the operation.
[0023] The operational tasks that the workstation to be controlled needs to perform on the sample to be processed include specific operational requirements for the sample, such as sample receiving, shaking and mixing, pipetting and digestion, pipetting to centrifuge tubes, ICPMS injection, result generation, waste liquid treatment, etc. The user needs to clearly specify which operational tasks the workstation to be controlled wants to perform on the sample.
[0024] Step 120: Input the user input data into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; Here, the digital twin 3D model is a high-precision 3D model built based on the physical layout parameters, equipment configuration parameters, and workflow parameters of the workstation, which can highly simulate the actual operating status and operation process of the workstation.
[0025] Physical layout parameters include, but are not limited to: spatial dimensions (such as the length, width, and height of the workstation, as well as the distance and relative position between various devices in the workstation); device dimensions (the three-dimensional dimensions of all devices in the workstation, including length, width, height, and shape); and piping layout (the routing, connection method, and material of all pipes in the workstation).
[0026] Equipment configuration parameters include, but are not limited to: equipment type (such as robot, analyzer, pipette, centrifuge, etc.); equipment performance (such as the sensitivity, resolution, linear range, etc. of the analyzer, the accuracy error, repeatability error, etc. of the pipette); equipment specifications (such as the detection range of the analyzer, the pipetting volume range of the pipette, the speed range of the centrifuge, etc.).
[0027] Workflow parameters include, but are not limited to: equipment startup and linkage parameters (defining which devices need to be started when a specific task is received, and their startup sequence and linkage method; for example, in a heavy metal workstation, when a sample processing task is received, the sample loading robot first grabs the sample, then according to the process parameters, the digestion robot performs digestion, and then the pipetting robot performs pipetting operations, etc.); sample processing step parameters (detailing the specific operations that the sample needs to undergo in each processing step, and the equipment conditions required for each operation (such as temperature, pressure, time, etc.). For example, in the digestion step, the digester needs to follow preset parameters (such as digestion...). Digestion of samples is performed using temperature and time parameters; equipment motion trajectory parameters (defining the movement trajectory, speed, and target position of components such as robotic arms and grippers during operation; for example, when a sample-grabbing robot grasps a sample, it needs to move to the sample location according to the trajectory and speed indicated by the parameters and accurately grasp the sample); data recording and analysis parameters (defining what data needs to be recorded during operation (such as sample status, equipment operating status, processing results, etc.), and specifying the data storage format, analysis method, and output method; for example, in a heavy metal workstation, all equipment needs to record and upload key data during sample processing).
[0028] After determining the above key parameters, select appropriate software for 3D model construction, such as 3D modeling software. In the 3D modeling software, create the basic model of the workstation based on the physical layout parameters, including walls, floor, equipment supports, etc. Based on the equipment configuration parameters, import the 3D model of each device into the basic model and perform precise positioning and layout. Finally, based on the workflow parameters, write a control program to simulate the sample processing flow within the workstation. This includes simulating the movement, transformation, and operation steps of the sample between various devices in the workstation, and using the software's animation function to visually demonstrate the sample processing process.
[0029] In this embodiment, after receiving user input data, the user input data is input into the digital twin 3D model. The digital twin 3D model will simulate the process of the workstation performing a specified operation task based on this user input data and output simulation data. Here, the simulation data typically includes workstation simulation running status data, workstation simulation operation process data, and sample simulation processing result data, etc.
[0030] It should be understood that the workstation simulation operation status data describes the operating status of each device in the workstation under control during the simulation process. This includes the device's start-up time, running time, shutdown time, and parameters such as speed, temperature, and pressure at different operating stages. The sample simulation processing result data reflects the final state or result of the sample after processing under given conditions.
[0031] The workstation simulation operation process data describes the sequence of each simulation operation step, the simulation equipment unit to which each simulation operation step belongs, the simulation execution mechanism (the mechanism that performs the specific operation, such as a robotic arm, gripper, etc.) in the simulation equipment unit, and related simulation parameter values (such as position, speed, time, etc.).
[0032] Step 130: Determine that there is no abnormal simulation data in the simulation data, generate a control command corresponding to the user input data, and send the control command to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
[0033] After obtaining the simulation data output from the digital twin 3D model, the simulation data is checked to determine whether there is any abnormal simulation data.
[0034] Specifically, abnormal simulation data includes, but is not limited to: abnormal workstation simulation operation status data (such as excessively high equipment operating temperature, excessively high pressure, fault codes, etc.), abnormal workstation simulation operation process data (such as abnormal robot movements, incorrect liquid transfer volume, excessively long digestion time, etc.), and abnormal sample simulation processing result data (such as abnormal test results, sample damage, etc.).
[0035] If no abnormal simulation data is found, corresponding control commands will be generated based on the user input data. These control commands instruct the workstation to be controlled to perform specific operational tasks on the sample. After generating the control commands, they are sent to the workstation corresponding to the second identifier. Upon receiving the control commands, the workstation to be controlled will execute the corresponding operational tasks according to the requirements of the control commands.
[0036] The workstation control method provided by this invention receives user input data, including a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the required operational task. This data is then input into a digital twin 3D model constructed based on workstation physical layout parameters, equipment configuration parameters, and workflow parameters, enabling simulation of the operational task. By verifying that the simulation data does not contain abnormal simulation data, including abnormal workstation operating states, abnormal operation processes, and abnormal sample processing results, the effectiveness and safety of the operational task can be ensured. Corresponding control commands are then generated and sent to the designated workstation. This improves the accuracy and reliability of workstation operation, reduces the risk of errors or malfunctions in actual operation, and achieves efficient control and optimization of the sample processing flow.
[0037] In some embodiments, after sending the control command to the workstation to be controlled corresponding to the second identifier, the method further includes: During the execution of the operation task of the workstation to be controlled corresponding to the second identifier, real data fed back by the workstation to be controlled corresponding to the second identifier is acquired in real time; wherein, the real data includes real workstation operating status data, real workstation operation process data, and real sample processing result data; Identify the target twin object in the digital twin 3D model that is related to the real data; Based on the real data, the state parameters of the target twin object in the digital twin 3D model are updated in real time.
[0038] In this embodiment, after sending the control command to the actual workstation to be controlled, it is also necessary to monitor the operating status and operation process of the workstation to be controlled in real time, and update the digital twin model in real time to ensure the synchronization between the model and the actual workstation.
[0039] Specifically, through IoT technology, real-time data is collected from the workstations under control, including but not limited to: equipment operating status data (describing the operating status of each device in the workstation under control during the simulation process, such as the device's start-up time, running time, shutdown time, and parameters such as speed, temperature, and pressure at different operating stages); operation process data (describing the details of each step in the simulation, such as the time when the sample is fed into the device, the operations performed on the sample by the device (such as heating, cooling, mixing, etc.), the duration of the operation, and the results of any intermediate steps); and sample processing result data (reflecting the final state or result of the sample after processing under given conditions).
[0040] It should be understood that a digital twin 3D model is a virtual mirror image of a physical workstation, capable of reflecting its state and changes in real time. Therefore, in this embodiment, after real-time acquisition of the actual data fed back by the workstation to be controlled, the target twin object corresponding to the actual data in the digital twin model is first determined through predefined mapping relationships or data labels.
[0041] After identifying the target twin objects, their status parameters are dynamically updated based on real-time acquired data. It should be understood that status parameters are numerical values or codes describing the current state of the target twin object, such as the operating status of equipment, the processing progress of samples, and the progress of operational steps. By updating the status parameters, the animation display effect of the target twin object in the digital twin 3D model can be updated in real time, thus accurately reflecting the actual state and changes of the physical workstation.
[0042] Furthermore, in this embodiment, after determining that the operation task of the workstation to be controlled corresponding to the second identifier has been completed, all the real data fed back by the workstation to be controlled corresponding to the second identifier is obtained and compared with the simulation data output by the digital twin 3D model. Machine learning methods are used to identify the differences between the real data and the simulation data. When the difference exceeds the acceptable error range, the parameters of the digital twin 3D model are adjusted according to the real data to better simulate the actual behavior of the simulation workstation.
[0043] The workstation control method provided by this invention enables the digital twin 3D model to reflect the actual workstation's operating status and process in real time through the above steps, and provides users with an intuitive visual display, thereby realizing intelligent management and optimization of the workstation.
[0044] In some embodiments, the method further includes: If abnormal workstation simulation operation status data is found in the simulation data, a first anomaly analysis report corresponding to the abnormal workstation simulation operation status data is generated; wherein, the first anomaly analysis report includes a third identifier of the abnormal simulation device and the abnormal simulation type corresponding to the abnormal simulation device; The first warning message is output in the user interface of the digital twin platform, and the first anomaly analysis report is visualized.
[0045] In this embodiment, during the simulation operation using the digital twin 3D model, the simulation operation status data of the twin workstation corresponding to the workstation to be controlled in the digital twin 3D model is continuously monitored. This data reflects the operating status of each device in the twin workstation in the simulation environment, including but not limited to device operating efficiency, failure rate, energy consumption, etc. When the simulation operation status data of the twin workstation corresponding to the workstation to be controlled is detected to exceed the preset normal range, it is considered that the twin workstation corresponding to the workstation to be controlled is in an abnormal simulation operation state, and the abnormal workstation simulation operation status data is recorded simultaneously.
[0046] After the simulation using the digital twin 3D model is completed, anomaly analysis is performed on the recorded abnormal workstation simulation status data, and a first anomaly analysis report is generated based on the analysis results. Key information in this first anomaly analysis report includes, but is not limited to: the third identifier of the abnormal simulation device (a code or name used to identify the abnormal device for quick location of the problematic device), and the type of abnormal simulation corresponding to the abnormal device (such as hardware failure, software error, operational error, etc.). Other relevant information may also be included, such as the duration and scope of the anomaly, to facilitate a comprehensive analysis of the anomaly.
[0047] After generating the first anomaly analysis report, a first warning message will be output to the user interface of the digital twin platform (e.g., through flashing red, highlighting, etc.) to alert the user to potential problems. Simultaneously, the first anomaly analysis report will be visualized in the user interface, such as through charts, color coding, or animation, allowing the user to intuitively see the detailed information of the anomaly.
[0048] The workstation control method provided by this invention, through the above steps, can not only simulate the operating status of the workstation through a digital twin 3D model, but also promptly detect and report anomalies, thereby helping users take measures to prevent or solve potential problems and ensure the safety and efficiency of actual operation.
[0049] In some embodiments, the method further includes: The simulation data is determined to contain abnormal workstation simulation operation process data. Based on the digital twin 3D model, the simulation operation process video corresponding to the abnormal workstation simulation operation process data is obtained. The second warning message is output in the user interface of the digital twin platform, and the simulation operation process video is displayed visually.
[0050] During the simulation operation using the digital twin 3D model, the simulation operation data of the workstation corresponding to the workstation to be controlled in the digital twin 3D model will be continuously monitored. When abnormal equipment movement trajectory, incorrect operation sequence, or state value exceeding the preset range is detected in the operation process of the twin workstation corresponding to the workstation to be controlled, it is considered that the twin workstation corresponding to the workstation to be controlled is in an abnormal simulation operation process, and the abnormal workstation simulation operation process data will be recorded simultaneously.
[0051] After the simulation using the digital twin 3D model is completed, a video of the simulation operation process that matches the data of the abnormal workstation simulation operation is extracted from the digital twin 3D model. Here, the simulation operation process video is a visual representation of the abnormal operation process, which can be achieved through 3D model rendering technology, and there are no restrictions on this.
[0052] After obtaining a simulation operation video that matches the abnormal workstation simulation operation data, a second warning message is output to the digital twin platform's user interface to notify the user of the abnormal operation. This warning message may be a pop-up window, an audio prompt, or a warning icon on the interface. Simultaneously, the generated abnormal simulation operation video is visually displayed in the user interface, allowing the user to directly view the detailed process of the abnormal operation.
[0053] The workstation control method provided by this invention, through the above steps, visually displays the abnormal situation in video form when abnormal workstation simulation operation data is detected. This helps users understand the problem more quickly and make accurate decisions, thereby optimizing the workstation's operation process and improving overall production efficiency and safety.
[0054] In some embodiments, the method further includes: If abnormal sample simulation processing result data is found in the simulation data, a second anomaly analysis report corresponding to the abnormal sample simulation processing result data is generated; wherein, the second anomaly analysis report includes a fourth identifier of the abnormal sample simulation processing step and the anomaly type corresponding to the abnormal sample simulation processing step; The third warning message is output in the user interface of the digital twin platform, and the second anomaly analysis report is visualized.
[0055] In this embodiment, during the simulation operation using the digital twin 3D model, the simulation processing result data of the sample from the twin workstation corresponding to the workstation to be controlled in the digital twin 3D model is continuously monitored. When it is detected that the sample in the twin workstation corresponding to the workstation to be controlled is damaged or the sample processing result data does not conform to the normal result data during the simulation processing, it is considered that the sample simulation processing result of the twin workstation corresponding to the workstation to be controlled is abnormal, and the abnormal sample simulation processing result data is recorded simultaneously.
[0056] After the simulation using the digital twin 3D model is completed, anomaly analysis is performed on the recorded simulation processing results of abnormal samples, and a second anomaly analysis report is generated based on the results. Key information in this second anomaly analysis report includes, but is not limited to: a fourth identifier for the abnormal sample simulation processing stage (used to specify which specific processing stage the anomaly occurred in. For example, if the anomaly occurred during the sample heating stage, the identifier corresponding to the sample heating stage is output); and the anomaly type corresponding to the abnormal sample simulation processing stage (such as operational error, equipment malfunction, etc.).
[0057] After generating the second anomaly analysis report, a third warning message will be output to the user interface of the digital twin platform (e.g., through flashing red, highlighting, etc.) to alert the user to potential problems. Simultaneously, the second anomaly analysis report will be visualized in the user interface, such as through charts, color coding, or animations, allowing users to intuitively see the detailed information of the anomaly.
[0058] The workstation control method provided by this invention, through the above steps, can not only simulate the processing results of the workstation on the sample using a digital twin 3D model, but also promptly detect and report anomalies, thereby helping users take measures to prevent or solve potential problems and ensure the safety and efficiency of actual operation.
[0059] In some embodiments, the method further includes: Real-time acquisition of real sensor data from the workstation mapped by the digital twin 3D model; Based on the real sensor data, the state values of the corresponding twin sensors in the digital twin 3D model are updated through a data synchronization mechanism.
[0060] To ensure that the digital twin 3D model accurately reflects the condition of the actual workstation, this embodiment also continuously collects data from the actual sensors installed in the workstation. These sensors include, but are not limited to, temperature sensors, humidity sensors, cleanliness sensors, and light intensity sensors.
[0061] This embodiment also employs a data synchronization mechanism to ensure that the real sensor data remains consistent with the state values of the twin sensors in the digital twin 3D model. Specifically, when the real sensor data changes, the data synchronization mechanism immediately captures these changes and transmits them in real time to the corresponding twin sensors in the digital twin model via a specific communication protocol.
[0062] Upon receiving real sensor data, the twin sensors in the digital twin 3D model immediately update their data values to reflect the actual state of the workstation environment.
[0063] Furthermore, this embodiment also includes a threshold monitoring mechanism. When a certain data exceeds a preset safety range, an alarm or warning is automatically triggered. For example, if the temperature in the digital twin 3D model continues to rise to a dangerous level, the digital twin platform will notify relevant personnel via sound, light signals, or SMS to remind them to take emergency cooling measures.
[0064] The workstation control method provided by this invention, through real-time acquisition and synchronization of real sensor data, enables a digital twin 3D model to more accurately simulate and reflect the actual working environment of the workstation. This allows operators to monitor, analyze, and predict workstation performance in a secure virtual environment without having to directly intervene in the actual workstation.
[0065] Based on any of the above embodiments, the present invention also provides a workstation control device. Figure 2 This is a schematic diagram of the workstation control device provided by the present invention, as shown below. Figure 2 As shown, the device includes: The first workstation control module 210 is used to receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation tasks that the workstation to be controlled needs to perform on the sample to be processed. The second workstation control module 220 is used to input the user input data into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; The third workstation control module 230 is used to determine that there is no abnormal simulation data in the simulation data, generate control instructions corresponding to the user input data, and send the control instructions to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
[0066] The workstation control device provided by this invention receives user input data, including a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the required operational task. This data is then input into a digital twin 3D model constructed based on workstation physical layout parameters, equipment configuration parameters, and workflow parameters, enabling simulation of the operational task. By verifying that the simulation data does not contain abnormal simulation data, including abnormal workstation operating states, abnormal operation processes, and abnormal sample processing results, the effectiveness and safety of the operational task can be ensured. Corresponding control commands are then generated and sent to the designated workstation. This improves the accuracy and reliability of workstation operation, reduces the risk of errors or malfunctions in actual operation, and achieves efficient control and optimization of the sample processing flow.
[0067] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 430, and a communication bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute a workstation control method, which includes: Receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation task that the workstation to be controlled needs to perform on the sample to be processed. The user input data is input into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; If it is determined that there is no abnormal simulation data in the simulation data, a control command corresponding to the user input data is generated and the control command is sent to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
[0068] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0069] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being able to be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer being able to execute the workstation control method provided by the above methods, the method comprising: Receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation task that the workstation to be controlled needs to perform on the sample to be processed. The user input data is input into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; If it is determined that there is no abnormal simulation data in the simulation data, a control command corresponding to the user input data is generated and the control command is sent to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
[0070] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the workstation control methods provided by the methods described above, the method comprising: Receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation task that the workstation to be controlled needs to perform on the sample to be processed. The user input data is input into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; If it is determined that there is no abnormal simulation data in the simulation data, a control command corresponding to the user input data is generated and the control command is sent to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
[0071] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.
[0072] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.
[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A workstation control method, characterized in that, include: Receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation task that the workstation to be controlled needs to perform on the sample to be processed. The user input data is input into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; If it is determined that there is no abnormal simulation data in the simulation data, a control command corresponding to the user input data is generated and the control command is sent to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
2. The workstation control method according to claim 1, characterized in that, After sending the control command to the workstation to be controlled corresponding to the second identifier, the method further includes: During the execution of the operation task of the workstation to be controlled corresponding to the second identifier, real data fed back by the workstation to be controlled corresponding to the second identifier is acquired in real time; wherein, the real data includes real workstation operating status data, real workstation operation process data, and real sample processing result data; Identify the target twin object in the digital twin 3D model that is related to the real data; Based on the real data, the state parameters of the target twin object in the digital twin 3D model are updated in real time.
3. The workstation control method according to claim 1, characterized in that, The method further includes: If abnormal workstation simulation operation status data is found in the simulation data, a first anomaly analysis report corresponding to the abnormal workstation simulation operation status data is generated; wherein, the first anomaly analysis report includes a third identifier of the abnormal simulation device and the abnormal simulation type corresponding to the abnormal simulation device; The first warning message is output in the user interface of the digital twin platform, and the first anomaly analysis report is visualized.
4. The workstation control method according to claim 1, characterized in that, The method further includes: The simulation data is determined to contain abnormal workstation simulation operation process data. Based on the digital twin 3D model, the simulation operation process video corresponding to the abnormal workstation simulation operation process data is obtained. The second warning message is output in the user interface of the digital twin platform, and the simulation operation process video is displayed visually.
5. The workstation control method according to claim 1, characterized in that, The method further includes: If abnormal sample simulation processing result data is found in the simulation data, a second anomaly analysis report corresponding to the abnormal sample simulation processing result data is generated; wherein, the second anomaly analysis report includes a fourth identifier of the abnormal sample simulation processing step and the anomaly type corresponding to the abnormal sample simulation processing step; The third warning message is output in the user interface of the digital twin platform, and the second anomaly analysis report is visualized.
6. The workstation control method according to claim 1, characterized in that, The method further includes: Real-time acquisition of real sensor data from the workstation mapped by the digital twin 3D model; Based on the real sensor data, the state values of the corresponding twin sensors in the digital twin 3D model are updated through a data synchronization mechanism.
7. A workstation control device, characterized in that, include: The first workstation control module is used to receive user input data, which includes a first identifier of the sample to be processed, a second identifier of the workstation to be controlled, and the operation tasks that the workstation to be controlled needs to perform on the sample to be processed. The second workstation control module is used to input the user input data into the digital twin 3D model to obtain the simulation data output by the digital twin 3D model; wherein, the digital twin 3D model is constructed based on the physical layout parameters, equipment configuration parameters and workflow parameters of the workstation; The third workstation control module is used to determine that there is no abnormal simulation data in the simulation data, generate control instructions corresponding to the user input data, and send the control instructions to the workstation to be controlled corresponding to the second identifier; wherein, the abnormal simulation data includes abnormal workstation simulation operation status data, abnormal workstation simulation operation process data, and abnormal sample simulation processing result data.
8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the workstation control method as described in any one of claims 1 to 6.
9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the workstation control method as described in any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the workstation control method as described in any one of claims 1 to 6.