Agricultural microbial preparation production line multi-device collaborative management and control method and system

Abstract

The invention relates to an agricultural microbial preparation production line multi-device collaborative control method and system, and the method comprises the steps: calculating a device health score based on operation state information, combining the device health score with a biological risk index to generate a task release score, and generating a production task instruction when the task release score meets a preset release threshold value, constructing a cooperative interlocking matrix between the multiple types of process equipment and the material handling equipment based on the production task instruction, distributing a control execution instruction to the multiple types of process equipment and the material handling equipment, respectively obtaining equipment feedback state information and material circulation information, executing consistency verification on the equipment feedback state information and the material circulation information, and sending a verification result to the material handling equipment; a consistency verification result is obtained, during manual modification, a revision audit chain corresponding to the control event information is generated, and when the running state information or the control event information triggers a preset abnormal threshold value, a disposal control instruction is generated. The method has the effect of improving the production safety.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of biological agent production monitoring control, and in particular to a method and system for multi-device collaborative management and control of an agricultural microbial agent production line. BACKGROUND

[0002] In the past operation of the agricultural microbial agent production line, the monitoring and control of the devices are usually carried out separately. For the evaluation of the device operation state, it is often only to simply check whether the device is in a normal open or closed state, and there is a lack of comprehensive quantitative analysis of the health condition of the device. For the task release, it is usually only to make a judgment according to experience or a basic production plan, without fully considering the biological risk factors. For the collaborative control of multiple devices, it is usually only to execute according to a fixed process sequence, without a real-time interlocking mechanism to ensure the accuracy of the device execution timing. For the information feedback and verification, it is usually only to simply receive the operation result feedback of the device, without consistency verification of the device feedback state information and the material flow information.

[0003] However, the existing conventional methods have obvious defects. The separate monitoring of the devices cannot accurately evaluate the health condition of the devices, which is likely to cause the devices to continue to operate when there is a potential failure, affecting the production quality and efficiency. The lack of comprehensive consideration of the biological risk makes the production process have biological safety hazards. The fixed process of the multi-device collaborative control cannot adapt to the dynamic changes in the production process, which is likely to cause confusion in the execution timing of the devices. Without consistency verification of the information, it is impossible to timely find the abnormalities in the production process, which leads to the accumulation and expansion of errors, and finally affects the production quality and yield of the agricultural microbial agent. SUMMARY

[0004] In order to improve the safety of production, the present application provides a method and system for multi-device collaborative management and control of an agricultural microbial agent production line.

[0005] The above-mentioned first application objective of the present application is achieved by the following technical solution:

[0006] The method for multi-device collaborative management and control of the agricultural microbial agent production line comprises:

[0007] obtaining operation state information of a target device in the production line, calculating a device health score based on the operation state information;

[0008] obtaining a biological risk index of a target batch, combining the device health score and the biological risk index to generate a task release score, and generating a production task instruction when the task release score meets a preset release threshold;

[0009] construct a collaborative interlocking matrix between the multiple types of process equipment and the material handling equipment based on the production task instruction, the collaborative interlocking matrix being used to constrain the execution timing between the multiple devices, and when the multiple types of process equipment are in an allowed execution state and the material handling equipment reaches a specified location and is in a safe state, a control execution instruction is generated;

[0010] distribute the control execution instruction to the multiple types of process equipment and the material handling equipment, drive the execution of the process operation and the material handling operation, and obtain device feedback state information and material flow information during the execution of the process operation and the material handling operation, respectively;

[0011] perform consistency checking on the device feedback state information and the material flow information to obtain a consistency checking result, when the consistency checking result indicates that there is a deviation between the device feedback state information and the material flow information, a control event information is generated, and when manual modification is detected, a revision audit chain corresponding to the control event information is generated;

[0012] when the running state information or the control event information triggers a preset abnormal threshold, a disposal control instruction is generated, and corresponding abnormal disposal operations are performed under different abnormal levels according to the disposal control instruction.

[0013] By adopting the above technical solutions, the device health score can be calculated based on the running state information, the quantitative evaluation of the device running stability and the collaboration situation can be realized, and the potential fault continuous running caused by the rough judgment of the switch state can be avoided. The device health score and the biological risk index of the target batch can be combined to generate a task release score at the task release link, so that the device state and the biological risk are considered in the task release process, and the biological safety hidden danger is reduced. The collaborative interlocking matrix can be constructed based on the production task instruction to ensure the accuracy of the execution timing of the process equipment and the material handling equipment, and to avoid the timing confusion under the fixed process. The device feedback state information and the material flow information can be compared through consistency checking to discover the running deviation in time, and the revision audit chain is generated when manual modification is detected, the target batch gene pedigree is combined to realize the traceability, and the integrity of the record is ensured. The disposal control instruction is generated when the abnormal triggering threshold is triggered, and the hierarchical or global disposal is dynamically implemented according to the abnormal level, and the response efficiency is improved. Overall, the scheme solves the problems of single device monitoring, lack of biological risk consideration in task release, lack of interlocking mechanism in multi-device collaboration, and insufficient information feedback checking in the prior art, thereby significantly improving the operation reliability, biological safety, and production efficiency of the agricultural microbial preparation production line.

[0014] Preferably, the running state information of the target device in the production line is obtained, and the device health score is calculated based on the running state information, including:

[0015] obtain a corresponding operation parameter time sequence from the operation state information, and calculate a fluctuation trend index representing operation stability of the equipment based on the operation parameter time sequence;

[0016] calculate a cooperative coupling deviation value of the target equipment based on an operation parameter representing a cooperative relationship between the target equipment and other process equipment in the operation state information;

[0017] combine the fluctuation trend index and the cooperative coupling deviation value, and perform weighted calculation according to a risk sensitive factor corresponding to the target process link to obtain an equipment health score.

[0018] By using the above technical solution, the operation parameter time sequence can be extracted based on the operation state information, and the fluctuation trend index can be calculated, so that the equipment operation stability is quantitatively expressed. The cooperative coupling deviation value can be calculated based on the operation parameter reflecting the cooperative relationship between the equipment in the operation state information, so as to reveal the deviation degree of the target equipment in the multi-equipment cooperation. The fluctuation trend index and the cooperative coupling deviation value can be combined, and weighted according to the risk sensitive factor corresponding to the different process links to obtain a comprehensive equipment health score, so that the equipment state not only reflects the single machine operation condition, but also reflects the cooperative adaptability and process risk weight. The scheme overcomes the limitation of the traditional method which only relies on whether the equipment is on or off or single parameter monitoring to judge the state, avoids the potential failure equipment to continue running and affect the production quality, and improves the adaptability of the health assessment to the process difference and risk sensitivity. More reliable quantitative basis is provided for subsequent task release and abnormal control.

[0019] Preferably, a biological risk index of the target batch is obtained, and the equipment health score and the biological risk index are combined to generate a task release score, including:

[0020] performing standardization processing on the risk parameter of the target batch to obtain a risk feature vector;

[0021] performing weighted calculation on the risk feature vector of the target batch according to a risk sensitive factor corresponding to the target process link to obtain a biological risk index;

[0022] when the biological risk index is higher than a preset risk threshold, modifying the equipment health score according to a preset inhibition rule to obtain a modified equipment health score;

[0023] performing weighted synthesis on the modified equipment health score and the biological risk index of the target batch according to a calculation rule of the task release score to obtain the task release score.

[0024] By adopting the technical scheme, the risk parameters of the target batch can be standardized, calculation deviation caused by inconsistent dimensions or different value ranges can be avoided, a risk feature vector with consistent comparability can be obtained, the risk feature vector can be weighted calculated in combination with the risk sensitive factors of the target process link, a biological risk index is obtained, the risk assessment result can reflect the influence degree of different process links on biological safety, when the biological risk index is higher than the preset risk threshold, the equipment health score is corrected according to the preset inhibition rule, the weight of the equipment health score is reduced under the condition of high risk, a corrected score more consistent with the actual operation risk level is obtained, and finally the corrected equipment health score and the biological risk index are weighted and synthesized to generate a task release score, so that the task release judgment considers both the equipment state and the biological risk. The scheme avoids the one-sidedness of single index release, and improves the scientificity and biological safety of release decision.

[0025] Preferably, a collaborative interlocking matrix between the multi-type process equipment and the material handling equipment is constructed based on the production task instruction, comprising:

[0026] The production task instruction is parsed to extract process execution requirements and material handling requirements corresponding to the production task instruction;

[0027] The execution sequence of the multi-type process equipment is determined according to the process execution requirements, and the running position and running time of the material handling equipment are determined according to the material handling requirements;

[0028] Based on the execution sequence of the multi-type process equipment and the running position and running time of the material handling equipment, a dependency relationship and safety constraint condition between equipment actions are established;

[0029] The dependency relationship and safety constraint condition are converted into interlocking rules to generate the collaborative interlocking matrix.

[0030] By adopting the technical scheme, the process execution requirements and material handling requirements can be accurately extracted after parsing the production task instruction, the control logic is consistent with the batch task, the execution sequence of the multi-type process equipment can be determined according to the process execution requirements, and the running position and running time of the material handling equipment can be determined in combination with the material handling requirements, so as to ensure the matching of material flow and process operation, the dependency relationship and safety constraint condition between equipment actions can be established based on the process equipment execution sequence and the space-time condition of the material handling equipment, the running risk caused by action conflict or missing safety condition is avoided, the dependency relationship and safety constraint condition are further converted into interlocking rules to generate the collaborative interlocking matrix, the equipment operation can be dynamically adjusted under the matrix constraint, and the process equipment and the material handling equipment have correct execution timing and safety boundary in the collaborative process. The scheme overcomes the limitations of the traditional fixed flow control mode, and realizes flexible adaptation to the dynamic working condition of the production line.

[0031] Preferably, the process of distributing the control execution instructions to the multiple types of process equipment and material handling equipment further comprises:

[0032] An idempotent identifier is attached to the control execution instruction to obtain a control execution instruction with an idempotent identifier;

[0033] The control execution instruction with the idempotent identifier is queued in a sequence determined by the collaborative interlocking matrix, and a pre-state check based on the device feedback state information and the material flow information is performed before issuance to obtain a control execution instruction that passes the check;

[0034] The control execution instruction that passes the check is issued to the corresponding target device, and an execution confirmation identifier is identified based on the device feedback state information within a preset confirmation time limit to obtain a confirmation result;

[0035] When the confirmation result indicates that the execution is not successful, the control execution instruction is reissued according to a preset number of retries and a retry interval, and when the retry fails, a rollback instruction is generated according to a preset rollback table, and the rollback instruction is issued to the corresponding device to restore to a safe baseline state.

[0036] By using the above technical solution, an idempotent identifier can be attached to the control execution instruction to ensure that the same device action will not be executed twice when repeatedly triggered, thereby avoiding process disorder caused by repeated operations. The control execution instruction with the idempotent identifier can be queued in a sequence determined by the collaborative interlocking matrix, and a pre-state check based on the device feedback state information and the material flow information can be performed before issuance to make the instruction issuance process have prerequisite constraints and ensure the synchronization of device actions and material flow. The confirmation result can be obtained by identifying the execution confirmation identifier within a preset confirmation time limit after issuance, making the execution process verifiable. When the confirmation result indicates that the execution is not successful, the device can be safely rolled back to a safe baseline state through a preset retry mechanism and a rollback table, thereby ensuring that the device can be safely rolled back in abnormal situations. This solution effectively improves the reliability of the control instruction and the controllability of the execution process.

[0037] Preferably, consistency check is performed on the device feedback state information and the material flow information to obtain a consistency check result, including:

[0038] Batch identifiers, tray identifiers, container identifiers, station identifiers, and time slice identifiers are extracted based on the device feedback state information and the material flow information to obtain five-element association elements;

[0039] The five-element association elements are combined to establish a five-element association key;

[0040] The corresponding records of the device feedback state information and the material flow information are compared under the constraint of the five-element association key to generate a consistency check result.

[0041] By adopting the technical scheme, the batch identifier, the tray identifier, the container identifier, the station identifier and the time slice identifier can be extracted based on the equipment feedback state information and the material flow information, five-element association elements are formed, the key objects and time sequences in the production process are uniformly described at the data level, the five-element association elements are combined, the five-element association key is established, the equipment operation and the material flow have a bindable relationship in the batch, space and time dimensions, the corresponding records of the equipment feedback state information and the material flow information are compared under the constraint of the five-element association key, the consistency check result is generated, and it is ensured that the actual action of the equipment is consistent with the material flow path. The scheme overcomes the defects of the traditional method which only relies on single equipment feedback or material record and lacks cross-checking, can find deviations and abnormalities in time, prevents errors from accumulating and expanding in the production process, and thus improves the consistency and reliability of the process data of the agricultural microbial preparation production line.

[0042] Preferably, when the manual modification is detected, a revision audit chain corresponding to the control event information is generated, including:

[0043] Based on the detected manual modification, the manual modification association information corresponding to the manual modification is obtained, and a manual modification record is obtained;

[0044] Based on the production task instruction corresponding to the target batch, the corresponding relationship between the target batch and the process equipment, the sterilization cycle and the inoculation interval account is extracted, and a target batch genealogy is constructed;

[0045] The manual modification record is bound to the target batch genealogy to obtain bound modification trace information;

[0046] The bound modification trace information is sequentially written into the revision audit chain to generate a revision audit chain corresponding to the control event information.

[0047] By adopting the technical scheme, the artificial modification associated information can be acquired when the artificial modification is detected, and an artificial modification record is formed, so that the key information such as data before and after modification, operator identity and operation time is completely retained; the corresponding relationship between the target batch and the process equipment, the sterilization cycle and the inoculation interval account can be extracted based on the production task instruction corresponding to the target batch, the target batch gene pedigree is constructed, and the batch execution track has traceability among multiple links; the artificial modification record and the target batch gene pedigree can be bound to generate the bound modification trace information, so that the artificial intervention behavior can be mapped to a specific process link; the modification trace information can be sequentially written into the revision audit chain to generate the revision audit chain corresponding to the control event information, so that the complete traceability across links and time is realized. The scheme overcomes the defects that the traditional production line artificial intervention cannot be systematically recorded and traced across links, guarantees the integrity and transparency of data management, and improves the controllability of abnormal event processing and responsibility investigation.

[0048] Preferably, when the running state information or the control event information triggers the preset abnormal threshold, a disposal control instruction is generated, including:

[0049] Based on the running state information, deviation information in a continuous time slice is extracted to obtain a deviation information sequence;

[0050] Obtain historical control event information;

[0051] Based on the target batch gene pedigree corresponding to the target batch and the historical control event information, the abnormal occurrence is counted to obtain pedigree abnormality statistical information;

[0052] The task release score and the pedigree abnormality statistical information are weighted and synthesized to obtain threshold correction factor information, and the preset abnormal threshold is corrected based on the threshold correction factor information to obtain dynamic abnormal threshold information;

[0053] The deviation information sequence is accumulated and calculated in a sliding time slice to obtain abnormal accumulation degree information, the abnormal accumulation degree information is compared with the dynamic abnormal threshold information to obtain an abnormal judgment result, and a disposal control instruction is generated according to the abnormal judgment result.

[0054] By adopting the technical scheme, the deviation information in continuous time slices can be extracted based on the running state information and a deviation information sequence is formed, so that the equipment running deviation is quantitatively expressed in the time dimension; the pedigree abnormality statistical information is formed by combining the historical control event information and the abnormal occurrence of the target batch gene pedigree system, so that the abnormality determination can be associated with the batch trajectory and historical experience; the threshold correction factor information is obtained by weighting and synthesizing the task release score and the pedigree abnormality statistical information, and the preset abnormal threshold is corrected, so as to form the dynamic abnormal threshold information, so that the threshold has self-adaptability; the abnormality accumulation degree information is obtained by accumulating the deviation information sequence in the sliding time slice, and the abnormality accumulation degree information is compared with the dynamic abnormal threshold information to obtain the abnormality determination result; and the disposal control instruction is further generated according to the abnormality determination result, so as to ensure timely and effective abnormal response. The scheme solves the problems of fixed threshold, lagging abnormality determination and inaccurate response in the traditional method, and improves the reliability and intelligent level of the production line monitoring and abnormality control.

[0055] Preferably, the corresponding abnormal disposal operation is executed under different abnormality levels according to the disposal control instruction, including:

[0056] The disposal coverage range information is obtained by identifying the device action dependency related to the abnormality based on the disposal control instruction and the cooperative interlocking matrix;

[0057] The disposal control instruction is subjected to range contraction and time sequence rearrangement processing according to the disposal coverage range information, to obtain the contracted disposal control instruction;

[0058] The contracted disposal control instruction is issued to the corresponding process equipment and material handling equipment to obtain the disposal information;

[0059] When the abnormality level is a non-emergency stop level, the hierarchical disposal action is implemented in sequence according to the staging execution strategy, and the disposal coverage range information is updated based on the equipment feedback state information and the material flow information after the completion of each stage;

[0060] When the abnormality level is an emergency stop level, global disposal is executed based on the contracted disposal control instruction, and the disposal information and the control event information are bound to obtain the bound disposal information, and the bound disposal information is written into the revision audit chain for the revision of the target batch gene pedigree.

[0061] By adopting the technical scheme, abnormality-related device action dependency relationship can be identified based on the treatment control instruction and the collaborative interlocking matrix, treatment coverage range information is obtained, the treatment range can cover all process equipment and material handling equipment affected by the abnormality, the treatment control instruction can be range-contracted and time sequence rearranged according to the treatment coverage range information, the contracted treatment control instruction is generated, thus irrelevant actions are avoided and the action sequence is reasonable, the contracted treatment control instruction can be issued to the corresponding equipment and feedback is collected, treatment information is formed, the abnormality treatment process is verifiable, when the abnormality level is a non-emergency stop level, hierarchical treatment can be implemented according to a phased execution strategy, and the treatment coverage range information is dynamically updated based on the feedback after each phase is completed, gradual convergence of the treatment is realized, when the abnormality level is an emergency stop level, global treatment can be directly implemented, the treatment information is bound with the control event information and written into a revision audit chain, and the target batch genealogy can record the emergency stop event completely. The scheme realizes unified management of hierarchical and global treatment, and guarantees safety, flexibility and traceability of abnormality response.

[0062] The second invention purpose of the present application is achieved by the following technical scheme:

[0063] The agricultural microbial agent production line multi-device collaborative management and control system comprises:

[0064] The running state evaluation module is configured to obtain running state information of the target device in the production line, and calculate a device health score based on the running state information.

[0065] The task release determination module is configured to obtain a biological risk index of the target batch, combine the device health score with the biological risk index to generate a task release score, and generate a production task instruction when the task release score meets a preset release threshold.

[0066] The collaborative interlocking construction module is configured to construct a collaborative interlocking matrix between the multi-type process equipment and the material handling equipment based on the production task instruction, and the collaborative interlocking matrix is configured to constrain the execution time sequence between the multi-device.

[0067] The instruction distribution and execution module is configured to distribute the control execution instruction to the multi-type process equipment and the material handling equipment, drive the execution of the process operation and the material handling operation, and obtain device feedback state information and material flow information during the execution of the process operation and the material handling operation, respectively.

[0068] A consistency check and event management module is configured to perform consistency check on the equipment feedback state information and the material flow information, obtain a consistency check result, generate control event information when the consistency check result indicates that the equipment feedback state information and the material flow information have a deviation, and generate a revision audit chain corresponding to the control event information when manual modification is detected.

[0069] An abnormality disposal module is configured to generate a disposal control instruction when the running state information or the control event information triggers a preset abnormality threshold, and perform corresponding abnormality disposal operation under different abnormality levels according to the disposal control instruction.

[0070] By using the above technical solutions, the running state evaluation module can calculate the equipment health score based on the running parameter time sequence and the cooperative relationship, so that the equipment state evaluation is more comprehensive, the task release judgment module can combine the equipment health score with the biological risk index of the target batch to generate a task release score, so that the release decision takes into account the equipment stability and the biological safety, the cooperative interlocking construction module can establish an interlocking matrix between the process equipment and the material handling equipment, ensure the correct execution timing, and avoid process conflicts, the instruction distribution and execution module can collect feedback while issuing control execution instructions to form corresponding records of equipment operation and material flow, ensure that the operation process is traceable, the consistency check and event management module can compare the five-element correlation elements to find inconsistencies between the feedback and the flow, and generate a revision audit chain to realize cross-link tracing, and the abnormality disposal module can dynamically implement graded disposal or global emergency stop according to the abnormality level, so as to improve the safety and flexibility of abnormal response. The system as a whole improves the reliability, traceability and intelligent level of the production line operation.

[0071] In summary, the present application has at least one of the following beneficial technical effects:

[0072] 1. The device health score can be calculated based on the running state information, the quantitative evaluation of the device running stability and coordination can be realized, and the potential fault continuous running caused by rough judgment of the switch state can be avoided. The device health score and the biological risk index of the target batch can be combined to generate a task release score in the task release link, so that the device state and biological risk are considered in the task release process, and the biological safety hidden danger is reduced. The coordination interlocking matrix can be constructed based on the production task instruction, the accuracy of the execution time sequence of the process equipment and the material handling equipment is ensured, and the time sequence confusion under the fixed process is avoided. The device feedback state information and the material flow information can be compared through consistency check, the running deviation can be found in time, and the revision audit chain is generated when the manual modification is detected, the traceability is realized combined with the target batch gene pedigree, and the integrity of the record is ensured. The disposal control instruction can be generated when the abnormal trigger threshold is reached, and the hierarchical or global disposal is dynamically implemented according to the abnormal level, and the response efficiency is improved. Overall, the scheme solves the problems of single device monitoring, lack of biological risk consideration in task release, lack of interlocking mechanism in multi-device coordination and insufficient information feedback check in the prior art, thereby significantly improving the operation reliability, biological safety and production efficiency of the agricultural microbial preparation production line. BRIEF DESCRIPTION OF DRAWINGS

[0073] Figure 1 is a flowchart of the agricultural microbial preparation production line multi-device coordination management method in an embodiment of the present application.

[0074] Figure 2 is an implementation flowchart of step S10 in the agricultural microbial preparation production line multi-device coordination management method in an embodiment of the present application.

[0075] Figure 3 is an implementation flowchart of step S20 in the agricultural microbial preparation production line multi-device coordination management method in an embodiment of the present application.

[0076] Figure 4 is a principle block diagram of the agricultural microbial preparation production line multi-device coordination management system in an embodiment of the present application. DETAILED DESCRIPTION

[0077] The present application will be further described in detail below with reference to the accompanying drawings.

[0078] In an embodiment, as shown in Figure 1 , the present application discloses an agricultural microbial preparation production line multi-device coordination management method, which specifically includes the following steps:

[0079] S10: Obtain the running state information of the target device in the production line, and calculate the device health score based on the running state information.

[0080] Specifically, the running state information refers to the running parameter information generated and collected by the target device in the production line during the execution of the process operation or the material handling operation. The running state information includes not only the running parameter information collected in real time during the current batch production process, but also the running parameter information stored in the historical batch or multiple production cycles. The content of the running state information includes but is not limited to the start-stop state of the device, the access switch state, the sterilization cabinet temperature and pressure parameters, the roll-up door lifting position, the inoculation interval operation state, and the running position and task execution state of the automatic guided vehicle. By setting a data collection channel in the control interface of the target device, the running state information is obtained in real time, and the running state information is converted into a running parameter time sequence arranged in time sequence. The device health score refers to a quantitative score obtained based on the running stability of the target device represented by the running state information and the collaborative relationship with other devices. The running parameter time sequence is statistically analyzed to extract the fluctuation trend index, which is a numerical feature reflecting the running stability of the device by calculating the mean, variance and change rate of the time sequence; then, in combination with the running parameters representing the interaction between the target device and other process devices in the running state information, the collaborative coupling deviation value is calculated, which is the difference between the running parameters of the target device and the running parameters of the dependent or cooperating devices. Finally, the fluctuation trend index and the collaborative coupling deviation value are weighted to obtain the device health score, and the production priority level of the target device is further determined according to the device health score sequence of different batches or cycles.

[0081] S20: Obtain the biological risk index of the target batch, combine the device health score with the biological risk index to generate a task release score, and generate a production task instruction when the task release score meets a preset release threshold.

[0082] Specifically, the target batch refers to a specific production batch executed according to a production plan on an agricultural microbial preparation production line, the target batch has a unique batch number and corresponds to a corresponding process link, material flow record and operation account. The biological risk index refers to a quantitative indicator representing the degree of biological safety risk calculated based on the risk parameters associated with the target batch, the risk parameters include the sterilization temperature and sterilization time of the sterilization cabinet, the cleanliness level and operation time of the inoculation interval, the temperature and humidity stability of the culture link and the material exposure time in the automatic guided vehicle transportation process. The risk parameters of the target batch are standardized to form a risk feature vector, and then the risk feature vector is weighted according to the risk sensitive factor corresponding to the target process link to obtain the biological risk index. The task release score refers to the quantitative result of weighting and synthesizing the equipment health score and the biological risk index according to the pre-designed calculation rule, which is used to represent whether the target batch meets the release condition under the current production state. The task release score is compared with the release threshold, and when the task release score is greater than or equal to the release threshold, a production task instruction is generated, the production task instruction refers to a control instruction for driving various process equipment and material handling equipment to execute according to the interlocking matrix.

[0083] S30: Construct a collaborative interlocking matrix between the multi-type process equipment and the material handling equipment based on the production task instruction, the collaborative interlocking matrix is used to constrain the execution timing between the multi-equipment, and a control execution instruction is generated when the multi-type process equipment is in an allowed execution state and the material handling equipment reaches a specified position and is in a safe state.

[0084] Specifically, the production task instruction refers to a control instruction generated based on the task release score for driving multiple types of process equipment and material handling equipment in the production line to perform process operations and material transfer operations. The process equipment refers to equipment in the production line that undertakes process processing functions, including sterilization cabinets, inoculation rooms, culture cabins, and roll-up doors and access control devices matched therewith. The material handling equipment refers to an automated guided vehicle used to transfer materials between different process links. The interlocking matrix refers to a rule set for establishing execution dependency relationships and safety constraint conditions between the process equipment and the material handling equipment according to process execution requirements and material handling requirements contained in the production task instruction. In specific implementation, the process execution requirements and the material handling requirements are obtained by analyzing the production task instruction, the start-stop sequence and the running condition of each process equipment are determined according to the process execution requirements, and the arrival position and the running time of the automated guided vehicle are determined according to the material handling requirements. The start-stop sequence of the process equipment and the arrival condition of the material handling equipment are combined to form a dependency relationship between equipment actions, and the interlocking matrix is constructed in combination with safety constraint conditions. When the process equipment is in an allowed execution state and the material handling equipment arrives at a specified position and is in a safe state, a control execution instruction is generated based on the interlocking matrix, which refers to a specific control instruction for driving the target process equipment and the target material handling equipment to perform corresponding operations.

[0085] S40: Distribute the control execution instruction to the multiple types of process equipment and material handling equipment, drive the execution of process operations and material handling operations, and obtain device feedback state information and material transfer information during the execution of the process operations and the material handling operations, respectively.

[0086] Specifically, when the control execution instruction is issued to the multiple types of process equipment and material handling equipment, the process equipment includes sterilization cabinets, inoculation rooms, culture cabins, and roll-up doors and access control devices, and the material handling equipment is an automated guided vehicle. The control execution instruction establishes a communication connection with the control port of the process equipment and the scheduling interface of the automated guided vehicle through Ethernet or an industrial communication bus, and drives the target process equipment to complete the process operation and the automated guided vehicle to complete the material handling operation after the instruction is issued. The device feedback state information refers to running feedback information generated by the process equipment during the execution of the control execution instruction, including temperature and pressure feedback values of the sterilization cabinet, air cleanliness parameters of the inoculation room, opening and closing states of the roll-up door and the access control, and temperature and humidity parameters of the culture cabin. The material transfer information refers to material position and handling progress information generated by the automated guided vehicle during the execution of the material handling operation, including material batch identification, tray identification, container identification, running path coordinates, and arrival time. By configuring a state acquisition module on the control node of the process equipment and the automated guided vehicle, the device feedback state information and the material transfer information are acquired in real time.

[0087] S50: consistency check is performed on the equipment feedback state information and the material flow transfer information to obtain a consistency check result, when the consistency check result indicates that the equipment feedback state information and the material flow transfer information have a deviation, a control event information is generated, and when manual modification is detected, a revision audit chain corresponding to the control event information is generated.

[0088] Specifically, when the consistency check is performed on the equipment feedback state information and the material flow transfer information, first, the batch identifier, the tray identifier, the container identifier, the station identifier and the time slice identifier are extracted based on the equipment feedback state information and the material flow transfer information to form five associated elements, and the five associated elements are combined to establish a five associated key. Using the five associated key as the comparison basis, the corresponding records of the equipment feedback state information and the material flow transfer information are matched one by one to obtain the consistency check result. The consistency check result is the comparison result reflecting whether the equipment feedback state information and the material flow transfer information maintain a corresponding relationship. If the comparison result indicates that there is a deviation, a control event information is generated. The control event information is an event record used to mark an exception when the equipment feedback state information and the material flow transfer information are inconsistent. The control event information includes the deviation position, the deviation time and the corresponding batch identifier. When manual modification is detected during the consistency check process, a revision audit chain corresponding to the control event information is generated. The revision audit chain is a sequential trace record constructed based on the pre-modification value, the post-modification value, the operator identity information and the modification time information of the manual modification, and the revision audit chain is associated with the target batch genealogy to ensure that the manual intervention behavior during the production line operation can be traced and verified.

[0089] S60: When the running state information or the control event information triggers a preset abnormal threshold, a disposal control instruction is generated, and corresponding abnormal disposal operations are performed under different abnormal levels according to the disposal control instruction.

[0090] Specifically, the abnormal threshold refers to a numerical limit set for the running state information and the control event information for determining whether the production line is in an abnormal state, and the abnormal threshold includes a temperature threshold, a pressure threshold, a cleanliness threshold, a position deviation threshold, and a station time deviation threshold. When the running state information or the control event information exceeds the abnormal threshold, a treatment control instruction is triggered to be generated. The treatment control instruction refers to a control command formed based on the abnormal determination result for driving the process equipment and the material handling equipment to perform an abnormal treatment operation. The abnormal level refers to a classification category classified according to the abnormal threshold overrun degree and the abnormal influence range, and the abnormal level includes a prompt level, a speed limit level, a segmented shutdown level, and an emergency stop level. The abnormal treatment operation refers to a countermeasure performed by the process equipment and the material handling equipment under the action of the treatment control instruction, and different abnormal levels correspond to different abnormal treatment operations, wherein the prompt level performs an audible and visual prompt operation, the speed limit level performs a reduction of the automatic guided vehicle running speed and a delay of the rolling shutter door opening and closing action, the segmented shutdown level performs a closing of the sterilization cabinet of the target process link or a suspension of the operation process in the inoculation room, and the emergency stop level performs a full-line shutdown and a locking of the access control and the rolling shutter door. After the treatment control instruction is generated, the treatment control instruction is issued to the target process equipment and the material handling equipment according to the corresponding abnormal level, and after the execution is completed, the treatment information and the control event information are associated to support subsequent complete tracing in the revision audit chain.

[0091] In an embodiment, as shown in FIG. 10, in step S10, the running state information of the target equipment in the production line is obtained, and a device health score is calculated based on the running state information, including: Figure 2

[0092] S101: Obtain the corresponding running parameter time sequence from the running state information, and calculate a fluctuation trend index representing the stability of the equipment running based on the running parameter time sequence.

[0093] Specifically, the running parameter time sequence refers to a numerical sequence formed by arranging the same type of running parameters in the running state information in time sequence, such as a sterilization cabinet temperature parameter sequence, a sterilization cabinet pressure parameter sequence, an inoculation room cleanliness parameter sequence, a rolling shutter door position parameter sequence, and an automatic guided vehicle position coordinate sequence. The fluctuation trend index refers to a numerical index representing the stability of the target equipment running calculated by normalizing the running parameter time sequence. In specific implementation, first, the running parameter time sequence x(t) is normalized to obtain a dimensionless sequence x ’ (t), and the normalization method is: wherein, is the mean of the running parameter time sequence, is the standard deviation of the running parameter time sequence, and the x ’ ​(t) is a dimensionless number, which ensures that the subsequent calculation results have dimensional consistency. Then, based on the normalized sequence, the fluctuation trend index W is calculated, and the calculation formula is: where N is the number of sampling points, represents the normalized change amplitude between adjacent time slices. The larger the value of the fluctuation trend index W, the more obvious the fluctuation of the operating parameters of the target device, the lower the operating stability, and the smaller the value, the more stable the operating parameters of the target device, and the higher the operating stability.

[0094] S102: According to the operating parameters in the running state information representing the coordination relationship between the target device and other process devices, the coordination coupling deviation value of the target device is calculated.

[0095] Specifically, the coordination coupling deviation value refers to a dimensionless index for quantifying the coordination consistency degree of the target device and the associated device, which is calculated based on the operating parameters in the running state information representing the coordination relationship between the target device and other process devices. To calculate the coordination coupling deviation value, first, according to the process interlocking and coordination logic, the operating parameter pairing set is constructed . The operating parameter pairing set refers to a set formed by pairing the time series of key operating parameters of the target device with the time series of key operating parameters of the associated process device or material handling device, for example: pairing of the sterilization cabinet cabin pressure parameter sequence and the sterilization cabinet access opening and closing state sequence, pairing of the roll-up door opening and closing position parameter sequence and the automated guided vehicle arrival state sequence, and pairing of the inoculation room door control state sequence and the automated guided vehicle running position sequence. To ensure dimensional consistency, normalize and time-align each pair of operating parameter time series. Normalization refers to converting time series of different physical quantities into dimensionless sequences with zero mean and unit standard deviation, and time alignment refers to setting an expected time lag for each pair of paired parameters according to the order of the coordination process and the process beat (for example, the automated guided vehicle arrives one fixed time slice ahead of the roll-up door opening). For the ith pair of operating parameters, the following processing is performed: where , and are the mean and standard deviation of the corresponding time series, respectively. After normalization and time alignment, the correlation consistency degree and the interlocking violation rate pi of the ith pair of parameters are calculated. The correlation consistency degree refers to the Pearson correlation coefficient reflecting the degree of synchronous change of two aligned dimensionless sequences, and the interlocking violation rate refers to the dimensionless ratio of the proportion of samples that violate the given process interlocking rule. The calculation formula is: where is the set of overlapping time slices after alignment of the two sequences, is the number of samples, The interlocking rule corresponding to the i-th pair of parameters is determined (for example, "the door cannot be opened until the cabin pressure is returned to zero", "the roll-up door cannot be opened until the automated guided vehicle is in place"), and the corresponding interlocking rule is determined. is an indicator function. The correlation bias term di is constructed from the correlation consistency: When the two sequences are highly consistent, and When the two sequences are reversed or not correlated, di increases. Considering the process risk differences of different collaborative relationships, a risk sensitivity factor is introduced to determine the weight wi (satisfying ), and the collaborative coupling deviation value C is obtained by weighted fusion: wherein, is a compromise coefficient of the correlation bias and the interlocking violation rate. The larger the value of the collaborative coupling deviation value C, the worse the collaborative consistency of the target device and the associated device, and the smaller the value of the collaborative coupling deviation value C, the better the collaborative consistency. This calculation process is uniformly applicable to process scenarios such as access control-cabin pressure, roll-up door-automated guided vehicle in place, and inoculation interval door control-automated guided vehicle position.

[0096] S103: Combine the fluctuation trend index and the collaborative coupling deviation value, and perform weighted calculation according to the risk sensitivity factor corresponding to the target process link to obtain the device health score.

[0097] Specifically, the risk sensitivity factor refers to the weight parameter set for the target process link, which is used to adjust the influence proportion of the fluctuation trend index and the collaborative coupling deviation value in the calculation of the device health score. The risk sensitivity factor is composed of the fluctuation weight and the collaborative weight to form a risk sensitivity factor vector wherein, In the calculation process, first, the fluctuation trend index W obtained from the time series of the operating parameters is subjected to a benchmarking process, which refers to mapping W to a dimensionless ratio value with the baseline value obtained by statistics on the same process link of the historical stable batch as a reference: wherein, characterizes the fluctuation degree of the target device at the current process link. The collaborative coupling deviation value C is calculated from the operating parameters representing the collaborative relationship between the target device and other process devices in the operating state information, and the value range is [0, 1]. After obtaining the dimensionless and C, the health risk amount R is calculated by weighted combination according to the risk sensitivity factor: The device health score H is defined as: A health score (H) closer to 1 indicates stable operation and good consistency of the target equipment, while a score closer to 0 indicates significant fluctuations or poor consistency. In practice, risk sensitivity factors can be configured based on the characteristics of each process step; for example, a higher value can be set when consistency is emphasized in the sterilization process. When emphasizing operational stability during the cultivation process, a larger setting is required. .

[0098] In one embodiment, such as Figure 3 As shown, in step S20, the biological risk index of the target batch is obtained, and the equipment health score is combined with the biological risk index to generate a task release score, including:

[0099] S201: Perform standardization processing on the risk parameters of the target batch to obtain the risk feature vector.

[0100] Specifically, a target batch refers to a specific production batch executed according to the production plan on the agricultural microbial preparation production line. This target batch is associated with several risk parameters. Risk parameters are quantitative data characterizing the biosafety risk level of the target batch during the production process, including sterilization temperature and time in the sterilizer, air cleanliness level and operation time in the inoculation room, temperature and humidity stability parameters during the cultivation phase, and material exposure time during automated guided vehicle (AGV) transportation. To ensure comparability of different physical quantities, the risk parameters are standardized to obtain a risk feature vector. Standardization involves averaging each risk parameter xj according to its historical statistical mean. and standard deviation The dimensionless conversion is performed using the following formula: Where m is the dimension of the risk parameter, and xj' is the j-th risk parameter after standardization. By performing standardization on all risk parameters, the risk feature vector is obtained: .

[0101] S202: The risk feature vector of the target batch is weighted and calculated based on the risk sensitivity factors corresponding to the target process steps to obtain the biological risk index.

[0102] Specifically, risk sensitivity factors refer to weighted parameters set for the target process stage, used to adjust the influence ratio of different risk parameters in the calculation of the biological risk index. The risk feature vector of the target batch is represented as... The risk sensitivity factor corresponding to the target process step is expressed as: ,in, Here is the weight corresponding to the j-th risk parameter. The biological risk index is the result calculated by weighting the risk feature vector and risk sensitivity factors, and its calculation formula is: wherein Rb is a biological risk index. Through this weighting manner, the risk difference of the target batch under different process links can be reflected, for example, greater weight is given to the temperature and pressure parameters in the sterilization link, and greater weight is given to the air cleanliness and operation time parameters in the inoculation link.

[0103] S203: When the biological risk index is higher than the preset risk threshold, the equipment health score is corrected according to a preset suppression rule to obtain a corrected equipment health score.

[0104] Specifically, the risk threshold refers to a reference value for determining whether the biological risk index is in an acceptable range, which is set according to historical batch statistical results and process safety specifications. When the biological risk index R_b is higher than the risk threshold T_b, the correction of the equipment health score is triggered. The suppression rule refers to an adjustment rule for reducing the equipment health score, which usually adopts a decreasing function based on an over-limit amplitude. Let the original equipment health score be H, and the suppression factor function be: wherein is an adjustment coefficient. The original equipment health score is multiplied by the suppression factor function to obtain the corrected equipment health score H': When , the suppression factor function takes 1, and the equipment health score remains unchanged. When R_b>T_b, with the increase of the over-limit amplitude, the suppression factor function decreases, and the equipment health score is correspondingly depressed.

[0105] S204: The corrected equipment health score and the biological risk index of the target batch are weighted and synthesized according to the calculation rule of the task release score to obtain the task release score.

[0106] Specifically, the task release score refers to an evaluation result for determining whether the production task is released, which is obtained by weighting and synthesizing the corrected equipment health score and the biological risk index of the target batch. Let the corrected equipment health score be H', the biological risk index of the target batch be R_b, and the task release score be S_f. According to the calculation rule of the task release score, the weight vector is defined as wherein . The calculation formula of the task release score is: . Wherein (1-R_b) is used to represent that the greater the biological risk index, the more obvious the deduction to the release score, and the corrected equipment health score H' and the risk suppression effect jointly affect the final result. The higher the task release score value, the more the target batch meets the process safety and operation stability requirements. When the task release score is greater than or equal to the release threshold, the production task instruction is generated.

[0107] In an embodiment, in step S30, a collaborative interlocking matrix between the multi-type process equipment and the material handling equipment is constructed based on the production task instruction, including:

[0108] S301: Analyzing the production task instruction to extract process execution requirements and material handling requirements corresponding to the production task instruction.

[0109] Specifically, the process execution requirements refer to the operation requirements generated for the process equipment in the production task instruction, including the heating and pressure maintaining process of the sterilization cabinet, the air purification and operation period allocation of the inoculation room, the temperature and humidity adjustment of the culture cabin, and the opening and closing control of the roller shutter door and the access control. The material handling requirements refer to the transfer requirements generated for the material handling equipment in the production task instruction, including the running path of the automated guided vehicle, the batch identification of the loading tray, the station information of the container in place, and the time constraint in the handling process. When analyzing the production task instruction, first, the parameter fields in the production task instruction are subjected to syntax analysis and structured decomposition, the fields related to the process equipment are classified as process execution requirements, and the fields related to the automated guided vehicle are classified as material handling requirements. Subsequently, the process execution requirements and the material handling requirements are associated according to the task number and the batch identification to ensure that the process operation and the material handling operation remain synchronized and traceable during the execution process.

[0110] S302: Determining the execution sequence of the multi-type process equipment according to the process execution requirements, and determining the running position and running time of the material handling equipment according to the material handling requirements.

[0111] Specifically, the running position refers to the spatial coordinates or specified station that the material handling equipment needs to reach during the execution of the handling task, and the running position is identified by the station number, path node coordinates, or sensor positioning information. The running time refers to the triggering time of the material handling equipment to execute the handling task in the production process, and the running time is set according to the execution state of the process equipment and the production rhythm. When determining the execution sequence of the process equipment according to the process execution requirements, the heating and pressure maintaining process of the sterilization cabinet is placed before the material enters the culture cabin, the air purification and inoculation operation of the inoculation room is placed after the sterilization process, and the opening and closing sequence of the roller shutter door and the access control is matched with the operation state of the inoculation room and the culture cabin to form an orderly start-stop chain of the process equipment. When determining the running position and running time of the material handling equipment according to the material handling requirements, the running path of the automated guided vehicle is bound with the corresponding tray identification, and the automated guided vehicle is triggered to run to the inoculation room station after the sterilization cabinet completes sterilization, and the automated guided vehicle is triggered to run to the culture cabin station after the inoculation room operation is completed. In this way, the execution sequence of the process equipment, the running position, and the running time of the material handling equipment are kept consistent, realizing the continuity and coordination of the process flow.

[0112] S303: Establish the dependency relationship and safety constraint condition between the device actions based on the execution sequence of the multi-type process equipment and the running position and timing of the material handling equipment.

[0113] Specifically, the dependency relationship refers to the front and rear connection relationship formed by the process equipment and the material handling equipment in the execution sequence, and the dependency relationship is defined by the task trigger condition and the completion confirmation condition. For example, the heating and pressure maintaining task of the sterilization cabinet is completed, and then the automatic guided vehicle is triggered to run to the inoculation room station, and the inoculation room operation is completed, and then the opening of the rolling shutter door and the start of the incubation cabin are triggered. The safety constraint condition refers to the running restriction rule set to avoid the action conflict between the devices and the process risk. The safety constraint condition includes the space isolation constraint, the time interval constraint, and the state confirmation constraint. The space isolation constraint refers to the prohibition of the entry of non-related material handling equipment into the same area during the execution of the inoculation room operation. The time interval constraint refers to the requirement that the cooling process of the sterilization cabinet must reach a specified time before the subsequent operation is performed. The state confirmation constraint refers to the requirement that the automatic guided vehicle enters the target station after the rolling shutter door is completely opened. By combining the dependency relationship and the safety constraint condition, the execution logic chain between the process equipment and the material handling equipment is formed, which is used to ensure the smooth progress of the production task under the conditions of process continuity and biological safety.

[0114] S304: Convert the dependency relationship and the safety constraint condition into interlocking rules to generate the collaborative interlocking matrix.

[0115] Specifically, the interlocking rule refers to the logic control rule formed by the conversion of the dependency relationship and the safety constraint condition, and the interlocking rule is used to limit the execution condition and trigger sequence of the process equipment and the material handling equipment. When the dependency relationship is converted into the interlocking rule, the completion confirmation state of the previous device is taken as the pre-condition for the start of the subsequent device. For example, after the sterilization and cooling confirmation of the sterilization cabinet is completed, the interlocking rule is generated to allow the automatic guided vehicle to enter the inoculation room station, and after the operation confirmation of the inoculation room is completed, the interlocking rule is generated to allow the rolling shutter door to be opened and trigger the incubation cabin to run. When the safety constraint condition is converted into the interlocking rule, the space isolation constraint, the time interval constraint, and the state confirmation constraint are taken as the barrier condition for the triggering of the device action. For example, during the operation of the inoculation room, the interlocking rule is generated to prohibit the entry of non-associated automatic guided vehicles into the inoculation area, during the cooling of the sterilization cabinet, the interlocking rule is generated to prohibit the execution of the subsequent material loading task, and before the rolling shutter door is completely opened, the interlocking rule is generated to prohibit the automatic guided vehicle from entering the target station. Finally, all the interlocking rules are organized in a matrix structure to form the collaborative interlocking matrix, which refers to a two-dimensional logic table arranged according to the task number, device type, and trigger condition, and is used to uniformly constrain the execution timing of the multi-type process equipment and the material handling equipment

[0116] In an embodiment, in the process of distributing the control execution instruction to the multi-type process equipment and material handling equipment in step S40, the process further includes:

[0117] S401: An idempotent identifier is attached to the control execution instruction to obtain a control execution instruction with an idempotent identifier.

[0118] Specifically, the idempotent identifier refers to unique marking information attached to the control execution instruction, which is used to ensure that the same execution action is not executed twice by the equipment when repeatedly triggered. The idempotent identifier is composed of an instruction number, a target equipment identifier, a task timestamp, and a batch identifier, wherein the instruction number is used to distinguish multiple control execution instructions under the same production task, the target equipment identifier is used to distinguish different process equipment and material handling equipment, the task timestamp is used to mark the generation time of the control execution instruction, and the batch identifier is used to correspond to a specific production batch. After generating the control execution instruction, the idempotent identifier is attached to the metadata field of the instruction message to form a control execution instruction with an idempotent identifier. When the control execution instruction with the idempotent identifier is issued to the sterilization cabinet, the inoculation room, the roller shutter door, the access control, and the automated guided vehicle, the target equipment confirms whether the instruction is an executed instruction by analyzing the idempotent identifier, and if it is executed, the repeated instruction is discarded, and if it is not executed, the normal execution process is entered. Through the effect of the idempotent identifier, the uniqueness and traceability of the target equipment action are ensured in the case of communication delay, repeated triggering, or manual intervention.

[0119] S402: The control execution instruction with the idempotent identifier is queued in the order determined by the coordination interlocking matrix, and pre-state verification is performed based on the device feedback state information and the material flow information before issuance to obtain a control execution instruction that passes the verification.

[0120] Specifically, the pre-state verification refers to a process of determining whether a target device has execution conditions based on device feedback state information and material flow information before a control execution instruction is issued. The control execution instruction with idempotent identifier is sorted by the interlocking matrix to form a queuing sequence. The queuing sequence is arranged according to the execution sequence of process equipment and the operation timing of material handling equipment. For example, after the sterilization cabinet completes the sterilization task, the queuing sequence triggers the automated guided vehicle to transport materials to the inoculation room, and then triggers the roller shutter door to open and the inoculation room operation. Subsequently, pre-state verification is performed on each control execution instruction in the queuing sequence. The verification content includes whether the device running state reflected in the device feedback state information and the material arrival state reflected in the material flow information meet the constraint conditions in the interlocking matrix. For example, when the automated guided vehicle has not arrived at the inoculation room station or the air cleanliness of the inoculation room does not meet the standard, the corresponding control execution instruction is determined as not passing the pre-state verification and is not allowed to be issued. When the device feedback state information and the material flow information both meet the constraint conditions, the corresponding control execution instruction is marked as a control execution instruction that passes the verification. The control execution instruction that passes the verification refers to a control execution instruction that is confirmed to meet the execution conditions through pre-state verification and can be issued to the target device for execution, ensuring that the process operation and material handling operation proceed safely and orderly according to the established logic.

[0121] S403: issuing the control execution instruction that passes the verification to the corresponding target device, and identifying an execution confirmation mark based on the device feedback state information within a preset confirmation time limit to obtain a confirmation result.

[0122] Specifically, the preset confirmation time limit refers to the maximum time interval allowed for the target device to return an execution feedback after the control execution instruction is issued. The preset confirmation time limit is set according to the device type and the execution period of the process link. For example, the confirmation time limit for the sterilization cabinet to execute the temperature rising phase is a few minutes, and the confirmation time limit for the roller shutter door to execute the opening operation is a few seconds. The execution confirmation mark refers to a state mark extracted from the device feedback state information to represent whether the target device has completed the instruction execution. For example, the temperature state code of the sterilization cabinet reaching the set temperature and stably maintaining, the cleanliness state code of the inoculation room air cleanliness reaching the set level, the limit signal of the roller shutter door reaching the fully open position, the feedback signal of the access control unlocking completion, and the position confirmation code of the automated guided vehicle reaching the target station. The confirmation result refers to the result of determining the execution of the target device based on the execution confirmation mark. When a valid execution confirmation mark is identified within the preset confirmation time limit, the confirmation result indicates that the control execution instruction has been successfully completed. When no execution confirmation mark is identified within the preset confirmation time limit, the confirmation result indicates that the control execution instruction has not been completed as required.

[0123] S404: When the confirmation result represents that the execution is not successful, the control execution instruction is retransmitted according to the preset retry number and retry interval, and when the retry still fails, a rollback instruction is generated according to the preset rollback table, and the rollback instruction is sent to the corresponding device to restore to the safe baseline state.

[0124] Specifically, the retry number refers to the maximum number of repetitions of retransmitting the control execution instruction in the case where the confirmation result represents that the execution is not successful, and the retry interval refers to the time interval between adjacent two retries. The retry number and the retry interval are set according to the response characteristics and the production rhythm of the target device. For example, the retry number of the roller shutter door is three, and the retry interval is two seconds. The retry number of the sterilization cabinet is two, and the retry interval is five minutes. The rollback table refers to a pre-established comparison table recording the action path and the safety parameter that can be rolled back by the device in the execution failure scenario. The rollback table is configured according to the device type and the process link. For example, the rollback table of the inoculation room contains the parameters for restoring the air purification system to the initial cleanliness, and the rollback table of the automated guided vehicle contains the path for returning to the last safe station. The rollback instruction refers to a control instruction generated according to the rollback table for driving the target device to restore to the safe baseline state. The safe baseline state refers to an operating state that ensures that the process equipment and the material handling equipment do not cause risks to the production process. For example, the sterilization cabinet is in the closed and cooling state, the roller shutter door and the access control are in the locked state, the inoculation room is in the air purification operating state, and the automated guided vehicle is parked at the safe station. In specific implementation, when the confirmation result represents that the execution is not successful, the control execution instruction is retransmitted according to the retry number and the retry interval. When the retry is still unsuccessful, the rollback instruction is generated according to the rollback table, and the rollback instruction is sent to the target device to restore the target device to the safe baseline state, thereby ensuring the safety and controllability of the production line operation.

[0125] In an embodiment, in step S50, consistency verification is performed on the device feedback state information and the material flow transfer information to obtain a consistency verification result, including:

[0126] S501: Based on the device feedback state information and the material flow transfer information, a batch identifier, a tray identifier, a container identifier, a station identifier, and a time slice identifier are extracted to obtain five associated elements.

[0127] Specifically, the batch identifier refers to the number information for uniquely identifying the production batch of the agricultural microbial preparation. The batch identifier is assigned by the production planning system and is consistent in the device feedback state information and the material flow information. The tray identifier refers to the number information for uniquely identifying the material loading tray. The tray identifier is associated with the carrying record of the automated guided vehicle. The container identifier refers to the number of the container for storing the culture medium or the strain. The container identifier corresponds to the sterilization record of the sterilization cabinet and the inter-inoculation operation log. The station identifier refers to the number information for distinguishing different process positions in the production line. The station identifier includes the sterilization cabinet station, the inter-inoculation station, the culture cabin station, and the corresponding access station of the rolling shutter door and the access control. The time slice identifier refers to the time period number generated according to a fixed sampling period during the process operation and the material carrying process. The time slice identifier is used to ensure the comparability of the running state of different devices and the position of the material in the time dimension. The five-element association element refers to a data set composed of the batch identifier, the tray identifier, the container identifier, the station identifier, and the time slice identifier. The five-element association element is used to establish the correspondence between the device feedback state information and the material flow information.

[0128] S502: Combine the five-element association elements to establish a five-element association key.

[0129] Specifically, the five-element association key refers to a composite index composed of the batch identifier, the tray identifier, the container identifier, the station identifier, and the time slice identifier in a predetermined order. The five-element association key is used to uniquely identify the correspondence between the device feedback state information and the material flow information. In specific implementation, the batch identifier is first taken as the top-level field to ensure that all records in the same batch are classified. Then, the tray identifier and the container identifier are sequentially attached under the batch identifier to form a unique combination of the material unit. The station identifier is then attached to distinguish the execution of the material in different process positions such as the sterilization cabinet, the inter-inoculation room, the culture cabin, or the rolling shutter door and the access control. Finally, the time slice identifier is attached to make the execution records of the same material unit in different time periods distinguishable.

[0130] S503: Under the constraint of the five-element association key, compare the corresponding records of the device feedback state information and the material flow information to generate a consistency check result.

[0131] Specifically, the consistency check result refers to the conformity determination result obtained by comparing the equipment feedback state information and the material flow information based on the five-element association key. In specific implementation, first, the five-element association key is taken as an index to retrieve the corresponding records of the equipment feedback state information and the material flow information in the database. For the same combination of batch identifier, tray identifier and container identifier, it is checked whether they exist in the equipment feedback state information and the material flow information at the same workstation identifier and the same time slice identifier. If the states of the two types of information records are consistent at the corresponding workstation identifier and time slice identifier, for example, the sterilization completion flag in the equipment feedback state information after the sterilization cabinet completes sterilization is consistent with the cabinet-out record in the material flow information, and the operation end flag in the equipment feedback state information after the inoculation interval operation is completed is consistent with the tray flow record in the material flow information, then the consistency check result is consistent. If there is only one-sided record or a difference under the same five-element association key, for example, the roll-up door feedback state shows closed but the material flow information record shows that the automated guided vehicle has passed, or the automated guided vehicle feedback shows that it has not arrived but the material flow record shows that the material has entered the inoculation interval, then the consistency check result is inconsistent. The final consistency check result is output in the form of consistent or inconsistent, which provides a basis for subsequent generation of control event information.

[0132] In an embodiment, in step S50, when the manual modification is detected, a revision audit chain corresponding to the control event information is generated, including:

[0133] S504: Based on the detected manual modification, the manual modification association information corresponding to the manual modification is obtained to obtain a manual modification record.

[0134] Specifically, the manual modification association information refers to the context information generated when the operator manually adjusts the equipment feedback state information or the material flow information through the man-machine interface or the console during the operation of the production line. The manual modification association information includes the pre-modification value, the post-modification value, the operator identity information, the operation timestamp and the modification position identifier. The manual modification record refers to the structured data obtained by arranging the manual modification association information according to the batch dimension and the workstation dimension, which is used to represent the occurrence of manual intervention in the operation of the production line. In specific implementation, when the inoculation interval air cleanliness parameter is manually overwritten by the operator, or the sterilization cabinet temperature and pressure data are modified, or the switch state of the roll-up door and the access control is manually changed, or the automated guided vehicle running position is adjusted, the system automatically collects the corresponding manual modification association information after detecting the manual modification and writes it into the database to form the manual modification record. The manual modification record is indexed by the batch identifier and the workstation identifier, which is used to generate the revision audit chain and bind it to the target batch genealogy in the subsequent process.

[0135] S505: Based on the production task instruction corresponding to the target batch, the corresponding relationship between the target batch and the process equipment, the sterilization cycle and the inoculation interval account is extracted, and the target batch gene pedigree is constructed.

[0136] Specifically, the target batch gene pedigree refers to the hierarchical link containing the corresponding relationship between the process equipment, the sterilization cycle and the inoculation interval account, which is constructed based on the process flow path of the target batch in the production task instruction, and is used to represent the traceability relationship of the target batch across the links in the production process. In specific implementation, first, based on the production task instruction corresponding to the target batch, the process equipment information associated with the batch is extracted, including sterilization cabinet, inoculation room, culture cabin and related roller shutter door and access control. Then the sterilization cycle information of the target batch in the sterilization link is extracted, including sterilization temperature curve, pressure holding time and cooling time, and the sterilization cycle is associated with the sterilization cabinet equipment number. Further, the inoculation interval account information is extracted, including inoculation operation time, operator number, air cleanliness detection result and material batch flow record, and the inoculation interval account is bound with the inoculation interval equipment number. Finally, the process equipment information, sterilization cycle information and inoculation interval account information are integrated with the target batch identifier as the index to construct the target batch gene pedigree. The target batch gene pedigree represents the execution trajectory of the target batch in different process links in the form of directed link, providing a basis for the binding and cross-link tracing of subsequent revision audit chain.

[0137] S506: Bind the artificial modification record with the target batch gene pedigree to obtain the bound modification trace information.

[0138] Specifically, the modification trace information refers to the composite trace data formed after binding the artificial modification record with the target batch gene pedigree. The modification trace information is used to represent the corresponding relationship between the artificial intervention and the cross-link execution trajectory of the target batch. In specific implementation, first, based on the batch identifier, workstation identifier and operation timestamp fields in the artificial modification record, the corresponding process equipment node and link information in the target batch gene pedigree are retrieved, such as the sterilization cycle node of the sterilization cabinet, the operation record node of the inoculation room and the passage node of the roller shutter door and the access control. Then the pre-modification value, post-modification value, operator identity information and modification time information in the artificial modification record are bound with the retrieved gene pedigree node to form the modification annotation corresponding to the execution trajectory of the target batch. Finally, all the binding results are integrated according to the execution order of the target batch to obtain the modification trace information. The modification trace information reflects the position and influence range of the artificial intervention behavior in the cross-link flow of the target batch in the form of link, providing a data basis for the generation of subsequent revision audit chain.

[0139] S507: Write the bound modification trace information into the revision audit chain in sequence to generate the revision audit chain corresponding to the control event information.

[0140] Specifically, the revision audit chain refers to the traceable records stored in a sequential linked list structure, used for complete recording and subsequent verification of manual modification process. In specific implementation, first, the abnormal scene that needs to be associated is determined according to the control event information, for example, the sterilization cabinet temperature is manually covered, the inoculation room operation log is modified, the roller shutter door or access control state is adjusted, and the automatic guided vehicle running track is tampered. Subsequently, the modified trace information after binding is written into the revision audit chain node in chronological order, each node contains batch identification, station identification, pre-modification value, post-modification value, operator identity information and modification time information, and the check value is calculated by the hash digest algorithm to prevent tampering. The revision audit chain is bound with the corresponding control event information after generation, forming a complete event link that can be traced, so that the manual intervention of the target batch in different process links can be verified and traced back step by step.

[0141] In an embodiment, in step S60, that is, when the running state information or the control event information triggers the preset abnormal threshold, the disposal control instruction is generated, including:

[0142] S601: Extract the deviation information in the continuous time slice based on the running state information to obtain a deviation information sequence.

[0143] Specifically, the deviation information refers to the numerical quantization result reflecting the difference between the target parameter and the set value in the running state information, and the deviation information is obtained by calculating the difference between the running parameter and the reference set value. The deviation information sequence refers to a set of deviation information arranged in chronological order within a continuous time slice, used to reflect the deviation change trend of the target device within a certain time range. In specific implementation, first, the key running parameters are extracted from the running state information, including the temperature and pressure of the sterilization cabinet, the air cleanliness of the inoculation room, the opening and closing position of the roller shutter door, the unlocking state of the access control, the position coordinates of the automatic guided vehicle, and the humidity and temperature of the incubation cabin. Then, the corresponding reference set value is determined for each type of running parameter, such as the target temperature and pressure set value of the sterilization cabinet, the target cleanliness level of the inoculation room, the full open and full close state threshold of the roller shutter door, and the target station coordinates of the automatic guided vehicle. By calculating the difference between the actual running parameter value and the corresponding reference set value, the deviation information of each time slice is obtained. Finally, all the deviation information of the time slices is arranged in chronological order to form a deviation information sequence, which is used for subsequent abnormality judgment and disposal control instruction generation.

[0144] S602: Obtain historical control event information.

[0145] Specifically, the historical control event information refers to a set of historical data related to control events recorded by the system during the operation of the production line, used to reflect the past abnormal handling and manual intervention. The historical control event information includes batch identification, station identification, event type, handling control instruction, execution confirmation result, modification trace information and corresponding timestamp. In specific implementation, first, the historical control event information records related to the target batch are retrieved in the database according to the batch identification, and the corresponding equipment operation abnormal event and material transfer abnormal event are extracted. For the sterilization cabinet, the historical control event information includes the handling control instruction and rollback record generated when the temperature or pressure is not up to standard, for the inoculation room, the historical control event information includes the operation interruption record and manual modification trace when the air cleanliness is not up to standard, for the roller shutter door and access control, the historical control event information includes the abnormal stop event when not acting according to the instruction, for the automated guided vehicle, the historical control event information includes the abnormal event of deviating from the path or not reaching the target station. Through the acquisition of the historical control event information, reference basis can be provided for subsequent pedigree abnormality statistics and dynamic abnormality threshold correction.

[0146] S603: Based on the target batch corresponding to the target batch gene pedigree and the historical control event information, the abnormality occurrence is counted to obtain pedigree abnormality statistics information.

[0147] Specifically, the pedigree abnormality statistics information refers to the statistical result formed after the abnormal events are classified and quantified based on the target batch gene pedigree and the historical control event information, used to represent the abnormal distribution of the target batch at different process links. In specific implementation, first, the target batch gene pedigree is taken as the main index, and the corresponding historical control event information records are matched one by one, and the abnormal events are established in correspondence with the process equipment nodes and link nodes in the gene pedigree. For example, in the sterilization cabinet link, the occurrence frequency of temperature non-compliance events and pressure abnormal events is counted, in the inoculation room link, the number of air cleanliness non-compliance events and manual modification events is counted, in the roller shutter door and access control link, the abnormal number of not opening or closing according to the instruction is counted, in the automated guided vehicle link, the abnormal records of path deviation and arrival failure are counted, and in the incubator link, the abnormal data of temperature and humidity exceeding the standard are counted. Then, according to the process equipment category and link order, the abnormal events are counted and weighted to obtain the pedigree abnormality statistics information containing batch dimension, link dimension and abnormal type dimension.

[0148] S604: The task release score and the pedigree abnormality statistics information are weighted and synthesized to obtain the threshold correction factor information, and the preset abnormal threshold is corrected according to the threshold correction factor information to obtain the dynamic abnormal threshold information.

[0149] Specifically, the threshold correction factor information refers to a correction coefficient obtained by weighted synthesis based on the task release score and the pedigree abnormality statistical information, and is used for dynamically adjusting the preset abnormality threshold. The dynamic abnormality threshold information refers to an abnormality judgment threshold after being corrected by the threshold correction factor information, and is used for adapting to actual operation states under different batches and different process conditions. In specific implementation, first, the task release score is standardized to the 0-1 interval, and is weighted and synthesized with the abnormality frequency and severity index in the pedigree abnormality statistical information to form the threshold correction factor information. The weighted synthesis adopts the following calculation formula: wherein Fadj represents the threshold correction factor information, Srel represents the standardized value of the task release score, Astat represents the weighted abnormality index of the pedigree abnormality statistical information, and are weight coefficients, and satisfy to ensure dimensional consistency. Then, the threshold correction factor information is applied to the preset abnormality threshold to obtain the dynamic abnormality threshold information, and the calculation formula is as follows: wherein Tdyn represents the dynamic abnormality threshold information, and Tpre represents the preset abnormality threshold. Through the calculation mode, if the pedigree abnormality statistical information represents frequent abnormalities or the task release score is low, the threshold correction factor information increases, so that the dynamic abnormality threshold information decreases, and thus the abnormality judgment is more easily triggered. Conversely, if the abnormalities are less and the task release score is high, the dynamic abnormality threshold information is increased to avoid excessive triggering. The dynamic abnormality threshold information serves as a reference threshold for subsequent deviation information sequence comparison, and ensures that the abnormality judgment process matches the actual risk level of the target batch.

[0150] S605: Accumulatively calculating the deviation information sequence in the sliding time slice to obtain abnormality accumulation degree information, comparing the abnormality accumulation degree information with the dynamic abnormality threshold information to obtain an abnormality judgment result, and generating a disposal control instruction according to the abnormality judgment result.

[0151] Specifically, the abnormality accumulation degree information refers to a measurement value obtained by accumulatively calculating the deviation information sequence in the sliding time slice, and is used for reflecting the accumulation degree of the deviation of the target device in a certain time range. The abnormality judgment result refers to a judgment conclusion obtained by comparing the abnormality accumulation degree information with the dynamic abnormality threshold information, and is used for representing whether the target device or process link enters an abnormal state. In specific implementation, first, the deviation information sequence is calculated in the sliding time slice by using a weighted accumulation method, and the formula is as follows: wherein Dcum(t) represents the abnormality accumulation degree information at the time slice t, wi represents a time decay factor, which ensures that recent deviations have higher weights in the cumulative calculation, and n represents the length of the sliding time slice. Then, the abnormal accumulation degree information is compared with the dynamic abnormal threshold information. When the abnormal accumulation degree information is greater than the dynamic abnormal threshold information, an abnormal determination result is generated as an abnormal state, otherwise it is determined as a normal state. Finally, a treatment control instruction is generated according to the abnormal determination result, such as a temperature rollback or shutdown instruction in the sterilization cabinet link, an air purification enhancement instruction in the inoculation room link, a passage prohibition instruction in the roller shutter door and access control link, a path rollback instruction in the automated guided vehicle link, and a humidity regulation or shutdown instruction in the culture chamber link. The treatment control instruction is the output of the abnormal management, which is used to trigger different levels of treatment measures.

[0152] In an embodiment, in step S60, corresponding abnormal treatment operations are performed under different abnormal levels according to the treatment control instruction, including:

[0153] S606: Based on the treatment control instruction and the cooperative interlocking matrix, the device action dependency relationship related to the abnormality is identified to obtain treatment coverage range information.

[0154] Specifically, the treatment coverage range information refers to the affected device set and its execution range formed by the device action dependency relationship identified based on the treatment control instruction and the cooperative interlocking matrix in the abnormal treatment process. In specific implementation, first, the target link and target device in the treatment control instruction are parsed, such as sterilization cabinet shutdown instruction, inoculation room air purification enhancement instruction, roller shutter door closing instruction, access control locking instruction, or automated guided vehicle path rollback instruction. Then, the device action dependency relationship related to the target device is searched in the cooperative interlocking matrix, such as inoculation room operation dependent on sterilization cabinet out-of-cabinet confirmation, automated guided vehicle access dependent on roller shutter door and access control state, and culture chamber operation dependent on inoculation room completion confirmation. Through dependency relationship expansion, a multi-level device link that may be affected by the treatment control instruction is obtained, such as sterilization cabinet shutdown affecting not only the sterilization cabinet itself, but also the subsequent operation of the inoculation room and the material handling of the automated guided vehicle. Finally, all affected devices and action ranges are subjected to set operation and boundary condition identification to generate treatment coverage range information. The treatment coverage range information is indexed by batch identification and station identification, and represents the overall device range that needs to be constrained when executing the treatment control instruction.

[0155] S607: According to the treatment coverage range information, the treatment control instruction is subjected to range contraction and time sequence rearrangement processing to obtain a contracted treatment control instruction.

[0156] Specifically, the shrunken treatment control instruction refers to an optimized treatment instruction set generated through range shrinkage and timing rearrangement processing under the constraint of treatment coverage range information, used to reduce irrelevant device actions and ensure reasonable execution order during abnormal treatment process. In specific implementation, first, all affected device action sets are identified based on the treatment coverage range information, such as sterilization cabinet shutdown action, inoculation room air purification enhancement action, roller shutter door closing action, access control locking action, and automatic guided vehicle back-off action. Then, the range shrinkage processing is performed on the device action set, that is, the device actions that are not directly related to the current abnormal treatment or repeatedly covered are removed, such as the actions irrelevant to the culture chamber in the sterilization cabinet shutdown abnormal treatment scenario. Subsequently, the timing rearrangement processing is performed on the remaining device actions according to the dependency relationship in the interlocking matrix, such as postponing the inoculation operation stop action until the air purification action in the inoculation room is completed, and performing the automatic guided vehicle back-off action after the roller shutter door is closed. Finally, the device actions after range shrinkage and timing rearrangement are recombined into a complete treatment control instruction set to obtain the shrunken treatment control instruction, which is used as the input basis for subsequent abnormal level judgment and treatment execution.

[0157] S608: The shrunken treatment control instruction is issued to the corresponding process equipment and material handling equipment to obtain treatment information.

[0158] Specifically, the treatment information refers to the execution feedback information returned by the process equipment and material handling equipment after receiving the shrunken treatment control instruction, used to represent the actual execution of the abnormal treatment action. In specific implementation, first, the shrunken treatment control instruction is distributed to the corresponding target equipment according to the equipment category, such as issuing the sterilization shutdown instruction to the sterilization cabinet control unit, issuing the air purification enhancement instruction to the inoculation room environment control device, issuing the closing instruction to the roller shutter door and access control, issuing the back-off instruction to the automatic guided vehicle navigation system, and issuing the shutdown or regulation instruction to the culture chamber monitoring unit. Subsequently, the device feedback state information is collected within a preset confirmation time limit, and the confirmation marks corresponding to the treatment actions are extracted, such as sterilization cabinet shutdown confirmation signal, inoculation room cleanliness recovery signal, roller shutter door and access control closing signal, automatic guided vehicle in-place signal, and culture chamber environment parameter recovery signal. The treatment information is generated by organizing and timestamp sorting the device feedback state information. The treatment information is stored with batch identifier and station identifier as index, used for subsequent abnormal level processing and revision audit chain writing.

[0159] S609: When the abnormal level is non-emergency stop level, the staged execution strategy is used to sequentially implement the graded treatment actions, and the treatment coverage range information is updated based on the device feedback state information and material flow information after the completion of each stage execution.

[0160] Specifically, the phased execution strategy refers to dividing the disposal process into several consecutive stages in the abnormal scenario of non-emergency stop level, and each stage corresponds to different intensity and range of disposal actions. The graded disposal action refers to the disposal measures that are gradually tightened according to the phased execution strategy, such as speed limiting, partial shutdown and full shutdown, etc. In specific implementation, first, the phased execution strategy is selected according to the abnormal level judgment result, for example, when the air cleanliness of the inoculation room deviates slightly, the first stage implements the speed limiting ventilation action, the second stage implements the partial shutdown action, and the third stage implements the full shutdown action. When the automated guided vehicle appears a slight deviation in the path, the first stage implements the speed limiting driving action, the second stage implements the local parking action, and the third stage implements the full parking action. Then, after the execution of each stage disposal action is completed, the state information and material flow information of the equipment are collected, it is verified whether the current disposal action is effective, and the disposal coverage range information is updated based on the new running state, for example, after the sterilization cabinet is shut down, the constraint range of the related actions of the inoculation room and the culture cabin is expanded, and after the roller shutter door is closed, the range of the related actions of the automated guided vehicle is contracted. In this way, a dynamic iterative disposal process is formed, which enables the disposal coverage range information to be gradually adjusted according to the phased execution strategy, and ensures that the graded disposal action is consistent with the running state of the production line.

[0161] S610: When the abnormal level is the emergency stop level, execute global disposal based on the contracted disposal control instruction, bind the disposal information and the control event information to obtain bound disposal information, and write the bound disposal information into the revision audit chain for revision of the target batch genetic pedigree.

[0162] Specifically, the bound disposal information refers to the composite record formed by one-to-one correspondence between the disposal information and the control event information in the abnormal scenario of the emergency stop level, which is used to represent the association between the global disposal action and the abnormal event. In specific implementation, first, the disposal action is executed in the global range based on the contracted disposal control instruction, including immediate shutdown of the sterilization cabinet, full-process suspension of the inoculation room operation, forced closure of the roller shutter door and the access control, emergency parking of the automated guided vehicle, and shutdown of the culture cabin. Then, the feedback state of each process equipment and material handling equipment during the emergency stop disposal process is collected to form the disposal information, and the corresponding action confirmation time and state marker are recorded in the database. Then, the disposal information and the control event information are bound according to the batch identifier and the station identifier to generate the bound disposal information, ensuring that each disposal action can be traced back to the corresponding abnormal event. Finally, the bound disposal information is written into the revision audit chain in a sequential node manner, and is associated with the target batch genetic pedigree for updating, so that the target batch genetic pedigree can reflect the occurrence of the emergency stop disposal in the traceability link, thereby ensuring the integrity of the cross-link abnormal management and traceability.

[0163] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0164] In one embodiment, a multi-equipment collaborative management and control system for an agricultural microbial preparation production line is provided. This system corresponds one-to-one with the multi-equipment collaborative management and control method for agricultural microbial preparation production lines described in the above embodiments. For example... Figure 4 As shown, the multi-equipment collaborative management and control system for the agricultural microbial preparation production line includes an operation status assessment module, a task release judgment module, a collaborative interlock construction module, an instruction distribution and execution module, a consistency verification and event management module, and an anomaly handling module.

Claims

1. A method for collaborative management and control of multiple devices in an agricultural microbial formulation production line, characterized in that, The method comprises the following steps: Obtain the running state information of the target device in the production line, and calculate the device health score based on the running state information; Obtain the biological risk index of the target batch, combine the device health score with the biological risk index to generate a task release score, and generate a production task instruction when the task release score meets a preset release threshold; Construct a collaborative interlocking matrix between the multi-type process equipment and the material handling equipment based on the production task instruction, and the collaborative interlocking matrix is used to constrain the execution timing between the multi-equipment, and a control execution instruction is generated when the multi-type process equipment is in an allowed execution state and the material handling equipment reaches a specified position and is in a safe state; Distribute the control execution instruction to the multi-type process equipment and the material handling equipment, drive the process operation and the material handling operation, and obtain device feedback state information and material flow information during the execution of the process operation and the material handling operation; Perform consistency checking on the device feedback state information and the material flow information to obtain a consistency checking result, generate control event information when the consistency checking result indicates that there is a deviation between the device feedback state information and the material flow information, and generate a revision audit chain corresponding to the control event information when manual modification is detected; When the running state information or the control event information triggers a preset abnormal threshold, generate a disposal control instruction, and execute corresponding abnormal disposal operations under different abnormal levels according to the disposal control instruction.

2. The method according to claim 1, wherein the method is characterized by, Obtain the running state information of the target device in the production line, and calculate the device health score based on the running state information, including: Obtain the corresponding running parameter time series from the running state information, and calculate the fluctuation trend index representing the stability of the device running based on the running parameter time series; According to the running parameters in the running state information representing the cooperative relationship between the target device and other process equipment, calculate the cooperative coupling deviation value of the target device; Combine the fluctuation trend index and the cooperative coupling deviation value, and perform weighted calculation according to the risk sensitive factor corresponding to the target process link to obtain the device health score.

3. The method according to claim 2, wherein the method is characterized by, Obtain the biological risk index of the target batch, combine the device health score with the biological risk index to generate a task release score, including: Perform standardization processing on the risk parameters of the target batch to obtain a risk feature vector; According to the risk sensitive factor corresponding to the target process link, perform weighted calculation on the risk feature vector of the target batch to obtain the biological risk index; When the biological risk index is higher than a preset risk threshold, modify the device health score according to a preset suppression rule to obtain a modified device health score; Combine the modified device health score and the biological risk index of the target batch according to the calculation rule of the task release score to obtain the task release score.

4. The method according to claim 1, wherein the method is characterized by, Based on the production task instruction, construct a collaborative interlocking matrix between the multi-type process equipment and the material handling equipment, including: Analyze the production task instruction, extract the process execution demand and material handling demand corresponding to the production task instruction; Determine the execution sequence of the multi-type process equipment according to the process execution demand, and determine the running position and running time of the material handling equipment according to the material handling demand; Based on the execution sequence of the multiple types of process equipment, the running position and timing of the material handling equipment, a dependency relationship and safety constraint condition between equipment actions are established; The dependency relationship and safety constraint condition are converted into interlocking rules to generate a collaborative interlocking matrix.

5. The method of claim 1, wherein the method comprises: In the process of distributing the control execution instructions to the multiple types of process equipment and the material handling equipment, the following steps are further included: An idempotent identifier is attached to the control execution instructions to obtain control execution instructions with idempotent identifiers; The control execution instructions with idempotent identifiers are queued according to the sequence determined by the collaborative interlocking matrix, and a pre-state check is performed based on the equipment feedback state information and the material flow information before issuance to obtain control execution instructions that pass the check; The control execution instructions that pass the check are issued to the corresponding target equipment, and an execution confirmation identifier is identified based on the equipment feedback state information within a preset confirmation time limit to obtain a confirmation result; When the confirmation result indicates that the execution is not successful, the control execution instructions are reissued according to the preset retry number and retry interval, and when the retry still fails, a rollback instruction is generated according to the preset rollback table, and the rollback instruction is issued to the corresponding equipment to restore to a safe baseline state.

6. The method of claim 1, wherein the method comprises: A consistency check is performed on the equipment feedback state information and the material flow information to obtain a consistency check result, including: Based on the equipment feedback state information and the material flow information, batch identifiers, tray identifiers, container identifiers, station identifiers, and time slice identifiers are extracted to obtain five-element association elements; The five-element association elements are combined to establish a five-element association key; Under the constraint of the five-element association key, the corresponding records of the equipment feedback state information and the material flow information are compared to generate a consistency check result.

7. The method according to claim 1, wherein the method is characterized by, When a manual modification is detected, a revision audit chain corresponding to the control event information is generated, including: Based on the detected manual modification, the manual modification association information corresponding to the manual modification is obtained to obtain a manual modification record; Based on the production task instruction corresponding to the target batch, the corresponding relationship between the target batch and the process equipment, the sterilization cycle, and the inoculation interval account is extracted to construct a target batch genealogy; The manual modification record and the target batch genealogy are bound to obtain bound modification trace information; The bound modification trace information is sequentially written into the revision audit chain to generate a revision audit chain corresponding to the control event information.

8. The method according to claim 1, wherein the method is characterized by, When the running state information or the control event information triggers a preset abnormal threshold, a disposal control instruction is generated, including: Based on the running state information, deviation information within a continuous time slice is extracted to obtain a deviation information sequence; Historical control event information is obtained; Based on the target batch genealogy corresponding to the target batch and the historical control event information, abnormal occurrence is counted to obtain spectrum abnormality statistical information; The task release score and the spectrum abnormality statistical information are weighted and synthesized to obtain a threshold correction factor information, and the preset abnormal threshold is corrected based on the threshold correction factor information to obtain dynamic abnormal threshold information; The deviation information sequence is accumulated within a sliding time slice to obtain abnormal accumulation degree information, and the abnormal accumulation degree information is compared with the dynamic abnormal threshold information to obtain an abnormality determination result, and a disposal control instruction is generated according to the abnormality determination result.

9. The method according to claim 1, wherein the method is characterized by, The corresponding abnormality handling operation is executed under different abnormality levels according to the handling control instruction, including: Based on the handling control instruction and the cooperative interlocking matrix, the device action dependency relationship related to the abnormality is identified to obtain handling coverage range information; According to the handling coverage range information, the range of the handling control instruction is contracted and the time sequence is rearranged to obtain a contracted handling control instruction; The contracted handling control instruction is issued to the corresponding process equipment and material handling equipment to obtain handling information; When the abnormality level is a non-emergency stop level, the hierarchical handling action is implemented in sequence according to the staging execution strategy, and the handling coverage range information is updated based on the device feedback state information and the material flow information after the completion of each stage; When the abnormality level is an emergency stop level, global handling is performed based on the contracted handling control instruction, and the handling information and the control event information are bound to obtain bound handling information, which is written into a revision audit chain for modification of the target batch gene pedigree.

10. An agricultural microbial preparation production line multi-device collaborative management and control system, characterized in that, The agricultural microbial preparation production line multi-device cooperative management and control system device includes: An operating state evaluation module is configured to obtain operating state information of a target device in a production line, and calculate a device health score based on the operating state information; A task release determination module is configured to obtain a biological risk index of a target batch, combine the device health score with the biological risk index to generate a task release score, and generate a production task instruction when the task release score meets a preset release threshold; A cooperative interlocking construction module is configured to construct a cooperative interlocking matrix between multi-type process equipment and material handling equipment based on a production task instruction, and the cooperative interlocking matrix is used to constrain the execution time sequence between the multi-devices, and a control execution instruction is generated when the multi-type process equipment is in an allowed execution state and the material handling equipment reaches a specified position and is in a safe state; An instruction distribution and execution module is configured to distribute the control execution instruction to the multi-type process equipment and the material handling equipment, drive the execution of process operations and material handling operations, and obtain device feedback state information and material flow information during the execution of the process operations and the material handling operations; A consistency check and event management module is configured to perform consistency checking on the device feedback state information and the material flow information to obtain a consistency checking result, generate a control event information when the consistency checking result indicates that there is a deviation between the device feedback state information and the material flow information, and generate a revision audit chain corresponding to the control event information when manual modification is detected; An abnormality handling module is configured to generate a handling control instruction when the operating state information or the control event information triggers a preset abnormality threshold, and execute corresponding abnormality handling operations under different abnormality levels according to the handling control instruction.

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