Beef cold chain processing and production scheduling system based on digital twinning

Abstract

The present application relates to the field of cold chain processing and digital twin technology, in particular to a beef cold chain processing production scheduling system based on digital twin; including a digital twin platform, a data determination module, a state acquisition module, a scheduling generation module, an instruction issuing module and a verification module; synchronously collecting beef parameters and station parameters, calculating batch heat load and estimating center temperature, determining heat risk grade, generating heat state data, determining process path according to heat risk weight, waiting time weight, order urgency weight, station congestion weight and energy consumption penalty weight, and outputting conveying line speed and shunt baffle instruction; when the center temperature is out of limit, triggering degradation shunt to the standby cooling area and recalculating the process path through the virtual twin model.

Description

Technical Field

[0001] This invention relates to the fields of cold chain processing and digital twin technology, specifically a production scheduling system for beef cold chain processing based on digital twins. Background Technology

[0002] In the cold chain processing of beef, the dynamic scheduling of material transportation and diversion is directly related to the temperature safety of the flow process; however, existing scheduling technologies usually adopt static rules such as single temperature monitoring, fixed threshold judgment or first-come-first-served, which often only focus on local temperature measurement results or static queuing status. This approach fails to comprehensively correlate factors such as batch heat load, core temperature changes, workstation congestion, and order urgency, making it difficult to accurately assess the real-time heating and cooling status of materials within the workstation. Fluctuations in a single parameter can easily lead to inaccurate diversion control strategies and path allocation, which not only poses a risk of localized processing temperatures exceeding limits but also exacerbates workstation congestion, ultimately restricting the overall material flow rate and product quality stability of the cold chain. Summary of the Invention

[0003] The purpose of this invention is to provide a production scheduling system for beef cold chain processing based on digital twins, addressing the following technical problems: Existing scheduling technologies have significant shortcomings in real-time temperature assessment and dynamic diversion control based on multiple parameters during beef cold chain circulation. There is an urgent need for a production scheduling system based on digital twins that can more accurately handle the correlation between batch thermal state and workstation factors and dynamically optimize process paths. Specifically, this invention provides the following technical solution: The beef cold chain processing production scheduling system based on digital twins includes a digital twin platform, a data judgment module, a status acquisition module, a scheduling generation module, an instruction issuance module, and a verification module. The digital twin platform is used to construct the virtual-real mapping relationship between the physical processing environment and the virtual twin model, and to update it synchronously in each update cycle. The data determination module is used to set the update cycle, collect beef parameters and workstation parameters, calculate the heat load of beef batches and estimate the center temperature, and determine the thermal risk level of the current cycle; the status acquisition module is used to generate thermal status data containing heat absorption and cooling based on the beef parameters, the workstation parameters and the maximum allowable heat load threshold obtained based on historical processing data. The scheduling generation module is used to establish queuing rules based on the thermal status data, and calculate the process path by combining the cold chain safety weights, which include thermal risk weights, waiting time weights, order urgency weights, workstation congestion weights, and energy consumption penalty weights; the instruction issuing module is used to generate conveyor line speed instructions and diversion baffle action instructions based on the thermal risk level, and output them to the physical processing environment after verification of the preset safe temperature upper limit, preset conveyor speed upper limit, and preset diversion baffle action boundary. The verification module is used to perform temperature limit checks on the conveyor line speed command and the diversion baffle action command to determine whether the center temperature exceeds the upper limit of the safe temperature; if it does, a downgrade diversion is triggered, diverting the corresponding batch of beef to the backup cooling area, and the process path is recalculated through the virtual twin model.

[0004] Preferably, the beef parameters include total batch mass, surface temperature, and equivalent thickness, which are obtained through a weighing sensor, an infrared thermometer, and a contour sensor, respectively; the workstation parameters include workstation air temperature, real-time wind speed, and queue length, which are obtained through a temperature and humidity sensor, a wind speed sensor, and a position sensor, respectively; the beef parameters and the workstation parameters are collected synchronously in each update cycle.

[0005] Preferably, determining the thermal risk level for the current period includes: calculating the ratio of the batch heat load to the maximum allowable heat load threshold; if the ratio is less than 50%, it is determined to be at a normal level; if the ratio is greater than or equal to 50% and less than 75%, it is determined to be at a concern level; if the ratio is greater than or equal to 75% and less than 90%, it is determined to be at a warning level; and if the ratio is greater than or equal to 90%, it is determined to be at a protection level.

[0006] Preferably, the data determination module determines the batch heat load based on the beef parameters and the workstation parameters, and obtains the batch heat load and center temperature of the previous update cycle to estimate the center temperature of the current cycle.

[0007] Preferably, the queuing rule schedules each batch of beef entering the buffer zone; it acquires the thermal risk value, waiting time, order urgency score, workstation congestion score, and energy consumption score corresponding to each batch of beef, and uses the thermal risk value, waiting time, and order urgency score as positive factors, and the workstation congestion score and energy consumption score as negative factors, wherein the weight of thermal risk is not less than the weight of order urgency; it determines the scheduling priority of each batch of beef based on the thermal risk value, waiting time, order urgency score, workstation congestion score, and energy consumption score, and outputs the processing order from high to low according to the scheduling priority as the process path.

[0008] Preferably, when generating the conveyor line speed command and the diversion baffle action command, the surface temperature is subjected to median filtering and the temperature change rate is calculated; when the absolute value of the temperature change rate is greater than a preset threshold determined based on the sensor no-load calibration for three consecutive times, it is determined as a temperature measurement failure, the unit of the preset threshold is ℃ / cycle; during the temperature measurement failure period, the heat load of the batch is estimated using the most recent effective surface temperature, the workstation air temperature and the real-time wind speed; if the temperature measurement failure lasts for more than 180 seconds, forced protection is triggered, and the thermal risk level is upgraded by one level; the heating rate of the current cycle is obtained, and when the beef batch residence time is greater than or equal to the limit residence time determined based on the upper limit of the safe temperature and the heating rate, a pre-cooling diversion command including the diversion baffle opening command is generated and output.

[0009] Preferably, the heat absorption and the cooling amount are determined based on the workstation air temperature, surface temperature, real-time wind speed, and material stacking form, respectively; the material stacking form includes flat laying, overlapping, and dense stacking, and the corresponding heat absorption correction coefficient and heat dissipation correction coefficient are obtained from a preset correction coefficient mapping table.

[0010] Preferably, after the pre-cooling diversion command is output, if the system communication or power supply is interrupted, a power-off reset operation is performed; the power-off reset operation uses the mechanical spring reset structure of the diversion baffle to make the diversion baffle return to its default physical position in the direction of guiding to the cooling zone, and to block the beef batch under protection from being sent to the packaging area.

[0011] In summary, the following beneficial effects can be obtained by applying the technical solution provided by this invention: 1. By collecting data on beef and workstation parameters, the batch heat load is calculated and the center temperature is estimated. Combined with multi-dimensional weights such as heat risk level and workstation congestion, the process path is dynamically planned. This solution breaks the limitations of traditional single fixed rule scheduling, can accurately assess the heating and heat dissipation status of materials during flow, effectively avoid the risk of local processing temperature exceeding the standard, and ensure the quality stability of cold chain products. 2. This system uses a verification module to perform temperature over-limit checks on control commands. When the estimated center temperature exceeds the safe upper limit, it automatically triggers a downgrade diversion to direct the beef to a backup cooling area and recalculates the path through a digital twin platform. This solves the congestion and heat accumulation problems caused by traditional static queuing, avoids inaccurate diversion control strategies, and effectively improves the overall material handling and flow rate of the cold chain. 3. During the temperature measurement failure period, this system can continue to estimate the heat load using the most recent valid temperature measurement value and environmental parameters. If the timeout is exceeded, the risk level will be upgraded and a pre-cooling diversion command will be output. In addition, in the event of power or communication interruption, the diversion baffle will be returned to the cooling zone direction through a mechanical spring reset structure. This mechanism ensures a safe closed loop for scheduling under abnormal operating conditions and prevents problematic materials from entering the packaging process. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0013] Figure 1 This is an architecture diagram of the beef cold chain processing production scheduling system based on digital twins, as described in this application. Detailed Implementation

[0014] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0015] Reference Figure 1 One embodiment of this application provides a digital twin-based beef cold chain processing production scheduling system, comprising: A digital twin platform is used to construct a virtual-real mapping relationship between the physical processing environment and the virtual twin model, and to update it synchronously in each update cycle; The data judgment module is used to set the update cycle, collect beef parameters and workstation parameters, calculate the heat load of beef batches and estimate the core temperature, and determine the thermal risk level of the current cycle. The status acquisition module is used to generate thermal status data containing heat absorption and cooling based on beef parameters, workstation parameters, and the maximum allowable heat load threshold obtained from historical processing data. The scheduling generation module is used to establish queuing rules based on thermal status data and calculate the process path by combining cold chain safety weights, which include thermal risk weights, waiting time weights, order urgency weights, workstation congestion weights, and energy consumption penalty weights. The instruction issuing module is used to generate conveyor line speed instructions and diversion baffle action instructions according to the thermal risk level, and outputs them to the physical processing environment after verification of the preset safe temperature limit, preset conveyor speed limit and preset diversion baffle action boundary. The verification module is used to check the temperature limits of the conveyor line speed command and the diversion baffle action command to determine whether the center temperature exceeds the preset safe temperature limit. If it does, it triggers a downgrade diversion, diverting the corresponding batch of beef to the backup cooling area, and recalculates the process path through a virtual twin model.

[0016] The beef parameters include total batch mass, surface temperature, and equivalent thickness, which are obtained through a weighing sensor, an infrared thermometer, and a contour sensor, respectively. The workstation parameters include workstation air temperature, real-time wind speed, and queue length, which are obtained through a temperature and humidity sensor, a wind speed sensor, and a position sensor, respectively. The beef parameters and workstation parameters are collected synchronously in each update cycle.

[0017] The determination of the current cycle's thermal risk level includes: calculating the ratio of the batch heat load to the maximum allowable heat load threshold; if the ratio is less than 50%, it is determined to be at the normal level; if the ratio is greater than or equal to 50% and less than 75%, it is determined to be at the attention level; if the ratio is greater than or equal to 75% and less than 90%, it is determined to be at the warning level; if the ratio is greater than or equal to 90%, it is determined to be at the protection level.

[0018] In practical applications: When beef batches are transferred between processes such as cutting, trimming, weighing, packaging and temporary storage, the system synchronously reads data such as total batch mass, surface temperature, equivalent thickness, workstation air temperature, real-time wind speed and queue length according to the set system cycle. The digital twin platform establishes a mapping table containing workstation node numbers, batch unique identifiers, and timestamps to store the correspondence between the physical processing environment and the virtual twin model. In each update cycle, the current workstation status parameters, batch parameters, and historical processing records are written into the same database tuple as status records according to the batch unique identifier, so that subsequent modules can directly read the current cycle data without tracing back the original sampling link; the update cycle is preferably 5 seconds to 30 seconds. When the conveyor line speed is greater than the set speed threshold or the batch switching frequency is greater than the set frequency threshold, the first preset period is taken. When the change rate of the workstation status is less than the set change rate threshold, the second preset period is taken. The first preset period is less than the second preset period, so as to ensure that various parameters are comparable within the same period. The data judgment module generates a heat load judgment result based on the synchronously collected data and estimates the center temperature; this estimation result, together with the maximum allowable heat load threshold, serves as the basis for thermal risk judgment; the status acquisition module generates thermal status data based on this, and writes the heat absorption and cooling amount into the status record respectively, which is then called by the scheduling generation module. Among them, the maximum allowable heat load threshold is associated with the heat absorption and cooling amount in the same state record in the current cycle. When the state acquisition module generates thermal state data, it first determines the heat absorption and cooling amount based on the beef parameters and workstation parameters in the current cycle, and then writes the maximum allowable heat load threshold corresponding to the batch into the same record for the data judgment module to directly read and calculate the ratio in the current cycle. Therefore, the threshold is used for subsequent thermal risk comparison and does not replace the generation process of heat absorption and cooling. The maximum allowable heat load threshold is established by cross-checking offline static statistics and online dynamic physical boundaries: first, batches whose center temperature has never exceeded the upper limit of safe temperature and whose finished product inspection is qualified are selected from historical processing data, and then grouped and statistically analyzed according to the equivalent thickness range and the total mass range of the batch. For each group of historical samples, the 95th percentile of the heat load distribution of the corresponding workstation is taken as the initial offline threshold. When the number of historical samples in a certain group is less than 30 batches, the smaller value of the corresponding percentile of the adjacent specification group in the most recent 30 days is used as the replacement. The system introduces online dynamic boundaries for secondary verification constraints to prevent the heat absorbed by the preceding process from causing the current workstation's capacity to be overestimated. The calculation process for the upper limit of the allowable heat load is as follows: the difference between the preset safe upper limit and the estimated center temperature when the batch enters the current workstation is multiplied by the specific heat capacity parameter of the beef of that specification retrieved from the preset product specification database and the total mass of the batch. The maximum net heat that the batch can absorb in the current workstation after deducting the heat absorbed by the preceding process is calculated and used as the upper limit of the online allowable heat load. When calculating the thermal state data for the same period, the system takes the smaller value between the offline initial threshold and the online allowable heat load upper limit as the real-time maximum allowable heat load threshold for that batch at the current workstation; the source of the threshold for the ratio calculation is clear, and the thresholds called for different specification batches are consistent; The scheduling generation module establishes queuing rules based on thermal status data, and combines thermal risk weight, waiting time weight, order urgency weight, workstation congestion weight and energy consumption penalty weight into cold chain safety weight to participate in process path calculation, thereby determining the processing order of each batch in the current cycle. When the instruction issuing module generates the conveyor line speed instruction and the diversion baffle action instruction, which are collectively referred to as the linkage control instruction, it first verifies the upper limit of temperature, the upper limit of conveyor speed, and the action boundary of the diversion baffle, and then sends the execution instruction to the physical processing environment; the verification module performs a temperature over-limit check on the linkage control instruction. If the estimated center temperature exceeds the preset safe temperature upper limit, the corresponding batch is transferred to the standby cooling area. Before outputting the degradation and diversion command, the verification module combines the physical position of the material from the target diversion baffle, the current actual linear velocity, and the physical deceleration and acceleration of the conveyor line, using kinematic equations. Solve for the actual remaining time of arrival, where, This indicates the physical location of the material relative to the target diversion baffle. This represents the current actual linear velocity. This indicates the physical deceleration acceleration of the conveyor line. Indicates the actual remaining time to arrive; If the remaining time is greater than the sum of the delay times of control communication and mechanical action pre-calibrated by the system, the instruction is issued directly; if the remaining time is insufficient, the diversion action is postponed and allocated to the next level of backup physical diversion node, and the subsequent process path is recalculated and updated through the virtual twin model. The steps of recalculating the process path include: updating the current status record with the backup physical diversion node that receives the postponed diversion batch as the new position starting point. When generating a new processing order to avoid the original congested nodes, the system forces the weight of the connected edge corresponding to the original congested node to infinity in the virtual mapping topology graph of the digital twin platform, thus blocking the possible route to that workstation. Starting from the next-level backup physical diversion node, a depth-first search is performed on the remaining available processing stations on each optional physical branch to obtain all logically reachable stations. The queue length corresponding to the above reachable stations and the upper limit of the queue allowed for that station are re-substituted into the calculation of station congestion score in the cold chain safety weight, thereby generating a new processing order that avoids the original over-limit congestion node as the process path, so that the scheduling basis of the next cycle is consistent with the actual physical flow. In one embodiment, the data determination module determines the batch heat load based on beef parameters and workstation parameters, and obtains the batch heat load and center temperature of the previous update cycle to estimate the center temperature of the current cycle.

[0019] The queuing rules schedule each batch of beef entering the buffer zone. They acquire the corresponding thermal risk value, waiting time, order urgency score, workstation congestion score, and energy consumption score for each batch, using thermal risk value, waiting time, and order urgency score as positive factors, and workstation congestion score and energy consumption score as negative factors, with thermal risk weighting no less than order urgency weighting. Based on these factors, the scheduling priority of each batch of beef is determined, and the processing order is output from high to low priority as the process path.

[0020] In practical applications: When a batch of beef enters the buffer, the system no longer determines the processing order solely based on the order of arrival. Instead, it incorporates the heat load of the current batch with the heat load and center temperature of the previous update cycle into the same calculation process. The data determination module first uses the beef parameters and workstation parameters collected in the current cycle to form the batch heat load, and then writes the batch heat load and center temperature of the previous update cycle into the estimation process to generate the center temperature of the current cycle. The steps for estimating the center temperature of the current cycle include: multiplying the batch heat load of the current cycle, i.e., the net heat of the current workstation heat absorption minus the cooling amount, by a preset thermal resistance coefficient determined by the equivalent thickness and the total mass of the batch, to obtain the temperature change of the current cycle, and then adding the temperature change to the center temperature of the previous update cycle to obtain the estimated value of the center temperature of the current cycle. The preset thermal resistance coefficient is set as a conversion factor for the conversion of net heat to temperature rise. Its value is equal to the reciprocal of the product of the specific heat capacity of the beef of this specification and the total mass of the batch. An equivalent thickness is introduced to correct the internal heat transfer hysteresis caused by the irregular shape. The steps for correcting the internal heat transfer hysteresis include: calculating the ratio between the equivalent thickness of the beef batch and the preset standard thickness of the corresponding product specification retrieved from the preset product specification database; if the ratio is greater than 1, the reciprocal is divided by the ratio. The calculation formula is as follows: in, Indicates the preset thermal resistance coefficient. This indicates the specific heat capacity parameter of beef of this specification. Indicates the total mass of the batch. Indicates standard thickness. This represents the equivalent thickness; by reducing the value of the conversion factor, it characterizes the delayed central heating caused by the sluggish heat transfer inside the thick-cut meat block. If the ratio is less than or equal to 1, the original reciprocal remains unchanged; the state records read by the scheduling generation module reflect continuous changes and conform to the thermodynamic self-consistency rule; In the process path calculation, the system takes thermal risk value, waiting time, and order urgency score as positive factors, and workstation congestion score and energy consumption score as negative factors. It also combines the corresponding thermal risk weight, waiting time weight, order urgency weight, workstation congestion weight and energy consumption penalty weight to perform weighted calculation to obtain cold chain safety weight, thereby determining the scheduling priority of each beef batch. Since the thermal risk weight is no less than the order urgency weight, batches with thermal risk levels at the warning or protection levels will be given priority in the processing order; and when the congestion score of a target workstation reaches the preset congestion limit threshold or the energy consumption score reaches the preset energy consumption limit threshold, the system will reduce the priority of the path corresponding to that workstation. The queuing rules are thus applied to each batch entering the buffer and output the processing order from high to low as the process path for the current cycle. When dealing with high concurrency, if multiple new beef batches flood into the buffer concurrently in the same update cycle, the status acquisition module uses a double-ended asynchronous queue to cache the batch data and ensures timing consistency through a read-write lock mechanism. After the process path is written into the scheduling record in the form of an ordered list composed of workstation node sequence and timestamp, it can be directly called by the subsequent instruction issuing module to avoid repeated calculations. Furthermore, if the batch at the head of the queue loses its physical position due to an accident before the instruction is executed, the system will listen for the position status change event of the virtual twin model and slide the pointer of the ordered list one position to the right to trigger the suboptimal batch, without triggering the synchronous recalculation of the entire buffer. To avoid directly mixing data of different dimensions, the heat risk value, waiting time, order urgency score, workstation congestion score, and energy consumption score are uniformly converted to 0 to 100 points before entering the weighted calculation; the heat risk value is mapped to 25 points, 50 points, 75 points, and 100 points respectively according to the four levels of normal, attention, warning, and protection. Waiting time is calculated as the ratio of the actual waiting time of the current batch in the buffer to the preset maximum waiting time. If the waiting time exceeds the preset maximum waiting time, it is scored out of 100 points. The order urgency score is mapped to three levels: normal, express, and express, which are respectively 40 points, 70 points, and 100 points. The workstation congestion score is calculated by converting the current queue length of the target workstation to the allowed queue limit for that workstation. If the queue length reaches or exceeds the allowed queue limit, it is scored as 100 points. The average energy consumption per unit time of the target path is calculated by multiplying the preset rated power records of the workstation equipment with the equipment start-stop status signals fed back from the physical processing environment and then summing them up. The energy consumption score is calculated by converting the average energy consumption per unit time of the target path to the benchmark energy consumption of similar paths. If the energy consumption reaches 1.2 times or more of the benchmark energy consumption, it is scored as 100 points. The scheduling priority corresponding to the cold chain security weight is calculated using the following formula: Priority Score = in, , , , , These correspond to the weights of thermal risk, waiting time, order urgency, workstation congestion, and energy consumption penalty, respectively. , ; Preferably, Take a value between 0.30 and 0.40. Take a value between 0.15 and 0.25. Take a value between 0.10 and 0.20. Take a value between 0.10 and 0.20. The priority score is set between 0.10 and 0.20. When priority scores are the same, the order of priority for batches is as follows: higher heat risk value, longer waiting time, and earlier arrival time in the buffer zone. When the congestion score of the target workstation reaches 100 points, the workstation will not be used as a new route in the current cycle, and only the batches that are already in transit will continue to be executed. In one embodiment, when generating conveyor line speed commands and diversion baffle action commands, the surface temperature is filtered by median and the temperature change rate is calculated; when the absolute value of the temperature change rate is greater than a preset threshold determined based on sensor no-load calibration for three consecutive times, it is determined that the temperature measurement has failed; during the temperature measurement failure period, the batch heat load is estimated using the most recent effective surface temperature, workstation air temperature and real-time wind speed. If the temperature measurement failure lasts for more than 180 seconds, a forced protection is triggered, and the thermal risk level is raised by one level. The heating rate of the current cycle is obtained. When the residence time of the beef batch is greater than or equal to the limit residence time determined based on the preset upper limit of safe temperature and heating rate, a pre-cooling diversion command containing the diversion baffle opening command is generated and output.

[0021] The heat absorption and cooling capacity are determined based on the workstation air temperature, surface temperature, real-time wind speed, and material stacking form, respectively. The material stacking form includes flat laying, overlapping, and dense stacking, and the corresponding heat absorption correction coefficient and heat dissipation correction coefficient are obtained from the preset correction coefficient mapping table. The total volume calculated using the total batch mass and standard density of beef is divided by the equivalent thickness to obtain the single-sided projected area. This area is then multiplied by the surface area exposure coefficient determined based on the material stacking morphology to determine the effective surface area for convective heat transfer. The formula is as follows: in, This represents the effective surface area for convective heat transfer. Indicates the total mass of the batch. Indicates the standard density of beef. Indicates the equivalent thickness. Indicates the surface area exposure coefficient; The basic heat absorption and basic cooling are calculated by multiplying the real-time temperature difference between the workstation air temperature and the surface temperature, the convective heat transfer coefficient obtained from the real-time wind speed query, and the update cycle time. The final heat absorption and cooling are calculated by multiplying the corresponding basic values ​​by the heat absorption correction coefficient and the heat dissipation correction coefficient, respectively.

[0022] After the pre-cooling diversion command is output, if the system communication or power supply is interrupted, a power-off reset operation is performed. The power-off reset operation uses the mechanical spring reset structure of the diversion baffle to make the diversion baffle return to its default physical position in the direction of guiding to the cooling zone, and blocks the beef batch under protection from being sent to the packaging area.

[0023] In practical applications: When generating conveyor line speed commands and diversion baffle action commands, the system first performs median filtering on the surface temperature and then calculates the temperature change rate to reduce the impact of temperature fluctuations on scheduling decisions; if the temperature change rate exceeds a preset threshold set based on sensor noise characteristics three times in a row, the system determines that the temperature measurement link has failed. During this period, the data determination module no longer relies on the current surface temperature, but instead calls the most recent effective surface temperature and combines it with the workstation air temperature and real-time wind speed to estimate the batch heat load, maintaining continuous updates of the heat load data; the steps for estimating the batch heat load include: the system first calculates the total volume of the corresponding batch based on the total mass of the batch and the standard density of beef called from the preset product specification database, and then divides the total volume by the equivalent thickness to obtain the effective surface area for Newtonian cooling heat exchange. Based on the temperature difference between the workstation air temperature and the nearest effective surface temperature, combined with the convective heat transfer coefficient obtained by querying the preset wind speed convection mapping table from the real-time wind speed and the effective surface area derived above, the three are multiplied to calculate the theoretical heat absorption power per unit time. Then, the theoretical heat absorption power is multiplied by the duration of the update cycle to obtain the theoretical heat absorption of the current cycle. The baseline cooling amount set based on historical records is subtracted to obtain the estimated batch heat load, which is in joules. This eliminates the dimensional contradiction between power and heat in the time dimension during the conversion and completes the physical boundary conditions missing in the heat transfer equation in the system scheduling. The preset wind speed convection mapping table stores the definite mapping relationship between wind speed range and convection heat transfer coefficient. For example, wind speed of 0 to 0.5 m / s corresponds to heat transfer coefficient of 15, 0.5 to 2.0 m / s corresponds to 25, and greater than 2.0 m / s corresponds to 35. Based on the baseline cooling capacity set by historical records, the average heat dissipation power per unit time of the same specifications and whose center temperature has not exceeded the limit in the corresponding workstation of the most recent 7 production days is extracted and multiplied by the duration of the update cycle. If the temperature measurement failure lasts for more than 180 seconds, the thermal risk level will be upgraded by one level, and the processing order of this batch will be rewritten into the scheduling record. The duration of the temperature measurement failure is calculated based on the cumulative duration of the continuous failure to restore the effective surface temperature. Once the effective temperature measurement value is restored to a value that does not exceed the preset threshold within any update cycle, the cumulative duration will be cleared and the timer will start again. The median filter uses surface temperature samples from three consecutive update cycles as a sliding window. The preset threshold is determined through sensor no-load calibration, which involves continuously collecting surface temperature data for at least 10 minutes under no-load conditions on the conveyor line and with stable station temperature. The absolute values ​​of the temperature change rates in adjacent cycles are statistically analyzed, and three times the 95th percentile value is taken as the preset threshold, which is not less than 0.3℃ / cycle. This provides a repeatable calibration basis for determining if the temperature change rate exceeds the preset threshold three times consecutively. In the calculation of heat absorption and cooling, the system uses the workstation air temperature, surface temperature, real-time wind speed and material stacking form as judgment conditions. The material stacking form is distinguished by flat, overlapping and dense stacking. The corresponding heat absorption correction coefficient and heat dissipation correction coefficient are read from the preset mapping table and used in the calculation, so that the same batch can obtain different thermal state data under different stacking states. The stacking pattern of the materials is determined according to the coverage ratio of adjacent meat pieces: a coverage ratio of less than 20% is considered flat, a coverage ratio of 20% or more but less than 50% is considered overlapping, and a coverage ratio of 50% or more is considered dense stacking; correspondingly, the heat absorption correction coefficient is preferably 1.00, 1.08, or 1.15, and the heat dissipation correction coefficient is preferably 1.00, 0.92, or 0.85. This data is passed to the scheduling generation module to update the process path; for the extreme residence time in the embodiment, the system determines it according to the remaining temperature difference between the current estimated center temperature and the set upper limit of the safe temperature and the current heating rate. The current heating rate is calculated by dividing the change in center temperature in the current cycle by the duration of the update cycle, in °C / second. When the current heating rate is greater than 0, to eliminate the timing conflict between dwell time and remaining available time, the system strictly divides the timing boundary into the already spent time and the remaining safe time: the theoretical remaining safe time in seconds is calculated by dividing the difference between the set upper limit of the safe temperature and the current estimated center temperature by the current heating rate. The calculation formula is as follows: in, Indicates the theoretical remaining safe time. This indicates that a safe upper temperature limit has been set. This indicates the current estimated center temperature. Indicates the current heating rate; The remaining safe time is added to the accumulated dwell time of the batch since it entered the current workstation. The sum of the two is used as a scale to characterize the total safe dwell time span of the physical processing of the batch, i.e., the limit dwell time. When the current heating rate is less than or equal to 0, it indicates that the batch is cooling down or the temperature is stable. The maximum residence time is considered to be infinite. The system maintains the original path and continues to verify in subsequent update cycles, without triggering pre-cooling diversion due to this rule alone. The system directly compares the accumulated dwell time of beef batches with the limit dwell time to eliminate the timing conflict of equating the remaining allowable time with the absolute overtime standard. This ensures that the precooling diversion command is strictly aligned with the dimensional conversion from the cycle increment to the second-level time scale, accurately corresponding to the remaining temperature difference, heating rate and accumulated dwell time. In addition, to ensure that the linkage control commands have clear execution quantities, the conveyor speed commands are output in stages according to the thermal risk level: the normal level maintains the preset conveyor base speed, the attention level is reduced to 90% of the base speed, the warning level is reduced to 75% of the base speed, and the protection level is reduced to 60% of the base speed and the diversion baffle opening command is generated first. If the verification module determines that the estimated center temperature has exceeded the upper limit of the safe temperature, it will no longer execute the operation of reducing the conveyor line speed, but will directly output a downgrade diversion command; the action boundary of the diversion baffle is based on the open and closed signals of the mechanical limit switch, and the command is only confirmed to be completed when the feedback from the target position is valid. In the instruction interaction control logic, the instruction issuing module maintains an instruction state machine. When an instruction is issued, the state machine flips to the action waiting state and starts a two-way handshake countdown. If no valid position feedback is obtained within two update cycles, it is considered that the baffle execution is abnormal, and the state machine is forcibly flipped to the abnormal blocking state. In this state, the system broadcasts a fault interruption event to the upstream node to cut off the new batch of conveyor speed instructions. On the other hand, it shields the control enable of the diversion baffle at the bottom layer, so that it relies entirely on its own power-off return physical characteristics to maintain the safe action of guiding to the cooling area, thus realizing a safe closed loop from the software control layer to the physical execution layer. If the system communication or power supply is interrupted after the pre-cooling diversion command is output, a power-off reset operation is performed. The diversion baffle returns to its physical position guided to the cooling zone by the mechanical spring reset structure, and blocks the beef batch under protection from continuing to be sent to the packaging area. This processing method ensures that the material flow direction remains in the preset safe direction when the control link is interrupted, avoiding inconsistency between the status record and the actual execution position.

[0024] For any part not mentioned in this invention, existing technologies can be used or referenced. Of course, the above description is not a limitation of this invention, and this invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of this invention should also be within the protection scope of this invention.

Claims

1. A beef cold chain processing production scheduling system based on digital twins, characterized in that, include: A digital twin platform is used to construct a virtual-real mapping relationship between the physical processing environment and the virtual twin model, and to update it synchronously in each update cycle; The data judgment module is used to set the update cycle, collect beef parameters and workstation parameters, calculate the heat load of beef batches and estimate the core temperature, and determine the thermal risk level of the current cycle. The status acquisition module is used to generate thermal status data containing heat absorption and cooling based on the beef parameters, the workstation parameters, and the maximum allowable heat load threshold obtained based on historical processing data. The scheduling generation module is used to establish queuing rules based on the thermal state data, and calculate the process path by combining the cold chain safety weights, which include thermal risk weights, waiting time weights, order urgency weights, workstation congestion weights, and energy consumption penalty weights. The instruction issuing module is used to generate conveyor line speed instructions and diversion baffle action instructions according to the thermal risk level, and output them to the physical processing environment after verification of the preset safe temperature upper limit, preset conveyor speed upper limit and preset diversion baffle action boundary. The verification module is used to perform temperature over-limit checks on the conveyor line speed command and the diversion baffle action command to determine whether the center temperature exceeds the preset safe temperature limit. If the quantity exceeds the limit, a downgraded diversion is triggered, diverting the corresponding batch of beef to a backup cooling area, and recalculating the process path using the virtual twin model.

2. The beef cold chain processing production scheduling system based on digital twins according to claim 1, characterized in that, The beef parameters include total batch mass, surface temperature, and equivalent thickness, which are obtained through a weighing sensor, an infrared thermometer, and a contour sensor, respectively. The workstation parameters include workstation air temperature, real-time wind speed, and queue length, which are obtained through a temperature and humidity sensor, a wind speed sensor, and a position sensor, respectively. The beef parameters and the workstation parameters are collected synchronously in each update cycle.

3. The beef cold chain processing production scheduling system based on digital twins according to claim 1, characterized in that, The determination of the current cycle's thermal risk level includes: calculating the ratio of the batch heat load to the maximum allowable heat load threshold; if the ratio is less than 50%, it is determined to be at the normal level; if the ratio is greater than or equal to 50% and less than 75%, it is determined to be at the attention level; if the ratio is greater than or equal to 75% and less than 90%, it is determined to be at the warning level; if the ratio is greater than or equal to 90%, it is determined to be at the protection level.

4. The beef cold chain processing production scheduling system based on digital twins according to claim 2, characterized in that, The data determination module determines the batch heat load based on the beef parameters and the workstation parameters, and obtains the batch heat load and center temperature of the previous update cycle to estimate the center temperature of the current cycle.

5. The beef cold chain processing production scheduling system based on digital twins according to claim 1, characterized in that, The queuing rule schedules each batch of beef entering the buffer zone; it obtains the heat risk value, waiting time, order urgency score, workstation congestion score, and energy consumption score corresponding to each batch of beef, and uses the heat risk value, waiting time, and order urgency score as positive factors, and the workstation congestion score and energy consumption score as negative factors, wherein the weight of heat risk is not less than the weight of order urgency. The scheduling priority of each beef batch is determined based on the heat risk value, waiting time, order urgency score, workstation congestion score, and energy consumption score. The processing order is then output in descending order of scheduling priority as the process path.

6. The beef cold chain processing production scheduling system based on digital twins according to claim 2, characterized in that, When generating conveyor speed commands and diversion baffle action commands, the surface temperature is filtered by median and the temperature change rate is calculated. If the absolute value of the temperature change rate exceeds a preset threshold determined based on sensor no-load calibration three times consecutively, it is determined as a temperature measurement failure. During the temperature measurement failure period, the heat load of the batch is estimated using the most recent effective surface temperature, workstation air temperature, and real-time wind speed. If the temperature measurement failure lasts for more than 180 seconds, forced protection is triggered, and the thermal risk level is increased by one level. The heating rate of the current cycle is obtained. When the beef batch residence time is greater than or equal to the limit residence time determined based on the preset safe temperature upper limit and the heating rate, a pre-cooling diversion command including a diversion baffle opening command is generated and output.

7. The beef cold chain processing production scheduling system based on digital twins according to claim 4, characterized in that, The heat absorption and the cooling amount are determined based on the workstation air temperature, surface temperature, real-time wind speed, and material stacking form, respectively; the material stacking form includes flat laying, overlapping, and dense stacking, and the corresponding heat absorption correction coefficient and heat dissipation correction coefficient are obtained from a preset correction coefficient mapping table; The total volume calculated using the batch total mass and standard density of beef is divided by the equivalent thickness to obtain the single-sided projected area. This area is then multiplied by the surface area exposure coefficient determined based on the material stacking morphology to determine the effective surface area for convective heat transfer. The formula is as follows: The basic heat absorption and basic cooling are calculated by multiplying the real-time temperature difference between the workstation air temperature and the surface temperature, the convective heat transfer coefficient obtained from the real-time wind speed query, and the update cycle time. The final heat absorption and cooling are calculated by multiplying the corresponding basic values ​​by the heat absorption correction coefficient and the heat dissipation correction coefficient, respectively.

8. The beef cold chain processing production scheduling system based on digital twins according to claim 6, characterized in that, After the pre-cooling diversion command is output, if the system communication or power supply is interrupted, a power-off reset operation is performed. The power-off reset operation uses the mechanical spring reset structure of the diversion baffle to make the diversion baffle return to its default physical position in the direction of guiding to the cooling zone, and to block the beef batch under protection from being sent to the packaging area.

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