A pre-prepared food product full life cycle data management method

Abstract

This invention relates to the field of pre-prepared food management technology, specifically a method for managing the entire lifecycle data of pre-prepared food products. The method includes the following steps: collecting real-time temperature data inside the sterilization autoclave, extracting the lethality reduction coefficient and target temperature sterilization time parameters corresponding to target microorganisms in the pre-prepared food products, and generating a set of microbial thermal lethality kinetic parameters. In this invention, simple production schedule management is transformed into decision-making based on default risk and energy cost economics. Nonlinear gain calculations are used to strengthen the weight of high-energy-efficiency orders. Power supply access control is implemented for orders in production based on a generated priority sequence for power resource allocation. Low-priority power supplies are cut off, and steam allocation signals are responded to simultaneously. While ensuring the timely delivery of core high-value orders, peak shaving and valley filling are achieved using electricity price fluctuations and energy consumption differences, thus achieving optimal control over both food safety and production energy costs.

Description

Technical Field

[0001] This invention relates to the field of pre-prepared food management technology, and in particular to a method for managing the entire lifecycle data of pre-prepared food products. Background Technology

[0002] The field of pre-prepared food management covers the systematic control of the entire industrial chain, from the selection of agricultural raw materials, standardized central kitchen processing, finished product packaging, cold chain logistics distribution to end consumers. It is used to solve problems such as low standardization, low efficiency and difficulty in tracing food safety in traditional catering.

[0003] In current pre-prepared food production management, the sterilization process often relies on experience-based fixed temperatures and durations, leading to widespread over-sterilization in the pursuit of safety. This not only results in wasted steam energy but also damages the taste and nutritional components of ingredients due to prolonged high-temperature maintenance. Furthermore, production scheduling strategies typically follow a first-in, first-out (FIFO) or single-delivery-date principle, neglecting the impact of fluctuating electricity prices and varying production line energy consumption on production costs. It is also difficult to quantify and assess the economic balance between order default risk and energy input. When facing energy supply shortages or cost control pressures, the lack of scientific data to guide production line start-up and shutdown decisions leads to high-energy-consuming, low-value orders crowding out power resources during peak electricity price periods, while urgent orders with high default penalties are delayed due to a lack of priority guarantees. This results in inflated energy costs and increased contract fulfillment risks for enterprises. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method for managing the entire lifecycle data of pre-prepared food products.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for managing the entire lifecycle data of pre-prepared food products, comprising the following steps:

[0006] Real-time temperature data inside the sterilization autoclave is collected, and the lethality reduction coefficient and the target temperature sterilization time parameter corresponding to the target microorganism in the pre-cooked food product are extracted to generate a set of microbial thermal lethality kinetic parameters. The sterilization safety threshold data is obtained by calculating the set of microbial thermal lethality kinetic parameters.

[0007] Using the sterilization safety threshold data and the real-time temperature data of the sterilization autoclave, the real-time cumulative lethality value is calculated. The difference between the real-time cumulative lethality value and the sterilization safety threshold data is compared. The opening of the steam valve is adjusted according to the comparison difference to generate a dynamic steam energy distribution signal.

[0008] Obtain the rated power of the packaging production line, the remaining processing time of the current batch, the amount of order default penalty, and the electricity price data for the current period. Calculate the ratio of the order default penalty to the product of the rated power, the remaining processing time, and the electricity price, and then calculate it with the remaining processing time to obtain the order energy efficiency urgency index.

[0009] Based on the order energy efficiency urgency index, all orders in production are sorted and the power supply access range is defined, generating a power resource allocation priority sequence. Based on the power resource allocation priority sequence, the power supply to packaging production lines with lower priority than the target is cut off. At the same time, the main steam pipeline is opened and closed in response to the dynamic steam energy allocation signal, generating a comprehensive energy allocation execution plan.

[0010] Preferably, the step of obtaining the sterilization safety threshold data is as follows:

[0011] The continuous temperature sampling sequence is read from fixed measuring points inside the sterilizer. The integrity of the timestamp is verified and missing records are removed. The sensor calibration coefficient is synchronized and the temperature scale unit is unified. The data is rearranged according to the sampling order and the batch identifier is retained to obtain real-time temperature data.

[0012] Based on the real-time temperature data, the target microbial identifier is parsed and the temperature range is located. The lethal time reduction coefficient and the target temperature sterilization time parameter are retrieved. Consistency is checked by batch and temperature range and concatenated by field to generate a set of microbial thermal lethality kinetic parameters.

[0013] Based on the set of microbial thermal lethality kinetic parameters, parameters are filled in according to the field order of the benchmark sterilization formula and the time window boundary is set. The termination point of the cumulative lethality curve is located as the target integration cutoff point, and sterilization safety threshold data is generated.

[0014] Preferably, the step of obtaining the real-time cumulative lethality value is as follows:

[0015] Using the sterilization safety threshold data and the real-time temperature data of the sterilization autoclave, the data is aligned by timestamp and missing records are removed. Fixed sampling intervals are divided and the lethal contribution of each interval is calculated. The data is then accumulated to the current time in chronological order to generate a real-time cumulative lethality rate value.

[0016] Preferably, the step of acquiring the dynamic steam energy distribution signal is as follows:

[0017] Based on the real-time cumulative mortality rate, the sterilization safety threshold data is called for hourly comparison, the absolute difference is calculated and marked with positive and negative signs, the direction and magnitude of the difference change are recorded, and the comparison difference is generated.

[0018] Based on the comparison difference and the current position of the steam valve opening, the upper limit of the steam valve opening change step size and opening change rate is set, the adjustment direction is mapped as the opening increase / decrease command, encoded as a control field, and a dynamic steam energy distribution signal is generated.

[0019] Preferably, the step of obtaining the order energy efficiency urgency index is as follows:

[0020] It aggregates rated power, remaining processing time for the current batch, order default penalty amount, and electricity price data for the current period, unifying the power unit to kilowatts, the time unit to hours, the currency unit to a single currency, and the electricity price unit to the currency per kilowatt-hour, generating unified metering parameter items;

[0021] Based on the unified metering parameters, align the records of the same batch by timestamp and lock the remaining processing time of the current batch. Calculate the product of the rated power, the remaining processing time of the current batch, and the electricity price data for the current period. Calculate the ratio of the order default penalty amount to the product to obtain the default risk ratio.

[0022] Based on the default risk ratio, and combined with the rated power, remaining processing time of the current batch, order default penalty amount, and electricity price data in the unified metering parameters, the order energy efficiency urgency index is calculated.

[0023] Preferably, the step of obtaining the power resource allocation priority sequence is as follows:

[0024] Based on the order energy efficiency urgency index, the list of orders in production is sorted in descending order, a power supply access threshold number is set and a cut-off mark is marked below the threshold number, the batch number, work station number and timestamp fields are merged, the completeness of the records is checked and the current valid list is locked to form a power resource allocation priority sequence.

[0025] Preferably, the step of obtaining the integrated energy allocation execution plan is as follows:

[0026] Based on the power resource allocation priority sequence, the power circuit numbers of the packaging production line below the target priority threshold are extracted and a processing queue is established. The consistency between the circuit status identifier and the power outage permission identifier is verified. Disconnection action code and reset action code are generated in the order of the processing queue to obtain the power cut-off control instruction set.

[0027] Preferably, the step of obtaining the integrated energy allocation execution plan further includes: reading the main steam pipeline on / off identifier in the dynamic steam energy distribution signal according to the power cut-off control instruction set and cross-aligning it according to the timestamp, verifying that the power disconnection sequence of the same batch does not conflict with the main steam pipeline on / off sequence, merging the execution window and safety interlock conditions, and generating the integrated energy allocation execution plan.

[0028] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0029] In this invention, real-time temperature data inside the sterilization autoclave is collected, and the lethal kinetic parameters of the target microorganisms are extracted. A sterilization model is constructed by combining the lethality time reduction coefficient and the target temperature sterilization time parameter. This model breaks free from the constraints of traditional fixed-time sterilization methods. By setting a target integral cutoff point to generate a sterilization safety threshold, the sterilization process is ensured to closely follow the microbial lethality threshold. This avoids both overheating leading to taste deterioration and energy waste, and incomplete sterilization preventing food safety incidents. The real-time cumulative lethality rate is calculated using the sterilization safety threshold and real-time temperature data. The difference between these two values ​​is used to adjust the steam valve opening, achieving dynamic on-demand distribution of steam energy and improving thermal energy utilization efficiency. Simultaneously, data on the rated power of the packaging production line, remaining processing time, order default penalties, and real-time electricity prices are acquired to construct a multi-dimensional evaluation system that includes an order energy efficiency urgency index. This transforms simple production schedule management into decision-making based on default risk and energy cost economics. By using nonlinear gain calculations to enhance the weight of high-energy-efficiency orders, and by implementing power supply access control for orders in production based on the generated power resource allocation priority sequence, low-priority power supplies are cut off and steam allocation signals are responded to simultaneously. While ensuring the timely delivery of core high-value orders, peak shaving and valley filling are carried out using electricity price fluctuations and energy consumption differences, achieving optimal control of both food safety and production energy costs. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the steps of the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0032] Please see Figure 1 This invention provides a technical solution: a method for managing the entire lifecycle data of pre-prepared food products, comprising the following steps:

[0033] Real-time temperature data inside the sterilization autoclave is collected, and the lethality reduction coefficient and the target temperature sterilization time parameter corresponding to the target microorganisms in the pre-cooked food products are extracted to generate a set of microbial thermal lethality kinetic parameters. The sterilization safety threshold data is obtained by calculating the microbial thermal lethality kinetic parameter set.

[0034] By referencing sterilization safety threshold data and real-time temperature data of the autoclave, the real-time cumulative lethality value is calculated. The difference between the real-time cumulative lethality value and the sterilization safety threshold data is compared. Based on the comparison difference, the opening degree of the steam valve is adjusted to generate a dynamic steam energy distribution signal.

[0035] Obtain the rated power of the packaging production line, the remaining processing time of the current batch, the amount of order default penalty, and the electricity price data for the current period. Calculate the ratio of the order default penalty to the product of the rated power, the remaining processing time, and the electricity price, and then calculate it with the remaining processing time to obtain the order energy efficiency urgency index.

[0036] Based on the order energy efficiency urgency index, all orders in production are sorted and the power supply access range is defined, generating a power resource allocation priority sequence. Based on the power resource allocation priority sequence, the power supply to packaging production lines with lower priority than the target is cut off. At the same time, the main steam pipeline is opened and closed in response to the dynamic steam energy allocation signal, generating a comprehensive energy allocation execution plan.

[0037] The steps for obtaining sterilization safety threshold data are as follows:

[0038] The continuous temperature sampling sequence is read from fixed measuring points inside the sterilizer. The integrity of the timestamp is verified and missing records are removed. The sensor calibration coefficient is synchronized and the temperature scale unit is unified. The data is rearranged according to the sampling order and the batch identifier is retained to obtain real-time temperature data.

[0039] Based on real-time temperature data, the target microbial identifier is analyzed and the temperature range is located. The lethal time reduction coefficient and the target temperature sterilization time parameter are retrieved. Consistency is checked by batch and temperature range and concatenated by field to generate a set of microbial thermal lethality kinetic parameters.

[0040] Based on the set of microbial thermal lethality kinetic parameters, parameters are filled in according to the field order of the benchmark sterilization formula and the time window boundary is set. The termination point of the cumulative lethality curve is located as the target integration cutoff point, and sterilization safety threshold data is generated.

[0041] Specifically, a continuous temperature sampling sequence is read from fixed measuring points inside the sterilizer. A multi-channel temperature acquisition module is configured to acquire signals from PT100 resistance temperature detectors deployed at three key locations (top, middle, and bottom) inside the sterilizer. The sampling frequency is set to once per second to obtain details of high-frequency temperature fluctuations. The acquired raw voltage signals are converted into digital sequences using an analog-to-digital converter. Each timestamp in the sequence is traversed to check its continuity. If the difference between two adjacent timestamps exceeds the preset allowable error range of the sampling interval (e.g., if the standard sampling interval is set to 1 second and the difference between adjacent timestamps is greater than 1.5 seconds), it is determined that packet loss or communication delay has occurred. At this time, the position is marked as a missing record, and the adjacent valid data points are automatically called up for linear interpolation to complete the record. The specific interpolation calculation is based on... ,in The temperature value to be completed. This is the previous valid temperature value. This is the next effective temperature value. Representing the corresponding timestamp, the system then reads the sensor calibration coefficient file stored in the device's non-volatile memory. This file is obtained by fitting the sensor to a high-precision standard thermometer by placing it in a standard constant-temperature oil bath, and includes slope correction coefficients. With intercept correction factor For each original temperature value Perform correction operation ,in Let it be a real number between 0.998 and 1.002. Set the value to a real number between -0.5 and 0.5, and check the temperature scale attribute of the data. If a data identifier that is not in degrees Celsius is identified, convert it to degrees Celsius using a standard conversion formula. Finally, merge and sort all the processed channel data according to the order of timestamps, and attach the unique code "BATCH_ID" of the current production batch as a metadata tag to the header field of each temperature record to obtain the real-time temperature data.

[0042] Based on real-time temperature data, the recipe code field of pre-cooked food products is analyzed to identify the most heat-sensitive or representative spoilage bacteria as target microorganisms. For example, Clostridium botulinum is targeted for low-acid meat pre-cooked dishes, while pasteurization-resistant heat-resistant bacteria are targeted for acidic fruits and vegetables. Subsequently, a pre-constructed microbial heat lethality kinetics database is accessed. This database is based on laboratory heat resistance tests, where the target microorganisms are inoculated into a specific substrate, heated at different constant temperatures, and the logarithmic decrease curve of the survival rate is recorded to calculate the lethality reduction coefficient. The value and the sterilization time parameter at the target temperature are... During the search process, it is necessary to match the product matrix type and pH range to extract the corresponding values. Value and reference temperature Below Values, for example, for botulinum toxin extract. as well as Next, the extracted parameters are checked for applicability and consistency to determine whether the current sterilization autoclave's set temperature range is within the lethal temperature range of the microorganism. For example, it is confirmed whether the sterilization temperature set value of 121 degrees Celsius is within the range of lethal temperature range of the microorganism. Within the effective killing range, if the verification passes, the batch number, product type, target microorganism name, and other relevant information will be recorded. value, value and The values ​​are concatenated bit by bit according to a predefined data structure protocol to form a parameter package containing complete thermodynamic properties, generating a set of kinetic parameters for microbial thermal death.

[0043] Based on the set of microbial thermal death kinetic parameters, the commonly used industrial benchmark sterilization intensity calculation formula is invoked. The value calculation model will use the parameter set Value and reference temperature Enter the exponent term in the integral formula and set the time window boundary for the integral calculation. Generally, the moment when the temperature inside the reactor first reaches the effective sterilization initiation temperature, such as 100 degrees Celsius, is marked as the integration starting point. The point at which the temperature drops below the effective temperature during the cooling phase is marked as the integration termination point. The sterilization safety threshold is set according to the hygiene requirements of commercial aseptic technology. This threshold is based on the requirement of achieving a microbial reduction of 12 logarithmic cycles, i.e., the "12D" principle. The basic safety threshold is calculated as follows: In order to address the uncertainty of the cold spot location and the heating lag effect, a safety factor is introduced. The value is typically between 1.1 and 1.3, used to calculate the final sterilization safety threshold data. The calculation formula is: ,in The final set sterilization safety threshold represents the equivalent sterilization time required at the reference temperature. For safety redundancy coefficient, The attenuation time parameter for the target microorganism at a reference temperature is the time required to kill 90% of the microorganisms. For example, when , The calculated threshold is 3.6 minutes. This value is used as the minimum cumulative lethal dose that must be reached in this sterilization process to generate sterilization safety threshold data.

[0044] The steps to obtain the real-time cumulative lethality rate are as follows:

[0045] By referencing sterilization safety threshold data and real-time temperature data of the autoclave, aligning them by timestamp and removing missing records, dividing them into fixed sampling intervals and calculating the lethal contribution of each interval, and accumulating them in chronological order to the current moment, a real-time cumulative lethality rate value is generated.

[0046] Specifically, by referencing sterilization safety threshold data and real-time temperature data of the autoclave, key thermodynamic constants contained in the threshold data package are extracted, including the reference temperature. The temperature is typically set at 121.1 degrees Celsius, along with the lethal temperature coefficient of the target microorganism. The value, typically set to 10 degrees Celsius, is used to simultaneously read real-time temperature data streams uploaded from the internal temperature sensor of the sterilizer. This data stream contains a continuous sequence of timestamps and corresponding temperature measurements. A time axis alignment operation is performed, mapping the sampling points of the temperature data onto a standard time axis using a preset system control clock as a reference. During this process, data integrity is verified by iterating through and checking the time difference between adjacent timestamps. If a time difference exceeds a preset sampling period tolerance (e.g., 1.5 times the sampling interval), a record is considered missing. A linear interpolation algorithm is immediately invoked, using intermediate values ​​calculated from valid temperature records before and after the missing point to fill the gap and ensure the continuity of the temperature curve. Finally, a fixed integral sampling interval is defined. For example, it can be set to 1 minute or 0.0167 hours for the effective temperature within each sampling interval. Substitute the values ​​into the microbial thermal lethality kinetic equation to calculate the instantaneous lethality at that moment. The calculation formula is: ,in This represents the ratio of sterilization effectiveness per unit time at the current temperature to that at the reference temperature. To measure temperature in real time, For reference temperature, For microbial heat resistance parameters, after calculating the instantaneous values, initialize the cumulative calculator and calculate all instantaneous lethal contributions from the start of sterilization to the current time in ascending order of time. The formula is to accumulate the results. ,in For the current moment The real-time cumulative fatality rate. This is the index of the sampling point corresponding to the current time. For the first Instantaneous lethality at a given point Using the sampling time step, the effectiveness of the sterilization process is quantified in real time by accumulating data point by point, generating a real-time cumulative lethality value.

[0047] The steps for obtaining dynamic steam energy distribution signals are as follows:

[0048] Based on the real-time cumulative mortality rate, the sterilization safety threshold data is called for hourly comparison, the absolute difference is calculated and marked with positive and negative signs, the direction and magnitude of the difference change are recorded, and the comparison difference is generated.

[0049] Based on the comparison difference and the current position of the steam valve opening, the upper limit of the steam valve opening change step size and opening change rate is set, the adjustment direction is mapped as the opening increase / decrease command, encoded as a control field, and a dynamic steam energy distribution signal is generated.

[0050] Specifically, based on the real-time cumulative lethality rate, the system calls the preset standard sterilization reference curve from the sterilization safety threshold data. This reference curve is generated by simulating the integration of the ideal heating and isothermal processes, based on the pre-prepared food product's process formula and target microbial characteristics, to trace the trajectory of the standard lethality rate over time. The current system running time Using the index key, the corresponding theoretical target lethal rate is retrieved from the standard reference curve, and the cumulative lethal rate value calculated in real time is then used. The deviation between the measured value and the theoretical target mortality rate was calculated by comparing them hourly. The calculation formula is: ,in The deviation in sterilization intensity. The cumulative mortality rate is calculated in real time. For the standard trajectory at time The theoretical value is calculated. If the result is positive, it is marked as a positive deviation, meaning the current sterilization intensity is higher than the standard process requirement. If it is negative, it is marked as a negative deviation, meaning the sterilization intensity is insufficient. The absolute value of the deviation is also calculated. The deviation magnitude is quantified, and the difference between the deviation at the current time and the deviation at the previous sampling time is further compared. The direction of the deviation change is recorded, i.e., whether the deviation is approaching zero or moving away from zero, as well as the rate and magnitude of change. This information, including the deviation value, symbol, trend and magnitude, is integrated into a structured comparison data packet to generate the comparison difference.

[0051] Based on the comparison difference and the current opening position of the steam valve, the position feedback signal of the steam regulating valve is first read to obtain the current actual opening percentage of the valve. Based on the deviation magnitude in the comparison difference The theoretical adjustment step size of the valve is calculated using a preset proportional control logic, along with the deviation sign. The calculation function for the valve opening change step size is set as follows: ,in To adjust the calculated theoretical step size, This is the proportional gain coefficient. For example, if it is set to 2.5 based on on-site debugging, it means that each unit of lethality deviation corresponds to a 2.5% adjustment in the opening. The absolute value of the deviation is used, and an upper limit is set for the rate of change of valve opening to protect the valve actuator and prevent system oscillation. For example, if the change is set to no more than 5% per second, and the calculated theoretical step size divided by the control cycle results in a rate exceeding... Then the step size will be restricted to 1. ,in To control the cycle duration, the adjustment direction is determined based on the sign of the deviation. A negative deviation indicates insufficient sterilization, which is mapped to an increase in valve opening (i.e., the valve moves to full opening). A positive deviation indicates over-sterilization, which is mapped to a decrease in valve opening (i.e., the valve moves to close). The final target valve opening command is then calculated. ,in For the target opening, For the current opening, This is the direction coefficient; it is set to 1 when the value is increased and -1 when the value is decreased. The determined adjustment direction and step size are encoded into a hexadecimal control field containing the opcode and operand to generate a dynamic steam energy distribution signal, which is the actual execution step size after the amplitude is limited.

[0052] The steps to obtain the order energy efficiency urgency index are as follows:

[0053] It aggregates rated power, remaining processing time for the current batch, order default penalty amount, and electricity price data for the current period, unifying the power unit to kilowatts, the time unit to hours, the currency unit to a single currency, and the electricity price unit to the currency per kilowatt-hour, generating unified metering parameter items;

[0054] Based on the unified metering parameters, align the records of the same batch by timestamp and lock the remaining processing time of the current batch. Calculate the product of the rated power, the remaining processing time of the current batch, and the electricity price data for the current period. Calculate the ratio of the order default penalty amount to the product to obtain the default risk ratio.

[0055] Based on the default risk ratio, and combined with the rated power, remaining processing time of the current batch, order default penalty amount, and current electricity price data from the unified metering parameters, the order energy efficiency urgency index is calculated using the following formula:

[0056] ;

[0057] in, The energy efficiency urgency index for orders. This refers to the amount of liquidated damages for breach of contract, which is the amount of compensation for breach of contract stipulated in the order contract. Rated power refers to the stable power output value of the packaging production line under rated operating conditions. This represents the remaining processing time for the current batch, from the current moment until the processing of the current batch is completed. This shows the electricity price data for the current period, and the real-time unit price of electricity for the corresponding period.

[0058] Specifically, the system aggregates data on rated power, remaining processing time for the current batch, order penalty amount, and current electricity price. First, it reads register addresses 40001 to 40004 of the main controller of the packaging production line via an industrial fieldbus protocol such as Modbus TCP to obtain the real-time power reading and nameplate rated power parameters of the equipment in the current operating mode. If the raw power data is in watts, it is immediately divided by 1000 to convert it to kilowatts. Simultaneously, it accesses the database interface of the production execution system to retrieve the currently executing batch task number, extracting the total planned output and current completed output for that batch. Combined with the current real-time operating speed of the production line (i.e., the number of packages per minute), it calculates the remaining processing time. If the result is in minutes, it is divided by 60 to convert it to hours and rounded to two decimal places. Then, it uses the API of the enterprise resource planning system... The system queries the electronic contract terms associated with the current batch of orders, parses the breach of contract liability field, extracts the agreed liquidated damages, and checks the currency type identifier. If the currency unit is inconsistent with the system's base currency, it calls the real-time exchange rate interface to query the current exchange rate for conversion, for example, converting USD to RMB at an exchange rate of 6.85, ensuring that all monetary data is normalized to a single currency. Finally, it matches the peak, off-peak, and valley periods of the current time through the power company's smart meter data interface or a pre-set time-of-use electricity price table to obtain the corresponding real-time electricity price, ensuring that the electricity price unit is uniformly "currency per kilowatt-hour". The four types of data that have been cleaned, converted, and formatted are then encapsulated into a structured data object, generating a unified metering parameter item.

[0059] Based on the unified metering parameters, records in the same batch are aligned by timestamp and the remaining processing time of the current batch is locked. Using the current system clock as the reference point, the rated power, electricity price, and remaining time data contained in the unified metering parameters are extracted. The time validity of the data is verified to ensure that the time window corresponding to the electricity price data covers the range of the remaining processing time. For example, if the remaining processing time spans the electricity price switching point from the flat period to the peak period, the electricity price needs to be weighted averaged or locked in segments. Here, to simplify the calculation, the electricity price at the current moment is locked as the reference price for the entire remaining period. Then, the energy cost estimation is performed by multiplying the rated power value with the remaining processing time value of the current batch and the electricity price data value of the current period. Specifically, the power... Multiply by time Get the total amount of electricity to be consumed, then multiply by the electricity price. The projected energy consumption cost is obtained, which represents the estimated power resource input required to complete the remaining tasks of the current batch. Then, the order default penalty amount in the parameter field is read, and a ratio calculation is performed. The order default penalty amount is used as the numerator, and the energy consumption cost calculated above is used as the denominator. The ratio reflects the multiple relationship between the economic loss caused by the risk of order default and the energy cost required to complete the order. If the denominator approaches zero during the calculation, a very small positive number, such as 0.01, is set to avoid calculation errors. Through this step, the economic leverage effect between the consequences of default and energy input is quantified, and the default risk ratio is obtained.

[0060] In the formula for calculating the energy efficiency urgency index of orders, a nonlinear urgency assessment model between default amount and energy cost is constructed by introducing a quadratic term correction. Compared with a simple linear ratio, this formula can produce a more significant priority amplification effect for high-value orders or low-energy-consumption orders with high default risk, thereby ensuring that high-payout-risk tasks are prioritized when power resources are limited.

[0061] The steps to obtain the order default penalty amount are as follows: Access the company's contract management database, use the order number of the current production batch as the index key to search, locate the "Breach of Contract Liability" table in the contract terms, and read the defined "Late Delivery Compensation" field. This field is usually a fixed amount. For example, in one actual read, the value obtained through the SQL query "SELECT Penalty_Amount FROM Orders WHERE Order_ID = '20240501-A'" is 5000.00 yuan. If the database stores a percentage relative to the total order amount, such as "10% of the total order amount," then it is necessary to further read the total order amount field and perform multiplication to obtain the specific amount. In this example, the fixed value of 5000.00 yuan is directly used as the parameter. The input value;

[0062] The steps to obtain the rated power are as follows: Establish communication with the PLC control system of the packaging production line, read the parameter storage area on the equipment nameplate, or read the historical average active power history of the equipment under full-load operation. To ensure data accuracy, statistical analysis is performed on the operating power data of the equipment at rated speed over the past 72 hours. Abnormally low values ​​during standby or fault shutdown are removed, and the average value of the valid operating data is calculated. For example, the collected power sequence, after averaging, yields a value of 15.0 kilowatts. This value represents the standard energy consumption level of the equipment during normal production operation and is used as a parameter. The input value;

[0063] The steps to obtain the remaining processing time for the current batch are as follows: First, obtain the number of products completed in the current batch through the production line counting sensor. Then, read the total target output for this batch from the production planning system and calculate the difference between the two to obtain the remaining quantity to be processed. Next, read the current set operating speed of the production line (unit: pieces / hour) and calculate using the formula "Remaining Time = Remaining Quantity / Operating Speed". For example, if the total task for the current batch is 10,000 pieces, 6,000 pieces have been completed, and 4,000 pieces remain, and the current operating speed is 1,000 pieces / hour, then the calculated remaining processing time is 4.0 hours. This value accurately reflects the time window length required to complete the task and is used as a parameter. The input value;

[0064] The steps to obtain the current electricity price data are as follows: Obtain the unit electricity price for the current time and the next few hours by accessing the regional power grid company's real-time electricity price API interface or reading the locally stored time-of-use electricity price configuration file. Considering the peak-valley-flat characteristics of industrial electricity consumption, if the remaining processing time falls entirely within a specific electricity price period, then the price for that period is directly taken. For example, if the current period is within a flat price range, the obtained electricity price is 0.8 yuan / kWh. This value represents the economic cost of unit energy and is used as a parameter. The input value;

[0065] Calculations based on parameters:

[0066] First, calculate the energy cost item in the denominator. Substitute the values:

[0067] (Yuan);

[0068] The first term of the calculation formula Substitute the values:

[0069] ;

[0070] The numerator of the second term in the calculation formula Substitute the values:

[0071] ;

[0072] The second term in the calculation formula is the denominator. Right now Substitute the values:

[0073] ;

[0074] The value of the second term in the calculation formula:

[0075] ;

[0076] Finally, the two are added together to obtain the order energy efficiency urgency index. :

[0077] ;

[0078] Calculated order energy efficiency urgency index A value of 10850.6945 indicates that the penalty for breach of contract for this order is extremely high relative to the energy cost required to complete it, and has extremely high economic sensitivity. It should be given extremely high priority in the energy allocation sequence. If the calculated result of this index is small, for example, close to 1, it means that the penalty for breach of contract is equivalent to the energy cost, and the priority is relatively low. The system will sort all orders in production in descending order according to the specific value of this index to determine the order of power cut-off and calculate the order energy efficiency urgency index.

[0079] The steps for obtaining the priority sequence of power resource allocation are as follows:

[0080] The in-production order list is sorted in descending order based on the order energy efficiency urgency index. A power supply access threshold number is set and a cut-off mark is marked below the threshold number. The batch number, work station number and timestamp fields are merged. After verifying the integrity of the records, the current valid list is locked to form a power resource allocation priority sequence.

[0081] Specifically, the in-production order list is sorted in descending order based on the order energy efficiency urgency index. For each in-production order record, its associated energy efficiency urgency index is extracted. A quick sorting algorithm is used to rearrange the entire list in descending order of index values, placing high-urgency orders at the top of the list. A power supply access threshold number is set, which is based on the comparison between the real-time maximum load capacity of the current factory power distribution system and the cumulative rated power of all in-production orders. First, the rated capacity of the distribution transformer is read, for example, 2000kVA, and the safe load rate is set to 85%, i.e., the maximum allowable load is 1700kW. Then, starting from the top of the sorted list, the rated power of the packaging production line corresponding to each order is accumulated one by one. When the total power is accumulated... When the maximum allowable load of 1700kW is exceeded for the first time, the position index of the current order in the list is recorded, and this index number is defined as the power supply access threshold number. For example, if the accumulated power is 1650kW when the 5th order is calculated, and becomes 1750kW after the 6th order is added, then the threshold number is set to 5. For all orders in the list with an index number greater than 5, they are uniformly marked as "pending disconnection" in the status field. Then, information aggregation is performed, and the unique production batch number, the physical number of the workstation to which each order belongs, and the timestamp of the current operation are combined bit by bit to generate a composite key value. The integrity of the fields of these composite key values ​​is checked again to ensure that there are no empty values ​​or garbled characters. The status of this list, which has been sorted, truncated and verified, is locked to form a power resource allocation priority sequence.

[0082] The steps to obtain the integrated energy distribution implementation plan are as follows:

[0083] Based on the priority sequence of power resource allocation, extract the power circuit numbers of the packaging production line below the target priority threshold and establish a processing queue. Verify the consistency between the circuit status identifier and the power outage permission identifier. Generate disconnection action code and reset action code according to the processing queue order to obtain the power cut-off control instruction set.

[0084] Based on the power cut-off control instruction set, the main steam pipeline on / off identifier in the dynamic steam energy distribution signal is read and cross-aligned according to the timestamp. The power disconnection sequence of the same batch is checked to ensure that it does not conflict with the main steam pipeline on / off sequence. The execution window and safety interlock conditions are merged to generate a comprehensive energy distribution execution plan.

[0085] Specifically, based on the power resource allocation priority sequence, the power circuit numbers of the packaging production line below the target priority threshold are extracted and a processing queue is established. Order records marked "to be disconnected" in the priority sequence are traversed, their workstation number fields are parsed, and the specific circuit breaker circuit number of the corresponding packaging production line in the distribution cabinet is found by consulting a pre-set equipment electrical wiring mapping table. For example, "Workstation 03" corresponds to "Circuit C-12". All extracted circuit numbers to be operated are stored in a first-in-first-out processing queue. For each circuit number in the queue, a status query command is sent to the intelligent circuit breaker via the Modbus communication protocol to read its current closing / opening status and remote control permission flag. The status consistency is verified, confirming that it is currently in the closed state and remote operation is allowed. If a manual lockout flag is detected, the circuit is skipped and an exception log is recorded. For circuits that pass the verification, a corresponding circuit breaker disconnection control message is generated according to their order in the queue. The message contains the device address, function code, and operation command, such as "01 05 00 12 FF". "00" is set to prepare reset instruction code for subsequent power restoration. This series of logically verified control instructions are then compiled into a set to obtain the power cut-off control instruction set.

[0086] Based on the power cut-off control command set, the main steam pipeline on / off identifier in the dynamic steam energy distribution signal is read and cross-aligned according to the timestamp. The on / off status bit of the main steam valve in the dynamic steam distribution signal is parsed to obtain its predetermined action execution time. This time is compared synchronously with the planned execution time in the power cut-off command set on the time axis to check for timing conflicts. The focus is on verifying whether the necessary steam supply was mistakenly shut off or the auxiliary power was cut off when steam sterilization was required during the power cut-off of the same production batch. Safety interlock logic is set, for example, stipulating that the steam valve must be in a safe closed or low flow circulation state before the power cut-off action is executed to prevent steam runaway leakage due to power failure. If timestamp overlap or logic mutual exclusion is found, the execution time of the power cut-off command is automatically fine-tuned, for example, delayed by 500 milliseconds. The adjusted power action window and steam action window are merged, and the necessary safety interlock condition judgment logic is added, such as "if the steam pressure > 0.1MPa, power cut-off is prohibited". Finally, a comprehensive scheme including electrical and thermal energy coordinated operation steps is generated, and a comprehensive energy distribution execution scheme is generated.

[0087] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for managing the entire lifecycle data of pre-prepared food products, characterized in that, Includes the following steps: Real-time temperature data inside the sterilization autoclave is collected, and the lethality reduction coefficient and the target temperature sterilization time parameter corresponding to the target microorganism in the pre-cooked food product are extracted to generate a set of microbial thermal lethality kinetic parameters. The sterilization safety threshold data is obtained by calculating the set of microbial thermal lethality kinetic parameters. Using the sterilization safety threshold data and the real-time temperature data of the sterilization autoclave, the real-time cumulative lethality value is calculated. The difference between the real-time cumulative lethality value and the sterilization safety threshold data is compared. The opening of the steam valve is adjusted according to the comparison difference to generate a dynamic steam energy distribution signal. Obtain the rated power of the packaging production line, the remaining processing time of the current batch, the amount of order default penalty, and the electricity price data for the current period. Calculate the ratio of the order default penalty to the product of the rated power, the remaining processing time, and the electricity price, and then calculate it with the remaining processing time to obtain the order energy efficiency urgency index. Based on the order energy efficiency urgency index, all orders in production are sorted and the power supply access range is defined, generating a power resource allocation priority sequence. Based on the power resource allocation priority sequence, the power supply to packaging production lines with lower priority than the target is cut off. At the same time, the main steam pipeline is opened and closed in response to the dynamic steam energy allocation signal, generating a comprehensive energy allocation execution plan. The steps for obtaining the order energy efficiency urgency index are as follows: It aggregates rated power, remaining processing time for the current batch, order default penalty amount, and electricity price data for the current period, unifying the power unit to kilowatts, the time unit to hours, the currency unit to a single currency, and the electricity price unit to the currency per kilowatt-hour, generating unified metering parameter items; Based on the unified metering parameters, align the records of the same batch by timestamp and lock the remaining processing time of the current batch. Calculate the product of the rated power, the remaining processing time of the current batch, and the electricity price data for the current period. Calculate the ratio of the order default penalty amount to the product to obtain the default risk ratio. Based on the aforementioned default risk ratio, and combined with the rated power, remaining processing time of the current batch, order default penalty amount, and current electricity price data from the unified metering parameters, the order energy efficiency urgency index is calculated using the following formula: ； in, The energy efficiency urgency index for orders. This refers to the amount of liquidated damages for breach of contract, which is the amount of compensation for breach of contract stipulated in the order contract. Rated power refers to the stable power output value of the packaging production line under rated operating conditions. This represents the remaining processing time for the current batch, from the current moment until the processing of the current batch is completed. This shows the electricity price data for the current time period, and the real-time unit electricity price for the corresponding time period. The steps for obtaining the power resource allocation priority sequence are as follows: Based on the order energy efficiency urgency index, the list of orders in production is sorted in descending order, a power supply access threshold number is set and a cut-off mark is marked below the threshold number, the batch number, work station number and timestamp fields are merged, the completeness of the records is checked and the current valid list is locked to form a power resource allocation priority sequence.

2. The method for managing the entire lifecycle data of pre-prepared food products according to claim 1, characterized in that, The steps for obtaining the sterilization safety threshold data are as follows: The continuous temperature sampling sequence is read from fixed measuring points inside the sterilizer. The integrity of the timestamp is verified and missing records are removed. The sensor calibration coefficient is synchronized and the temperature scale unit is unified. The data is rearranged according to the sampling order and the batch identifier is retained to obtain real-time temperature data. Based on the real-time temperature data, the target microbial identifier is parsed and the temperature range is located. The lethal time reduction coefficient and the target temperature sterilization time parameter are retrieved. Consistency is checked by batch and temperature range and concatenated by field to generate a set of microbial thermal lethality kinetic parameters. Based on the set of microbial thermal lethality kinetic parameters, parameters are filled in according to the field order of the benchmark sterilization formula and the time window boundary is set. The termination point of the cumulative lethality curve is located as the target integration cutoff point, and sterilization safety threshold data is generated.

3. The method for managing the entire lifecycle data of pre-prepared food products according to claim 1, characterized in that, The steps for obtaining the real-time cumulative lethality rate are as follows: Using the sterilization safety threshold data and the real-time temperature data of the sterilization autoclave, the data is aligned by timestamp and missing records are removed. Fixed sampling intervals are divided and the lethal contribution of each interval is calculated. The data is then accumulated to the current time in chronological order to generate a real-time cumulative lethality rate value.

4. The method for managing the entire lifecycle data of pre-prepared food products according to claim 1, characterized in that, The steps for obtaining the dynamic steam energy distribution signal are as follows: Based on the real-time cumulative mortality rate, the sterilization safety threshold data is called for hourly comparison, the absolute difference is calculated and marked with positive and negative signs, the direction and magnitude of the difference change are recorded, and the comparison difference is generated. Based on the comparison difference and the current position of the steam valve opening, the upper limit of the steam valve opening change step size and opening change rate is set, the adjustment direction is mapped as the opening increase / decrease command, encoded as a control field, and a dynamic steam energy distribution signal is generated.

5. The method for managing the entire lifecycle data of pre-prepared food products according to claim 1, characterized in that, The steps for obtaining the integrated energy distribution execution plan are as follows: Based on the power resource allocation priority sequence, the power circuit numbers of the packaging production line below the target priority threshold are extracted and a processing queue is established. The consistency between the circuit status identifier and the power outage permission identifier is verified. Disconnection action code and reset action code are generated in the order of the processing queue to obtain the power cut-off control instruction set.

6. The method for managing the entire lifecycle data of pre-prepared food products according to claim 5, characterized in that, The steps for obtaining the comprehensive energy allocation execution plan also include: reading the main steam pipeline on / off identifier in the dynamic steam energy supply signal according to the power cut-off control instruction set and cross-aligning it according to the timestamp; verifying that the power disconnection sequence of the same batch does not conflict with the main steam pipeline on / off sequence; merging the execution window and safety interlock conditions; and generating the comprehensive energy allocation execution plan.

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