A dairy product processing abnormality interception analysis method and system based on a process dynamic process and multi-system linkage

Abstract

The application discloses a dairy product processing abnormality interception analysis method and system based on a process dynamic process and multi-system linkage, comprising: acquiring quality detection result data of a dairy product processing process, and transmitting the quality detection result data to a manufacturing execution system; the manufacturing execution system generates production control instructions based on the quality detection result data, and issues the production control instructions to an industrial Internet of Things platform; the industrial Internet of Things platform converts the production control instructions into device control instructions suitable for an operation technology layer, and issues the device control instructions to a terminal control system; the terminal control system executes target device actions in response to the device control instructions to intercept unqualified products or release qualified products in the dairy product processing process, and the application combines real-time online monitoring of process parameters, early warning and bottom-layer equipment linkage, greatly improving the stability, compliance and intelligent control level of the dairy product processing process.

Description

Technical Field

[0001] This application relates to food production processes, and more particularly to a method and system for intercepting and analyzing anomalies in dairy product processing based on dynamic process flow and multi-system linkage. Background Technology

[0002] As consumers' demands for dairy product quality and safety continue to rise, dairy manufacturers are implementing increasingly stringent quality control measures during processing. Currently, in dairy processing, quality inspection typically relies on laboratory information management systems, production scheduling on manufacturing execution systems, and the operation of underlying processing equipment is handled independently by field control systems. However, this traditional production control model suffers from significant information silos, lacking real-time, deep integration between systems. When quality anomalies are detected, manual transmission of test results and manual issuance of transfer restrictions or shutdown commands often result in severe lag in response. This lag frequently leads to defective products already flowing into the next process, causing significant waste of raw materials and greatly increasing the safety risks of defective products entering the market. Furthermore, dynamic process parameters during production are difficult to map to quality results in a timely manner and achieve automatic control feedback. Summary of the Invention

[0003] To address the aforementioned problems, this application discloses a method for intercepting and analyzing anomalies in dairy product processing based on dynamic process flow and multi-system linkage. The method includes: acquiring quality inspection result data of the dairy product processing process and transmitting the quality inspection result data to a manufacturing execution system (MAS); the MAS generating production control instructions based on the quality inspection result data and issuing the production control instructions to an industrial Internet of Things (IIoT) platform; the IIoT platform converting the production control instructions into equipment control instructions applicable to the operational technology layer and issuing the equipment control instructions to a terminal control system; and the terminal control system responding to the equipment control instructions by executing target equipment actions to intercept non-conforming products or release conforming products during the dairy product processing.

[0004] Furthermore, the quality inspection results data include at least one of the following: raw milk acceptance inspection data, in-process semi-finished product inspection data, and finished product inspection data.

[0005] Furthermore, the method also includes: collecting real-time process parameters of the dairy product processing process; the manufacturing execution system obtains the real-time process parameters via the industrial Internet of Things platform and verifies the real-time process parameters based on a preset process control analysis model; if the verification result indicates an anomaly, the manufacturing execution system generates an interception command to control the processing process.

[0006] Furthermore, when the terminal control system is a milk silo central control system, the terminal control system responds to the equipment control command to execute target equipment actions, including: when the quality inspection result data indicates that the raw milk semi-finished product is unqualified, the milk silo central control system receives the unqualified command and restricts the raw milk transfer; when the quality inspection result data indicates that the raw milk semi-finished product is qualified, the milk silo central control system receives the release command and allows the raw milk to transfer.

[0007] Furthermore, when the terminal control system is a pre-processing central control system, the terminal control system responds to the equipment control command to execute target equipment actions, including: when the quality inspection result data indicates that the pre-processing semi-finished product is unqualified, the pre-processing central control system receives an unqualified command to restrict the transfer process and triggers the downstream filling equipment to stop; when the quality inspection result data indicates that the pre-processing semi-finished product is qualified, the pre-processing central control system receives a release command to allow the transfer process and triggers the downstream filling equipment to run.

[0008] Furthermore, when the terminal control system includes a higher-level packaging material control system and a filling control system, the terminal control system executes target equipment actions in response to the equipment control command, including: If the quality inspection results indicate that the finished product is unqualified, the manufacturing execution system sends the unqualified instruction to the upper-level packaging material control system via the industrial Internet of Things platform; The upper-level packaging material control system responds to the non-compliance command by outputting a first voltage to turn on the packaging material relay and trigger the stop relay of the filling control system to control the filling equipment to stop. The filling control system is linked to the central control system of the tank to be filled to limit the material supply.

[0009] Furthermore, the terminal control system, in response to the device control command, executes the target device action, further includes: When the quality inspection results indicate that the finished product is qualified, the manufacturing execution system issues a delivery instruction to the upper-level packaging material control system via the industrial Internet of Things platform; The upper-level packaging material control system responds to the release command by outputting a second voltage to disconnect the packaging material relay, resets the shutdown relay to control the filling equipment to start up, and links the central control system of the can to be filled to resume material supply.

[0010] The second aspect of this application discloses a dairy processing anomaly interception system based on dynamic process and multi-system linkage, comprising: The business layer is configured to acquire quality inspection results data during the dairy product processing process; The execution layer, which is communicatively connected to the business layer, is configured to generate production control instructions based on the quality inspection result data, and convert the production control instructions into equipment control instructions applicable to the operation technology layer. The control layer, which is communicatively connected to the execution layer, is configured to execute target equipment actions in response to the equipment control commands, so as to intercept non-conforming products or release conforming products during the dairy product processing.

[0011] Furthermore, the execution layer includes a manufacturing execution system and an industrial IoT platform, wherein the manufacturing execution system and the industrial IoT platform are configured to interact with each other via the OPC UA communication protocol.

[0012] Furthermore, the system is configured to integrate inspection and judgment flow, production execution instruction issuance flow, equipment data acquisition flow, and linkage control flow to construct a closed loop for quality control.

[0013] In summary, compared with existing technologies, the dairy processing anomaly interception and analysis method and system proposed in this application, based on dynamic process and multi-system linkage, achieves deep and effective integration of the IT business layer and the OT control layer. First, this system breaks down information silos in traditional dairy production, using an industrial IoT platform to convert LIMS quality inspection results and MES scheduling instructions into real-time automatic control actions for underlying equipment, significantly reducing anomaly response time from tens of minutes in traditional manual mode to seconds. Second, this solution achieves immediate automatic shutdown and interception at key nodes such as raw milk transfer, pre-processing, and finished product filling, completely changing the lag of previous post-event traceability and manual calls, fundamentally preventing substandard products from flowing to downstream processes or the consumer market, and significantly reducing waste of raw and auxiliary materials and the risk of product recalls during production. Finally, this invention combines real-time online monitoring and early warning of process parameters with underlying equipment linkage to construct an automated quality control closed loop covering production-detection / monitoring-decision-execution, greatly improving the stability, compliance, and intelligent control level of the dairy processing process. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0015] Figure 1 This is a flowchart provided in an exemplary embodiment of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] like Figure 1 As shown, a method for intercepting and analyzing anomalies in dairy processing based on dynamic processes and multi-system linkage is proposed, including: Step S10: Obtain quality inspection result data of the dairy product processing process, and transmit the quality inspection result data to the manufacturing execution system; Step S20: The manufacturing execution system generates production control instructions based on the quality inspection result data and sends the production control instructions to the industrial Internet of Things platform; Step S30: The industrial IoT platform converts the production control instructions into equipment control instructions applicable to the operation technology layer, and sends the equipment control instructions to the terminal control system; Step S40: The terminal control system responds to the equipment control command and executes the target equipment action to intercept unqualified products or release qualified products during the dairy product processing.

[0018] During the liquid milk production process, laboratory personnel input sample test data into the laboratory information management system. If any indicators are deemed unqualified, the results are pushed to the manufacturing execution system (MES) in real time. The MES then generates corresponding production control instructions and sends them to the industrial IoT platform. The MES platform converts these instructions into operational control commands that the underlying equipment can recognize, thereby driving the field terminal control system to immediately execute shutdown or restriction actions. This implementation method overcomes the lag inherent in traditional manual transmission of test reports, achieving deep integration between the information technology business layer and the operational field equipment. It reduces anomaly response and interception time from tens of minutes to seconds, ensuring the immediacy of quality control.

[0019] In some embodiments, the quality inspection result data includes at least one of raw milk acceptance inspection data, in-process semi-finished product inspection data, and finished product inspection data.

[0020] Building upon the aforementioned methods, this embodiment comprehensively covers the entire lifecycle of dairy product processing with no blind spots in quality inspection. Specifically, data acquisition includes not only raw milk protein and microbial testing during the milk collection stage, but also pre-filling physicochemical index testing of the milk during the blending and fermentation stage, and finished product shelf-life verification during the production stage. Its technical advantage lies in ensuring comprehensive monitoring of the quality status throughout the entire production process, providing a complete and reliable data-driven decision-making basis for precise control and automatic interception at each processing stage.

[0021] In some embodiments, the method further includes: Collect real-time process parameters of the dairy product processing; The manufacturing execution system acquires the real-time process parameters via the industrial Internet of Things platform and verifies the real-time process parameters based on a preset process control analysis model. If the verification result indicates an anomaly, the manufacturing execution system generates an interception command to control the processing.

[0022] In addition to post-process testing, this embodiment also introduces a real-time defense based on parameter monitoring. During critical processes such as sterilization or fermentation, multi-source sensors collect process parameters such as temperature and pressure in real time. The manufacturing execution system (MES) acquires these parameters via an industrial IoT platform and performs online verification using a pre-set process control analysis model. If the sterilization temperature is detected to have fallen below the process threshold, the system can trigger an interception directly without waiting for the final test results. This approach represents a leap from static post-process inspection to dynamic process prevention, effectively reducing quality risks and nutrient loss caused by parameter fluctuations.

[0023] In some embodiments, when the terminal control system is a milk silo central control system, the terminal control system executes target equipment actions in response to the equipment control command, including: If the quality inspection results indicate that the semi-finished product in the raw milk process is unqualified, the milk warehouse central control system receives the unqualified instruction and restricts the transfer of raw milk to the next process. When the quality inspection results indicate that the raw milk semi-finished product is qualified, the milk warehouse central control system receives a release instruction and allows the raw milk to be transferred to the next process.

[0024] When specifically applied to the raw milk storage stage, when the laboratory information management system detects that the raw milk in a certain milk warehouse is substandard, the manufacturing execution system sends an interception command to the central control system of the milk warehouse, which has completed automation integration, via the industrial Internet of Things platform. The central control system then automatically locks the output valve, strictly restricting the transfer of that batch of raw milk to the next process. Only after the problem is resolved or the quality assurance department releases the milk can the transfer be permitted again. The technical effect is that it creates a tight physical barrier at the source of production, preventing contaminated raw milk from mixing into the complex downstream processing network, and significantly reducing the cost of large-scale equipment cleaning and the risk of raw material waste.

[0025] In some embodiments, when the terminal control system is a pre-processing central control system, the terminal control system executes target device actions in response to the device control command, including: If the quality inspection result data indicates that the pre-processed semi-finished product is unqualified, the pre-processing central control system receives the unqualified instruction to restrict the transfer of the process and triggers the downstream filling equipment to stop. If the quality inspection results indicate that the pre-processed semi-finished product is qualified, the pre-processing control system receives a release command to allow the process to proceed and triggers the operation of the downstream filling equipment.

[0026] During the conversion from semi-finished to finished products, if the semi-finished product in the fermentation tank or the container to be filled is deemed abnormal, the pre-processing control system, upon receiving the instruction, will not only restrict the material flow in this process but also simultaneously transmit the restriction status to the downstream filling equipment, triggering the filling machine to stop. Subsequently, upon receiving a release instruction from the quality assurance department, the filling equipment will then resume operation. This interception effect is extremely significant; it effectively prevents substandard milk from being filled and sealed, greatly saving on high packaging material costs, and also facilitating the centralized processing and return of abnormal milk.

[0027] In some embodiments, when the terminal control system includes a higher-level packaging material control system and a filling control system, the terminal control system executes target equipment actions in response to the equipment control command, including: If the quality inspection results indicate that the finished product is unqualified, the manufacturing execution system sends the unqualified instruction to the upper-level packaging material control system via the industrial Internet of Things platform; The upper-level packaging material control system responds to the non-compliance command by outputting a first voltage to turn on the packaging material relay and trigger the stop relay of the filling control system to control the filling equipment to stop. The filling control system is linked to the central control system of the tank to be filled to limit the material supply.

[0028] For high-speed finished product filling production lines, this embodiment designs a highly reliable shutdown mechanism. When a finished product fails inspection, the manufacturing execution system sends a command to the upper-level packaging material control system. Its programmable logic controller outputs a first preset voltage (e.g., 24V) to activate the packaging material relay, and directly triggers the shutdown relay of the downstream filling control system via hard-wired connection, forcing the filling machine to stop and simultaneously stopping the feeding of the cans to be filled. The technical effect is that, through the combination of network commands and hard-wired relays, a double physical safety mechanism ensures an absolute execution rate of shutdown action within seconds, resolutely curbing the continuous production of substandard liquid milk products.

[0029] In some embodiments, the terminal control system, in response to the device control command, executes a target device action, further comprising: When the quality inspection results indicate that the finished product is qualified, the manufacturing execution system issues a delivery instruction to the upper-level packaging material control system via the industrial Internet of Things platform; The upper-level packaging material control system responds to the release command by outputting a second voltage to disconnect the packaging material relay, resets the shutdown relay to control the filling equipment to start up, and links the central control system of the can to be filled to resume material supply.

[0030] As a continuation of the filling process control, when the finished product quality issue is resolved and the system releases the product, the upper-level packaging material control system responds to the release command and outputs a second preset voltage (such as 0V) to disconnect the packaging material relay. This allows the filling machine's shutdown relay to reset smoothly, and the filling equipment resumes operation, simultaneously restarting the cans waiting to be filled and resuming normal material supply. This design achieves automated resumption of production after the abnormal interception is resolved, significantly reducing the cumbersome process of manual on-site intervention and equipment restart, and effectively ensuring the continuity of production scheduling.

[0031] The second aspect of this application discloses a dairy processing anomaly interception system based on dynamic process and multi-system linkage, comprising: The business layer is configured to acquire quality inspection results data during the dairy product processing process; The execution layer, which is communicatively connected to the business layer, is configured to generate production control instructions based on the quality inspection result data, and convert the production control instructions into equipment control instructions applicable to the operation technology layer. The control layer, which is communicatively connected to the execution layer, is configured to execute target equipment actions in response to the equipment control commands, so as to intercept non-conforming products or release conforming products during the dairy product processing.

[0032] Based on the above method, this embodiment provides a hierarchical, loosely coupled anomaly interception system entity. The business layer deploys a laboratory information management system to obtain quality assessment data; the execution layer deploys a manufacturing execution system and an industrial IoT platform, with the manufacturing execution system acting as the production brain to generate scheduling instructions based on data, and the industrial IoT platform responsible for network transmission and protocol conversion; the control layer includes a field control system and equipment controllers, responsible for receiving instructions and ultimately executing actions. This system architecture provides enterprises with a clearly structured industrial digitalization implementation solution, facilitating modular upgrades of existing automated production lines while ensuring smooth flow of control instructions.

[0033] In some embodiments, the execution layer includes a manufacturing execution system and an industrial IoT platform, wherein the manufacturing execution system and the industrial IoT platform are configured to interact with commands and parameters via the OPC UA communication protocol.

[0034] In the above system architecture embodiment, the manufacturing execution system within the execution layer is configured to connect with the industrial IoT platform via an open platform communication unified architecture standard protocol. Both high-frequency sensor parameters from the field and low-frequency production control commands are transmitted bidirectionally through this unified standard interface. The technical advantage lies in completely overcoming communication barriers caused by inconsistent data standards between different manufacturers' equipment and heterogeneous systems, ensuring the efficiency, real-time performance, and security of production and quality data during cross-system interaction.

[0035] In some embodiments, the system is configured to integrate inspection and judgment flow, production execution instruction issuance flow, equipment data acquisition flow, and linkage control flow to build a closed loop for quality control.

[0036] In its overall operation, this system seamlessly integrates the inspection and judgment flow of the laboratory information management system, the instruction issuance flow of the manufacturing execution system, the IoT data acquisition flow of the underlying equipment, and the action execution linkage flow. When external quality complaints or internal audits occur, the system can quickly trace the inspection records, instruction records, and equipment operating status corresponding to a specific batch through this closed loop. This truly constructs an automated control closed loop covering the entire chain of "production, testing and monitoring, and decision feedback," fully aligning with the stringent Good Manufacturing Practices (GMP) and Hazard Analysis and Critical Control Point (HACCP) standards of the dairy industry, providing tamper-proof, comprehensive data support for the company's quality accountability.

[0037] The accompanying drawings referenced in this specification are for illustrative purposes only. Their dimensions, scale, or colors may be adjusted according to actual production needs. The reference numerals in the drawings should not be construed as limiting the scope of protection.

[0038] All the technical features disclosed in this application can be combined in any way to form an interactive or collaborative structure, as long as the combination does not contradict each other or conflict with the technology.

[0039] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope of protection claimed in this application.

Claims

1. A method for intercepting and analyzing anomalies in dairy product processing based on dynamic process and multi-system linkage, characterized in that, include: Acquire quality inspection results data of the dairy product processing process, and transmit the quality inspection results data to the manufacturing execution system; The manufacturing execution system generates production control instructions based on the quality inspection result data and sends the production control instructions to the industrial Internet of Things platform; The industrial IoT platform converts the production control commands into equipment control commands applicable to the operation technology layer, and sends the equipment control commands to the terminal control system. The terminal control system responds to the equipment control command and executes the target equipment action to intercept unqualified products or release qualified products during the dairy product processing.

2. The method according to claim 1, characterized in that, The quality inspection results data include at least one of the following: raw milk acceptance inspection data, semi-finished product inspection data, and finished product inspection data.

3. The method according to claim 1, characterized in that, The method further includes: Collect real-time process parameters of the dairy product processing; The manufacturing execution system acquires the real-time process parameters via the industrial Internet of Things platform and verifies the real-time process parameters based on a preset process control analysis model. If the verification result indicates an anomaly, the manufacturing execution system generates an interception command to control the processing.

4. The method according to claim 1, characterized in that, When the terminal control system is a milk silo central control system, the terminal control system executes target equipment actions in response to the equipment control command, including: If the quality inspection results indicate that the semi-finished product in the raw milk process is unqualified, the milk warehouse central control system receives the unqualified instruction and restricts the transfer of raw milk to the next process. When the quality inspection results indicate that the raw milk semi-finished product is qualified, the milk warehouse central control system receives a release instruction and allows the raw milk to be transferred to the next process.

5. The method according to claim 1, characterized in that, When the terminal control system is a pre-processing central control system, the terminal control system executes target device actions in response to the device control command, including: If the quality inspection result data indicates that the pre-processed semi-finished product is unqualified, the pre-processing central control system receives the unqualified instruction to restrict the transfer of the process and triggers the downstream filling equipment to stop. If the quality inspection results indicate that the pre-processed semi-finished product is qualified, the pre-processing control system receives a release command to allow the process to proceed and triggers the operation of the downstream filling equipment.

6. The method according to claim 1, characterized in that, When the terminal control system includes a higher-level packaging material control system and a filling control system, the terminal control system executes target equipment actions in response to the equipment control command, including: If the quality inspection results indicate that the finished product is unqualified, the manufacturing execution system sends the unqualified instruction to the upper-level packaging material control system via the industrial Internet of Things platform; The upper-level packaging material control system responds to the non-compliance command by outputting a first voltage to turn on the packaging material relay and trigger the stop relay of the filling control system to control the filling equipment to stop. The filling control system is linked to the central control system of the tank to be filled to limit the material supply.

7. The method according to claim 6, characterized in that, The terminal control system, in response to the device control command, executes the target device action and further includes: When the quality inspection results indicate that the finished product is qualified, the manufacturing execution system issues a delivery instruction to the upper-level packaging material control system via the industrial Internet of Things platform; The upper-level packaging material control system responds to the release command by outputting a second voltage to disconnect the packaging material relay, resets the shutdown relay to control the filling equipment to start up, and links the central control system of the can to be filled to resume material supply.

8. A dairy processing anomaly interception system based on dynamic process and multi-system linkage, characterized in that, include: The business layer is configured to acquire quality inspection results data during the dairy product processing process; The execution layer, which is communicatively connected to the business layer, is configured to generate production control instructions based on the quality inspection result data, and convert the production control instructions into equipment control instructions applicable to the operation technology layer. The control layer, which is communicatively connected to the execution layer, is configured to execute target equipment actions in response to the equipment control commands, so as to intercept non-conforming products or release conforming products during the dairy product processing.

9. The system according to claim 8, characterized in that, The execution layer includes a manufacturing execution system and an industrial IoT platform, and the manufacturing execution system and the industrial IoT platform are configured to interact with each other through the OPC UA communication protocol.

10. The system according to claim 8, characterized in that, The system is configured to integrate inspection and judgment flow, production execution instruction issuance flow, equipment data acquisition flow, and linkage control flow to build a closed loop for quality control.

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