A pet food production traceability supervision method and system based on big data

Abstract

The present application relates to the technical field of data supervision, in particular to a pet food production traceability supervision method and system based on big data, comprising: finding the positions of all key process nodes in the processing and production links in the basic data file; injecting raw material data into the raw material input node, and for each key process node, based on the traceability information and the supply timestamp, performing traceability calculation on the raw material procurement link and the production data of the corresponding area of the key process node to obtain the current time data chain corresponding to each data segment in the key process node. The present application finds and marks the positions of all key process nodes in the basic data file, generates corresponding traceability indexes, and assigns the indexes to the traceability marking attribute; this achieves accurate positioning of each process node and its data segment, and improves the pertinence and efficiency of traceability calculation.

Description

Technical Field

[0001] This invention relates to the field of data supervision technology, specifically to a method and system for production traceability supervision of pet food based on big data. Background Technology

[0002] Currently, traditional methods often only record data at a few points, such as raw material warehousing and finished product outbound, lacking data segment-level tracking of each key process node in the processing and production process. When it is necessary to locate a problem in a certain intermediate step, such as abnormal temperature of a specific piece of equipment or the mixing time of a batch of raw materials, a complete data chain from raw materials to finished products cannot be formed, resulting in interruption of traceability or inability to accurately locate the problem. Furthermore, traditional manual or semi-digital management usually relies on paper records or scattered spreadsheets, without unified marking and traceability indexing of the location of key process nodes. When quality problems occur, it is necessary to manually review a large number of records one by one to check, which is inefficient and prone to omissions, and cannot achieve rapid and accurate location of the problem link.

[0003] Furthermore, traditional traceability methods are mostly static records after the fact, unable to dynamically update the data chain according to the actual progress of the production process. When production plans change, process parameters are adjusted, or temporary data is added, the existing traceability records cannot automatically adapt to the changes, nor can they promptly identify and supplement incomplete traceability links, resulting in delayed and incomplete regulatory results. In addition, in traditional methods, timestamps of different links are often recorded independently by different personnel on different devices, lacking a unified correlation and calculation mechanism. This leads to unclear time connections between data segments, easily resulting in logical errors such as the previous link being later than the next link or inconsistent time bases, seriously affecting the credibility of traceability results. Summary of the Invention

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for traceability and supervision of pet food production based on big data, comprising: Obtain basic data files for the entire pet food production process, set raw material input nodes in the processing and production stages during the raw material procurement stage, and set traceability information for raw materials and supply timestamps for raw materials at the raw material input nodes; Locate all key process nodes in the processing and production process in the basic data file; inject raw material data into the raw material input node; for each key process node, perform traceability calculations on the production data of the raw material procurement process and the corresponding area of ​​the key process node based on traceability information and supply timestamps to obtain the current time data chain corresponding to each data segment in the key process node. At the current moment, add traceability markers to each data segment of key process nodes, and calculate the association status of all traceability markers at the next moment based on the current moment, the association information and position of all traceability markers; determine whether traceability has been completed for the entire production process; If traceability is not completed throughout the entire production process, traceability calculations are performed on the production data of the raw material procurement process and the corresponding area of ​​each key process node based on the raw material procurement process, the current data chain, traceability information, and supply timestamp, to obtain the next moment data chain corresponding to each data segment in each key process node. Update the data chain of the next moment to the data chain of the current moment and set the next moment as the current moment. Then return to the execution. In the current moment, add traceability markers to each data segment of the key process nodes. Based on the current moment, the association information and position of all traceability markers, calculate the association status of all traceability markers in the next moment until the traceability of the entire production process is completed. If the traceability of the entire production process is completed, output the association information of traceability markers at all moments.

[0005] Preferably, based on traceability information and supply timestamps, traceability calculations are performed on production data corresponding to the raw material procurement process and key process nodes to obtain the current-time data chain for each data segment in the key process node, including: For each data segment in each key process node, a correlation model for the data segment is set. Obtain each associated direction of the data segment and the corresponding stage position of the data segment in the production process; Based on traceability information, supply timestamps, each association direction of the data segment, and the position of each link, the association model is solved to obtain the data chain corresponding to the current moment of the data segment.

[0006] Preferably, after locating the positions of all key process nodes in the processing and production process in the basic data file, the method further includes: The location of each key process node in the processing and production process is marked to obtain the traceability index corresponding to each key process node.

[0007] Preferably, based on the current time, the association information and location of all traceability markers, the association status of all traceability markers at the next time step is calculated, including: For each traceability marker, the traceability index corresponding to the key process node is assigned to the attribute of the traceability marker, and the data chain at the current time corresponding to the data segment position where the traceability marker is located is determined as the association information of the traceability marker, thus obtaining the target traceability marker; Calculate the time difference between the next moment and the current moment; based on the time difference, the association information of the target tracing marker, and the location, calculate the association status of the tracing marker at the next moment.

[0008] Preferably, determining whether traceability has been completed throughout the entire production process includes: Based on the association information of traceability markers at all times, determine whether each data segment in each key process node contains a traceability marker; If every data segment in every key process node contains a traceability marker, then the entire production process is traceable. If every data segment in every critical process node does not contain a traceability marker, then the entire production process is not traceable.

[0009] Preferably, after outputting the association information of the source markers at all times, the method further includes: Determine the current production batch information of the target pet food that requires production traceability supervision. The current production batch information includes one or more target raw material objects and production process objects. The current production batch information is input into a preset traceability database for retrieval and analysis to obtain raw material traceability data for each target raw material and process traceability data for each production stage. The traceability data for each target raw material and production stage is then encapsulated to obtain a tracking code for each target raw material and production stage. The raw material traceability data includes at least the supplier information, test report information, and warehousing time information for the target raw material, while the process traceability data includes at least the operator information, equipment information, and processing time information for the production stage.

[0010] Preferably, the method further includes: Based on the identified set of regulatory rules corresponding to the target pet food, determine the tracking code for each traceable object in the set of regulatory rules. For each target raw material and production process object, based on the tracking codes of all traceable objects and the tracking code of the target object, determine whether the target object meets the preset traceability conditions. When it is determined that the target object meets the traceability conditions, the compliance status result of the target object is determined based on the current stage time information, the previous stage time information, and the preset stage time benchmark information corresponding to the target object. When it is determined that the target object does not meet the traceability conditions, based on the raw material traceability data or process traceability data corresponding to the target object, object category information and tracking code, and the set basic compliance status results, the corresponding element addition and data update operations are performed on the regulatory rule set, and the compliance status result of the target object is determined. Based on the compliance status of each traceable object in the regulatory rule set, determine the traceability regulatory results of the target pet food within the target production cycle; where all traceable objects include target raw material objects and production process objects.

[0011] Preferably, based on the current stage time information and the previous stage time information corresponding to the identified target object, and the preset stage time benchmark information, the compliance status result of the target object is determined, including: Based on the current time information corresponding to the target object, a first time value is determined, and based on the previous time information corresponding to the target object, a second time value is determined, and based on the preset time reference information, a reference time value is determined. When the first time value is later than the second time value and the first time value is later than the baseline time value, the compliance status type of the target object is determined to be the delayed status type. When the first time value is earlier than the second time value and the first time value is earlier than the baseline time value, the compliance status type of the target object is determined to be the advanced status type; wherein, the compliance status type includes one of the advanced status type, the delayed status type and other status types; the compliance status result of the target object is determined according to the compliance status type.

[0012] Preferably, based on the compliance status of each traceable object in the regulatory rule set, the traceability regulatory results of the target pet food within the target production cycle are determined, including: When the traceability supervision requirement of the target pet food is the full-chain traceability supervision type, based on the information of the target link that needs to be supervised in the full chain and the compliance status result of each traceable object in the set of supervision rules, the first target object that meets the preset link matching conditions is determined from all traceable objects; Calculate the number of stages corresponding to all first target objects; based on the number of stages, determine the traceability and supervision results of the target pet food within the target production cycle; When the traceability and supervision requirement type for the target pet food is the exclusive raw material traceability and supervision type, based on the identified target raw material category that needs to be subject to targeted supervision and the raw material category information of each traceable object in the set of supervision rules, a second target object that meets the preset raw material category matching conditions is determined from all traceable objects; Calculate the raw material quantities corresponding to all second target objects; based on the raw material quantities, determine the traceability and supervision results of the target pet food within the target production cycle.

[0013] A big data-based pet food production traceability and supervision system, applicable to the aforementioned big data-based pet food production traceability and supervision method, includes: The data acquisition unit is used to acquire basic data files for the entire pet food production process, set raw material input nodes for the processing and production stages in the raw material procurement stage, and set traceability information for raw materials and supply timestamps for raw materials at the raw material input nodes. The traceability calculation unit is used to find the location of all key process nodes in the processing and production process in the basic data file; inject raw material data into the raw material input node; and perform traceability calculation on the production data of the raw material procurement process and the corresponding area of ​​the key process node for each key process node based on traceability information and supply timestamp, so as to obtain the current time data chain corresponding to each data segment in the key process node. The tag association unit is used to add traceability tags to each data segment of key process nodes at the current time, and calculate the association status of all traceability tags at the next time based on the current time, the association information and position of all traceability tags; and determine whether the traceability of the entire production process has been completed. The first traceability unit is used to perform traceability calculations on the production data of the raw material procurement link and the corresponding area of ​​each key process node based on the raw material procurement link, the current data chain, traceability information and supply timestamp if the traceability of the entire production process is not completed, so as to obtain the next moment data chain corresponding to each data segment in each key process node. The second traceability unit is used to update the data chain of the next moment to the data chain of the current moment and to take the next moment as the current moment. It then returns to the execution of adding traceability markers to each data segment of the key process nodes in the current moment, and calculates the association status of all traceability markers in the next moment based on the current moment, the association information and position of all traceability markers, until the traceability of the entire production process is completed. If the traceability of the entire production process is completed, it outputs the association information of traceability markers at all moments.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention acquires basic data of the entire production process, sets raw material input nodes and supply timestamps, and performs traceability calculations at the data segment level at key process nodes. This generates a current-moment data chain for each data segment, enabling complete and continuous tracking of every step of the pet food production process from raw materials to finished product, avoiding traceability gaps. Furthermore, by finding and marking the locations of all key process nodes in the basic data file, generating corresponding traceability indexes, and assigning these indexes to traceability marker attributes, this achieves precise positioning of each process node and its data segment, improving the targeting and efficiency of traceability calculations. This invention employs a cyclical mechanism of "current moment data chain - add traceability marker - calculate the association status of the next moment - update data chain" until the entire traceability process is completed. This makes the traceability process real-time and adaptive, dynamically reflecting changes in the production process and promptly supplementing any incomplete traceability steps. Furthermore, by utilizing the association model, association direction, step location, and supply timestamp, combined with the time difference between the current moment and the next moment, the association status of the traceability marker is calculated. This accurately determines the connection relationship of each data segment on the timeline, avoiding traceability errors caused by time discrepancies. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart of the overall method in one embodiment of the present invention; Figure 2 This is a schematic diagram of the overall system architecture in one embodiment of the present invention.

[0016] In the diagram: 1. Data acquisition unit; 2. Traceability calculation unit; 3. Marking and association unit; 4. First traceability unit; 5. Second traceability unit. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 This invention provides a technical solution: a method for traceability and supervision of pet food production based on big data, comprising: S1. Obtain the basic data file of the entire pet food production process, set the raw material input node in the processing and production process in the raw material procurement process, and set the traceability information of the raw materials and the supply timestamp of the raw materials at the raw material input node. S2. Locate all key process nodes in the processing and production process in the basic data file; inject raw material data into the raw material input node; for each key process node, perform traceability calculations on the production data of the raw material procurement process and the corresponding area of ​​the key process node based on traceability information and supply timestamp, and obtain the current time data chain corresponding to each data segment in the key process node. S3. At the current moment, add traceability markers to each data segment of the key process nodes, and calculate the association status of all traceability markers at the next moment based on the current moment, the association information and position of all traceability markers; determine whether the traceability of the entire production process has been completed. S4. If the entire production process is not traceable, then based on the raw material procurement link, the current data chain, traceability information and supply timestamp, traceability calculations are performed on the production data of the raw material procurement link and the corresponding area of ​​each key process node to obtain the next moment data chain corresponding to each data segment in each key process node. S5. Update the data chain of the next moment to the data chain of the current moment and set the next moment as the current moment. Then return to the execution. In the current moment, add traceability markers to each data segment of the key process nodes. Calculate the association status of all traceability markers in the next moment based on the current moment, the association information and position of all traceability markers, until the traceability of the entire production process is completed. If the traceability of the entire production process is completed, output the association information of all traceability markers at all moments.

[0019] It should be noted that obtaining the basic data file for the entire pet food production process is crucial. This file covers various data from raw material procurement to final product output. In the raw material procurement process, the raw material input nodes in the processing and production process are determined. Just like on a production line, it is clear where the raw materials enter the processing workshop from the procurement warehouse. At the same time, traceability information is set for the raw materials, such as the origin, supplier, batch, etc. This information can help track the source of the raw materials. In addition, the supply timestamp of the raw materials at the input node is recorded, which is the specific time when the raw materials arrive at this input node. Carefully locate all critical process nodes in the processing and production process within the basic data file. Critical process nodes are those that have a significant impact on product quality and characteristics during the production process, such as mixing, baking, and sterilization in pet food. Identify the specific location of these nodes in the entire production process, just like marking important landmarks on a map. The relevant data of the raw materials is injected into the previously set raw material input nodes; for each key process node, based on the previously set traceability information and supply timestamp, traceability calculations are performed on the raw material procurement process and the production data of the corresponding area of ​​the key process node; this is like following a clue, starting from the source of the raw materials, tracing step by step along the production process, and finally obtaining the data chain corresponding to each data segment in the key process node at the current moment; this data chain records the information of each link that the raw materials go through from procurement to the key process node; The traceability marker is like a unique label used to identify the source and flow of the data segment; then, based on the current moment, the association information of all traceability markers (such as the order and mutual influence between different data segments), and their positions, the association state of all traceability markers at the next moment is calculated; this is similar to predicting the possible moves and relationships of the pieces in the next round based on the current position and layout of the pieces. Check whether traceability has been completed throughout the entire pet food production process; if not, proceed to the next step; if completed, output the associated information of traceability markers at all times. If traceability is not completed throughout the entire production process, traceability calculations are performed again on the production data of the raw material procurement process and the corresponding area of ​​each key process node based on the raw material procurement process, the current data chain, traceability information and supply timestamp, to obtain the next moment data chain corresponding to each data segment in each key process node. Update the data chain of the next moment to the data chain of the current moment, and at the same time take the next moment as the current moment; then return to execute the operation of adding traceability mark and calculating the traceability mark association state of the next moment, and keep looping until the traceability of the entire production process is completed; this is like constantly repeating the process of playing chess and making predictions until the game ends. Once the entire production process is traceable, the associated information of all traceability markers at all times is output. This information can clearly show the flow and changes of raw materials in pet food throughout the entire production process, facilitating quality traceability and management.

[0020] In an optional embodiment, based on traceability information and supply timestamps, traceability calculations are performed on production data corresponding to the raw material procurement process and key process nodes to obtain the current-time data chain for each data segment in the key process node, including: For each data segment in each key process node, a correlation model for the data segment is set. Obtain each associated direction of the data segment and the corresponding stage position of the data segment in the production process; Based on traceability information, supply timestamps, each association direction of the data segment, and the position of each link, the association model is solved to obtain the data chain corresponding to the current moment of the data segment.

[0021] It should be noted that each key process node contains multiple data segments. For example, the mixing stage may contain data segments such as the mixing ratio of different raw materials and the mixing time. Setting up a correlation model for these data segments is to clarify how these data segments affect and relate to each other. The direction of association refers to the direction of influence transmission between data segments; the link position is the specific location of the data segment in the entire production process; clarifying the link position helps to accurately track the flow and changes of data segments in the production process; The traceability information includes the source and batch of raw materials, and the supply timestamp records the time when the raw materials arrive at each node; combining this information, as well as the previously determined correlation direction and link position, the established correlation model is solved. The solution process is like reasoning along a clue; starting with the traceability information and supply timestamps of the raw materials, based on the position of the data segment in the production process, the state and interrelationship of each data segment at the current moment are gradually deduced along the correlation direction, and finally the data chain corresponding to the data segment at the current moment is obtained; this data chain records the specific value of each data segment at the current moment and the relationship between them, just like a map that records the footprints of each data segment in the production process.

[0022] In an optional embodiment, after locating the positions of all critical process nodes in the manufacturing process in the basic data file, the method further includes: The location of each key process node in the processing and production process is marked to obtain the traceability index corresponding to each key process node.

[0023] It should be noted that the location of key process nodes refers to their sequence and stage in the production process; marking the location means clarifying the specific coordinates of each key process node in the entire production process, such as whether it is in the early, middle or late stage of production, and what stages precede and precede it; through this marking, the production process can be clearly outlined, and the status and role of each key process node in the whole process can be understood. The traceability index is like an ID number for each key process node. It is a unique identifier that allows you to trace all the information related to that key process node. This information includes the source of raw materials, the equipment used, the operators, the production time, and the process parameters. With the traceability index, when a product has a quality problem or when you need to understand a certain detail in the production process, you can quickly and accurately locate the corresponding key process node and obtain relevant detailed information, thereby finding the root cause of the problem or understanding the specific production situation.

[0024] In an optional embodiment, the association status of all traceability markers at the next time step is calculated based on the current time, the association information of all traceability markers, and their positions, including: For each traceability marker, the traceability index corresponding to the key process node is assigned to the attribute of the traceability marker, and the data chain at the current time corresponding to the data segment position where the traceability marker is located is determined as the association information of the traceability marker, thus obtaining the target traceability marker; Calculate the time difference between the next moment and the current moment; based on the time difference, the association information of the target tracing marker, and the location, calculate the association status of the tracing marker at the next moment.

[0025] It should be noted that traceability tags are like small labels in the product manufacturing process, used to identify and track information about the product at each stage; while the traceability index corresponding to the key process node contains detailed information about raw materials, operations, equipment, etc. at that node; assigning the traceability index to the attribute of the traceability tag is like writing a detailed description on the small label, so that each traceability tag carries the key information of the corresponding key process node. For example, in a food production process, there is a traceability tag that corresponds to the key process node of sterilization. The traceability index of the sterilization step (such as sterilization temperature, time, sterilization equipment number used, etc.) is assigned to the attribute of this traceability tag. In this way, the specific situation of the sterilization step can be understood through this traceability tag. The data segment location refers to the specific position of the traceability marker in the production data flow. The current moment data chain records the status and relationship of each related data at the current moment. Determining the current moment data chain as the associated information of the traceability marker means that the traceability marker not only carries information about key process nodes, but also establishes a connection with the overall data situation at its current position. After the first two steps, the traceability tag has both detailed attribute information of key process nodes and correlation information with the current data situation. Such a traceability tag becomes a target traceability tag. It can more completely and accurately reflect the specific state and information of the product in the production process, providing richer evidence for subsequent traceability and analysis. The time difference refers to the interval between two different moments in time. In the production process, it is important to know the time difference between the next moment and the current moment because it can help predict and calculate the changes in various states during the production process. The associated state refers to the relationship and state of the traceability marker with the surrounding data and environment at the next moment. By using the time difference, we can know how much time has passed from the current moment to the next moment. By combining the associated information of the target traceability marker (such as the data chain status at the current moment) and its location (the specific stage in the production process), we can infer the associated state of the traceability marker at the next moment.

[0026] In an optional embodiment, determining whether traceability has been completed throughout the entire production process includes: Based on the association information of traceability markers at all times, determine whether each data segment in each key process node contains a traceability marker; If every data segment in every key process node contains a traceability marker, then the entire production process is traceable. If every data segment in every critical process node does not contain a traceability marker, then the entire production process is not traceable.

[0027] It should be noted that during the product manufacturing process, the association information of the traceability markers at various moments is recorded. This association information reflects the connection between the traceability markers and the production data, such as which production stage the traceability marker corresponds to, which equipment operations are involved, and what raw materials are used. The judgment process involves checking each data segment under each key process node to see if there is a corresponding traceability mark. If a data segment does not have a traceability mark, it means that the information of this data segment cannot be traced and queried through the traceability mark, and there may be a situation where information is missing or cannot be traced. When all data segments under all key process nodes are equipped with traceability tags, it means that every detail in the entire production process has a corresponding identifier that can be traced. Whether it is the source of raw materials, operation records during the production process, or equipment operation status, the corresponding records can be found through traceability tags. This means that the traceability work of the entire production process has been completed, which can realize the full tracking and query of products from raw materials to finished products, which helps to ensure product quality, solve quality problems, and meet regulatory requirements. If, during the inspection process, it is found that a data segment under a critical process node lacks a traceability tag, it indicates a loophole in the traceability work of the entire production process. This is because a data segment lacking a traceability tag cannot form a complete traceability chain with other tagged data, resulting in incomplete traceability of the entire production process. In this case, it cannot be determined whether the entire production process has been traced. It is necessary to further investigate the cause of the missing traceability tag and supplement the corresponding traceability tag to ensure the traceability of the production process.

[0028] In an optional embodiment, after outputting the association information of the source markers at all times, the method further includes: Determine the current production batch information of the target pet food that requires production traceability supervision. The current production batch information includes one or more target raw material objects and production process objects. The current production batch information is input into a preset traceability database for retrieval and analysis to obtain raw material traceability data for each target raw material and process traceability data for each production stage. The traceability data for each target raw material and production stage is then encapsulated to obtain a tracking code for each target raw material and production stage. The raw material traceability data includes at least the supplier information, test report information, and warehousing time information for the target raw material, while the process traceability data includes at least the operator information, equipment information, and processing time information for the production stage.

[0029] It should be noted that in order to achieve effective traceability and supervision during the production process of pet food, it is first necessary to clarify which batch of pet food needs to be supervised. Each production batch has its own unique identification and related information, just like giving each batch of products an identity tag. The current production batch information covers the key aspects involved in the production of this batch of pet food, including one or more target raw materials and production process objects. Target raw materials refer to the various raw materials used in the production of this batch of pet food, such as meat, grains, and additives. Production process objects refer to the key steps in the entire production process from raw material input to finished product output, such as raw material cleaning, mixing, baking, and packaging. The traceability database is a large repository specifically for storing information related to pet food production. It contains detailed data on raw materials and production processes collected and organized in advance. Once the information of the current production batch is determined, this information is entered into this database. The database acts like an intelligent searcher, retrieving and analyzing information based on input. It can find data related to each target raw material and production process in the current production batch from massive amounts of data, just as accurately as finding a specific book by its title in a library. Through the retrieval and analysis of the traceability database, detailed traceability data for each target raw material will be obtained. This data includes supplier information for the target raw material, which tells you from which supplier the raw material was purchased; and test report information, which records the results of various quality tests that the raw material underwent before entering the production process, ensuring that the raw material meets safety standards. The warehousing time information, which is the specific time when the raw materials enter the factory warehouse, helps to understand the freshness and storage conditions of the raw materials. Similarly, for each production link, traceability data will also be obtained, including the operator information of the production link, so that we can know who is performing the operation of this link; equipment information, which specifies which equipment is used for processing; and processing time information, which records the specific start and end times of the link, so as to facilitate the monitoring of production progress and quality. Traceability data encapsulation is like packaging these detailed data information, integrating all traceability data of each target raw material object and production link object into a complete data package; then generating a unique tracking code for this data package, which is like an ID number and has uniqueness; through this tracking code, all traceability information of the corresponding raw material or production link can be found quickly and accurately, making it convenient to query and trace when needed.

[0030] In an optional embodiment, the method further includes: Based on the identified set of regulatory rules corresponding to the target pet food, determine the tracking code for each traceable object in the set of regulatory rules. For each target raw material and production process object, based on the tracking codes of all traceable objects and the tracking code of the target object, determine whether the target object meets the preset traceability conditions. When it is determined that the target object meets the traceability conditions, the compliance status result of the target object is determined based on the current stage time information, the previous stage time information, and the preset stage time benchmark information corresponding to the target object. When it is determined that the target object does not meet the traceability conditions, based on the raw material traceability data or process traceability data corresponding to the target object, object category information and tracking code, and the set basic compliance status results, the corresponding element addition and data update operations are performed on the regulatory rule set, and the compliance status result of the target object is determined. Based on the compliance status of each traceable object in the regulatory rule set, determine the traceability regulatory results of the target pet food within the target production cycle; where all traceable objects include target raw material objects and production process objects.

[0031] It should be noted that the set of regulatory rules is a series of rules formulated for the production process of the target pet food, used to regulate and supervise the production process and ensure product quality and safety; the traceable objects include the target raw materials (such as meat, grains, etc. used in the production of pet food) and the production process objects (such as raw material processing, mixing, baking, etc.). Each traceable object has a unique tracking code, which acts like an ID card, recording various information about the object from its source to its production process. According to the set of regulatory rules, it is necessary to find the tracking code corresponding to each traceable object involved in order to conduct subsequent traceability and supervision. Traceability criteria are pre-defined standards used to determine whether a target object has completed the full traceability process. For example, for a target raw material, traceability criteria may include complete supplier information, qualified test reports, and accurate warehousing time records. For objects in the production process, traceability conditions may include clear operator information, complete equipment usage records, and processing time meeting requirements. By comparing the information contained in the tracking codes of all traceable objects with the tracking code information of the target object, it can be determined whether the target object meets these preset conditions. If the target object meets the traceability conditions, it means that its traceability information is complete and reliable. Next, it is necessary to further determine its compliance status. The current stage time information refers to the time spent by the target object in the current production stage, the previous stage time information refers to the time spent in the previous production stage, and the stage time benchmark information is the standard time that should be spent in each production stage in advance. By comparing the current time and the previous time with the time reference information, it can be determined whether the time of the target object in the production process meets the requirements, thereby determining its compliance status, such as whether it has exceeded the time limit or completed ahead of schedule. If the target object does not meet the traceability conditions, it indicates that its traceability information is missing or problematic. In this case, it is necessary to make corresponding adjustments to the set of regulatory rules based on the specific traceability data of the target object (such as missing supplier information for raw materials, unclear information on operators in the production process, etc.), object category information (whether it is raw material or production process), and tracking code. For example, add new rules to supplement missing information, or update existing rules to more accurately reflect the actual situation; at the same time, determine the final compliance status of the target object based on the established basic compliance status result (such as initially setting it as non-compliant); After assessing the compliance status of each traceable item, the results need to be combined to determine the traceability and regulatory outcome of the target pet food throughout the entire production cycle. If the compliance status of all traceable items meets the requirements, then the traceability and regulatory outcome of the target pet food is considered satisfactory. If any traceable item fails to meet compliance requirements, then the traceability supervision result for the target pet food is also considered unqualified. This helps to fully understand whether the production process of the target pet food complies with regulations, ensuring product quality and safety.

[0032] In an optional embodiment, the compliance status result of the target object is determined based on the current stage time information and the previous stage time information corresponding to the determined target object, and the preset stage time reference information, including: Based on the current time information corresponding to the target object, a first time value is determined, and based on the previous time information corresponding to the target object, a second time value is determined, and based on the preset time reference information, a reference time value is determined. When the first time value is later than the second time value and the first time value is later than the baseline time value, the compliance status type of the target object is determined to be the delayed status type. When the first time value is earlier than the second time value and the first time value is earlier than the baseline time value, the compliance status type of the target object is determined to be the advanced status type; wherein, the compliance status type includes one of the advanced status type, the delayed status type and other status types; the compliance status result of the target object is determined according to the compliance status type.

[0033] It should be noted that the first time value is determined based on the time information corresponding to the target object in the current production stage; the current stage time information records key time data such as the length of time the target object has experienced from the beginning to the end of the current production step or the specific end time. By analyzing and extracting this data, the first time value can be obtained. For example, in pet food production, the current stage is baking. It is recorded that the total time from the start of baking to the end of baking is 30 minutes. This 30 minutes can be used as the first time value (if measured by duration). Alternatively, if the specific time of baking end is recorded as 3 pm, this time can also be used as a reference to further determine the first time value (by combining other time information to calculate the duration, etc.). The second time value is determined by the time information corresponding to the target object in the previous production stage. The time information of the previous stage also includes data such as the time length or key moments of the previous production step, which are processed to obtain the second time value. For example, if the previous stage is the raw material mixing stage and the mixing takes 20 minutes, then these 20 minutes are the second time value (measured by duration). The baseline time value is determined based on the preset time baseline information for each stage. The time baseline information for each stage is the standard time that should be spent for each production stage, which is determined in advance based on production experience, process requirements, etc. For example, for the baking stage, after multiple trials and optimizations, the standard baking time is determined to be 25 minutes. This 25 minutes is the baseline time value for the baking stage. The delayed state type refers to a situation where the first time value is later than the second time value and the first time value is later than the baseline time value, indicating that the target object spends more time in the current stage than in the previous stage, and exceeds the preset standard time. In pet food production, if the baking process (current process) takes 30 minutes, while the previous process of mixing raw materials took 20 minutes, and the standard baking time is 25 minutes, then 30 minutes is greater than both 20 minutes and 25 minutes, which indicates that there is a delay in the current process. Therefore, the compliance status type of the target object is determined to be the delayed status type. The "advanced state" type means that when the first time value is earlier than the second time value and the first time value is earlier than the baseline time value, it means that the target object spends less time in the current stage than in the previous stage, and also less than the preset standard time. For example, if the baking process takes 20 minutes and the previous process of mixing ingredients takes 25 minutes, and the standard baking time is 25 minutes, then 20 minutes is less than 25 minutes and less than the previous process's 25 minutes, indicating that the current process was completed ahead of schedule. Therefore, the compliance status type of this target object is determined to be the "ahead of schedule" status type. In addition to the two explicit cases mentioned above, if the relationship between the first time value, the second time value, and the reference time value does not meet the conditions for delay or advance, it is classified as other state types; for example, the first time value is equal to the second time value, or the first time value is earlier than the second time value but later than the reference time value, etc. Based on the determined compliance status type, the compliance status result of the target object is further determined; different compliance status types correspond to different result descriptions. For example, if it is a delay status type, the compliance status result can be described as a production delay in the current stage, which does not meet the preset time requirements. If it is an early completion status, the compliance status result can be described as the current stage of production being completed ahead of schedule, but it is necessary to check whether it affects product quality; if it is another status type, the compliance status result will be described accordingly based on the specific situation, such as the current stage of production time being in line with general conditions, but continuous monitoring is required, etc.

[0034] In an optional embodiment, the traceability regulatory result of the target pet food within the target production cycle is determined based on the compliance status result of each traceable object in the regulatory rule set, including: When the traceability supervision requirement of the target pet food is the full-chain traceability supervision type, based on the information of the target link that needs to be supervised in the full chain and the compliance status result of each traceable object in the set of supervision rules, the first target object that meets the preset link matching conditions is determined from all traceable objects; Calculate the number of stages corresponding to all first target objects; based on the number of stages, determine the traceability and supervision results of the target pet food within the target production cycle; When the traceability and supervision requirement type for the target pet food is the exclusive raw material traceability and supervision type, based on the identified target raw material category that needs to be subject to targeted supervision and the raw material category information of each traceable object in the set of supervision rules, a second target object that meets the preset raw material category matching conditions is determined from all traceable objects; Calculate the raw material quantities corresponding to all second target objects; based on the raw material quantities, determine the traceability and supervision results of the target pet food within the target production cycle.

[0035] It should be noted that when the traceability and supervision requirement for the target pet food is the full-chain traceability and supervision type, it means that the entire production chain of the pet food, from raw material procurement to finished product delivery, needs to be fully supervised. First, the target links that need to be supervised in the full chain need to be identified. These target links cover all key steps in the production process, such as raw material acceptance, processing, packaging, and storage. Based on the compliance status results of each traceable object in the regulatory rule set, the first target object that meets the preset matching conditions is selected from all traceable objects. The matching conditions here can be that the process is in a normal compliance status, the key operations of the process meet the standards, etc. Only traceable objects that meet these conditions will be selected as the first target object. After identifying the primary target objects, count the number of links corresponding to these primary target objects; that is, count how many links in the entire production chain meet the link matching conditions. The traceability and supervision results of the target pet food within the target production cycle are determined based on the calculated number of links. If the number of links reaches or exceeds the preset standard number, it means that most of the key links meet the regulatory requirements, and the traceability and supervision results can be judged as qualified. Conversely, if the number of links is less than the preset standard number, it means that there are many problems in the key links, and the traceability and supervision results are judged as unqualified. When the traceability and supervision requirement for the target pet food is the specific raw material traceability and supervision type, the focus is on targeted supervision of specific raw materials; first, determine the target raw material category that needs to be targeted for supervision, such as meat raw materials, grain raw materials, or additive raw materials; based on the raw material category information of each traceable object in the set of supervision rules, find the second target object that meets the preset raw material category matching conditions from all traceable objects; The matching criteria for raw material categories can be reliable raw material sources, qualified raw material quality testing, etc. The raw materials corresponding to traceable objects that meet these conditions are the second target objects. For example, if it is stipulated that meat raw materials must come from certified suppliers and be tested to be free of veterinary drug residues in order to be considered a match, then only traceable objects corresponding to meat raw materials that meet these conditions will become the second target objects. After identifying the second target objects, count the quantity of raw materials corresponding to these second target objects; that is, see how many specific raw materials meet the raw material category matching conditions. Based on the calculated quantity of raw materials, the traceability and supervision results of the target pet food within the target production cycle are determined. If the quantity of raw materials reaches or exceeds the preset standard quantity, it indicates that most of the target raw materials meet the regulatory requirements, and the traceability and supervision result is judged as qualified. If the quantity of raw materials is less than the preset standard quantity, it indicates that a large number of target raw materials have problems, and the traceability and supervision result is judged as unqualified.

[0036] Example 2, please refer to Figure 2 This invention provides a technical solution: a big data-based pet food production traceability and supervision system, applicable to the aforementioned big data-based pet food production traceability and supervision method, comprising: Data acquisition unit 1 is used to acquire basic data files for the entire pet food production process, set raw material input nodes for the processing and production process in the raw material procurement stage, and set traceability information for raw materials and supply timestamps for raw materials at the raw material input nodes. Traceability calculation unit 2 is used to find the location of all key process nodes in the processing and production process in the basic data file; inject raw material data into the raw material input node; and perform traceability calculation on the production data of the raw material procurement process and the corresponding area of ​​the key process node for each key process node based on traceability information and supply timestamp, so as to obtain the current time data chain corresponding to each data segment in the key process node. The tag association unit 3 is used to add traceability tags to each data segment of key process nodes at the current time, and calculate the association status of all traceability tags at the next time based on the current time, the association information and position of all traceability tags; and determine whether the traceability of the entire production process has been completed. The first traceability unit 4 is used to perform traceability calculations on the production data of the raw material procurement link and the corresponding area of ​​each key process node based on the raw material procurement link, the current time data chain, traceability information and supply timestamp if the traceability of the entire production process is not completed, so as to obtain the next time data chain corresponding to each data segment in each key process node. The second traceability unit 5 is used to update the data chain of the next moment to the data chain of the current moment and to take the next moment as the current moment. It then returns to the current moment to add traceability markers to each data segment of the key process nodes. Based on the current moment, the association information and position of all traceability markers, it calculates the association status of all traceability markers in the next moment until the entire production process is traceable. If the entire production process is traceable, it outputs the association information of all traceability markers at all moments.

[0037] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A method for traceability and supervision of pet food production based on big data, characterized in that, include: Obtain basic data files for the entire pet food production process, set raw material input nodes in the processing and production stages during the raw material procurement stage, and set traceability information for raw materials and supply timestamps for raw materials at the raw material input nodes; Locate all key process nodes in the manufacturing process within the basic data file; Raw material data is injected into the raw material input node. For each key process node, traceability calculations are performed on the production data of the raw material procurement process and the corresponding area of ​​the key process node based on traceability information and supply timestamps to obtain the current time data chain corresponding to each data segment in the key process node. At the current moment, add traceability markers to each data segment of key process nodes, and calculate the association status of all traceability markers at the next moment based on the current moment, the association information and position of all traceability markers; determine whether traceability has been completed for the entire production process; If traceability is not completed throughout the entire production process, traceability calculations are performed on the production data of the raw material procurement process and the corresponding area of ​​each key process node based on the raw material procurement process, the current data chain, traceability information, and supply timestamp, to obtain the next moment data chain corresponding to each data segment in each key process node. Update the data chain of the next moment to the data chain of the current moment and set the next moment as the current moment. Then return to the execution in the current moment, add traceability markers to each data segment of the key process nodes, and calculate the association status of all traceability markers in the next moment based on the current moment, the association information and position of all traceability markers, until the traceability of the entire production process is completed. If traceability is completed throughout the entire production process, the associated information of traceability markers at all times will be output.

2. The method for traceability and supervision of pet food production based on big data according to claim 1, characterized in that, Based on traceability information and supply timestamps, traceability calculations are performed on production data corresponding to the raw material procurement process and key process nodes to obtain the current-time data chain for each data segment in the key process nodes, including: For each data segment in each key process node, a correlation model for the data segment is set. Obtain each associated direction of the data segment and the corresponding stage position of the data segment in the production process; Based on traceability information, supply timestamps, each association direction of the data segment, and the position of the link, the association model is solved to obtain the data chain corresponding to the current moment of the data segment.

3. The method for traceability and supervision of pet food production based on big data according to claim 2, characterized in that, After locating the positions of all critical process nodes in the manufacturing process within the basic data file, the method further includes: The location of each key process node in the processing and production process is marked to obtain the traceability index corresponding to each key process node.

4. The method for traceability and supervision of pet food production based on big data according to claim 3, characterized in that, Based on the current time, the association information and location of all traceability markers, calculate the association status of all traceability markers at the next time step, including: For each traceability marker, the traceability index corresponding to the key process node is assigned to the attribute of the traceability marker, and the data chain at the current time corresponding to the data segment position where the traceability marker is located is determined as the association information of the traceability marker, thus obtaining the target traceability marker; Calculate the time difference between the next moment and the current moment; based on the time difference, the association information of the target tracing marker, and the location, calculate the association status of the tracing marker at the next moment.

5. The method for traceability and supervision of pet food production based on big data according to claim 4, characterized in that, Determining whether traceability has been completed throughout the entire production process includes: Based on the association information of traceability markers at all times, determine whether each data segment in each key process node contains a traceability marker; If every data segment in every key process node contains a traceability marker, then the entire production process is traceable. If every data segment in every critical process node does not contain a traceability marker, then the entire production process is not traceable.

6. The method for traceability and supervision of pet food production based on big data according to claim 5, characterized in that, After outputting the association information of the source markers at all times, the method also includes: Determine the current production batch information of the target pet food that requires production traceability supervision. The current production batch information includes one or more target raw material objects and production process objects. The current production batch information is input into a preset traceability database for retrieval and analysis to obtain raw material traceability data for each target raw material and process traceability data for each production stage. The traceability data for each target raw material and production stage is then encapsulated to obtain a tracking code for each target raw material and production stage. The raw material traceability data includes at least the supplier information, test report information, and warehousing time information for the target raw material, while the process traceability data includes at least the operator information, equipment information, and processing time information for the production stage.

7. The method for traceability and supervision of pet food production based on big data according to claim 6, characterized in that, The method further includes: Based on the identified set of regulatory rules corresponding to the target pet food, determine the tracking code for each traceable object in the set of regulatory rules. For each target raw material and production process object, based on the tracking codes of all traceable objects and the tracking code of the target object, determine whether the target object meets the preset traceability conditions. When it is determined that the target object meets the traceability conditions, the compliance status result of the target object is determined based on the current stage time information, the previous stage time information, and the preset stage time benchmark information corresponding to the target object. When it is determined that the target object does not meet the traceability conditions, based on the raw material traceability data or process traceability data corresponding to the target object, object category information and tracking code, and the set basic compliance status results, the corresponding element addition and data update operations are performed on the regulatory rule set, and the compliance status result of the target object is determined. Based on the compliance status of each traceable object in the regulatory rule set, determine the traceability regulatory results of the target pet food within the target production cycle; where all traceable objects include target raw material objects and production process objects.

8. The method for traceability and supervision of pet food production based on big data according to claim 7, characterized in that, Based on the current stage time information and previous stage time information corresponding to the identified target object, and the preset stage time baseline information, the compliance status result of the target object is determined, including: Based on the current time information corresponding to the target object, a first time value is determined, and based on the previous time information corresponding to the target object, a second time value is determined, and based on the preset time reference information, a reference time value is determined. When the first time value is later than the second time value and the first time value is later than the baseline time value, the compliance status type of the target object is determined to be the delayed status type. When the first time value is earlier than the second time value and the first time value is earlier than the baseline time value, the compliance status type of the target object is determined to be the advanced status type; wherein, the compliance status type includes one of the advanced status type, the delayed status type and other status types; the compliance status result of the target object is determined according to the compliance status type.

9. A method for traceability and supervision of pet food production based on big data as described in claim 8, characterized in that, Based on the compliance status of each traceable object in the regulatory rule set, determine the traceability regulatory results of the target pet food within the target production cycle, including: When the traceability supervision requirement of the target pet food is the full-chain traceability supervision type, based on the information of the target link that needs to be supervised in the full chain and the compliance status result of each traceable object in the set of supervision rules, the first target object that meets the preset link matching conditions is determined from all traceable objects; Calculate the number of stages corresponding to all first target objects; based on the number of stages, determine the traceability and supervision results of the target pet food within the target production cycle; When the traceability and supervision requirement type for the target pet food is the exclusive raw material traceability and supervision type, based on the identified target raw material category that needs to be subject to targeted supervision and the raw material category information of each traceable object in the set of supervision rules, a second target object that meets the preset raw material category matching conditions is determined from all traceable objects; Calculate the raw material quantities corresponding to all second target objects; based on the raw material quantities, determine the traceability and supervision results of the target pet food within the target production cycle.

10. A big data-based pet food production traceability and supervision system, applicable to the big data-based pet food production traceability and supervision method described in any one of claims 1-9, characterized in that, include: The data acquisition unit is used to acquire basic data files for the entire pet food production process, set raw material input nodes for the processing and production stages in the raw material procurement stage, and set traceability information for raw materials and supply timestamps for raw materials at the raw material input nodes. The traceability calculation unit is used to locate the positions of all key process nodes in the processing and production process in the basic data file; Raw material data is injected into the raw material input node. For each key process node, traceability calculations are performed on the production data of the raw material procurement process and the corresponding area of ​​the key process node based on traceability information and supply timestamps to obtain the current time data chain corresponding to each data segment in the key process node. The tag association unit is used to add traceability tags to each data segment of key process nodes at the current time, and calculate the association status of all traceability tags at the next time based on the current time, the association information and position of all traceability tags; and determine whether the traceability of the entire production process has been completed. The first traceability unit is used to perform traceability calculations on the production data of the raw material procurement link and the corresponding area of ​​each key process node based on the raw material procurement link, the current data chain, traceability information and supply timestamp if the traceability of the entire production process is not completed, so as to obtain the next moment data chain corresponding to each data segment in each key process node. The second traceability unit is used to update the data chain of the next moment to the data chain of the current moment and to take the next moment as the current moment. It then returns to the execution of adding traceability markers to each data segment of the key process nodes in the current moment, and calculates the association status of all traceability markers in the next moment based on the current moment, the association information and position of all traceability markers, until the traceability of the entire production process is completed. If traceability is completed throughout the entire production process, the associated information of traceability markers at all times will be output.

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