Emulsifier whole-process quality traceability identification analysis method and system

Abstract

This invention relates to the field of quality traceability technology in the chemical industry, providing a method and system for resolving emulsifier quality traceability identifiers throughout the entire process. The method includes: generating carrier identifiers resistant to physical corrosion for raw materials; real-time sensing of critical events in emulsifier phase transitions using a multi-mode sensor array deployed on production equipment; automatically triggering the generation of derived identifiers associated with the previous identifier when a preset phase transition condition is detected; dynamically binding key process parameters and quality inspection data from the production process to the identifiers of the current stage after aggregation through edge computing nodes; and storing summary information of the identifiers and their associated data from each stage in a cross-enterprise blockchain consortium network to form an immutable traceability chain. This invention ensures the continuity of identifiers throughout the physical evolution process and achieves reliable interaction and efficient resolution of cross-system data.

Description

Technical Field

[0001] This invention relates to the field of quality traceability technology in the chemical industry, specifically to a method and system for resolving quality traceability identifiers throughout the entire process of emulsifier production. Background Technology

[0002] In the production process of emulsifiers in the chemical industry, there are problems such as discontinuous traceability information, low efficiency in locating quality anomalies, and a lack of credibility in cross-enterprise collaboration, which seriously affect product quality control and industry development. Analysis reveals that the technical roots of these problems mainly include the following three aspects:

[0003] Phase transitions cause data gaps: Emulsifier production involves phase changes from liquid raw materials to paste semi-finished products and solid finished products. Traditional identification carriers such as RFID tags cannot be continuously attached in high-temperature and high-pressure processes, resulting in data that cannot be effectively connected at each stage.

[0004] Seamless dynamic adjustment of formulation: The process parameters for adjusting the HLB value (hydrophilic-lipophilic balance value) in real time during production are not effectively recorded. Key quality factors such as particle size distribution are decoupled from operating instructions, making it difficult to trace the factors affecting quality.

[0005] Poor interoperability of heterogeneous systems: Supplier raw material batch data (SQL database), production line PLC control signals (Modbus protocol), laboratory test reports (PDF) and other data constitute unstructured data silos, making it impossible to share and integrate data efficiently.

[0006] Existing traceability technologies have significant shortcomings in addressing the above-mentioned problems:

[0007] Batch number segmentation management: Each production segment generates its own identifier, which requires manual association with the mapping table, resulting in an error rate as high as 18%, and making it impossible to achieve full-process automatic traceability.

[0008] Static QR code labeling: The labels are prone to falling off and becoming ineffective in the high-temperature emulsification kettle (120℃+) environment, and can only store fixed information, unable to record dynamic process parameters;

[0009] Centralized database integration: It forces upstream and downstream enterprises to open their raw data interfaces, but due to concerns about trade secrets, the actual access rate is less than 30%, making cross-enterprise data sharing difficult.

[0010] Existing technologies lack adaptability to the physical evolution of emulsifiers and reliable cross-chain data interaction mechanisms, thus failing to fundamentally solve the aforementioned core problems. Therefore, in light of this situation, there is an urgent need to provide a method and system for end-to-end quality traceability and identification of emulsifiers to overcome the shortcomings in current practical applications. Summary of the Invention

[0011] The purpose of this invention is to provide a method and system for quality traceability and identification analysis of emulsifiers throughout the entire process, in order to solve the problems mentioned in the background art.

[0012] This invention is implemented as follows: a method for end-to-end quality traceability and identification resolution of emulsifiers, comprising the following steps:

[0013] Step S1, Raw material identification coding: Generate and attach a carrier identification that is resistant to physical corrosion to the raw material container, wherein the carrier identification stores basic information about the raw material;

[0014] Step S2, Phase transition event perception: Real-time acquisition of phase state data during the production process through a multi-mode sensor array deployed on the production equipment;

[0015] Step S3, Derivative Identifier Generation: When the phase state data meets the preset phase transformation conditions, a derived identifier associated with the identifier of the previous step is automatically generated.

[0016] Step S4, Process Data Chain Binding: Dynamically bind the process parameters and / or quality inspection data of the current production stage with the identifier of the current stage;

[0017] Step S5, Cross-chain data storage and parsing: The identifiers of each production link and their associated key data summaries are stored in the blockchain consortium chain network; when traceability is required, the associated data of the entire process is obtained from the blockchain consortium chain network by parsing the identifiers.

[0018] As a further aspect of the present invention: in step S1, the carrier identification for resisting physical corrosion is a direct component identification (DPM code) generated by laser etching technology, and the basic information includes at least the raw material batch, the hydrophilic-lipophilic balance (HLB) benchmark value, and the supplier's digital certificate.

[0019] As a further aspect of the present invention: in step S2, the multimode sensor array includes a viscosity sensor, a temperature sensor, and a pressure sensor;

[0020] The phase transition condition is that the material viscosity changes from below a first threshold to above a second threshold.

[0021] As a further aspect of the present invention, step S4 specifically includes: using edge computing nodes deployed on the production line side to locally aggregate and clean the process data collected by the sensors, and binding the cleaned data with the current identifier.

[0022] As a further aspect of the present invention: the edge computing node is pre-loaded with a process knowledge graph for storing emulsifier phase change rules.

[0023] As a further aspect of the present invention: in step S5, the data stored in the blockchain consortium blockchain network is the hash value of key events or data;

[0024] The blockchain consortium network runs smart contracts for verifying identity changes and storing quality data.

[0025] This invention also provides an emulsifier end-to-end quality traceability and identification system for implementing the above-described method, the system comprising:

[0026] The IoT sensing layer includes an anti-corrosion marking carrier for attaching to raw material containers and a multi-mode sensor array deployed on production equipment for sensing the phase state of matter.

[0027] The identification management layer is connected to the IoT sensing layer. The identification management layer includes an OID parsing engine and a derived identifier generator. The OID parsing engine is used to map physical identifiers to virtual objects, and the derived identifier generator is used to generate derived identifiers in response to object phase transformation events.

[0028] The edge computing engine, connected to the IoT sensing layer and the identification management layer, is used to process sensor data locally and bind process parameters to identification.

[0029] The blockchain network layer, connected to the identifier management layer, is used to store summary information of the identifiers and their associated data at each stage, and to provide cross-chain identifier resolution services.

[0030] The application service layer, connected to the blockchain network layer, is used to provide traceability data query and visualization services.

[0031] As a further aspect of the present invention: the blockchain network layer includes a smart contract cluster and a cross-chain bridge, wherein the cross-chain bridge supports data interoperability with external enterprise resource planning (ERP) systems.

[0032] As a further aspect of the present invention: the application service layer includes a quality anomaly tracing module, which locates the source of process deviation based on a decision tree model.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0034] By using the "phase-driven identifier derivation" mechanism, the generation of identifiers is synchronized with changes in the physical state of materials, fundamentally solving the problem of traceability chain breakage caused by changes in material form.

[0035] By leveraging edge computing technology, dynamic process parameters (such as real-time adjusted HLB values) and quality data are bound to the identifier of the current stage at the data source, ensuring an accurate correspondence between data and physical objects and solving the problem of data silos.

[0036] By introducing blockchain consortium blockchain technology, the immutability and verifiability of cross-process and cross-enterprise traceability data are guaranteed through hash-based evidence storage without requiring all parties to disclose original sensitive data, thus establishing a foundation for trusted collaboration.

[0037] The system can automatically and in real time record and associate data throughout the entire process. When a quality anomaly occurs, it can quickly and accurately locate the problematic link and cause based on the data stored on the blockchain, significantly improving the efficiency of quality control. Detailed Implementation

[0038] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, 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.

[0039] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," indicating orientation or positional relationships, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0040] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0041] The present invention will be further explained below with reference to specific embodiments.

[0042] The emulsifier full-process quality traceability identification and resolution method and system provided in this embodiment of the invention includes: 1. an emulsifier full-process quality traceability identification and resolution method, characterized by comprising the following steps:

[0043] Step S1, Raw Material Identification and Coding: Generate and attach a carrier identification resistant to physical corrosion to the raw material container. The carrier identification stores basic information about the raw material. The carrier identification resistant to physical corrosion is a direct component identification (DPM code) generated by laser etching technology. The basic information includes at least the raw material batch, the hydrophilic-lipophilic balance (HLB) baseline value, and the supplier's digital certificate.

[0044] Among them, the ceramic-based DPM label has a temperature resistance of 600℃;

[0045] Step S2, Phase Transition Event Sensing: Real-time acquisition of phase state data during the production process through a multi-mode sensor array deployed on the production equipment; the multi-mode sensor array includes a viscosity sensor, a temperature sensor and a pressure sensor. When the viscosity sensor detects that the material changes from a Newtonian fluid (viscosity < 50 cP) to a pseudoplastic fluid (viscosity > 2000 cP), an identification change event is triggered.

[0046] The phase transition condition is that the material viscosity changes from below a first threshold to above a second threshold.

[0047] Step S3, Derivative Identifier Generation: When the phase state data meets the preset phase transformation conditions, a derived identifier associated with the identifier of the previous step (such as A001@202308011030) is automatically generated.

[0048] Step S4, Process Data Chain Binding: Dynamically bind the process parameters and / or quality inspection data of the current production stage with the identifier of the current stage;

[0049] Step S5, Cross-chain data storage and parsing: Store the identifiers of each production link and their associated key data summaries in the blockchain consortium blockchain network; when traceability is required, retrieve the associated data of the entire process from the blockchain consortium blockchain network by parsing the identifiers;

[0050] The data stored in the blockchain consortium blockchain network consists of hash values ​​of key events or data.

[0051] The blockchain consortium network runs smart contracts for verifying identity changes and storing quality data.

[0052] In a more specific example, step S4 specifically includes: locally aggregating and cleaning the process data collected by the sensors through edge computing nodes deployed on the production line side, and binding the cleaned data with the current identifier;

[0053] Write the report hash value to the blockchain and associate it with the current stage identifier.

[0054] In this step, the homogenizer reads the current identifier, obtains the viscosity-temperature correlation curve of the previous process, dynamically optimizes the homogenization pressure based on historical data: P=f(η,T), avoids demulsification, detects the particle size distribution D[3,2] using a near-infrared spectrometer, and generates an inspection report with a timestamp.

[0055] In a more specific example, the edge computing node is pre-loaded with a process knowledge graph for storing emulsifier phase change rules;

[0056] In step S3, the generation of derived identifiers also refers to the process knowledge graph.

[0057] This invention also provides an emulsifier end-to-end quality traceability and identification system for implementing the above method, the system comprising:

[0058] The IoT sensing layer includes an anti-corrosion marking carrier for attaching to raw material containers and a multi-mode sensor array deployed on production equipment for sensing the phase state of matter.

[0059] The identification management layer is connected to the IoT sensing layer. The identification management layer includes an OID parsing engine and a derived identifier generator. The OID parsing engine is used to map physical identifiers to virtual objects, and the derived identifier generator is used to generate derived identifiers in response to object phase transformation events.

[0060] The edge computing engine, connected to the IoT sensing layer and the identification management layer, is used to process sensor data locally and bind process parameters to identification.

[0061] The blockchain network layer, connected to the identifier management layer, is used to store summary information of identifiers and their associated data at each stage, and provides cross-chain identifier resolution services; the blockchain network layer includes a smart contract cluster and a cross-chain bridge, the cross-chain bridge supporting data interoperability with external enterprise resource planning (ERP) systems.

[0062] The application service layer, connected to the blockchain network layer, is used to provide traceability data query and visualization services; the application service layer includes a quality anomaly tracing module, which locates the source of process deviations based on a decision tree model.

[0063] In this embodiment, the system is applicable to the production line of emulsifiers for daily chemical products, enabling full-chain traceability from palmitic acid suppliers, pre-emulsification workshops, homogenization lines, and filling terminals;

[0064] This system also includes:

[0065] The phase-driven identifier derivation mechanism solves the core logic of traceability breaks caused by state transformation, ensuring data continuity;

[0066] The process-sensitive parameter binding module (edge ​​computing engine subunit) dynamically associates key operations such as HLB adjustment and pressure setting with identifiers.

[0067] A multimodal sensor fusion interface enables precise mapping from physical phase transition events to digital identifier changes;

[0068] Chain-based smart contracts, as a core component of the blockchain network layer, ensure the immutability of cross-enterprise data.

[0069] This system may also include:

[0070] The knowledge graph-assisted decision-making unit trains a phase transition prediction model (LSTM network) using historical data, triggering label preparation 10 minutes in advance to reduce production line delays.

[0071] The zero-knowledge proof verification module allows suppliers to submit encrypted raw material formulas (such as surfactant ratios) and verify compliance without decryption, thus enhancing the protection of trade secrets.

[0072] The AR visualization terminal uses HoloLens to scan finished barrels and instantly overlay full-chain process animations, improving troubleshooting efficiency by 65%.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for full-process quality traceability and identification analysis of emulsifiers, characterized in that, Includes the following steps: Step S1, Raw material identification coding: Generate and attach a carrier identification that is resistant to physical corrosion to the raw material container, wherein the carrier identification stores basic information about the raw material; Step S2, Phase transition event perception: Real-time acquisition of phase state data during the production process through a multi-mode sensor array deployed on the production equipment; Step S3, Derivative Identifier Generation: When the phase state data meets the preset phase transformation conditions, a derived identifier associated with the identifier of the previous step is automatically generated. Step S4, Process Data Chain Binding: Dynamically bind the process parameters and / or quality inspection data of the current production stage with the identifier of the current stage; Step S5, Cross-chain data storage and parsing: The identifiers of each production link and their associated key data summaries are stored in the blockchain consortium chain network; when traceability is required, the associated data of the entire process is obtained from the blockchain consortium chain network by parsing the identifiers.

2. The emulsifier whole-process quality traceability identification and resolution method according to claim 1, characterized in that, In step S1, the carrier identification for resisting physical corrosion is a direct component identification (DPM code) generated by laser etching technology. The basic information includes at least the raw material batch, the hydrophilic-lipophilic balance (HLB) benchmark value, and the supplier's digital certificate.

3. The emulsifier whole-process quality traceability identification and resolution method according to claim 1, characterized in that, In step S2, the multimode sensor array includes a viscosity sensor, a temperature sensor, and a pressure sensor; The phase transition condition is that the material viscosity changes from below a first threshold to above a second threshold.

4. The emulsifier whole-process quality traceability identification and resolution method according to claim 1, characterized in that, Step S4 specifically includes: using edge computing nodes deployed on the production line side to locally aggregate and clean the process data collected by the sensors, and binding the cleaned data with the current identifier.

5. The emulsifier whole-process quality traceability identification and resolution method according to claim 4, characterized in that, The edge computing nodes are pre-loaded with process knowledge graphs to store emulsifier phase change rules.

6. The method for full-process quality traceability and identification resolution of emulsifiers according to claim 1, characterized in that, In step S5, the data stored in the blockchain consortium blockchain network is the hash value of key events or data; The blockchain consortium network runs smart contracts for verifying identity changes and storing quality data.

7. An emulsifier end-to-end quality traceability and identification system, used to implement the method according to any one of claims 1-6, characterized in that, The system includes: The IoT sensing layer includes an anti-corrosion marking carrier for attaching to raw material containers and a multi-mode sensor array deployed on production equipment for sensing the phase state of matter. The identification management layer is connected to the IoT sensing layer. The identification management layer includes an OID parsing engine and a derived identifier generator. The OID parsing engine is used to map physical identifiers to virtual objects, and the derived identifier generator is used to generate derived identifiers in response to object phase transformation events. The edge computing engine, connected to the IoT sensing layer and the identification management layer, is used to process sensor data locally and bind process parameters to identification. The blockchain network layer, connected to the identifier management layer, is used to store summary information of the identifiers and their associated data at each stage, and to provide cross-chain identifier resolution services. The application service layer, connected to the blockchain network layer, is used to provide traceability data query and visualization services.

8. The emulsifier end-to-end quality traceability and identification system according to claim 7, characterized in that, The blockchain network layer includes a smart contract cluster and a cross-chain bridge, which supports data interoperability with external enterprise resource planning (ERP) systems.

9. The emulsifier end-to-end quality traceability and identification system according to claim 7, characterized in that, The application service layer includes a quality anomaly tracing module, which locates the source of process deviations based on a decision tree model.