CN-121998515-A - Low-freezing-point oleic acid production quality tracing and early warning system under industrial Internet architecture

CN121998515ACN 121998515 ACN121998515 ACN 121998515ACN-121998515-A

Abstract

The invention discloses a low-freezing-point oleic acid production quality tracing and early warning system under an industrial Internet architecture, which relates to the technical field of oil chemical production quality control and has the technical key points that global unique batch identification codes conforming to an industrial Internet identification analysis system are distributed for each independent production batch, and the identification codes are irreversibly and strongly bound with production source data of a whole process, influence weights of all nodes on a finished product freezing point and actual measurement data of a finished product core quality index through a hash encryption algorithm, so that the tracing data is ensured to be non-tamperable; meanwhile, batch identification codes are used as cores, traceable indexes with freeze point influence factors as associated dimensions are established, production data and finished product quality indexes are deeply associated, time-series storage and simple inquiry of the production data are not limited, when finished product quality abnormality occurs, specific process nodes and single-group production data which cause the abnormality can be directly positioned based on traceable links, and the investigation and disposal cycle of quality problems is shortened.

Inventors

WU ZHONGJIANG
WU ZHONGGAN
RAO YUHUA
JIA HAIJUN
QIN QUANFU

Assignees

江西润达新材料有限公司

Dates

Publication Date: 20260508
Application Date: 20260226

Claims (10)

1. Low freezing point oleic acid production quality traceback and early warning system under industry internet framework, its characterized in that includes: The dynamic acquisition module is used for deploying the edge acquisition terminals at all process nodes of the low-freezing-point oleic acid production whole process through an industrial Internet architecture, constructing an influence weight matrix of all the processes of the whole production process on the product core quality index in advance, setting a dynamic differential acquisition rule for the production source data of all the process nodes according to the influence weight matrix, and synchronously acquiring the multi-source heterogeneous production source data of the low-freezing-point oleic acid production whole process; The traceable link construction module is used for distributing globally unique batch identification codes to each independent production batch of low-freezing-point oleic acid, carrying out irreversible strong binding on the batch identification codes and production source data of all process nodes of the whole batch production process and influence weights of all processes on the product core quality index, establishing a whole process traceable index which takes the batch identification codes as a retrieval main body and the product core quality index influence factors as relevant dimensions, and generating traceable link information; the coupling analysis module is used for carrying out coupling analysis on quality fluctuation of each process node according to production source data corresponding to the full-process traceable link information by combining with a pre-constructed low-freezing-point oleic acid production full-process quality risk conduction coefficient matrix, and calculating to obtain a product core quality index pre-judging value and a full-process quality evaluating value; The early warning module is used for calculating a quality risk discrimination value according to the product core quality index pre-discrimination value and the full-flow quality assessment value and combining the quality fluctuation deviation degree of each process node; The management and control iteration module is used for judging whether the quality risk discrimination value exceeds a preset hierarchical management and control threshold value interval, judging a quality abnormal state if the quality risk discrimination value exceeds the preset hierarchical management and control threshold value interval, triggering early warning response of a corresponding level and production procedure management and control action according to the risk conduction level of an abnormal procedure node, otherwise, judging a quality qualified state, and storing the whole-flow production data into a core production database for iterative optimization of a low-freezing-point oleic acid production process.
2. The system for tracing and early warning low freezing point oleic acid production quality under an industrial internet architecture according to claim 1, wherein the dynamic acquisition module comprises: The raw material data acquisition unit is used for acquiring source information, batch information, core component detection data, basic quality index data and warehousing and storage environment data of raw materials used for low-freezing-point oleic acid production, and generating raw material attribute and component data; The key process data acquisition unit is used for acquiring real-time operation parameters of each key process which directly influence the core quality index of the product in the whole process of low-freezing-point oleic acid production and generating whole process production process parameter data; the equipment state acquisition unit is used for acquiring the operation state parameters, fault alarm information, maintenance records and operation precision data of the production equipment corresponding to the key working procedures and generating key equipment operation state data; The environment data acquisition unit is used for acquiring real-time environment parameters of a low-freezing-point oleic acid production core process workshop and a finished product storage area and generating full-scene environment monitoring data; The quality detection acquisition unit is used for acquiring central control semi-finished product detection data and finished product full quality index detection data in the low freezing point oleic acid production process, and generating process and finished product quality detection data; the logistics data acquisition unit is used for acquiring the warehouse-out information, warehouse transportation environment data, delivery information and terminal feedback data of the low-freezing-point oleic acid finished product to generate warehouse logistics data; The dynamic acquisition management and control unit is used for constructing an influence weight matrix of each process on the product core quality index based on the production history big data, setting an initial acquisition period and acquisition precision for each process node according to the influence weight matrix, and simultaneously monitoring the fluctuation amplitude of the process parameters of each process node in real time, and improving the acquisition frequency and the acquisition precision of the corresponding production source data of each process node when the process parameter fluctuation of one process node exceeds a preset stability threshold.
3. The low freezing point oleic acid production quality tracing and early warning system under the industrial internet architecture according to claim 2, wherein the dynamic acquisition module further comprises a full-link data standardization processing unit; the full-link data standardization processing unit is used for respectively carrying out format unification processing, outlier rejection processing and missing value completion processing on the collected full-class production source data; According to the process node and material circulation time sequence of the whole process of low-freezing-point oleic acid production, performing process time stamp and material batch double-reference alignment treatment on all production source data, and ensuring that all production source data in the same process node are in a uniform time reference and a material batch reference; And classifying, encrypting and storing various production source data subjected to standardized processing according to the batch identification codes and the process nodes, and providing a standardized data source for the whole-flow traceable link construction and quality risk coupling analysis.
4. The system for tracing and early warning low-freezing-point oleic acid production quality under an industrial internet architecture according to claim 1, wherein the tracing link construction module specifically comprises: The method comprises the steps of distributing global unique batch identification codes conforming to an industrial Internet identification analysis system for each independent production batch of low-freezing-point oleic acid, and carrying out irreversible encryption binding on the batch identification codes, raw material batch information of corresponding batches, production source data of all nodes in a full process, influence weight of all nodes on a product core quality index and actual measurement data of a finished product core quality index through an encryption algorithm; Taking the batch identification code as a core, carrying out time sequence association on all production source data of corresponding batches according to the sequence of production processes and process nodes, and establishing a full process traceability index which takes the batch identification code as a retrieval main body and takes a product core quality index influence factor as an associated dimension; And generating traceable link information covering the whole life cycle of the product based on the whole process traceable index, wherein the traceable link information supports forward whole process traceable and reverse root positioning, the forward traceable can completely display the whole life cycle information of the corresponding batch of products, and the reverse root positioning can be directly positioned to a specific process node and single-group production source data which cause quality abnormality based on the abnormal result of the core quality index of the finished product.
5. The system for tracing and early warning low-freezing-point oleic acid production quality under the industrial internet architecture according to claim 4, wherein the tracing link construction module further comprises a multi-scene batch tracing inquiry unit; The multi-scene batch traceability query unit is used for supporting hierarchical query services of different authorities and opening traceability data query authorities of corresponding authorities according to query requirements of different authorities, and can generate standardized traceability reports and product quality compliance certificates meeting the corresponding requirements according to the requirements of the query authorities.
6. The system for tracing and early warning low-freezing-point oleic acid production quality under an industrial internet architecture according to claim 1, wherein the coupling analysis module specifically comprises: the method comprises the steps of extracting standardized production source data of all nodes of a corresponding production batch in a full process according to full process traceability link information; The method comprises the steps of producing a full-process quality risk conduction coefficient matrix based on low-freezing-point oleic acid which is constructed through production history big data in advance, wherein the quality risk conduction coefficient matrix comprises quality fluctuation conduction coefficients among process nodes and direct influence coefficients of the process nodes on product core quality indexes; Calculating the conduction influence of process parameter fluctuation of each process node on the subsequent process and the comprehensive influence on the final finished product core quality index through a coupling analysis algorithm, and generating a product core quality index pre-judging value of the corresponding production batch; Meanwhile, calculating a multi-dimensional quality evaluation index of the corresponding production batch according to the production source data of each node in the whole process; and combining the product core quality index pre-judging value with the multi-dimensional quality evaluation index, and obtaining the full-flow quality evaluation value of the corresponding production batch through weighted fusion calculation.
7. The low freezing point oleic acid production quality tracing and early warning system under the industrial internet architecture according to claim 6, wherein the coupling analysis module further comprises a quality anomaly root cause intelligent identification unit; The quality anomaly root cause intelligent identification unit is used for pre-constructing a low-freezing-point oleic acid quality anomaly root cause knowledge base which comprises anomaly procedures, anomaly parameters, root cause analysis logic and optimization solutions corresponding to different quality anomaly manifestations; Comparing the multi-dimensional quality evaluation index of the corresponding production batch with a preset standard index interval, identifying an abnormal evaluation index exceeding the standard interval, and positioning the corresponding abnormal process node and production source data; And analyzing the influence path and influence degree of the quality fluctuation of the abnormal process nodes on the product core quality index by combining the quality risk conduction coefficient matrix, matching a quality abnormal root cause knowledge base, identifying the core root cause causing quality abnormality, and synchronously generating a process optimization solution.
8. The low freezing point oleic acid production quality tracing and early warning system under the industrial internet architecture according to claim 1, wherein the early warning module specifically comprises: the method comprises the steps of acquiring a process parameter preset standard interval of each node in the whole process of low-freezing-point oleic acid production, and calculating quality fluctuation deviation degree of real-time production source data of each process node and the standard interval; Calculating a deviation risk value of the core quality index by combining the product core quality index prejudgement value with the national quality standard of the low freezing point oleic acid product and the enterprise internal control quality standard; Calculating to obtain a quality risk discrimination value of a corresponding production batch by combining the full-flow quality evaluation value, the quality fluctuation deviation degree of each process node, the core quality index deviation risk value and the influence weight of each process node on the core quality index of the product; meanwhile, the method can update the product core quality index pre-judging value and the quality risk judging value in real time on the basis of the node and the production source data of the pre-working procedure at any working procedure node in the production process.
9. The low freezing point oleic acid production quality tracing and early warning system under the industrial internet architecture according to claim 8, wherein the early warning module further comprises a control system self-adaptive iteration unit; The control system self-adaptive iteration unit is used for acquiring production equipment state data, raw material component change data, production environment change data, production process adjustment data and product quality standard update data of low-freezing-point oleic acid in real time; Based on the obtained real-time data, the self-adaptive iterative updating is carried out on the whole process quality risk conduction coefficient matrix, the influence weight of each process node on the product core quality index and the hierarchical control threshold value interval through a machine learning algorithm.
10. The low freezing point oleic acid production quality tracing and early warning system under the industrial internet architecture of claim 1, wherein the control iteration module specifically comprises: the method comprises the steps that a grading control threshold interval containing a multi-level threshold is preset, and the grading control threshold interval is set based on low-freezing-point oleic acid national product quality standards, enterprise internal control quality standards and production history big data; Comparing the quality risk discrimination value obtained by real-time calculation with a grading management and control threshold interval, judging the quality abnormal grade according to the threshold interval where the quality risk discrimination value is located, and triggering management and control actions of the corresponding grade, wherein the management and control actions comprise early warning prompt, process parameter adjustment, high risk process suspension and whole-flow emergency stop; And storing the whole-flow production source data, the traceable link information and the quality analysis result of the corresponding batch into a core production database aiming at the production batch with qualified quality, and iteratively optimizing a quality risk conduction coefficient matrix, a process parameter standard interval and a hierarchical control threshold interval through a machine learning algorithm.

Description

Low-freezing-point oleic acid production quality tracing and early warning system under industrial Internet architecture Technical Field The invention relates to the technical field of oil chemical production quality control, in particular to a low freezing point oleic acid production quality tracing and early warning system under an industrial Internet architecture. Background The low freezing point oleic acid is used as a core raw material in the fields of high-end lubricating oil base oil, food emulsifying agent, cosmetic active raw material, medical intermediate and the like, the core quality index of the low freezing point oleic acid is the freezing point, the high-end application of the industry generally requires the freezing point to be less than or equal to 5 ℃, and the process stability and the control precision of the production process are extremely high; however, in the implementation process of the technical scheme, at least the following technical problems are found: Firstly, a final freeze point detection of a finished product is taken as a core control node, the quality fluctuation conduction effect among all working procedures is not quantized, a correlation prediction model of the whole process technological parameters and the freeze point index of the finished product is not established, only the parameter out-of-limit alarm of a single working procedure can be realized, the comprehensive influence of the technological fluctuation on the final finished product freeze point cannot be prejudged in the production process, namely, in actual production, the problem of unqualified batch can be found only after the finished product is produced in the whole process and the freeze point detection result is obtained, at the moment, the raw materials, energy sources, manpower and equipment productivity of the whole batch are input, the reworking and scrapping treatment of the unqualified product can cause great waste of production cost, meanwhile, the production delivery period is delayed, and the production requirements of high stability and high qualification rate of high-end low freeze point oleic acid cannot be adapted; The traceability system in the prior art can only realize simple storage and post-inquiring of batch production data, does not deeply bind the influence weights of the production data and the frozen point of a finished product, and is not disjointed with quality control requirements, when the frozen point of the finished product exceeds standard, abnormal core procedures and key parameters cannot be directly positioned through the traceability system, manual investigation is needed by technicians step by step and parameter by parameter, the quality problem treatment efficiency is extremely low because the positioning period is as long as several hours to several days, meanwhile, the conventional system cannot iteratively optimize the process standard through the historical production data of qualified batches, can not perfect the control rule through the quality abnormal data, can only adjust the process through manual repeated experiments, has long optimization period and high trial-error cost, and cannot realize self-optimization of the production process and continuous improvement of the product quality. Disclosure of Invention (One) solving the technical problems Aiming at the defects of the prior art, the invention provides a low-freezing-point oleic acid production quality tracing and early warning system under an industrial Internet architecture, and solves the core technical problems of post control, no quality association of tracing, stiff acquisition mode, no pre-warning capability and no cyclic iteration capability in the prior art. (II) technical scheme In order to achieve the above purpose, the invention is realized by the following technical scheme: low freezing point oleic acid production quality tracing and early warning system under industrial internet architecture, the system comprises the following steps: The dynamic acquisition module is used for deploying the edge acquisition terminals at all process nodes of the low-freezing-point oleic acid production whole process through an industrial Internet architecture, constructing an influence weight matrix of all the processes of the whole production process on the product core quality index in advance, setting a dynamic differential acquisition rule for the production source data of all the process nodes according to the influence weight matrix, and synchronously acquiring the multi-source heterogeneous production source data of the low-freezing-point oleic acid production whole process; The traceable link construction module is used for distributing globally unique batch identification codes to each independent production batch of low-freezing-point oleic acid, carrying out irreversible strong binding on the batch identification codes and production source data of all process nodes of the whole batch production