FPC production information tracing method and system based on product identification codes

Abstract

The invention relates to the technical field of Internet of Things, and discloses an FPC production information tracing method and system based on a product identification code, and the method comprises the steps: determining a tracing demand of an FPC product, defining a coding rule of the FPC product, coding the FPC product through the coding rule, and obtaining an FPC product code; a production detection device of the FPC product is defined, a tracing integrity coefficient of the production detection device to the FPC product is calculated, and a tracing block chain network of the production detection device is constructed; associating the production flow data with the FPC product codes to obtain a flow data-code set, and establishing a product tracing library of the FPC products; obtaining tracing information of a target FPC product corresponding to the tracing instruction, and analyzing a tracing abnormal state of the target FPC product by using a trained tracing abnormal analysis model; and positioning an abnormal node of the target FPC product, analyzing a production optimization parameter of the abnormal node, and executing information tracing optimization of the FPC product based on the production optimization parameter. According to the invention, the tracing effect of the FPC production information can be improved.

Description

Technical Field

[0001] The invention relates to a method and system for tracing FPC production information based on a product identification code, and belongs to the technical field of Internet of Things. Background Art

[0002] FPC production information traceability refers to recording, tracking and analyzing all relevant information throughout the entire life cycle of FPC from raw material procurement, production process, quality control, warehousing logistics to final product delivery. The purpose of this traceability is to ensure product quality, improve production efficiency, quickly locate and solve problems in the production process, and meet customer and regulatory requirements for product traceability.

[0003] Traditional FPC production information traceability methods usually rely on manual records and paper document management. By setting checkpoints on the production line, workers manually record the production data and quality information of each product, and then summarize this information in a central database. This method relies too much on manual labor, resulting in low efficiency and error-prone data, which leads to incomplete traceability. Summary of the invention

[0004] The present invention provides a method and system for tracing FPC production information based on a product identification code, the main purpose of which is to improve the tracing effect of the FPC production information.

[0005] To achieve the above object, the present invention provides a FPC production information tracing method based on a product identification code, comprising:

[0006] Obtaining a production flow chart of an FPC product, determining traceability requirements of the FPC product according to the production flow chart, defining a coding rule of the FPC product based on the traceability requirements, and encoding the FPC product using the coding rule to obtain an FPC product code;

[0007] Based on the traceability requirements, define the production and testing equipment of the FPC product, calculate the traceability completeness coefficient of the production and testing equipment for the FPC product, and when the traceability completeness coefficient meets the preset traceability completeness threshold, build a traceability blockchain network for the production and testing equipment;

[0008] Based on the traceability blockchain network, the production process data of the FPC product is collected, the production process data and the FPC product code are associated to obtain a process data-code set, and a product traceability library of the FPC product is established through the process data-code set;

[0009] Obtaining a user's traceability instruction, obtaining traceability information of a target FPC product corresponding to the traceability instruction based on the traceability instruction and the FPC product code, and analyzing the traceability abnormality state of the target FPC product using a trained traceability abnormality analysis model according to the traceability information;

[0010] Based on the traceability abnormal state and the FPC product code, the abnormal node of the target FPC product is located, and the production optimization parameters of the abnormal node are analyzed, and the information traceability optimization of the FPC product is performed based on the production optimization parameters.

[0011] Optionally, determining the traceability requirements of the FPC product according to the production flow chart includes:

[0012] Analyze the actual production responsiveness of the production flow chart;

[0013] When the actual production reaction degree meets the preset actual production reaction threshold, identifying the key process of the production flow chart;

[0014] Identify the traceability points of the key processes;

[0015] Calculate the traceability risk of the traceability point;

[0016] According to the traceability risk, the traceability requirements of the traceability points are defined.

[0017] Optionally, the calculating the traceability risk of the traceability point includes:

[0018] Calculate the risk probability and risk non-detection probability of the traceability point;

[0019] Analyze the impact of risk product quality and risk product cost at the traceability point;

[0020] Based on the risk probability, the risk non-detection probability, the risk product quality impact and the risk product cost impact, the traceability risk of the traceability point is calculated using the following formula:

[0021]

[0022] Among them, R i represents the traceability risk of the ith traceability point, α represents the risk adjustment coefficient, and P i represents the risk probability of the ith traceability point, D i represents the probability of risk not being detected at the i-th traceability point, I i represents the risk product quality impact of the i-th traceability point, k represents the time impact coefficient, T i represents the time from the occurrence of anomaly at the i-th tracing point to the detection of anomaly, T0 represents the detection time of anomaly at the i-th tracing point, Ci represents the cost impact of the risk product at the ith traceability point, C max It represents the cost impact of the risk product with the largest traceability point, and β represents the cost impact coefficient.

[0023] Optionally, defining the coding rules of the FPC product based on the traceability requirement includes:

[0024] Determine the coding elements of the FPC product according to the traceability requirements;

[0025] Based on the coding element, establishing a coding module of the FPC product;

[0026] Defining the encoding order of the encoding module;

[0027] Determining the expansion space of the coding module through the coding sequence;

[0028] Based on the coding module, the coding sequence and the expansion space, a coding rule for the FPC product is established.

[0029] Optionally, the calculating of the traceability integrity coefficient of the production inspection equipment for the FPC product includes:

[0030] Define the complete traceability indicators of the production testing equipment for the FPC product;

[0031] Collecting equipment performance data and historical production data of the production and testing equipment;

[0032] Based on the complete traceability index, a traceability multi-dimensional model of the FPC product is constructed;

[0033] Based on the equipment performance data and historical production data, analyzing the traceability completeness indicator score of the traceability completeness indicator using the traceability multidimensional model;

[0034] The traceability completeness coefficient of the production inspection equipment for the FPC product is calculated through the traceability completeness index score.

[0035] Optionally, the step of calculating the traceability completeness coefficient of the production testing equipment for the FPC product by scoring the traceability completeness index includes:

[0036] Define the traceability completeness indicator weight corresponding to the traceability completeness indicator of the production testing equipment;

[0037] Calculate the correction factor of the traceability completeness indicator;

[0038] Based on the traceability completeness indicator weight, the traceability completeness indicator score and the correction factor, the traceability completeness coefficient of the production testing equipment for the FPC product is calculated using the following formula:

[0039]

[0040] Among them, TIC represents the traceability integrity coefficient of the production inspection equipment for the FPC product, S c represents the traceability completeness index score of the cth traceability completeness index of the production inspection equipment, ω c A represents the traceability completeness indicator weight of the cth traceability completeness indicator of the production inspection equipment, c It represents the correction factor of the cth traceability complete index of the production inspection equipment, m represents the number of traceability complete indexes, and c represents the cth traceability complete index of the production inspection equipment.

[0041] Optionally, establishing a product traceability library of the FPC product through the process data-code set includes:

[0042] Define the traceability library architecture of the FPC products;

[0043] Based on the traceability library architecture, a product database of the FPC product is established;

[0044] Standardizing the process data-code set to obtain a standard data-code set;

[0045] Establishing a data upload mechanism for the product database;

[0046] According to the data uploading mechanism, the standard data-code set is uploaded to the product database to obtain an uploaded data-code set;

[0047] Calculating a data integrity coefficient of the uploaded data-encoded set;

[0048] When the data integrity coefficient meets a preset data integrity threshold, a data traceability interface of the product database is established;

[0049] A product traceability library for the FPC product is established based on the data traceability interface, the uploaded data-coding set and the product database.

[0050] Optionally, analyzing the traceability abnormality state of the target FPC product using a trained traceability abnormality analysis model according to the traceability information includes:

[0051] Preprocessing the traceability information to obtain processed traceability information;

[0052] Extracting traceability information features of the processing traceability information;

[0053] Based on the traceability information features, identifying the feature anomaly probability of the target FPC product using the traceability anomaly analysis model;

[0054] Based on the feature abnormality probability, marking the abnormal feature of the traceability information feature;

[0055] The traceability abnormal state of the target FPC product is determined based on the abnormal characteristics.

[0056] Optionally, analyzing the production optimization parameters of the abnormal node includes:

[0057] Defining an optimization target for the abnormal node;

[0058] Identifying controllable parameters of the abnormal node;

[0059] Calculating parameter sensitivity coefficients of the controllable parameters;

[0060] Analyzing the parameter combination of the abnormal node according to the optimization target and the parameter sensitivity coefficient;

[0061] Based on the parameter sensitivity coefficient, the abnormal optimization coefficient of the parameter combination is calculated using the following formula:

[0062]

[0063] Among them, AOC represents the abnormal optimization coefficient of parameter combination, P r represents the actual value of the rth controllable parameter in the parameter combination, P r,out represents the optimal value of the rth controllable parameter in the parameter combination, W r represents the weight of the rth controllable parameter in the parameter combination, F r represents the parameter sensitivity coefficient of the rth controllable parameter in the parameter combination, and H represents the number of controllable parameters;

[0064] When the abnormal optimization coefficient meets the preset abnormal optimization threshold, the parameter combination is used as the production optimization parameter of the abnormal node.

[0065] In order to solve the above problems, the present invention also provides an FPC production information tracing system based on a product identification code, the system comprising:

[0066] A product coding construction module is used to obtain a production flow chart of an FPC product, determine the traceability requirements of the FPC product according to the production flow chart, define a coding rule for the FPC product based on the traceability requirements, and encode the FPC product using the coding rule to obtain an FPC product code;

[0067] A blockchain network construction module is used to define the production and testing equipment of the FPC product based on the traceability requirements, calculate the traceability completeness coefficient of the production and testing equipment for the FPC product, and build a traceability blockchain network for the production and testing equipment when the traceability completeness coefficient meets a preset traceability completeness threshold;

[0068] A product traceability library establishment module, which is used to collect the production process data of the FPC product based on the traceability blockchain network, associate the production process data with the FPC product code, obtain a process data-code set, and establish a product traceability library of the FPC product through the process data-code set;

[0069] A traceability abnormality status analysis module is used to obtain a user's traceability instruction, obtain traceability information of a target FPC product corresponding to the traceability instruction based on the traceability instruction and the FPC product code, and analyze the traceability abnormality status of the target FPC product using a trained traceability abnormality analysis model according to the traceability information;

[0070] The information tracing optimization module is used to locate the abnormal node of the target FPC product based on the traceability abnormal state and the FPC product code, analyze the production optimization parameters of the abnormal node, and perform information tracing optimization of the FPC product based on the production optimization parameters.

[0071] Compared with the problems described in the background technology, firstly, through precise production flow charts and defined traceability requirements, we ensure the rationality and practicality of the FPC product coding rules, so that each product can have a unique and detailed identification code, which greatly improves the traceability of the product. Secondly, calculating the traceability integrity coefficient of the production and testing equipment and building a traceability blockchain network not only ensures the immutability and transparency of the data, but also improves the trust and data security of the traceability system. In addition, by collecting and associating production process data with FPC product codes, we have established a process data-coding set, and then built a comprehensive product traceability library, which makes it possible to quickly and accurately query the history and current status of the product at any stage. The previous state significantly improves the problem location and response speed. By using the trained traceability anomaly analysis model, we can timely discover the traceability anomaly state of the target FPC product, and by locating the abnormal node, analyzing the production optimization parameters, effectively guide the production adjustment, thereby reducing the defective rate and improving product quality and production efficiency. Finally, the information traceability optimization based on the production optimization parameters not only optimizes the production process, but also enhances the quality control ability of the enterprise, improves customer satisfaction and enterprise competitiveness. Overall, this method provides an efficient, reliable and comprehensive product traceability solution for the FPC industry, which plays an important role in ensuring product quality, improving enterprise management and enhancing market competitiveness. Therefore, the present invention can improve the stability of the network. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A schematic diagram of a process for tracing FPC production information based on a product identification code provided by an embodiment of the present invention;

[0073] Figure 2 A schematic diagram of a module for implementing the FPC production information tracing method based on a product identification code provided in an embodiment of the present invention.

[0074] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0075] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0076] The embodiment of the present application provides a method for tracing FPC production information based on a product identification code. The execution subject of the method for tracing FPC production information based on a product identification code includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for tracing FPC production information based on a product identification code can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0077] Embodiment 1:

[0078] Reference Figure 1 FIG. 1 is a flow chart of a method for tracing FPC production information based on a product identification code according to an embodiment of the present invention. In this embodiment, the method for tracing FPC production information based on a product identification code includes:

[0079] S1. Obtain a production flow chart of an FPC product, determine traceability requirements of the FPC product according to the production flow chart, define a coding rule of the FPC product based on the traceability requirements, encode the FPC product using the coding rule, and obtain an FPC product code.

[0080] It should be explained that the FPC product refers to a flexible printed circuit (Flexible Printed Circuit), which is a printed circuit board that can be bent and folded, and the production flow chart refers to a chart of the entire production process of FPC products from raw material preparation to finished product delivery. It shows in detail the various stages, steps, inspection points, decision nodes in the production process, and the flow paths of materials and information.

[0081] The present invention determines the traceability requirements of the FPC products according to the production flow chart, which can ensure that the traceability requirements of the FPC products are comprehensively and accurately defined, and lay a solid foundation for the subsequent traceability system design and implementation.

[0082] In detail, determining the traceability requirements of the FPC product according to the production flow chart includes:

[0083] Analyze the actual production responsiveness of the production flow chart;

[0084] When the actual production reaction degree meets the preset actual production reaction threshold, identifying the key process of the production flow chart;

[0085] Identify the traceability points of the key processes;

[0086] Calculate the traceability risk of the traceability point;

[0087] According to the traceability risk, the traceability requirements of the traceability points are defined.

[0088] Among them, the actual production responsiveness refers to the degree to which the production flow chart accurately reflects the actual production situation. The actual production response threshold refers to a pre-set standard or limit used to determine whether the production flow chart accurately reflects the actual production situation. The key process refers to the process that has a significant impact on product quality, cost, delivery time, etc. in the FPC production process. The traceability point refers to the specific location or step that needs to be recorded and tracked in the key process. The traceability risk refers to the potential risks such as quality problems, production delays, and cost increases caused by failure to correctly track information during the production process. The traceability demand refers to the type and degree of information that needs to be collected, recorded, and reported at each traceability point, determined based on the results of the traceability risk analysis.

[0089] Furthermore, the calculating the traceability risk of the traceability point includes:

[0090] Calculate the risk probability and risk non-detection probability of the traceability point;

[0091] Analyze the impact of risk product quality and risk product cost at the traceability point;

[0092] Based on the risk probability, the risk non-detection probability, the risk product quality impact and the risk product cost impact, the traceability risk of the traceability point is calculated using the following formula:

[0093]

[0094] Among them, R i represents the traceability risk of the ith traceability point, α represents the risk adjustment coefficient, and P irepresents the risk probability of the ith traceability point, D i represents the probability of risk not being detected at the i-th traceability point, I i represents the risk product quality impact of the i-th traceability point, k represents the time impact coefficient, T i represents the time from the occurrence of anomaly at the i-th tracing point to the detection of anomaly, T0 represents the detection time of anomaly at the i-th tracing point, C i represents the cost impact of the risk product at the ith traceability point, C max It represents the cost impact of the risk product with the largest traceability point, and β represents the cost impact coefficient.

[0095] Among them, the risk probability refers to the probability of a certain risk or error occurring at the i-th traceability point, the risk undetected probability refers to the probability that the risk occurring at the i-th traceability point is not detected, the risk product quality impact refers to the potential impact of the risk occurring at the i-th traceability point on the quality of the final product, the risk product cost impact refers to the potential impact of the risk occurring at the i-th traceability point on the quality of the final product, the risk adjustment coefficient refers to the coefficient used to adjust the risk calculation result, the time impact coefficient refers to the coefficient used to adjust the risk change over time, the cost impact coefficient refers to the coefficient used to adjust the weight of the cost impact in the risk calculation, and the abnormal detection time refers to the time from the occurrence of the abnormality at the i-th traceability point to the detection of the abnormality.

[0096] Based on the traceability requirements, the present invention defines the coding rules of the FPC products and can define a set of efficient, flexible and safe FPC product coding rules, thereby improving the efficiency and reliability of production information traceability.

[0097] In detail, based on the traceability requirements, the coding rules of the FPC products are defined, including:

[0098] Determine the coding elements of the FPC product according to the traceability requirements;

[0099] Based on the coding element, establishing a coding module of the FPC product;

[0100] Defining the encoding order of the encoding module;

[0101] Determining the expansion space of the coding module through the coding sequence;

[0102] Based on the coding module, the coding sequence and the expansion space, a coding rule for the FPC product is established.

[0103] Among them, the coding element refers to the basic information unit that constitutes the product identification code, each element represents a specific attribute of the product or a key data point in the production process, such as product type, production date, batch number, etc. The coding module refers to the logical structure that organizes the coding elements into manageable parts, the coding order refers to the arrangement order of the coding modules in the final product identification code, the extended space refers to the additional digits or characters reserved for each coding module in the coding rules, and the coding rules refer to the criteria that define how to combine coding elements into a complete product identification code.

[0104] S2. Based on the traceability requirements, define the production and testing equipment of the FPC product, calculate the traceability integrity coefficient of the production and testing equipment for the FPC product, and when the traceability integrity coefficient meets the preset traceability integrity threshold, build a traceability blockchain network for the production and testing equipment.

[0105] Based on the traceability requirements, the present invention defines the production inspection equipment of the FPC product to ensure that the production inspection equipment can meet the traceability requirements of the FPC product and effectively support the quality control in the production process. The production inspection equipment refers to various instruments used to inspect, measure, test and verify whether the product meets specific quality standards, specifications or performance requirements during the manufacturing process, such as automated optical inspection (AOI) equipment, X-ray inspection equipment, functional testing equipment and other equipment.

[0106] Optionally, the present invention calculates the traceability integrity coefficient of the production inspection equipment to the FPC product to quantify the contribution of the production inspection equipment to the traceability integrity of the FPC product, and performs system optimization accordingly.

[0107] In detail, the calculation of the traceability integrity coefficient of the production inspection equipment for the FPC product includes:

[0108] Define the complete traceability indicators of the production testing equipment for the FPC product;

[0109] Collecting equipment performance data and historical production data of the production and testing equipment;

[0110] Based on the complete traceability index, a traceability multi-dimensional model of the FPC product is constructed;

[0111] Based on the equipment performance data and historical production data, analyzing the traceability completeness indicator score of the traceability completeness indicator using the traceability multidimensional model;

[0112] The traceability completeness coefficient of the production inspection equipment for the FPC product is calculated through the traceability completeness index score.

[0113] Among them, the traceability completeness index refers to an index used to measure the ability of production and testing equipment to provide complete, accurate and timely traceability information during the production process of FPC products, such as data collection rate, data error rate, response time, data storage integrity, system stability and other indicators. The equipment performance data refers to data on the equipment operation status and efficiency directly collected from the production and testing equipment, such as detection speed, detection accuracy, failure rate, maintenance records, operating time and other data. The historical production data refers to all relevant data generated in the production process of FPC products in the past period of time, including product quality data, production efficiency data, equipment performance data and other data. The traceability multidimensional model refers to a comprehensive evaluation framework, which classifies and weights the traceability completeness indicators according to different dimensions to comprehensively evaluate the performance of the traceability system. The traceability completeness index scoring refers to the process of quantitatively scoring each traceability completeness indicator according to the traceability multidimensional model to reflect the performance of the testing equipment in each indicator. The traceability completeness coefficient refers to a comprehensive score, which is calculated based on the traceability completeness index scoring and the weights of each indicator, and is used to quantify the overall contribution of production and testing equipment to the traceability integrity of FPC products.

[0114] Furthermore, the traceability completeness index score is used to calculate the traceability completeness coefficient of the production testing equipment for the FPC product, including:

[0115] Define the traceability completeness indicator weight corresponding to the traceability completeness indicator of the production testing equipment;

[0116] Calculate the correction factor of the traceability completeness indicator;

[0117] Based on the traceability completeness indicator weight, the traceability completeness indicator score and the correction factor, the traceability completeness coefficient of the production testing equipment for the FPC product is calculated using the following formula:

[0118]

[0119] Among them, TIC represents the traceability integrity coefficient of the production inspection equipment for the FPC product, S c represents the traceability completeness index score of the cth traceability completeness index of the production inspection equipment, ω c A represents the traceability completeness indicator weight of the cth traceability completeness indicator of the production inspection equipment, c It represents the correction factor of the cth traceability complete index of the production inspection equipment, m represents the number of traceability complete indexes, and c represents the cth traceability complete index of the production inspection equipment.

[0120] The traceability completeness indicator weight refers to the relative importance value assigned to each traceability completeness indicator, and the correction factor refers to an adjustment coefficient used to adjust the original score of the indicator according to specific production conditions, technical requirements or external factors.

[0121] In the present invention, when the traceability integrity coefficient meets the preset traceability integrity threshold, the traceability blockchain network of the production inspection equipment can be constructed to collect the production data of FPC products to provide a basis for later information traceability. Among them, the traceability integrity threshold refers to the minimum traceability integrity level that the traceability system must achieve in order to meet specific traceability requirements or standards, and the traceability blockchain network refers to a decentralized, transparent, and tamper-proof data recording network constructed using blockchain technology.

[0122] S3. Based on the traceability blockchain network, the production process data of the FPC product is collected, the production process data and the FPC product code are associated to obtain a process data-code set, and a product traceability library of the FPC product is established through the process data-code set.

[0123] It should be explained that the production process data refers to various data generated during the entire FPC product production process, including but not limited to raw material information, process parameters, equipment status, test results, operator information, timestamps, etc. The process data-coding set refers to the data set formed by associating the production process data with the corresponding FPC product code. This set provides a complete production history record for each FPC product, which can be used for traceability and analysis.

[0124] The present invention establishes a product traceability library of the FPC product through the process data-code set, and can establish an efficient, reliable and easy-to-manage FPC product traceability library, thereby achieving comprehensive traceability of the product production history.

[0125] In detail, the product traceability library of the FPC product is established through the process data-code set, including:

[0126] Define the traceability library architecture of the FPC products;

[0127] Based on the traceability library architecture, a product database of the FPC product is established;

[0128] Standardizing the process data-code set to obtain a standard data-code set;

[0129] Establishing a data upload mechanism for the product database;

[0130] According to the data uploading mechanism, the standard data-code set is uploaded to the product database to obtain an uploaded data-code set;

[0131] Calculating a data integrity coefficient of the uploaded data-encoded set;

[0132] When the data integrity coefficient meets a preset data integrity threshold, a data traceability interface of the product database is established;

[0133] A product traceability library for the FPC product is established based on the data traceability interface, the uploaded data-coding set and the product database.

[0134] Among them, the traceability library architecture refers to the technical framework and structure determined when designing the traceability library, including data model, database type, data flow, storage scheme, security measures and access control, etc. The product database refers to the place where FPC product-related data is stored, including production data, test data, material information, employee information, etc. The standard data-code set refers to the combination of process data and corresponding codes after data standardization processing, the data upload mechanism refers to a set of rules for transferring data from the production system to the product database, the uploaded data-code set refers to the standard data-code set successfully uploaded to the product database through the data upload mechanism, the data integrity coefficient refers to a quantitative indicator used to measure the integrity and accuracy of the data in the uploaded data-code set, the data integrity threshold refers to a pre-set data integrity coefficient standard used to determine whether the data is complete enough for traceability, the data traceability interface refers to an interface that allows users to query and retrieve data in the product database, and the product traceability library refers to a complete system that integrates the product database, data upload mechanism, data traceability interface and other related components to achieve comprehensive traceability of FPC products.

[0135] Optionally, the data upload mechanism for establishing the product database may be constructed through a suitable transmission protocol, such as HTTP / HTTPS, FTP / SFTP, MQTT, etc.

[0136] S4. Obtain the user's traceability instruction, obtain the traceability information of the target FPC product corresponding to the traceability instruction based on the traceability instruction and the FPC product code, and analyze the traceability abnormality status of the target FPC product using the trained traceability abnormality analysis model according to the traceability information.

[0137] It should be explained that the traceability instruction refers to a specific instruction issued by the user to query the production history, status or location of a specific FPC product. These instructions usually contain a series of parameters to instruct the traceability system on how to retrieve and return relevant information. For example, the traceability instruction may include product code, query date range, type of information required (such as raw material source, production batch, test record, etc.). The traceability information refers to the data set of historical records and current status related to the FPC product corresponding to the traceability instruction.

[0138] According to the traceability information, the present invention uses a trained traceability anomaly analysis model to analyze the traceability anomaly status of the target FPC product, which can effectively analyze the traceability anomaly status of the target FPC product and take timely measures to ensure product quality and the stability of the production process.

[0139] In detail, the method of analyzing the traceability abnormality state of the target FPC product using a trained traceability abnormality analysis model according to the traceability information includes:

[0140] Preprocessing the traceability information to obtain processed traceability information;

[0141] Extracting traceability information features of the processing traceability information;

[0142] Based on the traceability information features, identifying the feature anomaly probability of the target FPC product using the traceability anomaly analysis model;

[0143] Based on the feature abnormality probability, marking the abnormal feature of the traceability information feature;

[0144] The traceability abnormal state of the target FPC product is determined based on the abnormal characteristics.

[0145] Among them, the processed traceability information refers to the information after a series of cleaning, conversion and formatting operations are performed on the original traceability data. The traceability information features refer to the representative data points or attributes extracted from the processed traceability information. The feature abnormality probability refers to the probability value of each feature showing abnormal behavior calculated by the traceability abnormality analysis model. The abnormal features refer to those features identified by the model as having an abnormal probability higher than the threshold. The traceability abnormal state refers to the judgment made on the overall state of the target FPC product based on the comprehensive analysis results of the abnormal features. The traceability abnormality analysis model refers to a model for identifying and evaluating abnormal situations in product production or supply chain processes.

[0146] S5. Based on the traceability abnormal state and the FPC product code, locate the abnormal node of the target FPC product, analyze the production optimization parameters of the abnormal node, and perform information traceability optimization of the FPC product based on the production optimization parameters.

[0147] The present invention locates the abnormal nodes of the target FPC product based on the traceability abnormal state and the FPC product code, which can effectively locate the abnormal nodes of the target FPC product and provide a basis for subsequent corrective and preventive measures. The abnormal node refers to a specific link in the product production process where the product or process deviates from the normal operating range due to some reason, thereby possibly affecting product quality or causing process interruption.

[0148] The present invention analyzes the production optimization parameters of the abnormal nodes, can systematically analyze the production optimization parameters of the abnormal nodes, and implement improvement measures to improve production efficiency and quality.

[0149] In detail, the analyzing the production optimization parameters of the abnormal node includes:

[0150] Defining an optimization target for the abnormal node;

[0151] Identifying controllable parameters of the abnormal node;

[0152] Calculating parameter sensitivity coefficients of the controllable parameters;

[0153] Analyzing the parameter combination of the abnormal node according to the optimization target and the parameter sensitivity coefficient;

[0154] Based on the parameter sensitivity coefficient, the abnormal optimization coefficient of the parameter combination is calculated using the following formula:

[0155]

[0156] Among them, AOC represents the abnormal optimization coefficient of parameter combination, P r represents the actual value of the rth controllable parameter in the parameter combination, P r,out represents the optimal value of the rth controllable parameter in the parameter combination, W r represents the weight of the rth controllable parameter in the parameter combination, F r represents the parameter sensitivity coefficient of the rth controllable parameter in the parameter combination, and H represents the number of controllable parameters;

[0157] When the abnormal optimization coefficient meets the preset abnormal optimization threshold, the parameter combination is used as the production optimization parameter of the abnormal node.

[0158] Among them, the optimization target refers to the specific performance index set in the production process to reduce or eliminate abnormal nodes, the controllable parameter refers to the variable that can be operated or adjusted in the abnormal node, such as temperature, pressure, speed, material ratio, machine setting and other parameters, the parameter sensitivity coefficient refers to a quantitative indicator of the influence of each controllable parameter on the optimization target, the parameter combination refers to a series of possible operation settings formed by combining different values ​​of multiple controllable parameters, the abnormal optimization coefficient refers to a quantitative indicator used to evaluate the optimization effect of a specific parameter combination on the abnormal node, the abnormal optimization threshold refers to the standard used to judge whether the abnormal optimization coefficient has reached an acceptable level of production optimization, the actual value of the controllable parameter refers to the value of the abnormal node in normal operation, and the production optimization parameter refers to a parameter combination that has been determined to be able to effectively optimize the abnormal node after analysis and verification.

[0159] Optionally, the parameter sensitivity coefficient of the controllable parameter can be determined by simulation analysis, such as one-way analysis of variance (ANOVA).

[0160] Compared with the problems described in the background technology, firstly, through precise production flow charts and defined traceability requirements, we ensure the rationality and practicality of the FPC product coding rules, so that each product can have a unique and detailed identification code, which greatly improves the traceability of the product. Secondly, calculating the traceability integrity coefficient of the production and testing equipment and building a traceability blockchain network not only ensures the immutability and transparency of the data, but also improves the trust and data security of the traceability system. In addition, by collecting and associating production process data with FPC product codes, we have established a process data-coding set, and then built a comprehensive product traceability library, which makes it possible to quickly and accurately query the history and current status of the product at any stage. The previous state significantly improves the problem location and response speed. By using the trained traceability anomaly analysis model, we can timely discover the traceability anomaly state of the target FPC product, and by locating the abnormal node, analyzing the production optimization parameters, effectively guide the production adjustment, thereby reducing the defective rate and improving product quality and production efficiency. Finally, the information traceability optimization based on the production optimization parameters not only optimizes the production process, but also enhances the quality control ability of the enterprise, improves customer satisfaction and enterprise competitiveness. Overall, this method provides an efficient, reliable and comprehensive product traceability solution for the FPC industry, which plays an important role in ensuring product quality, improving enterprise management and enhancing market competitiveness. Therefore, the present invention can improve the stability of the network.

[0161] Embodiment 2:

[0162] like Figure 2 FIG. 1 is a functional module diagram of an FPC production information tracing system based on a product identification code according to the present invention.

[0163] The FPC production information tracing system 200 based on product identification code of the present invention can be installed in an electronic device. According to the functions implemented, the FPC production information tracing system based on product identification code can include a product coding construction module 201, a blockchain network construction module 202, a product tracing library establishment module 203, a tracing abnormal state analysis module 204 and an information tracing optimization module 205. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0164] In the embodiment of the present invention, the functions of each module / unit are as follows:

[0165] The product coding construction module 201 is used to obtain a production flow chart of an FPC product, determine the traceability requirements of the FPC product according to the production flow chart, define a coding rule for the FPC product based on the traceability requirements, and encode the FPC product using the coding rule to obtain an FPC product code;

[0166] The blockchain network construction module 202 is used to define the production and testing equipment of the FPC product based on the traceability requirements, calculate the traceability completeness coefficient of the production and testing equipment for the FPC product, and when the traceability completeness coefficient meets the preset traceability completeness threshold, construct the traceability blockchain network of the production and testing equipment;

[0167] The product traceability library establishment module 203 is used to collect the production process data of the FPC product based on the traceability blockchain network, associate the production process data with the FPC product code, obtain a process data-code set, and establish a product traceability library of the FPC product through the process data-code set;

[0168] The traceability abnormality state analysis module 204 is used to obtain the traceability instruction of the user, obtain the traceability information of the target FPC product corresponding to the traceability instruction based on the traceability instruction and the FPC product code, and analyze the traceability abnormality state of the target FPC product using the trained traceability abnormality analysis model according to the traceability information;

[0169] The information tracing optimization module 205 is used to locate the abnormal node of the target FPC product based on the traceability abnormal state and the FPC product code, analyze the production optimization parameters of the abnormal node, and perform information tracing optimization of the FPC product based on the production optimization parameters.

[0170] In detail, each module in the FPC production information tracing system 200 based on product identification code in the embodiment of the present invention is used in the same manner as above. Figure 1 The same technical means as the FPC production information traceability method based on product identification code described in the specification and can produce the same technical effects, so I will not go into details here.

[0171] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0172] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for tracing FPC production information based on product identification code, characterized in that: The method comprises: Obtaining a production flow chart of an FPC product, determining traceability requirements of the FPC product according to the production flow chart, defining a coding rule of the FPC product based on the traceability requirements, and encoding the FPC product using the coding rule to obtain an FPC product code; Based on the traceability requirements, define the production and testing equipment of the FPC product, calculate the traceability completeness coefficient of the production and testing equipment for the FPC product, and when the traceability completeness coefficient meets the preset traceability completeness threshold, build a traceability blockchain network for the production and testing equipment; Based on the traceability blockchain network, the production process data of the FPC product is collected, the production process data and the FPC product code are associated to obtain a process data-code set, and a product traceability library of the FPC product is established through the process data-code set; Obtaining a user's traceability instruction, obtaining traceability information of a target FPC product corresponding to the traceability instruction based on the traceability instruction and the FPC product code, and analyzing the traceability abnormality state of the target FPC product using a trained traceability abnormality analysis model according to the traceability information; Based on the traceability abnormal state and the FPC product code, the abnormal node of the target FPC product is located, and the production optimization parameters of the abnormal node are analyzed, and the information traceability optimization of the FPC product is performed based on the production optimization parameters.

2. The FPC production information tracing method based on product identification code according to claim 1, characterized in that: Determining the traceability requirements of the FPC product according to the production flow chart includes: Analyze the actual production responsiveness of the production flow chart; When the actual production reaction degree meets the preset actual production reaction threshold, identifying the key process of the production flow chart; Identify the traceability points of the key processes; Calculate the traceability risk of the traceability point; According to the traceability risk, the traceability requirements of the traceability points are defined.

3. The FPC production information tracing method based on product identification code according to claim 2, characterized in that: The calculating the traceability risk of the traceability point includes: Calculate the risk probability and risk non-detection probability of the traceability point; Analyze the impact of risk product quality and risk product cost at the traceability point; Based on the risk probability, the risk non-detection probability, the risk product quality impact and the risk product cost impact, the traceability risk of the traceability point is calculated using the following formula: Among them, R i represents the traceability risk of the ith traceability point, α represents the risk adjustment coefficient, and P i represents the risk probability of the ith traceability point, D i represents the probability of undetected risk at the i-th traceability point, I i represents the risk product quality impact of the i-th traceability point, k represents the time impact coefficient, T i represents the time from the occurrence of anomaly at the i-th tracing point to the detection of anomaly, T0 represents the detection time of anomaly at the i-th tracing point, C i represents the cost impact of the risk product at the ith traceability point, C max It represents the cost impact of the risk product with the largest traceability point, and β represents the cost impact coefficient.

4. The FPC production information tracing method based on product identification code according to claim 3, characterized in that: Defining the coding rules of the FPC products based on the traceability requirements includes: Determine the coding elements of the FPC product according to the traceability requirements; Based on the coding element, establishing a coding module of the FPC product; Defining the encoding order of the encoding module; Determining the expansion space of the coding module through the coding sequence; Based on the coding module, the coding sequence and the expansion space, a coding rule for the FPC product is established.

5. The FPC production information tracing method based on product identification code according to claim 4, characterized in that: The calculation of the traceability completeness coefficient of the production testing equipment for the FPC product includes: Define the complete traceability indicators of the production testing equipment for the FPC product; Collecting equipment performance data and historical production data of the production and testing equipment; Based on the complete traceability index, a traceability multi-dimensional model of the FPC product is constructed; Based on the equipment performance data and historical production data, analyzing the traceability completeness indicator score of the traceability completeness indicator using the traceability multidimensional model; The traceability completeness coefficient of the production inspection equipment for the FPC product is calculated through the traceability completeness index score.

6. The FPC production information tracing method based on product identification code according to claim 5, characterized in that: The traceability completeness index score is used to calculate the traceability completeness coefficient of the production testing equipment for the FPC product, including: Define the traceability completeness indicator weight corresponding to the traceability completeness indicator of the production testing equipment; Calculate the correction factor of the traceability completeness indicator; Based on the traceability completeness indicator weight, the traceability completeness indicator score and the correction factor, the traceability completeness coefficient of the production testing equipment for the FPC product is calculated using the following formula: Among them, TIC represents the traceability integrity coefficient of the production inspection equipment for the FPC product, S c represents the traceability completeness index score of the cth traceability completeness index of the production inspection equipment, ω c A represents the traceability completeness indicator weight of the cth traceability completeness indicator of the production inspection equipment, c It represents the correction factor of the cth traceability complete index of the production inspection equipment, m represents the number of traceability complete indexes, and c represents the cth traceability complete index of the production inspection equipment.

7. The FPC production information tracing method based on product identification code according to claim 6, characterized in that: The process data-coding set is used to establish a product traceability library for the FPC product, including: Define the traceability library architecture of the FPC products; Based on the traceability library architecture, a product database of the FPC product is established; Standardizing the process data-code set to obtain a standard data-code set; Establishing a data upload mechanism for the product database; According to the data uploading mechanism, the standard data-code set is uploaded to the product database to obtain an uploaded data-code set; Calculating a data integrity coefficient of the uploaded data-encoded set; When the data integrity coefficient meets a preset data integrity threshold, a data traceability interface of the product database is established; A product traceability library for the FPC product is established based on the data traceability interface, the uploaded data-coding set and the product database.

8. The FPC production information tracing method based on product identification code according to claim 7, characterized in that: The method of analyzing the traceability abnormality state of the target FPC product using the trained traceability abnormality analysis model according to the traceability information includes: Preprocessing the traceability information to obtain processed traceability information; Extracting traceability information features of the processing traceability information; Based on the traceability information features, identifying the feature anomaly probability of the target FPC product using the traceability anomaly analysis model; Based on the feature abnormality probability, marking the abnormal feature of the traceability information feature; The traceability abnormal state of the target FPC product is determined based on the abnormal characteristics.

9. The FPC production information tracing method based on product identification code according to claim 8, characterized in that: The analyzing the production optimization parameters of the abnormal node includes: Defining an optimization target for the abnormal node; Identifying controllable parameters of the abnormal node; Calculating parameter sensitivity coefficients of the controllable parameters; Analyzing the parameter combination of the abnormal node according to the optimization target and the parameter sensitivity coefficient; Based on the parameter sensitivity coefficient, the abnormal optimization coefficient of the parameter combination is calculated using the following formula: Among them, AOC represents the abnormal optimization coefficient of parameter combination, P r represents the actual value of the rth controllable parameter in the parameter combination, P r,out represents the optimal value of the rth controllable parameter in the parameter combination, W r represents the weight of the rth controllable parameter in the parameter combination, F r represents the parameter sensitivity coefficient of the rth controllable parameter in the parameter combination, and H represents the number of controllable parameters; When the abnormal optimization coefficient meets the preset abnormal optimization threshold, the parameter combination is used as the production optimization parameter of the abnormal node.

10. An FPC production information tracing system based on product identification code, characterized in that: The system comprises: A product coding construction module is used to obtain a production flow chart of an FPC product, determine the traceability requirements of the FPC product according to the production flow chart, define a coding rule for the FPC product based on the traceability requirements, and encode the FPC product using the coding rule to obtain an FPC product code; A blockchain network construction module is used to define the production and testing equipment of the FPC product based on the traceability requirements, calculate the traceability completeness coefficient of the production and testing equipment for the FPC product, and build a traceability blockchain network for the production and testing equipment when the traceability completeness coefficient meets a preset traceability completeness threshold; A product traceability library establishment module, which is used to collect the production process data of the FPC product based on the traceability blockchain network, associate the production process data with the FPC product code, obtain a process data-code set, and establish a product traceability library of the FPC product through the process data-code set; A traceability abnormality status analysis module is used to obtain a user's traceability instruction, obtain traceability information of a target FPC product corresponding to the traceability instruction based on the traceability instruction and the FPC product code, and analyze the traceability abnormality status of the target FPC product using a trained traceability abnormality analysis model according to the traceability information; The information tracing optimization module is used to locate the abnormal node of the target FPC product based on the traceability abnormal state and the FPC product code, analyze the production optimization parameters of the abnormal node, and perform information tracing optimization of the FPC product based on the production optimization parameters.

Images