Cigarette pack printing defect management system and method based on two-dimensional code

Abstract

The invention discloses a cigarette pack printing defect management system and method based on a two-dimensional code, and belongs to the technical field of printing defect detection. According to the scheme, accurate identification, precise positioning and effective tracing of cigarette pack printing defects are realized through cooperation of the two-dimensional code generation and tagging module, the image acquisition module and the image analysis processing module by utilizing the characteristic of one object and one code of the two-dimensional code. According to the system, defect physical coordinates are converted by taking two-dimensional codes as coordinate reference points, working procedures and equipment in which defects appear for the first time can be quickly positioned by combining image acquisition and analysis of each working procedure, and meanwhile, an equipment defect mode library is established through defect data, so that equipment condition monitoring and dynamic quality control are realized. According to the scheme, collaborative dependence of multiple systems is reduced, the system stability is improved, the two-dimensional code overprinting policy in the tobacco industry is met, a production line does not need to be additionally transformed, the cigarette pack printing quality detection efficiency and tracing precision can be effectively improved, and support is provided for intelligent production of tobacco enterprises.

Description

Technical Field

[0001] This application relates to the field of printing defect detection technology, specifically to a QR code-based cigarette label printing defect management system. Background Technology

[0002] In the cigarette production process, the printing quality of cigarette packaging is crucial, affecting not only the product's appearance but also brand reputation and consumer purchasing decisions. Traditionally, cigarette packaging printing defects were primarily identified through manual visual inspection, with quality inspectors comparing defects to standard samples. However, this method reveals significant shortcomings in high-speed production scenarios: low inspection efficiency, high missed detection rate, and inability to adapt to the rapid pace of cigarette packaging machine production. With the intelligent transformation of the tobacco industry and the gradual introduction of machine vision technology, automated inspection using industrial cameras and image processing algorithms has gradually become dominant in the field of cigarette packaging printing defect detection. Currently, cigarette packaging production utilizes numerous new materials and processes, resulting in increasingly diverse printing defects compared to traditional techniques, placing stringent demands on defect detection technology. The development of defect detection technology focuses on improving detection accuracy, accelerating detection speed, and increasing the types of defects detected. These advancements enable manufacturers to quickly and accurately identify printing defects on cigarette packaging and facilitate the collection and summarization of defect type data, allowing for subsequent process improvements and adjustments to equipment. The aforementioned detection technologies are all based on the combination of machine vision and various sensors. Accurate location of defects requires the cooperation of multiple systems, namely the printing press mechanical system and the sensor and image acquisition system. When faced with complex printing patterns and minor defects, the recognition accuracy is limited, and it is impossible to achieve accurate location and effective traceability of defective products.

[0003] Specifically, high-speed industrial cameras are installed at key locations on the printing press to capture images of the printed materials in real time. The system compares the captured images with a pre-set standard template and uses algorithms to identify abnormal areas, i.e., defect locations, in the images. Then, combined with the calibration of the printing press's mechanical transmission system and vision system, the defect locations in the images are converted into their actual physical coordinates on the entire printed material.

[0004] Some companies use real-time marking methods for location. When the system detects a defect, it marks the location of the defect on the edge of the printed material or in the non-printed area using an inkjet marking device or a laser marking device. The defect is usually represented by specific symbols or numbers so that it can be manually inspected or automatically removed later.

[0005] These methods each have their own advantages in detecting and locating printing defects, but they all rely on the system coordination of multiple links such as image acquisition, preprocessing, defect identification, result analysis, and equipment control. Due to the different technical principles, operating logic, and data standards of each system, inconsistencies in coordination are likely to occur. In particular, the determination of defect location is easily affected by fluctuations in the mechanical transmission system and changes in paper transmission speed caused by changes in paper tension. Furthermore, existing technologies, after detecting printing defects, store the location information of the defects, such as their coordinates on the printed material, defect type, and detection time, in a database for subsequent analysis and traceability. By reviewing historical data, the patterns of defect occurrence can be understood, allowing for adjustments to printing parameters or equipment maintenance. However, it is impossible to determine the specific workstation and equipment causing the defect in real time and quickly, thus failing to make corresponding adjustments and changes promptly. In other words, there is a lack of effective monitoring methods for the correlation between production equipment status and product quality, making it difficult to detect potential equipment problems in a timely manner and achieve comprehensive quality control.

[0006] The announcement regarding the redesign of cigarette packaging with added QR code markings requires tobacco companies to fully implement the addition of QR codes to cigarette packaging, and to utilize these QR codes to display relevant product information. Specifically, in the cigarette label printing process, a unique QR code is placed on every complete printed cigarette label design. This unique code allows for real-time location tracking or rapid traceability of the label. The QR codes on cigarette packaging assist in the management of printing defects. Through technological integration and process optimization, a more efficient, accurate, and traceable cigarette packaging printing quality inspection solution with equipment monitoring capabilities can be provided, encompassing defect detection, quality management, instant traceability, and rapid rectification. Summary of the Invention

[0007] To address the shortcomings of existing cigarette label printing defect detection methods, such as the need for multiple systems, low stability, susceptibility to accuracy issues, and slow traceability adjustment, this application utilizes the "one item, one code" characteristic of QR codes to provide a cigarette label printing defect management system and method based on industry-mandated QR code identification. This system enables accurate identification, precise location, and effective traceability of printing defects in cigarette packaging, as well as equipment condition monitoring and quality control. This overcomes the deficiencies of existing technologies and improves the quality and efficiency of cigarette packaging production.

[0008] The present invention adopts the following technical solution: a QR code-based cigarette label printing defect management system, comprising: a QR code generation and coding module, an image acquisition module, and an image analysis and processing module; The QR code generation and coding module is located at the front end of the printing equipment. It includes a QR code encoding generation unit and a high-precision printing equipment control unit. It generates a QR code containing detailed production information and controls the printing equipment to clearly and accurately place the QR code at a designated position on any complete cigarette package. The image acquisition module includes several sets of image acquisition devices. The first set is installed at the end of the coding module, i.e., the front-end acquisition device. The last set is installed at the end of the cigarette packaging production line, i.e., the back-end acquisition device. The rest are installed at different parts where different printing processes are completed, becoming node acquisition devices. The front-end acquisition device collects and inputs the QR code on the cigarette packaging, and the node acquisition device collects images of the cigarette packaging after it has passed through the workstation in real time, as well as scans the QR code and records the precise time point and the process node and location node information corresponding to that time point; the back-end acquisition device collects the final printed image of the cigarette packaging and identifies the QR code information. The image analysis and processing module includes a QR code recognition unit, an image feature extraction unit, a temporary storage unit, a defect detection unit, and a coordinate transformation unit. The QR code recognition unit and the image feature extraction unit are independently connected to each group of image acquisition devices in the image acquisition module via wires or wireless networks, and then connected to the temporary storage unit respectively. The defect detection unit and the coordinate transformation unit are connected to the output end of the temporary storage unit. The QR code recognition unit quickly identifies the QR codes in the images acquired by each image acquisition module, extracts the corresponding process steps and participating equipment information based on the source of the image that belongs to the same category as the QR code, and sends it to the temporary storage unit. The image feature extraction unit also uniquely associates the image information acquired by each image acquisition module with the information acquired from the QR code on the same image and stores it temporarily; the temporary storage unit has the functions of querying and retrieving within a complete production process and responding quickly to traceability requests. The defect detection unit is located adjacent to the back-end acquisition device and the two are directly connected. The finished cigarette packaging image acquired by the back-end acquisition device is transmitted directly to the defect detection unit, bypassing the temporary storage unit. The defect detection unit compares the real-time image with the standard image. When a defect is identified in the cigarette packaging image, it communicates with the temporary storage unit in real time, sequentially retrieves all images acquired and temporarily stored by the image acquisition device for comparison, finds the image where the defect first appears, and reads the QR code on it, thereby determining the specific process stage and corresponding equipment where the defect occurred. The coordinate transformation unit can perform image positioning based on the QR code; when the defect detection unit identifies a defect in the cigarette packaging image, the coordinate transformation unit uses the QR code in the image as a coordinate reference point and combines it with the calibration parameters of the image acquisition device to convert the pixel coordinates of the defect in the image into the coordinates of the actual physical location of the cigarette packaging.

[0009] Based on the defects in the cigarette packaging images, the specific production time and location of the product at each station of the printing equipment can be located using QR codes, facilitating quick identification of the root cause of the problem. Through the above methods, this invention achieves accurate positioning of cigarette packaging printing defects based on QR codes, as well as effective traceability of product location during the production process. Compared with traditional positioning methods that rely on a large number of sensors and complex mechanical control systems, it has higher accuracy, stability and convenience.

[0010] This application also provides a QR code-based method for managing printing defects in cigarette labels, enabling accurate identification, precise location, and effective traceability of printing defects in cigarette packaging, as well as equipment condition detection and quality control, to overcome the shortcomings of existing technologies and improve the quality and efficiency of cigarette packaging production.

[0011] A method for managing defects in cigarette label printing based on QR codes, characterized by comprising the following steps: I. QR Code Generation and Assignment ① Code generation: Based on production requirements, generate a QR code containing detailed production information, which includes at least product identification, production batch, production date, process steps, and information on participating equipment; ② QR code printing: The generated QR code is clearly and accurately placed in the designated position on any complete cigarette package to ensure that the QR code can be accurately identified; II. Image Acquisition ① Image acquisition device layout: At least four sets of image acquisition devices are set up on the cigarette packaging production line: the first set is the front-end acquisition device, which is installed at the end of the coding module; the second and third sets are installed in the printing unit and the drying unit, respectively; the fourth set is the back-end acquisition device, which is installed at the end of the cigarette packaging production line. ② Image acquisition operation: The front-end acquisition device collects and inputs the QR code on the cigarette packaging; the second and third sets of acquisition devices collect images of the cigarette packaging after it has passed through the workstation in real time, and scan the QR code to record the precise time point and the corresponding process node and location node information; the back-end acquisition device collects the final printed image of the cigarette packaging and identifies the QR code information; all image acquisition devices are connected to the production line control system and collect images of the cigarette packaging according to the set time interval or trigger conditions to obtain complete image information of the printed pattern; III. Image Analysis and Processing ① Information association and storage: a. The QR code recognition unit quickly recognizes the QR codes in the images acquired by each image acquisition module, extracts the corresponding process steps and participating equipment information based on the source of the image that belongs to the same category as the QR code, and sends it to the temporary storage unit. b. The image feature extraction unit uniquely associates the image information acquired by each image acquisition module with the information acquired from the QR code on the same image, and temporarily stores it. c. The temporary storage unit has the function of querying and retrieving data and quickly responding to traceability requests throughout a complete production process. ②Defect Detection and Location: The defect detection unit is located adjacent to the back-end acquisition device. The finished cigarette packaging images acquired by the back-end acquisition device are directly transmitted to the defect detection unit, bypassing the temporary storage unit. The defect detection unit compares the real-time images with standard images. When a defect is identified in the cigarette packaging image, it communicates with the temporary storage unit in real time to retrieve all images acquired and temporarily stored by the image acquisition devices for comparison. It finds the image where the defect first appears and reads the QR code on it, thereby determining the specific process stage and corresponding equipment where the defect occurred. ③ The coordinate transformation unit uses the QR code in the defect image as the coordinate reference point and combines it with the calibration parameters of the image acquisition device to convert the pixel coordinates of the defect in the image into the coordinates of the actual physical location of the cigarette packaging.

[0012] Based on defects in cigarette packaging images, QR codes can be used to pinpoint the specific production time and location of the product at each station of the printing equipment, quickly identifying the root cause of the problem. This enables effective monitoring of the correlation between production equipment status and product quality, timely detection of potential equipment issues, and comprehensive quality control.

[0013] Preferably, the above method also includes an equipment condition detection step; by analyzing defect data of cigarette packaging produced by the same equipment during the production process, an equipment defect pattern library is established, and the operating status of the equipment is judged through statistical analysis of data such as the type, quantity, and frequency of product defects produced by the equipment. For example, repeated misregistration problems at a certain position may indicate that the corresponding parts of the equipment have problems such as wear, loosening, or improper parameter settings. Through real-time monitoring and analysis of equipment defect data, potential equipment failures can be detected in a timely manner, providing a basis for equipment maintenance and avoiding product quality problems and decreased production efficiency caused by equipment failures.

[0014] Preferably, the above method also includes a quality control step; based on the results of defect identification and equipment condition detection, quality control is carried out on the production process; when the printing defect rate is detected to exceed a set threshold, the process parameters of the production equipment, such as printing pressure, ink flow rate, and printing speed, are automatically adjusted to improve the printing quality; the effectiveness of the quality control measures is monitored and evaluated in real time, and the production process and equipment operating parameters are continuously optimized to ensure that the printing quality of cigarette packaging remains stable at a high level. Beneficial effects

[0015] The technical solution of this invention is based on the "one item, one code" characteristic of QR codes. By setting a unique QR code in cigarette label printing and combining it with multiple image acquisition devices and image analysis and processing modules, it achieves accurate identification, precise location, and effective traceability of printing defects. After a defect is detected, the process and equipment where the defect first appeared can be quickly located by associating the QR code with historical images. This reduces reliance on multi-system collaboration, avoids the impact of mechanical transmission fluctuations on positioning accuracy, improves system stability, and adapts to high-speed production scenarios. Furthermore, the QR code can be used as a coordinate reference point to convert the defect pixel coordinates into actual physical coordinates. It can also analyze defect data to establish an equipment defect pattern library for preventive maintenance. When the defect rate exceeds a threshold, process parameters are automatically adjusted to form a quality control closed loop. Relying on the industry-mandated QR code identification, no additional production line modifications are required, reducing deployment costs. The temporary storage unit supports rapid retrieval of data throughout the entire process, providing support for enterprise digital transformation. It breaks through the bottlenecks of traditional positioning technology and provides a precise, efficient, and intelligent solution for cigarette label printing defect management, improving production quality and efficiency. Attached Figure Description

[0016] Figure 1 This is a structural diagram of the cigarette label printing defect management system described in this application. Detailed Implementation

[0017] The technical solution of this application will be further described below through specific embodiments.

[0018] A QR code-based cigarette label printing defect management system includes: a QR code generation and coding module, an image acquisition module, and an image analysis and processing module.

[0019] The QR code generation and coding module is located at the front end of the printing equipment and includes a QR code encoding generation unit and a high-precision printing equipment control unit. The encoding generation unit uses an industrial-grade QR code encoder, which is integrated into the front-end control host of the printing equipment and supports standard QR code generation. The high-precision printing equipment uses a gravure printing unit and is equipped with an automatic registration system to ensure that the QR code clarity meets the standards.

[0020] The QR code must contain at least the product's unique identifier, production batch, production date, process steps, and the number of the equipment involved; the code is fixed in a specific area of ​​the cigarette label, usually on the side of the cigarette pack.

[0021] The image acquisition module comprises multiple sets.

[0022] The front-end acquisition device is installed at the end of the coding module and is equipped with an industrial camera for initial QR code acquisition.

[0023] The node acquisition device includes printing nodes, drying nodes, hot stamping nodes, etc., which are installed at different printing process completion parts such as printing unit, drying unit, and hot stamping unit; equipped with a high-pixel industrial camera, it can acquire images after the operation in real time and scan QR codes to record the time point and corresponding process and location node information.

[0024] The back-end acquisition device is installed at the end of the production line and is also equipped with a high-pixel industrial camera to acquire finished product images and recognize QR code information.

[0025] All acquisition devices are hard synchronized with the printing press via PLC to ensure strict synchronization between image acquisition and printing positions.

[0026] The image analysis and processing module includes a QR code recognition unit, an image feature extraction unit, a temporary storage unit, a defect detection unit, and a coordinate transformation unit. All hardware units communicate through an industrial Ethernet hybrid architecture to reduce image transmission latency.

[0027] The system includes a QR code recognition unit that extracts the associated process flow and equipment information from the QR code in real time and sends it to a temporary storage unit; an image feature extraction unit that extracts image texture, color, shape, and other features, uniquely associates them with the QR code information, and temporarily stores them, supporting second-level retrieval of full-process data; a defect detection unit located adjacent to the back-end acquisition device that detects defects such as misregistration and uneven ink color. After a defect is detected, historical images are retrieved in real time for comparison, and the process and equipment where the defect first appeared are located using a dynamic time warping algorithm; and a coordinate transformation unit that uses the QR code as a coordinate reference point and combines camera parameters to convert the defect pixel coordinates into actual physical coordinates.

[0028] The implementation steps of this management system are as follows: I. QR Code Generation and Assignment ① Code generation: The QR code generation unit obtains information such as product ID, batch, and date from the production management system and automatically generates QR code data.

[0029] ② Using a high-precision printing equipment control unit, the QR code is clearly printed on the designated position on the cigarette label.

[0030] II. Image Acquisition Operation ① At least four sets of acquisition devices should be set up: the front-end device acquires the initial information of the QR code; the node device after the printing unit and drying unit acquires the image and scans the QR code in real time, and records the time, process and position information; the back-end device acquires the finished product image and QR code information; all devices are triggered synchronously by the spindle encoder pulse to ensure that the image corresponds to the printing position.

[0031] ② Image preprocessing: After necessary processing, the acquired images are associated with and stored with QR code information.

[0032] III. Image Analysis and Defect Management ① The QR code recognition unit quickly extracts the QR code information from the image, associates it with the process flow and equipment data, and then stores it in the temporary storage unit.

[0033] ② The finished product images collected at the back end are directly transmitted to the defect detection unit. After the defect is found by comparing it with the standard image, the system automatically retrieves all historical images, finds the image where the defect first appeared by matching defect features, and reads the corresponding QR code to locate the process stage and equipment where the defect occurred.

[0034] ③ After defect detection, the QR code is used as a reference point to convert the pixel coordinates into physical coordinates, thereby achieving precise defect location.

[0035] We have collected more than 5,000 defect records and established a defect pattern library to detect potential equipment failures in advance.

[0036] When the defect rate is detected to exceed the set threshold, the system automatically adjusts the process parameters.

[0037] This embodiment, through a detailed description of hardware configuration, software algorithm, process parameters, and operation procedures, ensures that those skilled in the art can deploy and operate the system based on the description, meeting the needs for accurate detection, location, and traceability of defects in cigarette label printing, and providing a specific and feasible technical solution for intelligent quality control in the tobacco industry.

Claims

1. A QR code-based cigarette label printing defect management system, characterized in that, include: QR code generation and coding module, image acquisition module, image analysis and processing module; The QR code generation and coding module is located at the front end of the printing equipment. It includes a QR code encoding generation unit and a high-precision printing equipment control unit. It generates a QR code containing detailed production information and controls the printing equipment to clearly and accurately place the QR code at a designated position on any complete cigarette package. The image acquisition module includes several sets of image acquisition devices. The first set is installed at the end of the coding module, i.e., the front-end acquisition device. The last set is installed at the end of the cigarette packaging production line, i.e., the back-end acquisition device. The rest are installed at different parts where different printing processes are completed, becoming node acquisition devices. The front-end data acquisition device collects and inputs the QR code on the cigarette packaging; The node acquisition device collects real-time images of cigarette packaging after the work station has been completed, as well as scans QR codes, and records the precise time point and the corresponding process node and location node information. The back-end data acquisition device collects the final printed image of the cigarette packaging and identifies the QR code information. The image analysis and processing module includes a QR code recognition unit, an image feature extraction unit, a temporary storage unit, a defect detection unit, and a coordinate transformation unit; Among them, the QR code recognition unit and the image feature extraction unit are independently connected to each group of image acquisition devices in the image acquisition module via wires or wireless networks, and then connected to the temporary storage unit respectively. The defect detection unit and the coordinate transformation unit are connected to the output end of the temporary storage unit. The QR code recognition unit quickly identifies the QR codes in the images acquired by each image acquisition module, extracts the corresponding process steps and participating equipment information based on the source of the image that belongs to the same category as the QR code, and sends it to the temporary storage unit. The image feature extraction unit also uniquely associates the image information acquired by each image acquisition module with the information acquired from the QR code on the same image and stores it temporarily; the temporary storage unit has the functions of querying and retrieving within a complete production process and responding quickly to traceability requests. The defect detection unit is located adjacent to the back-end acquisition device and the two are directly connected. The finished cigarette packaging image acquired by the back-end acquisition device is transmitted directly to the defect detection unit, bypassing the temporary storage unit. The defect detection unit compares the real-time image with the standard image and establishes real-time communication with the temporary storage unit. It sequentially retrieves all images acquired and temporarily stored by the image acquisition device for comparison, finds the image where the defect first appears, and reads the QR code on it, thereby determining the specific process stage and corresponding equipment where the defect occurred. In addition, the coordinate transformation unit can perform image positioning based on the QR code; when the defect detection unit identifies a defect in the cigarette packaging image, the coordinate transformation unit uses the QR code in the image as a coordinate reference point and combines it with the calibration parameters of the image acquisition device to convert the pixel coordinates of the defect in the image into the coordinates of the actual physical location of the cigarette packaging.

2. A method for managing cigarette label printing defects based on QR codes, implemented using the management system described in claim 1, characterized in that, Includes the following steps: I. QR Code Generation and Assignment ① Code generation: Based on production requirements, generate a QR code containing detailed production information, which includes at least the product identifier, production batch, production date, process steps, and information on the participating equipment. ② QR code printing: The generated QR code is clearly and accurately placed in the designated position on any complete cigarette package to ensure that the QR code can be accurately identified; II. Image Acquisition ① Image acquisition device layout: At least four sets of image acquisition devices are set up on the cigarette packaging production line: the first set is the front-end acquisition device, which is installed at the end of the coding module; The second and third groups are installed in the printing unit and the drying unit, respectively; the fourth group is the back-end collection device, installed at the end of the cigarette packaging production line. ② Image Acquisition Operation: The front-end acquisition device collects and inputs the QR code on the cigarette packaging; the second and third sets of acquisition devices collect images of the cigarette packaging after it has passed through the workstation in real time, and simultaneously scan the QR code, recording the precise time point and the corresponding process node and location node information; the back-end acquisition device collects the final printed image of the cigarette packaging and identifies the QR code information; all image acquisition devices are connected to the production line control system, and collect images of the cigarette packaging according to the set time interval or trigger conditions to obtain complete image information of the printed pattern; III. Image Analysis and Processing ① Information association and storage: a. The QR code recognition unit quickly recognizes the QR codes in the images acquired by each image acquisition module, extracts the corresponding process steps and participating equipment information based on the source of the image that belongs to the same category as the QR code, and sends it to the temporary storage unit. b. The image feature extraction unit uniquely associates the image information acquired by each image acquisition module with the information acquired from the QR code on the same image, and temporarily stores it. c. The temporary storage unit has the function of querying and retrieving data and quickly responding to traceability requests throughout a complete production process. ② Defect Detection and Location: The defect detection unit is located adjacent to the back-end acquisition device. The finished cigarette packaging images acquired by the back-end acquisition device are directly transmitted to the defect detection unit, bypassing the temporary storage unit. The defect detection unit compares the real-time images with standard images. When a defect is identified in the cigarette packaging image, it communicates with the temporary storage unit in real time to retrieve all images acquired and temporarily stored by the image acquisition devices for comparison. It finds the image where the defect first appears and reads the QR code on it, thereby determining the specific process stage and corresponding equipment where the defect occurred. ③ The coordinate transformation unit uses the QR code in the defect image as the coordinate reference point and combines the calibration parameters of the image acquisition device to convert the pixel coordinates of the defect in the image into the coordinates of the actual physical location of the cigarette packaging.

3. The method for managing cigarette label printing defects based on QR codes according to claim 2, characterized in that, It also includes equipment condition detection steps; by analyzing the defect data of cigarette packaging produced by the same equipment during the production process, an equipment defect pattern library is established, and the operating status of the equipment is judged by statistical analysis of data such as the type, quantity, and frequency of product defects produced by the equipment.

4. The method for managing cigarette label printing defects based on QR codes according to claim 2, characterized in that, It also includes quality control steps; Based on the results of defect identification and equipment condition detection, quality control is carried out on the production process; when the printing defect rate is detected to exceed the set threshold, the process parameters of the production equipment, including printing pressure, ink flow rate, and printing speed, are automatically adjusted to improve printing quality; the effectiveness of the quality control measures is monitored and evaluated in real time, and the production process and equipment operating parameters are optimized.

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