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Intelligent Error Correction System For Packaging Bags

Based on AI vision algorithms, an intelligent error correction system is implemented for counting packaging bags, printing code information, and variety recognition on high-speed conveyor belts. The system achieves millisecond level recognition, with an accuracy rate of over 99% for counting packages, printing code information, and bagged variety.

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Industry pain points Content of the plan Application value Customer Cases

Industry pain points

Inaccurate Stacking Count

Stacking of packaging bags results in inaccurate counting of traditional packaging counters.
Difficult to recognize spray code errors

Information such as the date of cement production, coding, and spraying codes need to be identified and corresponded, and manual verification is time-consuming and difficult to ensure accuracy
Difficulty in tracing abnormal situations

Abnormal situation records are scattered and difficult to summarize and trace
Incomplete product information

Usually only counting quantities, with limited information

Content of the plan

Real time counting of packaging bags

Real time detection of the number of cement packages passing through the discharge belt of the packaging machine using industrial high-speed flying camera technology, which can accurately identify abnormal states such as continuous packaging and midway shutdown
Innovative millisecond level recognition and comparison algorithm for fast localization, tracking and detection, with a packet counting accuracy of over 99%

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Intelligent recognition of spray code characters

Using OCR character recognition technology to detect the label and spray code content on each bag of cement package passing through the conveyor belt, and comparing it in real-time with backend data
The recognition rate reaches 5 packets/second, with an accuracy rate of 99%

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Identification of bagged varieties

By detecting the side of the cement package, it is possible to effectively identify the type of bagged cement PO/PC and prevent packaging errors
Intelligent recognition and classification, effectively improving the factory qualification rate

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Detect data interaction

Adopting TCP and IP communication protocols can ensure stable and reliable data transmission
The detection system can expand its integration with customer MES systems, enabling real-time data exchange with customer systems

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Convenient information management

WeChat Mini Program: Provides mobile alarm message push for subsequent summary and query
Web and large screen: The large screen displays alarm reports and details, and can be customized to display reports

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Expandable and customizable

Multiple AI scene algorithms can be selected based on camera configuration, with the help of cameras to collect real-time data and perform intelligent analysis on the device or cloud, standardizing, digitizing, and intelligentizing inspection content
Support access to customer management systems such as one card management system, customer factory system, DCS system, etc., with convenient data exchange and management

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Application value

Accurate and efficient

The disadvantage of packaging bag stacking has been solved through dynamic target recognition algorithm, ensuring the accuracy of monitoring data
Improve packaging qualification rate

Using AI deep learning algorithms to accurately identify the production date, coding spray code, and quantity of bagged cement, improving the factory qualification rate of products
Convenient management

The system has a comprehensive multi task record storage and query function, which facilitates the retrieval of task status, abnormal data, photos, etc., and facilitates management
Strong extensibility

Support special interface customization and docking development

Customer Cases

Intelligent AI recognition and error correction system for packaging bags, improving the qualification rate of packaging products

A packaging bag intelligent error correction system has been developed for this purpose, which uses visual detection technology to visually detect bagged cement packages. AI deep learning algorithms are used to achieve dynamic tracking and statistics o

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Intelligent Error Correction System For Packaging Bags

Industry pain points

Content of the plan

Real time counting of packaging bags

Intelligent recognition of spray code characters

Identification of bagged varieties

Detect data interaction

Convenient information management

Expandable and customizable

Application value

Customer Cases

Intelligent AI recognition and error correction system for packaging bags, improving the qualification rate of packaging products