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Production
Quality Control Vision System
The system using vision sensors and analytical software automates the quality control process, reducing the need for manual work and eliminating human errors. Automation ensures higher product quality, increases production efficiency and reduces operating costs.
A plastic products factory commissioned us to design and implement a quality control vision system. The project aimed to increase production efficiency and improve product quality.
Quality Problems
The factory faced several serious problems regarding the quality of its products:
Surface irregularities and defects
The occurrence of cracks, holes and other surface defects that were difficult to detect by manual inspection.
Incorrect dimensions
Variations in product dimensions that often led to non-compliance with customer requirements.
Low inspection efficiency
Detailed manual quality control was time-consuming and prone to human error, leading to low productivity and inefficiencies in production.
Research and Development Part
The research and development process that led to the development of our solution included several key stages:
Requirements Analysis: We conducted a detailed analysis of quality problems in the factory and customer requirements. We have identified the most common defects and those that cause the most trouble for manual testers. We defined the parameters that the system had to monitor.
Market Research
We analyzed available vision technologies, selecting vision sensors with high accuracy, speed of operation and ease of integration with the customer’s vision software and hardware.
Prototyping
We developed a prototype of the vision system, which was tested on the factory production line. These tests allowed us to introduce the necessary modifications and optimizations.
Integration and Tests
After the prototype was approved, the system was integrated into the full production line. We performed extensive testing to ensure the system functions properly in real production conditions.
Staff Training
We trained factory staff in the operation and maintenance of the new system, providing technical support at every stage of implementation.
Elements and Technologies Used
Vision sensors
The basic element of the system, responsible for capturing and analyzing images of plastic products.
LED illumination
Provides even and adequate illumination for vision sensors, which is crucial for precise analysis.
Industrial computer
Controls the entire system, analyzes data from sensors and makes decisions about product quality. We used a device of our own production for this purpose.
Analytical software
Uses advanced algorithms to detect defects and deviations from the norm. We used a ready-made solution due to the complexity of the algorithms analyzing the sent image. The user interface allows operators to easily configure the system, monitor the quality control process, and view results.
Sensors, Communication, and Controllers in the Quality Control Vision System
1. Vision Sensors
The key component in the Quality Control Vision System is the vision sensor, which captures detailed images of the plastic products as they pass through the production line. These sensors are typically CMOS or CCD-based, designed for industrial applications requiring high accuracy and speed. CMOS sensors are preferred for their faster data readout and lower power consumption, making them ideal for real-time quality control in high-speed production environments. The sensors are also equipped with adjustable resolutions to accommodate various inspection needs, from detecting minute surface cracks to verifying product dimensions.
Vision sensors are paired with LED illumination systems to maintain consistent lighting, which enhances the quality and precision of image capture. Proper illumination helps eliminate shadows and reflections that could interfere with defect detection.
2. Communication Types
To ensure that data flows efficiently between the system components, various communication protocols are employed:
- Ethernet/IP: This protocol facilitates fast, high-bandwidth data transfer between sensors, the industrial computer, and other control devices. Ethernet/IP is a common choice for factory automation systems because of its reliability, scalability, and speed, making it ideal for large-scale, high-speed production lines.
- Modbus TCP/IP: This communication protocol is often used for communication between the industrial computer (controller) and Programmable Logic Controllers (PLCs). It allows devices to share information quickly and reliably, enabling smooth integration of the quality control vision system into existing automation frameworks.
- IO-Link: For connecting individual sensors or devices to the system, IO-Link technology is often used. It allows bi-directional communication between sensors and controllers, supporting diagnostic and configuration capabilities directly from the central system.
3. Controllers
The industrial controller, typically in the form of an Industrial PC (IPC), processes the data received from the vision sensors. This PC runs specialized analytical software that uses machine vision algorithms to analyze the images captured by the sensors, detect surface defects, and measure dimensions. The controller is responsible for:
- Image processing: Real-time image processing is handled using advanced algorithms that compare captured images to a predefined set of acceptable parameters.
- Decision-making: The controller decides whether a product passes or fails based on the analysis of the captured data.
- System coordination: The controller also manages communication between the vision sensors, illumination systems, and other factory systems (like PLCs or conveyors).
- User Interface (UI): The industrial PC often hosts a UI that allows operators to configure the system, view results, and manage reports.
Long-term profit for the customer
Improved product quality
Using a vision system, the factory can ensure that each product meets high-quality standards, which increases customer satisfaction and minimizes complaints.
Increased efficiency
Automating quality control allows for faster product processing, which increases the overall efficiency of production lines.
Cost reduction
Fewer rejections and reduced manual inspections.
Conclusion
The implementation of the quality control vision system brought tangible benefits to the factory. Automation of the quality control process ensures higher product quality, increases production efficiency and reduces operating costs. Thanks to this, our client can meet market requirements and remain competitive.
We are proud of this project and recommend vision systems as an effective tool for quality control in various manufacturing industries.
