Quality Control Inspection with Computer Vision

The project Quality Control Inspection with Computer Vision describes the design of automated inspection of bottle cap with computer vision system and sheds light on the working principle and the hardware structure of the system. The inspection of bottle cap is done by using computer vision system v

Project Title

Quality Control Inspection with Computer Vision

Project Area of Specialization

Artificial Intelligence

Project Summary

The project Quality Control Inspection with Computer Vision describes the design of automated inspection of bottle cap with computer vision system and sheds light on the working principle and the hardware structure of the system. The inspection of bottle cap is done by using computer vision system via image processing by taking continuous image of the bottle cap in production line on conveyer belt system. The components of the system are assessment unit, accepted unit and rejection unit. Raspberry Pi is used as microcontroller to control the system and it moves the mechanical and electronic components. Python is used as a programming language for image processing in inspection process. IR module is to be used at different positions to sense the presence of bottles on conveyor and to count them. Automatic rejection system is carried out by a flapper mechanism connected to the Stepper motor. This system can replace the existing conventional sensor based inspection and manual inspection. The system has an extensive social practical value thereby increasing the productivity; improve the quality of inspection, product variety and profitability The project Quality Control Inspection with Computer Vision describes the design of automated inspection of bottle cap with computer vision system and sheds light on the working principle and the hardware structure of the system. The inspection of bottle cap is done by using computer vision system via image processing by taking continuous image of the bottle cap in production line on conveyer belt system. The components of the system are assessment unit, accepted unit and rejection unit. Raspberry Pi is used as microcontroller to control the system and it moves the mechanical and electronic components. Python is used as a programming language for image processing in inspection process. IR module is to be used at different positions to sense the presence of bottles on conveyor and to count them. Automatic rejection system is carried out by a flapper mechanism connected to the Stepper motor. This system can replace the existing conventional sensor based inspection and manual inspection. The system has an extensive social practical value thereby increasing the productivity; improve the quality of inspection, product variety and profitability

Project Objectives

• To develop a quality control system to detect missing bottles caps, missing sealers, and loosed caps with camera based image processing system.

• Real time image processing and result showing on computer screen

• To develop a full conveyor belt assembly line to pass through parcels.

Project Implementation Method

Computer vision system is generally referred to the system which extracts desired features from digital images. Captured input images are the main objective of this system. In fact, human as inspectors are slower and their efficiency is affected by their state of illness, exhaustion or other human shortcomings. In some applications they need sometimes special environments which are dangerous and not conductive for human operation. On the other hand, especially in the manufacturing environment, it is necessary to improve quality control and productivity. Due to industrialization, everyday usage of bottles in fields like medicine, oil industries, automobile sectors, and chemicals industries have increased enormously. To face the huge demand industries are automated for filling and sealing the bottles with high precision. Sometimes there may be some defects like absence of cap or tamper or both. In automation, identifying such defect is become difficult if done with manual inspection. Using computer vision, vision sensor is used to identify such defects with the help of proper light settings. Computer is interfaced with vision sensor through USB or frame grabbers. This technique is used to inspect the bottles in seconds with high accuracy.

Benefits of the Project

• Eliminating manpower at industries by automating visual inspection systems.
• Drinks, Cooking oil, canned foods manufacturers are interested in automated quality control inspection.
• This project will give an idea for industries to look into different areas where they can utilize computer vision and image processing techniques.
• High accuracy rate in less time is a key point of this project.
• Cost effective solution will encourage more industries to adopt computer vision quality control.

Technical Details of Final Deliverable

Any repetitive control process from any business sphere which requires human actions can be automated today! And companies that do it see tangible benefits really soon in terms of money and working hours. The Industrial assembly lines should aim to focus on product's quality with minimizing human errors to zero by introducing an efficient system to monitor product quality, for instance observe perfection over bottle's cap fixing in assembly line. As our project focuses on designing an automated system which will be used in inspecting the bottle caps of the production line via computer vision aiming for much better efficiency and removing human defects.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Food

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Required Resources

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