Automation and Optimization of Food Process Using CNN and Six-Axis Robotic Arm
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Summary
This summary is machine-generated.The Food Process Robot Intelligent System (FPRIS) uses AI and computer vision for automated coffee roasting. This intelligent system precisely controls roasting degree, enhancing efficiency and quality.
Area Of Science
- Robotics and Automation
- Artificial Intelligence
- Food Science
Background
- Traditional coffee roasting lacks precise control over the degree of roasting.
- Automation in food processing can enhance efficiency and product consistency.
Purpose Of The Study
- To develop and evaluate the Food Process Robot Intelligent System (FPRIS) for automated coffee roasting.
- To investigate the system's ability to control the Degree of Roasting (DoR) using integrated sensors and AI.
Main Methods
- Integration of a 3D-printed six-axis robotic arm with AI and Computer Vision (CV).
- Utilizing a Convolutional Neural Network (CNN) for real-time coffee bean classification and roaster control.
- Combining gas and image sensor data for assessing coffee bean quality and DoR.
Main Results
- FPRIS demonstrated precise control over the DoR by correlating sensor data with roast intensity.
- Consistent trends observed: increased weight loss and Gas sensor Initial Difference (GID), decreased Sum of Pixel Grayscale Values (SPGVs) with higher roast intensity.
- The system effectively navigated obstacles and empty spaces within the roaster.
Conclusions
- FPRIS offers enhanced precision and efficiency in automated coffee roasting.
- The system shows potential for broader applications in food processing automation.
- Further research can establish FPRIS as a universal automation solution for the food industry.

