PCB Manufacturing Intelligent AOI System
PCB Manufacturing Intelligent AOI System
| Application Challenges
PCB manufacturing is highly competitive but not allowed to compromise accuracy. Traditional AOI(Automated Optical Inspection) systems suffer from high overkill rates due to accuracy limitations, leading to excessive rejection of functional components. PCB defects vary in complexity, from visible flaws to subtle anomalies. Also, PCB manufacturing often operates at high speeds, requiring AI AOI systems to perform inspections rapidly without compromising accuracy. Hence, Choosing the AI computing capability with high cost-performance ratio and low power consumption becomes an urgent issue.
| Application Goal
Necessity to adopt AI AOI in PCB manufacturing
AOI integrated with Artificial Intelligence (AI) is transforming PCB manufacturing quality control.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
Pain point:
※ Using a CPU for AI inference requires high-end processors like the Core i9 or i7, which raises system costs, consumes a lot of power, and delivers subpar performance.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
| Solution Architecture
Importing SUNIX AI AOI detection
| Product Feature
| Portfolio
SUNIX AI Series
Solutions
AI Inference
Banking
Restaurant / POS
Medical
Security
Factory Automation
CANbus Application
Transportation
Kiosk and Self-service
Public Utilities
Public Utilities
-
Application Video - EV Charging Station
-
Application Video - IoT Environmental Monitoring Solution
-
Currency Printing: Banknote Printing and Counterfeit Banknote Prevention
-
Airport : Airport Environment Monitoring System
-
Water Quality Monitoring : 2008 Beijing Olympics Project
-
Military : Missile Launch Control Testing a nd Simulation System
PCB Manufacturing Intelligent AOI System
PCB Manufacturing Intelligent AOI System
| Application Challenges
PCB manufacturing is highly competitive but not allowed to compromise accuracy. Traditional AOI(Automated Optical Inspection) systems suffer from high overkill rates due to accuracy limitations, leading to excessive rejection of functional components. PCB defects vary in complexity, from visible flaws to subtle anomalies. Also, PCB manufacturing often operates at high speeds, requiring AI AOI systems to perform inspections rapidly without compromising accuracy. Hence, Choosing the AI computing capability with high cost-performance ratio and low power consumption becomes an urgent issue.
| Application Goal
Necessity to adopt AI AOI in PCB manufacturing
AOI integrated with Artificial Intelligence (AI) is transforming PCB manufacturing quality control.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
Pain point:
※ Using a CPU for AI inference requires high-end processors like the Core i9 or i7, which raises system costs, consumes a lot of power, and delivers subpar performance.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
| Solution Architecture
Importing SUNIX AI AOI detection
| Product Feature
| Portfolio
SUNIX AI Series
Solutions
AI Inference
Banking
Restaurant / POS
Medical
Security
Factory Automation
CANbus Application
Transportation
Kiosk and Self-service
Public Utilities
Public Utilities
-
Application Video - EV Charging Station
-
Application Video - IoT Environmental Monitoring Solution
-
Currency Printing: Banknote Printing and Counterfeit Banknote Prevention
-
Airport : Airport Environment Monitoring System
-
Water Quality Monitoring : 2008 Beijing Olympics Project
-
Military : Missile Launch Control Testing a nd Simulation System
PCB Manufacturing Intelligent AOI System
PCB Manufacturing Intelligent AOI System
| Application Challenges
PCB manufacturing is highly competitive but not allowed to compromise accuracy. Traditional AOI(Automated Optical Inspection) systems suffer from high overkill rates due to accuracy limitations, leading to excessive rejection of functional components. PCB defects vary in complexity, from visible flaws to subtle anomalies. Also, PCB manufacturing often operates at high speeds, requiring AI AOI systems to perform inspections rapidly without compromising accuracy. Hence, Choosing the AI computing capability with high cost-performance ratio and low power consumption becomes an urgent issue.
| Application Goal
Necessity to adopt AI AOI in PCB manufacturing
AOI integrated with Artificial Intelligence (AI) is transforming PCB manufacturing quality control.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
Pain point:
※ Using a CPU for AI inference requires high-end processors like the Core i9 or i7, which raises system costs, consumes a lot of power, and delivers subpar performance.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
| Solution Architecture
Importing SUNIX AI AOI detection
| Product Feature
| Portfolio
SUNIX AI Series
Solutions
AI Inference
Banking
Restaurant / POS
Medical
Security
Factory Automation
CANbus Application
Transportation
Kiosk and Self-service
Public Utilities
Public Utilities
-
Application Video - EV Charging Station
-
Application Video - IoT Environmental Monitoring Solution
-
Currency Printing: Banknote Printing and Counterfeit Banknote Prevention
-
Airport : Airport Environment Monitoring System
-
Water Quality Monitoring : 2008 Beijing Olympics Project
-
Military : Missile Launch Control Testing a nd Simulation System
PCB Manufacturing Intelligent AOI System
PCB Manufacturing Intelligent AOI System
| Application Challenges
PCB manufacturing is highly competitive but not allowed to compromise accuracy. Traditional AOI(Automated Optical Inspection) systems suffer from high overkill rates due to accuracy limitations, leading to excessive rejection of functional components. PCB defects vary in complexity, from visible flaws to subtle anomalies. Also, PCB manufacturing often operates at high speeds, requiring AI AOI systems to perform inspections rapidly without compromising accuracy. Hence, Choosing the AI computing capability with high cost-performance ratio and low power consumption becomes an urgent issue.
| Application Goal
Necessity to adopt AI AOI in PCB manufacturing
AOI integrated with Artificial Intelligence (AI) is transforming PCB manufacturing quality control.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
◆ AI enhances traditional AOI systems by enabling rapid defect detection and classification.
◆ AI AOI systems can detect subtle defects that may go unnoticed by human inspectors or traditional AOI systems.
◆ This level of precision enables manufacturers to improve product quality, reduce material waste, and enhance overall production efficiency.
Pain point:
※ Using a CPU for AI inference requires high-end processors like the Core i9 or i7, which raises system costs, consumes a lot of power, and delivers subpar performance.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
※ Using a GPU for AI inference involves high-end graphics cards that are utilized mainly for their acceleration capabilities, but this also comes with high power consumption and expense.
| Solution Architecture
Importing SUNIX AI AOI detection
| Product Feature
| Portfolio
SUNIX AI Series
Solutions
AI Inference
Banking
Restaurant / POS
Medical
Security
Factory Automation
CANbus Application
Transportation
Kiosk and Self-service
Public Utilities
Public Utilities
-
Application Video - EV Charging Station
-
Application Video - IoT Environmental Monitoring Solution
-
Currency Printing: Banknote Printing and Counterfeit Banknote Prevention
-
Airport : Airport Environment Monitoring System
-
Water Quality Monitoring : 2008 Beijing Olympics Project
-
Military : Missile Launch Control Testing a nd Simulation System
