Vision Builder for Automated Inspection

• An understanding of basic electronics and inspection systems
• Experience with machine vision concepts or SMT processes
• Familiarity with Windows-based applications and general programming logic

Audience

• Automation engineers
• Quality assurance professionals working with SMT production lines
• Vision system developers and IoT specialists

Vision Builder for Automated Inspection (Vision Builder AI) is a graphical software environment for configuring, benchmarking, and deploying machine vision applications without programming.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to use Vision Builder AI to design, implement, and optimize automated inspection systems for SMT (Surface-Mount Technology) processes.

By the end of this training, participants will be able to:

• Set up and configure automated inspections using Vision Builder AI.
• Acquire and preprocess high-quality images for analysis.
• Implement logic-based decisions for defect detection and process validation.
• Generate inspection reports and optimize system performance.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Module 1: Introduction to Vision Builder AI and SMT Fundamentals

• Introduction to Vision Builder AI
  • Configuration and Inspection Interface
  • Inspection State Diagram
  • Basic Inspection Workflow
• SMT Fundamentals
  • SMT Assembly Process
  • Component Placement Defects (misalignment, rotation, absence, polarity, etc.)
  • Introduction to SPI and AOI

Module 2: Image Acquisition and Preprocessing

• Image Acquisition in Vision Builder AI
  • Image Acquisition Configuration (Simulate Acquisition)
  • Camera Types and SMT Considerations (resolution, lighting)
• Image Preprocessing
  • Filters to Enhance Features (edges, contrast)
  • Noise Reduction Techniques

Module 3: Component Location and Coordinate Adjustment

• Locating SMT Components
  • Using Match Pattern to Find Components
  • Template Creation Considerations (component variations)
  • Using ROI (Region of Interest) to Optimize Search
• Coordinate Systems
  • Creating Coordinate Systems Based on Component Location
  • Spatial Calibration (pixels to real-world units)

Module 4: Placement Defect Inspection

• Presence/Absence Inspection
  • Using Measure Intensity to Verify Component Presence
  • Detection of Missing Components
• Displacement Measurement
  • Using Measurement Tools (Geometry, Caliper) to Quantify Displacement
  • Calculating Deviation from Nominal Position
• Solder Inspection
  • Shape and Size Analysis (SPI)
  • Bridge and Insufficient Solder Detection (AOI)
• Polarity Detection
  • Pattern Recognition Techniques for Orientation Verification

Module 5: Logical Decisions, Reporting, and Optimization

• Logical Decision Making
  • Using Logic Calculator to Combine Inspection Results
  • Defining Pass/Fail Criteria
• Reporting and Data Output
  • Extracting Measurement Data
  • Communicating Results to External Systems
• Inspection System Optimization
  • Improving Inspection Speed
  • Parameter Adjustment for Accuracy
  • Common Troubleshooting Techniques

Summary and Next Steps