Machine Vision with Keyence IV 2 Built-In AI

Explore machine vision basics, including monochrome vs color, brightness and contrast, and field of view and depth of field, with built-in AI enabling faster programming and streamlined lighting and lenses.

Explore the physical setup of a Keyence IV-2 vision system, detailing components (controller, sensor amplifier, camera), interconnects (Ethernet, IO ribbon), power needs, lens and lighting options, and safe enclosure installation.

Perform the physical setup by mounting the controller and sensor head, connect the 24V power and Ethernet, and link the sensor with the umbilical and IO cables; monitor LED indicators.

Learn how to download and install the machine vision software, meet system requirements like Windows 10 and at least 8 GB RAM, and secure CSV files, manuals, and EDS files.

Demonstrates downloading and installing the iv2 navigator software from Keyence, including account creation, software and csv downloads, optional ip files, and essential manuals.

Install the vision software from the download folder, run the executable, then open the software to access edes files, progressors, manuals, csv files, and csp files.

Download and extract the IVI to Navigator software, run the installer, accept the license, choose install location and desktop icon, and complete the setup.

Demonstrates configuring the ai learning mode on a Keyence iv system, creating a master image, defining search windows, labeling good and bad waffles, and saving the program.

Create a second AI program for the machine vision sensor, expanding the AI process with multiple search windows, good/bad image criteria, masks, and testing to meet specs.

Set up a second AI program using multiple tools to inspect waffle quality and conveyor position, using learning mode to register images and calibrate windows for accurate pick-and-place.

Create a manual machine-vision program with the drive to vision sensor, covering naming conventions, lighting, focus, trigger, a golden image, up to 16 tools, and testing.

Set up a manual program for the iv 2 vision sensor, configure standard mode with auto brightness and focus, and use an outline tool to detect the circular waffle.

demonstrates adding good and bad images with the aid function to calibrate the vision sensor and refine AI-driven inspections, including single or multiple images via the sensor setup.

Demonstrates adding good and bad images to the artificial intelligence function, using single and multiple image learning, additional learning and learning settings in program mode to improve threshold and accuracy.

Adjust the image threshold on the Keyence IV2 vision sensor to meet criteria, noting that zero threshold disables the tool and the ai function's thresholds affect contrast and blob count.

Adjust thresholds in the three-tool machine vision demo using limit adjustment to lower sliders from 50 to 30 and raise another to 70 to maintain waffles' quality.

Save and back up machine vision programs to disk or on the entire system, restore or transfer via Ethernet to a new controller, and configure IP settings for network programming.

Save and restore machine vision programs with batch or individual backups in the Network Navigator software, transfer program settings to the IV 2 controller, and safeguard AI controls programs.

Configure ethernet IP in the IV2 Navigator with the PLC IP and subnet. Then set transfer conditions and output destination, and adjust device name.

Conclude the course with a walkthrough of building a machine vision application using the Kansai v2 vision sensor and Iveta Navigator software, covering installation, programming, threshold tuning, and IP configuration.