Industry 4.0

Date of Defense


Date of Graduation




First Advisor

Pavel Ikonomov

Second Advisor

Jason Johnson


The ultimate goal of this project is to automate quality control processes on various machines which include 3D printers, welders, routers, CNCs, and more. Using the “Digital Twin” approach, we want to automate monitoring, data collection, data analysis, and corrective action. Our involvement begins with building a new piece of software that can perform two specific functions and collect data from cameras. We are not attempting to analyze the data, make corrective action, or design a final version of the physical attributes. Our software provides the user with the ability to capture an image set or a 3D scan and save it to a directory. The software is comprised of an interface that connects to five cameras and a laser on a stepper motor through an Arduino.

The scanning portion of the project utilizes preexisting, open-source laser scanning software called Makerscanner. Makerscanner uses a standard USB webcam along with a LED line laser to create a point cloud model of the target object. Because the distance from the line laser to the center of the camera and the distance from the camera to the background is known/set, Makerscanner can accurately triangulate the height of the object’s features by the deflection of the laser line compared with a flat background. A stepper motor connected to the Arduino through a motor driver is used to rotate the laser in order to sweep the laser line across the object being scanned.

This project’s GUI is programmed in Python and handles the camera capture process, communication with the Arduino, and interfaces with Makerscanner. The capture and scanning processes can be started manually from the GUI or automatically from signals received from the Arduino. Parameters of the scanning and capture processes like the stepper motor speed, number of laser sweeps, and which cameras are captured can be set using the GUI as well.


Co-authored with:

Josh Getsinger

William Sinn

Jaden Perrine

Access Setting

Honors Thesis-Open Access

Included in

Data Science Commons