Purdue University Graduate School
Alexander_Meredith_MSET-Thesis_May_2023.pdf (5.41 MB)

Development and Evaluation of a Machine Vision System for Digital Thread Data Traceability in a Manufacturing Assembly Environment

Download (5.41 MB)
posted on 2023-04-29, 01:31 authored by Alexander W MeredithAlexander W Meredith

A thesis study investigating the development and evaluation of a computer vision (CV) system for a manufacturing assembly task is reported. The CV inference results are compared to a Manufacturing Process Plan and an automation method completes a buyoff in the software, Solumina. Research questions were created and three hypotheses were tested. A literature review was conducted recognizing little consensus of Industry 4.0 technology adoption in manufacturing industries. Furthermore, the literature review uncovered the need for additional research within the topic of CV. Specifically, literature points towards more research regarding the cognitive capabilities of CV in manufacturing. A CV system was developed and evaluated to test for 90% or greater confidence in part detection. A CV dataset was developed and the system was trained and validated with it. Dataset contextualization was leveraged and evaluated, as per literature. A CV system was trained from custom datasets, containing six classes of part. The pre-contextualization dataset and post-contextualization dataset was compared by a Two-Sample T-Test and statistical significance was noted for three classes. A python script was developed to compare as-assembled locations with as-defined positions of components, per the Manufacturing Process Plan. A comparison of yields test for CV-based True Positives (TPs) and human-based TPs was conducted with the system operating at a 2σ level. An automation method utilizing Microsoft Power Automate was developed to complete the cognitive functionality of the CV system testing, by completing a buyoff in the software, Solumina, if CV-based TPs were equal to or greater than human-based TPs.


Degree Type

  • Master of Science


  • Engineering Technology

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Nathan W. Hartman

Additional Committee Member 2

Chad Laux

Additional Committee Member 3

Jorge D. Camba