Computer Vision automation of MOST analysis.

Sponsor: Center for High Performance Systems (CHiPS) Lab   
Student Team: Claire Pauwels, Tyler Haug, Kenya Frias Rodriguez, Jade Ong  
Project Advisor(s):  Mr. Abhimanyu Sharotry 
Faculty Instructor: Dr. Gerardo Trevino-Garza

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This project applies time and motion studies, specifically MOST, to analyze wagon disassembly tasks using video-based protocols. Alongside traditional industrial engineering measurement techniques, a computer vision model is being developed to automatically detect task elements and compute MOST-based standardized times. Classical manual analysis is systematically compared with AI-driven methods, with documentation of error sources and process bottlenecks. The objective is to advance the integration of automated vision systems with established time study methodologies in practical industrial environments.

I2.01 Project Presentation

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I2.01 Project Presentation

I2.01 Poster Pitch

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I2.01 Poster.pdf

Team Contact Information

Team Project Manager: Claire Pauwels, gcg78@txstate.edu

Faculty Instructor: Dr. Gerardo Trevino-Garza, hts35@txstate.edu

I2.01 Group Photo
From left to right (Tyler Haug, Kenya Frias Rodriguez, Jade Ong, Claire Pauwels)

Let us know what you think! You can evaluate our project here: I2.01 Evaluation Form