Project Overview

Modern manufacturing increasingly relies on efficient, flexible, and error-resistant assembly processes, particularly in environments involving high product variability and human-machine collaboration. Traditional computer-based instructions (e.g., on monitors or tablets) require workers to shift attention between the workspace and instruction interface, which can increase cognitive load and reduce efficiency.

This REU project aims to develop and evaluate an augmented reality (AR)-based guidance system for manufacturing assembly tasks. Using a mixed-reality headset, students will design an interactive system that overlays step-by-step instructions directly onto physical components, as illustrated in the experimental workstation setup (bins with parts, tools, and assembly components). The AR system will be compared against conventional computer-based instructions to assess improvements in performance, usability, and user experience.

Research Objectives

The project will focus on the following key objectives:

1. Development of AR Assembly Guidance System

   • Design AR interfaces that visually guide users through assembly tasks (e.g., highlighting bins, parts, and assembly locations).

   • Integrate spatial tracking to align virtual instructions with physical components.

   • Implement interactive features such as step progression, error feedback, and visual cues.

2. Experimental Testbed Implementation

   • Utilize a structured assembly workstation with organized bins containing parts (as shown in the setup).

   • Develop standardized assembly tasks involving multi-step processes and component selection.

3. Comparative Evaluation

   • Compare AR-based guidance with traditional computer-based instructions displayed on a monitor.

   • Measure:

     • Task completion time

     • Error rates

     • Cognitive workload (e.g., NASA-TLX or SimTLX)

     • System usability (SUS)

     • User attention and behavior (optional: eye tracking or physiological data)

4. Human Factors and System Design Insights

   • Investigate how AR influences attention, situational awareness, and task efficiency.

   • Identify design principles for effective AR interfaces in manufacturing systems.

Student Activities

Participants will gain hands-on experience in:

• Developing AR applications (e.g., using Unity, Unreal Engine, or similar platforms)

• Designing human-centered interfaces for industrial systems

• Conducting user experiments and data collection

• Analyzing performance and human factors data

• Presenting findings in reports and research posters

Expected Outcomes

• A functional AR-based assembly guidance prototype

• Experimental dataset comparing AR and traditional instruction methods

• Design guidelines for AR-assisted manufacturing systems

• Contributions to research in human–systems engineering and smart manufacturing