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Project # 8
Optimizing Warehouse Order Picking: A Comparative Study of Paper, Handheld, and Augmented Reality Methods
| Team Lead: | Russel Abdullah |
| Other Team Members: | | Matin Ghasempour Anaraki |
| Faculty Advisor(s): | Dr. Mahmudur Rahman |
| Department: | IMSE |
| Project Type: | Graduate Student |
| Title: | Optimizing Warehouse Order Picking: A Comparative Study of Paper, Handheld, and Augmented Reality Methods |
| Abstract: | Order picking plays a vital role in warehouse efficiency, influencing productivity, accuracy, and cognitive workload. This study compares Paper-based, Handheld Device (HHD), and Augmented Reality (AR) picking methods to evaluate their impact on performance, error rates, situation awareness (SA), and workload. A controlled experiment with 15 participants measured items picked, errors, SA, and NASA TLX workload. Results show AR picking had the highest efficiency (mean items picked: 79.4), followed by Paper (77.6) and HHD (58.8), with a significant difference (p = 0.024). Error rates remained statistically similar across methods. SA analysis revealed HHD had the highest awareness (mean = 9.30), followed by Paper (9.15), while AR had the lowest (8.38), likely due to increased cognitive demand. NASA TLX workload scores showed AR imposed the least strain (25.87), while HHD had the highest (37.37). Despite its lower SA, AR picking emerged as the most efficient and least physically demanding, whereas HHD increased cognitive and physical strain. These findings suggest AR technology offers a promising alternative to traditional methods, enhancing efficiency while reducing worker fatigue, though cognitive adaptation is required for optimal usability. |
| Poster: | View Poster #8 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |