Improving time estimation accuracy in manufacturing systems: experimental assessment of MOST predetermined motion time system using laboratory data and Fitts' law

Farhad Mazareinezhad, Firdaous Sekkay and Daniel Imbeau

Article (2025)

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Uncontrolled Keywords

• Mechanical Engineering
• Cognitive Neuroscience
• Human-Computer Interaction
• Teleoperation and Haptic Systems
• Tactile and Sensory Interactions
• Gaze Tracking and Assistive Technology

Additional Information:	The research was conducted in compliance with Polytechnique Montréal's ethical standards and was approved under certificate CER-2223–38-D.
Department:	Department of Mathematics and Industrial Engineering
Funders:	Mitacs Canada
Grant number:	IT23624
PolyPublie URL:	https://publications.polymtl.ca/65987/
Journal Title:	The International Journal of Advanced Manufacturing Technology
Publisher:	Springer Science+Business Media
DOI:	10.1007/s00170-025-15791-6
Official URL:	https://doi.org/10.1007/s00170-025-15791-6
Date Deposited:	05 Jun 2025 15:32
Last Modified:	05 Jun 2025 15:32

Cite in APA 7:	Mazareinezhad, F., Sekkay, F., & Imbeau, D. (2025). Improving time estimation accuracy in manufacturing systems: experimental assessment of MOST predetermined motion time system using laboratory data and Fitts' law. The International Journal of Advanced Manufacturing Technology, 17 pages. https://doi.org/10.1007/s00170-025-15791-6
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