Dr Gokula Vasantha G.Vasantha@napier.ac.uk
Associate Professor
Dr Gokula Vasantha G.Vasantha@napier.ac.uk
Associate Professor
Hariketan Patel
Jack Hanson
Jonathan Corney
Hanane El-Raoui
Rachel Sales
John Quigley
Satya Saravan Kasarapu
Andrew Sherlock
Understanding the spatio-temporal dynamics of worker movements within complex factory environments, such as shipbuilding facilities, is crucial for proactively assessing safety and enhancing operations through potential process adjustments and factory layout optimizations. While existing literature offers methods to study worker movements, the detailed elicitation of movement patterns remains limited. This research proposes an analytical framework for studying spatio-temporal worker movements using Ultra-Wideband (UWB) tracking data. The framework classifies worker movements into two categories: dwell and transit, serving as the foundation for uncovering movement patterns. The study reports the movement patterns derived from data collected on six workers performing an assembly task and offers actionable recommendations to improve workplace safety and productivity.
Vasantha, G., Patel, H., Hanson, J., Corney, J., El-Raoui, H., Sales, R., Quigley, J., Kasarapu, S. S., & Sherlock, A. (2025, June). Analysing Spatio-Temporal Worker Movement Patterns: Implications for Safety and Productivity in Smart Factories. Presented at 11th IFAC Conference on Manufacturing Modelling, Management and Control – IFAC MIM2025, Norway
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 11th IFAC Conference on Manufacturing Modelling, Management and Control – IFAC MIM2025 |
Start Date | Jun 30, 2025 |
End Date | Jul 3, 2025 |
Acceptance Date | Feb 10, 2025 |
Deposit Date | Mar 16, 2025 |
Journal | IFAC-PapersOnLine |
Print ISSN | 2405-8971 |
Electronic ISSN | 2405-8963 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Series Number | 2405-8971 |
Keywords | Worker safety, Facility planning and materials handling, Industry 4.0, Risk Management |
Public URL | http://researchrepository.napier.ac.uk/Output/4176891 |
Publisher URL | https://www.sciencedirect.com/journal/ifac-papersonline |
External URL | https://conferences.ifac-control.org/mim2025/proceedings/ |
This file is under embargo due to copyright reasons.
Contact repository@napier.ac.uk to request a copy for personal use.
Safer and Efficient Factory by Predicting Worker Trajectories using Spatio-Temporal Graph Attention Networks
(2024)
Presentation / Conference Contribution
Design Of A Serious Game For Safety In Manufacturing Industry Using Hybrid Simulation Modelling: Towards Eliciting Risk Preferences
(2024)
Presentation / Conference Contribution
Hierarchical ensemble deep learning for data-driven lead time prediction
(2023)
Journal Article
A Knowledge Graph Approach for State-of-the-Art Implementation of Industrial Factory Movement Tracking System
(2023)
Presentation / Conference Contribution
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
Apache License Version 2.0 (http://www.apache.org/licenses/)
Apache License Version 2.0 (http://www.apache.org/licenses/)
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search