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All Outputs (70)

A Decision Support Model for Efficient Garment Reprocessing for a Sustainable Circular Business Model (2025)
Journal Article
Patel, H., Vasantha, G., Corney, J., Quigley, J., Raoui, H. E., Sales, R., Cusack, M., Burns, A., & Rough, A. (in press). A Decision Support Model for Efficient Garment Reprocessing for a Sustainable Circular Business Model. International Journal of Advanced Manufacturing Technology,

The rapidly growing fashion business has intensified environmental, and sustainability concerns due to its focus on high-volume production at low costs. The rental-based business models in the circular economy, by promoting alternative approach of ga... Read More about A Decision Support Model for Efficient Garment Reprocessing for a Sustainable Circular Business Model.

A scheduling decision-making framework using machine learning algorithm for energy efficient integrated factory (2025)
Presentation / Conference Contribution
Patel, H., Vasantha, G., Corney, J., Quigley, J., Raoui, H.-E., Sales, R., & Smith, S. (2025, June). A scheduling decision-making framework using machine learning algorithm for energy efficient integrated factory. Presented at FAIM 2025: The International Conference on Flexible Automation and Intelligent Manufacturing, New York

Sustainability enhancement is key factor in industrial decision-making. Maximizing use of energy-efficient factory to fulfill customer order deadlines is a significant problem for manufacturers. This paper focus on the study of integrated factory wit... Read More about A scheduling decision-making framework using machine learning algorithm for energy efficient integrated factory.

Experiences of Design for Disability in Collaborating with Students and Industries (2025)
Book Chapter
Harris, N., & Vasantha, G. (2025). Experiences of Design for Disability in Collaborating with Students and Industries. In Future of Design Education: InFuSED23 (205-219). Springer. https://doi.org/10.1007/978-981-97-7363-3_14

This chapter looks at the design and engineering of products to assist people with disability. It looks at the process that companies, disability organisations and universities employ to help develop aids and products that solve various needs. Althou... Read More about Experiences of Design for Disability in Collaborating with Students and Industries.

Analysing Spatio-Temporal Worker Movement Patterns: Implications for Safety and Productivity in Smart Factories (2025)
Presentation / Conference Contribution
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

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 factor... Read More about Analysing Spatio-Temporal Worker Movement Patterns: Implications for Safety and Productivity in Smart Factories.

Safer and Efficient Factory by Predicting Worker Trajectories using Spatio-Temporal Graph Attention Networks (2024)
Presentation / Conference Contribution
Kasarapu, S. S. K., Vasantha, G., Corney, J., Hanson, J., Quigley, J., El-Raoui, H., Thompson, N., & Sherlock, A. (2024, August). Safer and Efficient Factory by Predicting Worker Trajectories using Spatio-Temporal Graph Attention Networks. Presented at IDETC-CIE International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Washington, DC

Occupational accidents in manufacturing industries pose a significant risk, necessitating advanced strategies to ensure worker safety and enhance operational productivity. The unpredictable nature of worker movements, influenced by varied tasks such... Read More about Safer and Efficient Factory by Predicting Worker Trajectories using Spatio-Temporal Graph Attention Networks.

Safer and Efficient Assemblies: Harnessing Real Time Worker Movements with Digital Twins (2024)
Presentation / Conference Contribution
Kasarapu, S. S. K., Vasantha, G., Marzano, A., Corney, J., Hanson, J., Quigley, J., El-Raoui, H., Thompson, N., & Sherlock, A. (2024, August). Safer and Efficient Assemblies: Harnessing Real Time Worker Movements with Digital Twins. Presented at 21st International Conference on Manufacturing Research (ICMR2024), Glasgow

This paper addresses a critical gap in digital twin simulation within manufacturing environments by focusing on the dynamic representation of worker movements during assembly processes. We introduce an innovative approach that utilizes Ultra-Wideband... Read More about Safer and Efficient Assemblies: Harnessing Real Time Worker Movements with Digital Twins.

Smarter Facility Layout Design: Leveraging Worker Localisation Data to Minimise Travel Time and Alleviate Congestion (2024)
Journal Article
Aslan, A., Vasantha, G., El-Raoui, H., Quigley, J., Hanson, J., Corney, J., & Sherlock, A. (2025). Smarter Facility Layout Design: Leveraging Worker Localisation Data to Minimise Travel Time and Alleviate Congestion. International Journal of Production Research, 63(4), 1326-1353. https://doi.org/10.1080/00207543.2024.2374847

This paper introduces a novel methodology leveraging worker localisation data from ultrawide-band sensors to formulate alternative facility layouts aimed at minimising travel time and congestion in labour-intensive manufacturing systems. The system p... Read More about Smarter Facility Layout Design: Leveraging Worker Localisation Data to Minimise Travel Time and Alleviate Congestion.

Design Of A Serious Game For Safety In Manufacturing Industry Using Hybrid Simulation Modelling: Towards Eliciting Risk Preferences (2024)
Presentation / Conference Contribution
El Raoui, H., Quigley, J., Aslan, A., Vasantha, G., Hanson, J., Corney, J., & Sherlock, A. (2023, December). Design Of A Serious Game For Safety In Manufacturing Industry Using Hybrid Simulation Modelling: Towards Eliciting Risk Preferences. Presented at The Winter Simulation Conference 2023, San Antonio, Texas

Conventional methods used to elicit risk-taking preferences have demonstrated significant disparities with real-world behaviours, compromising the validity of the data collected. Serious gaming (SG) provides a high potential to bridge this gap. This... Read More about Design Of A Serious Game For Safety In Manufacturing Industry Using Hybrid Simulation Modelling: Towards Eliciting Risk Preferences.

Cognitive Factors Affecting the Manufacturing Optimization Skills of Rural Indian BPO Workers (2023)
Journal Article
Vasantha, G., Corney, J., & Upadhyay, C. K. (2023). Cognitive Factors Affecting the Manufacturing Optimization Skills of Rural Indian BPO Workers. Knowledge, 3(4), 626-641. https://doi.org/10.3390/knowledge3040039

Crowdsourcing offers on-demand access to large numbers of human workers to implement new forms of human–computer collaborative functionalities that can be seamlessly integrated into advanced software and algorithms. However, crowdsourcing tasks are p... Read More about Cognitive Factors Affecting the Manufacturing Optimization Skills of Rural Indian BPO Workers.

Hierarchical ensemble deep learning for data-driven lead time prediction (2023)
Journal Article
Aslan, A., Vasantha, G., El-Raoui, H., Quigley, J., Hanson, J., Corney, J., & Sherlock, A. (2023). Hierarchical ensemble deep learning for data-driven lead time prediction. International Journal of Advanced Manufacturing Technology, 128(9-10), 4169-4188. https://doi.org/10.1007/s00170-023-12123-4

This paper focuses on data-driven prediction of lead times for product orders based on the real-time production state captured at the arrival instants of orders in make-to-order production environments. In particular, we consider a sophisticated manu... Read More about Hierarchical ensemble deep learning for data-driven lead time prediction.

A Knowledge Graph Approach for State-of-the-Art Implementation of Industrial Factory Movement Tracking System (2023)
Presentation / Conference Contribution
Vasantha, G., Aslan, A., Hanson, J., El-Raoui, H., Corney, J., & Quigley, J. (2023, June). A Knowledge Graph Approach for State-of-the-Art Implementation of Industrial Factory Movement Tracking System. Presented at International Conference on Flexible Automation and Intelligent Manufacturing, Porto, Portugal

Digital sensing technologies are essential for realizing Industry 4.0, as they enhance productivity, assist with real-time decision-making, and provide flexibility and agility in manufacturing factories. However, implementing these technologies can b... Read More about A Knowledge Graph Approach for State-of-the-Art Implementation of Industrial Factory Movement Tracking System.

Movement Tracking-Based In-Situ Monitoring System for Additive Manufacturing (2023)
Presentation / Conference Contribution
Vasantha, G., Aslan, A., Lapok, P., Lawson, A., & Thomas, S. (2023, June). Movement Tracking-Based In-Situ Monitoring System for Additive Manufacturing. Presented at FAIM 2023: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems, Porto, Portugal

Monitoring and identification of defects during additive manufacturing is mostly done by bespoke optical or acoustic measurement systems. These in-situ monitoring technologies are either intrusive or sensitive to noisy manufacturing environments. We... Read More about Movement Tracking-Based In-Situ Monitoring System for Additive Manufacturing.

Data-driven Discovery of Manufacturing Processes and Performance from Worker Localisation (2023)
Presentation / Conference Contribution
Aslan, A., El-Raoui, H., Hanson, J., Vasantha, G., Quigley, J., & Corney, J. (2023, June). Data-driven Discovery of Manufacturing Processes and Performance from Worker Localisation. Presented at 32nd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2023), Porto, Portugal

In complex manufacturing industries that are not fully automated and involve human workers it is important to identify deviations from the planned production schedule and locate bottlenecks for improved efficiency. This is not an easy task as it requ... Read More about Data-driven Discovery of Manufacturing Processes and Performance from Worker Localisation.

Using Worker Position Data for Human-Driven Decision Support in Labour-Intensive Manufacturing (2023)
Journal Article
Aslan, A., El-Raoui, H., Hanson, J., Vasantha, G., Quigley, J., Corney, J., & Sherlock, A. (2023). Using Worker Position Data for Human-Driven Decision Support in Labour-Intensive Manufacturing. Sensors, 23(10), Article 4928. https://doi.org/10.3390/s23104928

This paper provides a novel methodology for human-driven decision support for capacity allocation in labour-intensive manufacturing systems. In such systems (where output depends solely on human labour) it is essential that any changes aimed at impro... Read More about Using Worker Position Data for Human-Driven Decision Support in Labour-Intensive Manufacturing.

Using Worker Position Data for Human-Driven Decision Support in Labour-intensive Manufacturing (2023)
Data
Aslan, A., El-Raoui, H., Hanson, J., Vasantha, G., Quigley, J., Corney, J., & Sherlock, A. (2023). Using Worker Position Data for Human-Driven Decision Support in Labour-intensive Manufacturing. [Data]. https://doi.org/10.17869/enu.2023.3100035

This data contains the worker position datasets (including the event logs) and the source codes of the discrete event simulation that are used in the research article titled "Using Worker Position Data for Human-Driven Decision Support in Labour-inte... Read More about Using Worker Position Data for Human-Driven Decision Support in Labour-intensive Manufacturing.

Agent based simulation of workers’ behaviours around hazard areas in manufacturing sites (2023)
Presentation / Conference Contribution
El Raoui, H., Quigley, J., Aslan, A., Vasantha, G., Hanson, J., Corney, J., & Sherlock, A. (2023, March). Agent based simulation of workers’ behaviours around hazard areas in manufacturing sites. Presented at The Operational Research Society Simulation Workshop 2023 (SW23), Southampton, UK

Rewards for risk taking behaviour by workers (if accidents do not occur) can be realised in the form of increased productivity or worker idle time. However, frequent unsafe behaviours of workers inevitably
results in accidents and an associated loss... Read More about Agent based simulation of workers’ behaviours around hazard areas in manufacturing sites.

Towards Predictive Design: Tracking a CNC Fixture Design Process to Identify the Requirements (2022)
Presentation / Conference Contribution
Vasantha, G., Purves, D., Corney, J., Canavan, M., Quigley, J., & Sherlock, A. (2022, September). Towards Predictive Design: Tracking a CNC Fixture Design Process to Identify the Requirements. Presented at International Conference on Manufacturing Research ICMR 2022, Derby, UK

Training novice production engineers to design manufacturing fixtures is a time-consuming process involving significant input from experienced experts. Motivated by the vision of providing an intelligent support system for general mechanical design,... Read More about Towards Predictive Design: Tracking a CNC Fixture Design Process to Identify the Requirements.

Assessment of Predictive Probability Models for Effective Mechanical Design Feature Reuse (2022)
Journal Article
Vasantha, G., Purves, D., Quigley, J., Corney, J., Sherlock, A., & Randika, G. (2022). Assessment of Predictive Probability Models for Effective Mechanical Design Feature Reuse. Artificial intelligence for engineering design, analysis and manufacturing : AI EDAM, 36, Article e17. https://doi.org/10.1017/S0890060422000014

This research envisages an automated system to inform engineers when opportunities occur to use existing features or configurations during the development of new products. Such a system could be termed a `predictive CAD system' because it would be a... Read More about Assessment of Predictive Probability Models for Effective Mechanical Design Feature Reuse.