Projects

AI6S: Energy and waste reduction in Foundation Industries

Currently working on an Innovate UK project that explores the use of Artificial Intelligence and Lean Six Sigma for energy intensive foundation industries. The multi-disciplinary consortium will use machine learning to improve lean six sigma process optimisation for foundation industries that help identify and eliminate wastes. As part of the project, Brunel University will develop a machine learning regression model to identify the sensitivity of the process parameters on the response variable which will provide insights into optimisation for energy consumption and product quality. This will be further verified and supported by the process simulation capabilities of the University of Sheffield. This algorithm will then be plugged in to the lean six sigma framework by IVY TECH. The ultimate aim is to provide an AI-Lean Six Sigma Platform for Foundation Industries such as metal, glass, ceramic, paper etc.

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ATTIC: Automated TeraherTz Imaging of Composites and tooling profiling

Currently working on an Innovate UK project that explores the use of Deep Learning and defect localisation for condition monitoring and Zero Defect Manufacturing. The overall objective of this project is to develop an automated on-line defect detection system of drilled composites. This will reduce the manual workload and serve as an enabler for zero defect manufacturing in composite structures. Laser profilers will be used scan and monitor the tooling system and terahertz imaging techniques are employed to detect and localise defects in the drilled composites. The deep learning technique of Faster R-CNN is used to process, learn, classify and localise the defects in the terahertz images. Advanced AI software will be employed to monitor the wear of the tools. The inspection systems are mounted on advanced and flexible robots for condition monitoring and defect detection.

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Automated Module to pack Pilot Line for Industrial Innovation (AMPLiFII)

A two year Innovate UK funded project with the aim of exploring the electric vehicle battery module and pack manufacture in the UK. As part of this project, I worked on the design of a modular automated battery assembly system and created process and product flow models of the pilot line at WMG. Several publications regarding the scalability of battery manufacturing lines were also presented as part of the project.

Digital material characterisation proof of process auto assembly (DigiMan)

The aim of the DigiMan project was to develop production capability for automotive PEM fuel cell stacks in EU. Intelligent Energy fuel cell technology was used for the project. My main role was to develop digital models and Discrete-Event Simulations of the fuel cell assembly systems and perform manufacturing feasibility analysis.

Integrated Manufacturing and Logistics (IML)

This project explores the collaboration of legacy manufacturing systems with state-of-the art Industry 4.0 material handling systems. This system serves as a demonstrator and education test-bed. My role in the project was to develop battery module designs, evaluate the assembly process and comparison of various scenarios using Discrete-Event Simulation.

Lear Seat Manufacturing (LSM)

The LSM project involved the analysis of various system designs for high variety manufacturing. The concepts of digitalisation and data-driven simulation were employed to understand and automate the seat manufacturing process. I worked on the creation of customisable parametric DES models that use data from Excel documents.

AMPLiFII 2

The main focus of this Innovate UK project is the production line modelling, simulation and data collection. This is enabling the system to support associated Industry 4.0 proving activities, e.g. via the creation of electronic work instructions, digital process validation and analytics. My main role was to create a digital twin of the assembly system during the concept phases that was used to make various decisions prior to the commissioning of the system.

H1PERBAT

H1PERBAT is a two-year, £8 million, Innovate UK funded project with the aim of establishing a UK pilot facility for high performance batteries. My main role was to support the design and commissioning of the pilot production line at its Coventry manufacturing centre. Various process flow and material handling solutions were analysed using a concept phase Digital Twin of the assembly system.

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