High-Value Manufacturing Research Group
Cutting edge research into materials, systems and technologies down to the micro/nano scale.
The High Value Manufacturing (HVM) Group conducts world class research that has valuable impacts and applications in manufacturing industry.
The Group has a strong track record of collaborative research with industrial partners to solve manufacturing challenges, including working with Airbus, BAE Systems, Bosch, Mazak, Ortho Clinical Diagnostics, Qioptiq, Renishaw, Sony, Tata Steel and Zimmer Biomet. It is established as a centre of excellence within Europe and has extensive, modern laboratories and state of the art equipment. Industrial partners are able to access equipment, academic expertise and skilled technical specialists.
The HVM group conducts research across a range of areas including:
- Additive Layer Manufacturing – Wide range of technologies including selective laser sintering, photo polymerisation (stereolithography), fused deposition modelling, selective laser sintering and 3D printing.
- Autonomous Systems and Robotics – Industrial robotics, service robotics, robots for medical applications and security, autonomous/semiautonomous control, human-robot interaction, intelligent navigation, object recognition and human tracking.
- Design and Manufacturing – Digital design, digital manufacturing, computer-aided product, process and systems design, manufacturing informatics, digital life cycle management, business process modelling and Industry 4.0.
- Intelligent and Knowledge-based Systems – Data mining, knowledge discovery, image processing, decision and performance support systems, optimisation, pattern recognition, machine learning, semantics, knowledge management and knowledge-based applications.
- Micro/Nano Manufacturing – Laser machining, product miniaturisation, future product platforms and production scale-up.
- Smart Systems – Systems with embedded intelligence, smart sensors, intelligent condition monitoring and prognostics, machine and process health management strategies and high speed real time data analytics.
- Systems Engineering – Systems integration, systems modelling, risk assessment and risk management, Cyber-Physical systems, Internet of Things and Industry 4.0.
- Sustainable Manufacturing – Design for sustainability, sustainable manufacturing, resilient and sustainable supply chains, energy efficiency and re-manufacturing.
Additive Manufacturing Research
The Additive Manufacturing (AM) Laboratory is a pioneer of AM in the UK having conducted research in this field since 1995. The AM Laboratory has a strong track record of regional, national and international collaborative research with recognised leading organisations in AM (TNO, DTU, EPSRC CIM in AM), as well as industrial partners (Renishaw, BAE Systems, Qioptiq). Our partners can directly benefit from the unique expertise of our academic and skilled technician specialists developed over the last 20 years and access our extensive range of equipment comprising of an industrial fleet of three resin based machines (Stereolithography and Digital light processing), three polymer and one metal powder based machines based on Selective Laser Sintering (SLS) and Selective Laser Melting (SLM) technologies. The AM Lab conducts research across a range of areas including:
- Materials - Development of application specific metal materials for SLM and polymers for Fused Deposition Modelling (FDM).
- Design for Additive Manufacturing - Benefit from our experience in a wide range of AM processes to answer your design problem or develop functional geometries to answer specific requirements (weight reduction, shock or vibration absorption).
- Applications and simulation - Use computer simulation to improve design functionality, manufacturability, performance and topology optimisation.
- Process characterisation, improvement and stability - Develop a better understanding, monitor and improve the capabilities and processing conditions of your AM process.
- Manufacturing process chains - Incorporate AM to your existing manufacturing process chain. Combine AM with conventional and high values manufacturing processes.
- AM Support chain - Investigate AM supply chain and distribution.
Digital Manufacturing Research
The Digital Manufacturing (DM) laboratory has a strong track record of collaborative research with industrial partners including Airbus, Bosch, Ford, Mazak, Olympus Surgical, Ortho Clinical Diagnostics, Qioptiq, Renishaw, and Tata Steel. We are able to provide the digital and smart solutions needed in creating a knowledge based economy. Skilled researchers work in our modern laboratory, which is equipped with state of the art intelligent software and equipment. Industrial partners are able to work with us and access our facilities, academic expertise and skilled technical specialists. We provide bespoke digital manufacturing solutions to improve process flow, machine management and efficiency, profitability and sustainability. The DM Lab research interests include:
- Design Informatics - Create and exploit advanced ICT solutions to integrate complex design information and pervasive user-generated data in the design of innovative products, systems and services.
- Manufacturing Informatics - Harness ICT technology and advanced data analytics to improve manufacturing intelligence. Support collaboration, increase efficiency and provide decision support to boost innovation, and enable new business models and sustainable technologies.
- Industry 4.0/Cyber-Physical Systems - Embrace Industry 4.0 in the digitisation and automation in the factory and supply chain. Connect communication cyber-systems to physical machines and sensors for networking and information sharing. Analysis of information for prognostic condition-based maintenance. Develop, test and deploy autonomous control and decision making in real-time environments.
- Big data analytics - Examine large datasets to uncover hidden patterns, unknown working principles and correlations. Interpret intriguing market trends, latent customer preferences and implicit insights to enhance engineering design and manufacturing.
- Semantic Technologies - Extract knowledge and information from unstructured text and images using lexical resources, taxonomies, ontologies and semantic networks. Provide improved modelling, reasoning with meaning and context, and decision making.
Sustainable Manufacturing Research
We conduct research and innovation into sustainable products, processes, materials and supply chains, supporting manufacturing industry as it evolves towards a circular economy. For global long term prosperity, health and resilience manufacturing needs to evolve from a model of high resource consumption and waste production towards one that is resource neutral/ zero waste. Making the circular economy a reality is a major challenge for researchers and industry but working together we can develop sustainable products, processes, materials and supply chains. We provide bespoke manufacturing solutions to improve sustainability of products and processes, reduce waste and energy usage, increase resilience of supply chains and develop new environmentally-friendly materials. Research interests include:
- Sustainable Products - Design for sustainability, design for remanufacturing and end of life.
- Sustainable Processes - Energy efficiency, waste reduction and remanufacturing.
- Sustainable Materials - Including bio composites, composites using recyclates, metal matrix nano-composites for additive layer manufacturing.
- Decision Support - Product life cycle management, inventory forecasting and measuring sustainability.
- Supply Chains - Resilient and sustainable supply chains and reshoring.
Micro and Nano Manufacturing Research
The Micro and Nano Manufacturing (MNM) laboratory has been conducting research in this field since 2002. The MNM Lab carries out research in processes and process chains complementary to semiconductor-based fabrication techniques. The main driver is to advance manufacturing knowledge and applications for producing components and devices with micro and nano-scale functionalities in a wide range of materials. The MNM Lab has been involved in national and international collaborative research initiatives, which include leading organisations in Europe (KIT, DTU, IK4-TEKNIKER) and further afield (HIT China) as well as a number of key industrial partners (Zimmer-Biomet, Renishaw). Our facilities enable the direct machining or the replication of features ranging from a few tens of nanometres to a few hundred micrometres. These include short and ultra-short pulsed laser systems, a micro EDM machine and a micro injection moulding machine. These are completed by advanced micro- and sub-micrometre characterisation equipment for dimensional inspection (optical microscopes, white light interferometer, SEM), and for material characterisation and/or for nano-manufacturing operations (atomic force microscope, focussed ion beam). The MNM lab conducts research across a range of application areas including:
- Nanomachining for future magnetic-based data storage devices - Nanoscale machining realised with the tip of an AFM probe is used to create nanostructures for controlling magnetic domain walls along NiFe nanowires.
- Laser surface texturing of orthopaedic implants - Pulsed ns laser irradiation of biomedical material is conducted for investigating the effect of different surface textures on the wear resistance of implants.
- Micro mechanical machining of aerospace materials - Expertise in numerical simulation enables the modelling of the cutting process of advanced composite materials.
- Computer-aided micro manufacturing - AI tools are developed for the virtual design and automated control of MNM process chains.
- Post processing of 3D printed metallic components - Micro features are integrated on metallic components produced by ALM to improve surface finish and functionalization.
Robotics and Autonomous Systems Research
One of our major research interests is in Robotics and Autonomous Systems, in particular to endow a higher level of autonomy to unmanned systems, providing capabilities of advanced situation awareness, localisation and mapping, path planning, and multiple robot collaboration. We aim, as part of this research, to enable direct and safe collaboration between humans and robots to accomplish difficult tasks together that are beyond individual human capabilities, such as assembly, lifting heavy objects and logistics.
One of our long-term research aims is to enhance the robot cognitive capability by deploying advanced perceptual capabilities, such as vision, RGB-D, Lidar, and other sensors, in order to interpret human gestures, understand environments, and eventually become natural companions of humans. Currently we are working in three main research areas related to robotics.
We have invested in a Robotics and Autonomous Systems Laboratory with a range of cutting-edge equipment which supports our research.
Mobile Robotics and Autonomous Vehicles
We aim to investigate safe and reliable navigation solutions for autonomous vehicles and mobile robots to operate in real-world environments that are safety-critical, dynamic, and unstructured.
The research is focused on developing intelligent algorithms processing and interpreting large amount of sensing data from Lidar and computer cameras for environmental mapping and robot localisation in GPS denied environments. Our Robotics Laboratory currently has several mobile robots, including three Kuka Youbots, a number of Turtlebots and also some Drones.
We have also developed an unmanned surface vehicle (USV) that can autonomously navigate and avoid collisions by using Lidar and vision for obstacle detection. The project is now being undertaken by a group of students working on a landing system for the drone to track and land on the USV autonomously.
Robots in Unstructured Domestic Environments
We are also working on the development and prototyping of autonomous robotic solutions in domestic environments to support elderly people to live independently. Our research focus is on domestic service robots designed to enable:
- Intent-based remote control for robust tele-operation over a real-world communication network.
- Adaptive autonomy to enable a highly efficient task execution for remotely controlled service robots.
- Robotic self-learning mechanisms to enable robots to learn from their experience.
- A safety-oriented framework derived through extensive usability and user acceptance studies that enable service robots to be effectively deployed into home care applications.
Another focus for us is the use of multimodal human computer interfaces allowing natural human robot interactions through gaze tracking, brain-computer interfaces (BCI), and human gesture understanding.
We are also working on multi robot systems that accommodate heterogeneous agents, including human operators. This is especially challenging, particularly for large applications. Introducing humans into the loop presents even more technical challenges including:
- environmental understanding through visual object recognition and pose identification for grasping and manipulations in unstructured workspace
- human behaviour monitoring and understanding
- shared task planning for robots and humans or multiple robots
- robot programming by demonstration, where robots learn new skills by observing demonstration by human operators.
Robotics and Autonomous Systems Research
- Additive Manufacturing and Robotics to Support Improved Response to Increased Flexibility, Value: £884,673 including £652,661 from Continental and £232,012 from WEFO, February 2018 – February 2019.
- Autonomous Systems and Robotics Lab and Care-O-Bot 4.0, £440,000, Funder: Research Infrastructure Fund, May 2017 to July 2018.
- Pushing the boundary of vision-based 3D surface imaging, £40,000, Funder: Renishaw and Cardiff Strategic Partner Fund, April 2018 to April 2019.
- EmerEEG – A novel medical device for early detection and treatment of traumatic brain injury, Value: £222468, Funder: Commission of the European Communities, October 2013 to September 2015.
- SRS – Multi-role shadow robotics system for independent living, EU FP7 project, EUR 5 136 039, Funder: Commission of the European Communities, February 2010 – February 2013.
- IWARD - Intelligent robot swarm for attendance, recognition, cleaning and delivery, Total cost: EUR 3 880 067, Funder: Commission of the European Communities, January 2007 to January 2010.
- Tai-Chi - Tangible Acoustic Interfaces for Computer-Human Interaction (The project received the EC FP6 IST Best Exhibition Award at Helsinki.), Value: EUR 3,308,701, Funder: Commission of the European Communities, December 2003 to December 2006.
Professor in Systems Engineering
- +44 (0)29 2087 5913
Senior Lecturer - Teaching and Research
- +44 (0)29 2087 5911