Industry digitalisation

Our research in the abilities and skills in the theme of Industry digitalisation are highly broad and comprehensive that cover the holistic and digitalised data integration, holistic monitoring and control systems, process integration and resource integration within an organisation or large scale of supply chain and supply network systems to achieve adaptive, smart, autonomous and collaborative control and management. As one of leading research groups in the UK on agent-based distributed modelling and control, over the past two decades as well as the pioneer of dynamically integrated manufacturing system, the theme has built up strong knowledge base in the fields of Industry 4.0, smart city environments to develop innovative approaches and solutions, digital tool applications to help companies with their digital transformation and generate their digital twins. The current research focuses on the application of digital-twin development, robotics, artificial intelligence, optimisation and advanced simulation technologies for:

Dynamic supervision, control and simulation of robotic production system
Integrated process and production control for human-robot collaborative production system
Dynamic re-scheduling and event handling for manufacturing system
Industry 4.0 and smart city applications
Digital twins, big data analytics, ontology-based data modelling, artificial intelligence and optimisation applications, cloud computing and high-performance computing
Digital transformation and innovation, business model innovation, sustainability.

Key Academics

Academic	Title	Relevant interests
Professor David Zhang	Professor of Manufacturing systems	Dynamically Integrated Manufacturing Systems (DIMS) and Products Supply Chain Optimisation, Design for Optimised Supply Chains Agile Product Development/Manufacturing and Innovation Road-mapping Multi-agent systems (MAS), complexity science and consumer dynamics modelling Adoption of metal 3D printing technology, and product design for metal 3D printing
Dr Allen He	Lecturer in Engineering Management	Dynamic supervision, control and simulation of robotic production system Integrated process and production control for human-robot collaborative production system Dynamic re-scheduling and event handling for manufacturing system
Dr Baris Yuce	Lecturer in Engineering Management	Manufacturing assembly line digitalisation and industry 4.0 applications ie sensory based system development, monitoring and control technologies Cloud ERP solutions and integration with other digitalised platforms
Dr Miying Yang	Lecturer in Engineering Management	Sustainable manufacturing Manufacturing servitization

Projects

Improving the design of flexible and responsive manufacturing systems involving autonomous and Collaborative RoboTs (Prof David Zhang and Dr Allen He)

The EU CoRoT project aims to develop innovative and affordable robot hardware and software platform focused on the needs and budgets of SME. The expected results from this project will include:

a) An open and modular mobile robot platform with three robotic functionalities, i.e., intelligent localisation and movement, picking and manipulation, and distributed communication and collaboration;

b) A dynamically integrated supervision, control and simulation platform for flexible manufacturing system equipped with the mobile robot developed. Meanwhile, the project also aims to establish a vertical collaboration between the research institutions and 50+ businesses or business intermediaries through industrial workshops and pilots for research outcomes demonstration and dissemination, as well as technology transfer.

Enhancing UK-Brazil competencies in digital technologies and business model innovation for circular economy (PI: Dr Miying Yang)

This project explores how to use the emerging digital technologies (e.g. Internet of Things, big data and artificial intelligence) and business model innovation to help manufacturing firms move towards circular economy. This requires the collaboration between the stakeholders across the entire supply chain. The project will identify the main drivers, process of adopting digital technologies in manufacturing firms, and the potential impacts on operation and supply chain performances.