Smart manufacturing and industrial automation

Forming collaborations between industry and researchers to embrace Industry 4.0 for future manufacturing.

Research

Cyber-physical Production Systems

Advancing the technologies and applications for CPPSs. Research topics include:

  • Cyber-Physical Machine Tool
  • Cyber-Physical 3D printing system
  • Real-time manufacturing data acquisition
  • Data communication, integration and management
  • Machine tool information modelling
  • Augmented Reality (AR)-based visualization of machine tool status and machining processes
  • Semantic Machine-to-Machine (M2M) communication between field-level manufacturing devices (e.g. machine tools, AGVs, robots)
  • IoT-enabled smart manufacturing

Digital Twin

Developing smart manufacturing systems and processes using Digital Twin technologies. Research topics include:

  • Digital Twin-driven smart manufacturing systems
  • Information modelling for Digital Twin
  • Digital Twin-enabled smart factory
  • Digital Twin-driven product design
  • Digital Twin-driven operation technology
  • Digital Twin in product lifecycles

Industrial Artificial Intelligence

Applying the latest artificial intelligence technologies to improve the cognition of industrial systems, such as robots, AGVs, machine tools and 3D printers so that they can sense, think and act by themselves in an autonomous factory environment. Find out more about the Industrial Artificial Intelligence research group.

Potential projects in this area include:

  • NLP technologies for understanding human knowledge
  • Machine learning for human-machine collaboration
  • Semantic reasoning for autonomous machine decision-making
  • Self-learning systems for smart machines
  • Machine learning for machining processes optimisation
  • Cognitive environment for intelligent manufacturing systems

Industrial Big Data Analytics

Focuses on proposing various solutions for small and medium-sized enterprises (SMEs) in implementing IoT technologies and Big Data Analytics to achieve data-driven smart manufacturing. Some of our research include:

  • IoT-enabled manufacturing execution systems
  • Data model for IoT-enabled manufacturing
  • Big Data classification and interpretation
  • Big Data visualization
  • Big Data-driven APS
  • Big data processing architecture
  • Effective time-series data processing
  • Data visualisation
  • Industrial applications of big data analysis
  • Data mining

Autonomous Robotics

Creating autonomous robots that can learn to act in unpredictable environments has been a long standing goal of robotics, artificial intelligence, and the cognitive sciences. In contrast, current commercially available industrial and service robots mostly execute fixed tasks and exhibit little adaptability. This research stream develops autonomous robotics for application in human-robot factory collaboration, precision farming, and construction.

  • Machine perception for robotics
  • Human-robot collaboration
  • Cloud-based robotics
  • Autonomous AGVs
  • Self-learning robotics
  • Robotics for smart construction

Cloud Manufacturing

Providing effective solutions to cloud-based resource sharing and collaboration among enterprises so as to enhance their competitiveness. Our projects include:

  • Cloud-based manufacturing system development
  • Cloud manufacturing service ontology development
  • Cloud manufacturing system modelling for optimal scheduling
  • Cloud service optimal scheduling approaches
  • Task scheduling approach in cloud manufacturing
  • Cloud manufacturing service composition
  • Real-time machining monitoring in the cloud manufacturing environment
  • Cloud-based product configuration system development
  • Big data management and analysis in the cloud manufacturing environment
  • Cloud-based 3D printing

Smart Production Management

Optimizing manufacturing operations, from machining on a single machine tool to the entire value chain/network scheduling. Projects include:

  • Smart factory architecture
  • Smart factory modelling in terms of resources, organization, information, and function
  • Resource scheduling within a smart factory
  • Supply chain scheduling
  • Energy-efficient machining decision-making for Industry 4.0
  • Ontology-based approach to process planning
  • Manufacturing resource representation for a smart factory

Smart Product Development

The Customised Product Development Research group carries out research relating to product configuration and development to enable co-creation process with early supplier involvement and high level of customer involvement during product design. A key purpose of our research is to bring ETO manufacturers closer to Mass Customisation/Mass Personalisation. Projects include:

  • Smart product configuration system
  • Design for additive manufacturing in a cloud environment
  • Conceptual design for mass personalisation in OKP companies
  • Enabling technology for rapid development of high value-added customised product
  • Design and development of novel hearing technology devices
  • Knowledge management technologies to support product development in medium-sized high technology enterprises
  • Product knowledge management tools, methods, and techniques for one-of-a-kind production

Facilities

Find out more about our facilities via the Laboratory for Industry 4.0 Smart Manufacturing systems website.

Commercial services

  • Robotics training
  • Industry 4.0 consultation
  • Industrial artificial intelligence applications
  • CAD/CAPP/CAM/CNC
  • Internet of Things-enabled manufacturing and solutions
  • Big data analytics for manufacturing
  • Automation applications
  • Discrete event simulation studies
  • CNC and STEP-NC applications
  • Product development

Partners and collaborators

Research institutions

Industry

Courses

Undergraduate

MECHENG 352 Manufacturing Systems
MECHENG 709 Industrial Automation
MECHENG 752 Technology Management

Postgraduate

MECHENG 710 Advanced Industrial Automation 
MECHENG 751 Advanced CAD/CAM/CNC
MECHENG 753 Manufacturing Information Systems

Our people

Related research groups