Department of Mechanical Engineering


LISMS research


The laboratory and associated researcher's capabilities.

Smart decision making


The Smart Decision-Making research group is currently conducting research on smart decision-making issues for Industry 4.0 such as smart factory modelling, resource scheduling and energy-efficient machining. The aim of our research is to optimize manufacturing operations (from machining on a single machine tool to the entire value chain/network scheduling).

Research projects

  • 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
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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.

Research Projects

  • 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
  • Cognitive environment for intelligent manufacturing systems
  • 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

Related Research/Projects

 

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CPS and IoT-enabled smart systems


Inspired by recent advances in Information and Communication Technology (ICT) such as Cyber-Physical Systems (CPS) and Internet of Things (IoT), this research theme focuses on the development and implementation of CPS and IoT technologies in the manufacturing environment to ultimately support Industry 4.0. It aims to advance current field-level manufacturing devices into CPS and IoT based smart manufacturing systems.

Research projects

1. Cyber-Physical Machine Tool (CPMT)

In the past five years, various industrial initiatives such as “Industry 4.0”, “Industrial Internet of Things”, “Factories of the Future” and “Made in China 2025”, have been announced by different governments and industrial leaders. These initiatives have clearly indicated an urgent need to advance current manufacturing systems into a high level of intelligence and autonomy. It is predicted that current CNC machine tools are not intelligent and autonomous enough to support the smart manufacturing systems envisioned by the aforementioned initiatives.

Inspired by recent advances in ICT such as Cyber-Physical Systems (CPS) and Internet of Things (IoT), this project proposes a new generation of machine tools, i.e. CPMT, as a future development trend of machine tools. CPMT is an application of CPS in the domain of manufacturing. It shares common features with typical Cyber-Physical Systems such as networked, adaptive, predictive, cooperative, intelligent, with real-time feedback loops and with humans in the loop.

 

2. Cyber-Physical 3D Printing System

Additive manufacturing, also known as 3D printing, has experienced a rapid development and been used in various situations from prototyping, molding to production. It is particularly suitable for small-batch and geometrically complex parts. Recently, Cyber-Physical System (CPS) has shown its potential to bring a normal 3D printer to a new level with greater adaptability, autonomy, efficiency, functionality, reliability, safety and usability. By creating a cyber twin of the 3D printer, the operator will be able to remotely control and monitor the 3D printer via the internet. More intelligent decisions can be made by the cyber twin to automatically adjust the printing process in the physical 3D printer.

Topics related to the development of CPMT include:

  • 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
 
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Cloud manufacturing


Research on cloud manufacturing currently focuses on key technologies for cloud manufacturing system development such as manufacturing ontology, service composition and scheduling, cloud-based product configuration, as well as real-time machine monitoring. The aim of our research is to provide effective solutions to cloud-based resource sharing and collaboration among enterprises so as to enhance their competitiveness.

 

Research Projects

  • 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

 

Cloud manufacturing related Projects and Videos

 
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Big data analytics for IoT-enabled manufacturing


Internet of Things (IoT) enabled manufacturing is an advanced principle where typical production resources are converted into smart objects which are able to sense, interconnect, and interact with each other to automatically carry out the manufacturing activities. As the wide usage of IoT digital devices which are able to generate huge number of data, manufacturing companies are facing challenges for making full use of these collected data. Big Data, an emerging ad-hoc term, refers to use advanced concept and technologies to deal with the data which is so large and complex that traditional approaches are not able to address. Our research focuses on proposing various solutions for small and medium-sized enterprises (SMEs) in implementing IoT technologies and Big Data Analytics so as to achieve Cloud Manufacturing.

Research

  • IoT-enabled manufacturing execution systems
  • Data model for IoT-enabled manufacturing
  • Big Data classification and interpretation
  • Big Data visualization
  • Big Data-driven APS
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Posters and case studies


 
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