Summary of Smart Manufacturing System Project


  • Industry 4.0 creates what has been called a “smart factory”. Smart factories make use of cyber-physical systems to monitor physical processes, giving a digital representation of the physical world. Smart factories create many new opportunities for industry. The digital representation of the factory allows different production strategies to be simulated and evaluated ahead of time. More sophisticated robotics allow for unprecedented amounts of customization in the production process, and thus greater customization of products to individual customers. New technologies provide new opportunities, but also new challenges. Previous strategies for coordinating production within a factory assume that large production runs of identical items being produced using the same process. New techniques need to optimally produce many small production runs of customized products. Furthermore these techniques must be automated wherever possible. New product recipes must be created quickly, and it is not practical to bring in expert in scheduling every time a new custom product is produced. In this project we investigate how DES can be used to quickly and easily model modern manufacturing systems. DES theory is already used to ensure that systems are both safe, and reliable. We extend DES theory in order to be able to optimally schedule production within the system. We are interested in developing new techniques for optimizing production within a smart factory so as to maximize throughput and machine usage in an environment which requires the production of varied and changing product types. Furthermore we seek to be able to model the system in a flexible way which allows the model to be updated with new product types easily by non experts.

Project Objectives

  • To develop a hybrid hierarchical modelling framework, which combines both finite-state automata and programming models to ensure expressiveness, verifiability, modularity and computational friendliness for low volume high mix reconfigurable manufacturing.

  • To develop a novel modeling and optimization framework, which facilitates drag-and-play functionalities in smart manufacturing.

Research Topics

  • Scheduling of Manufacturing Systems

  • AGV Scheduling of Material Handling Systems

  • Security for Cyber Physical Systems