Smart Factory

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Source: Manufacturing Operations Management, Quality and Aerospace Talk Picture
Scheduling and Control with Robots and Machine Learning
Simulation of Autonomous Robots for Material Handling in Factory

The application of the word ‘smart’ has extended from devices into facilities like factories. Smart factories can be defined as a factory where machines interact with each other without human control based on collaborative Internet of things (IoT) and cyber-physical systems (CPS). To reduce the human control or intervention, the consideration of various data from devices is essential. This research cluster focuses on various problems such as scheduling with inductive learning and vehicle routing problems with autonomous mobile robots (AMRs).

Faculty Collaborators

Members

Publications

Published
  • Jun, S., Lee, S., & Chun, H. (2019). Learning dispatching rules using random forest in flexible job shop scheduling problems. International Journal of Production Research, 1-21.

    • Under Review
  • Jun, S. & Lee, S. (2019). Pickup and delivery problem with recharging for material handling systems utilising autonomous mobile robots. Manuscript submitted for publication.

  • Jun, S., Lee, S., & Yih, Y. (2019). Pickup and delivery problem with recharging for material handling systems utilising autonomous mobile robots. Manuscript submitted for publication.

    • Presentations

  • Jun, S. & Lee, S. (2019). Learning Dispatching Rules from Optimal Schedules for Single Machine Scheduling Problems. INFORMS Annual Meeting 2019.
  • Jun, S. & Lee, S. (2019). Learning dispatching rules using random forest in flexible job shops. IISE Annual Conference.
  • Jun, S. & Lee, S. (2018). Design of a production logistics model with UAVs and AGVs. DSI 2018 Conference.
  • Jun, S. & Lee, S. (2018). Mathematical models and constraint programming for flexible job shop scheduling problem. IISE Annual Conference.