Tech Wisdom: IoT-Enhanced Truck Schedules
Interactions between container terminals and trucking companies are very important, however appointment systems don’t consider trucking company convenience or the need for real-time scheduling.
A recently published technical article was based on research by Amr Eltawil, Professor of Industrial Engineering, and Ahmed Azab, PhD Scholar, Egypt-Japan University of Science and Technology.
Truck appointment systems often ignore the convenience of the trucking companies, which aim to dispatch their trucks for their preferred arrival time.
The second issue with the appointment systems is they don't consider the dynamic nature of the scheduling problem, where both the demand for and supply of containers are changing dynamically.
The introduction of the IoT will allow realtime data to be collected from sensors implemented on all the CT equipment, allowing agility and fast adaptation to new circumstances
Both stakeholders’ decisions affect each other’s operational efficiency and productivity.
The papers' authors introduce the new concept of Dynamic Collaborative Truck Appointment Systems (DCTAS) as a future solution for smart CTs that can also be applied in the currently developing terminals, a new IOT-connected system to automate truck appointments.
The efficacy of the system was explained in the research:
"In a theoretical experiment, the requests of five trucking companies were submitted to a simple conventional and non-automated CT. The DCTAS was used to develop truck appointment schedules for the upcoming eight time windows. The results of the system were compared to current planned schedules of the CT in order to observe the impact of using the proposed system. The results show that the total truck turnaround times for the five trucking companies were reduced and the terminal workload was smoothed out and re-distributed into a more even pattern."
The authors conclude by predicting that the real time availability of input data through the IoT makes available and reductions of planning horizons will reduce the historical difficulty and complexity of scheduling problems.