Automation of Container Unloading from Large Cargo Ships and Color-Based Positioning Segmentation

Abstract

This work addresses, in the context of Discrete Event Systems, the development of a method for automation and control to tackle the issue of unloading large cargo ships and, additionally, the implementation of spatial segmentation of containers from different brands, a condition approximated by containers of different colors. The current unloading process heavily relies on human operators controlling the machinery that moves the containers. Human labor, in cases like this, poses a risk and vulnerability to the process, as workers are subject to fatigue, inattention, mistakes, and other conditions that can be very costly due to the large-scale loss of goods. Furthermore, automating the process is a means of increasing efficiency with significant potential to add value by saving time. These savings are reflected in the reduction of idle time for ships and in the decreased waiting time for other ships to dock.

Returning to the issue of spatial segmentation, it is understood that an important part of the unloading process is the ability to allocate containers in an organized manner to facilitate the transportation of goods out of the port. In this way, major brands can access their goods more easily, making the integration of the distribution network with the port less costly.

This work required the development of control for 39 signals, 30 of which were input signals. This was accomplished using the design methodology taught in the PMR 3305 course, whose steps include, in order: defining the physical architecture and structural model of the control system – its inputs and outputs (I/O); modeling the control behavior through PFS (Production Flow Schema) and RdP (Petri Nets) and defining interlocks; validating and simulating the model using PIPE 4.3; and applying isomorphism to program PLCs by converting the Petri Nets into Ladder Logic (LD). It is worth noting that the commissioning of the control system should mark the final stage of the project development, but the completion of this step was outside the proposed scope.

The conclusion of this project pointed to the real possibility of implementing safe automation systems for unloading cargo ships. The expected impact of the real implementation of a system similar to the one proposed here is to make large-scale freight transport networks more efficient, reducing costs and making the process safer, more organized, and more efficient.