How to avoid checkmate
Requirements are escalating
Like in a chess match, terminal operators have to react to the moves of shipping lines and terminal equipment suppliers again and again. On the one hand, the next generation of container vessels – carrying some 18,000 TEU – is expected to arrive soon. On the other hand, new technologies are available that increase productivity at some point on the terminal. Using twin and tandem lift STS cranes can double moves per hour at the vessel, but can also build up new bottlenecks in other areas of the terminal. Therefore, current Terminal Operating Systems (TOS) are becoming more and more complex, and have to calculate some moves beforehand to receive the best result.
Nowadays huge terminals, especially Greenfield ones, are planned and optimized using simulation technology (see box) to guarantee optimal operation. But small and medium-sized terminals are much more affected by the changes described, as not only might they lose business to their competitors, but it’s also rather a question of whether they thereby reach capacity and/or productivity limits. To avoid the checkmate, these terminals have to use new technologies like the virtual terminals described in this paper.
New strategies are demanded
To increase a terminal’s productivity, often new technological approaches are used. In this way some years ago ZPMC, the Chinese market-leading supplier of STS cranes, developed a new horizontal transport technology. The straightforward basic idea of this concept is to divide the whole transport between the STS crane and the yard into small pieces. Each part of transport is done on only one axis:
• First transport is parallel to the quay, via platform using a supported carriageway
• Second transport is vertical from the rail to the ground by a moving crane
• Third transport is perpendicular to the quay using another platform on the ground.
All handshakes between the STS and the platform, the platform and the moving crane, the moving crane and the ground platform, as well as the ground platform to the yard stacking crane are to be handled directly without any buffer. Thus the equipment control of this technology has to ensure that all devices needed for the handshake have to be at the same place at the same time. This task seems not to be a problem for transport of a single container, but looking at a productivity of some 200 moves/h at a vessel shows the extreme complexity of this control task.
The same holds for the automation of container terminal operation. As the manned device at the terminal is equipped with highly sophisticated local intelligence (the brain of the driver), the automated one is not. Each decision about bypassing traffic congestions on the terminal and exception handling may be done by the driver directly. However, the central control of automated technology has to regard all possibilities, and has to think for all single pieces of the equipment (e.g. some 70 AGV at the Container Terminal Altenwerder). The difference between artificial and human intelligence may be seen by the fact that chess computers are only just yet at the same level as the human Grandmasters after many years, and a lot of software developers trying to defeat them.
The basic idea of emulation technology (see box) that may support terminal operators is the provision of virtual terminals. These react to the TOS’s commands as the physical ones do. A complete model including seaside operation, horizontal transport, stacking yard, gate operation and all equipment used at the terminal is built into the computer. The TOS, which is connected to the virtual terminal, does not know whether it controls the virtual or the physical one.
In this way, the TOS may be tested without disturbing the real operation. Neither operating costs nor wear of the equipment will occur during the test. Furthermore, environmental impacts such as noise and pollutant emissions will be avoided. Running these tests with the TOS guarantees the correct functionality, as well as it may be used to fine-tune the parameters controlling the strategies. The tests may be repeated as many times as needed (e.g. with different parameter settings) under exactly the same conditions – while the real-life weather conditions and workers’ behavior will change for each test. Thus the changes in the results of these laboratory tests can be traced to the parameter changes.
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