The increasing capacity of container ships is playing a
large role in quay crane productivity, but not the only role.
As a key point in the international marine industry the
Panama Canal allows vessels to transit between the Atlantic and Pacific Oceans
without having to go around the southern tip of South America. The largest
ships currently able to travel through today are called Panamax, a term that
has been has been in use since the canal opened in 1914. The size of a Panamax
vessel is determined by the dimensions of the canal lock chambers with a length
of 965 feet and width of 106 feet. This roughly translates to a 13-wide
container ship with a capacity of about 4,500 TEU. The Panama Canal Authority
is currently building a second set of chambers to accommodate larger vessels,
and once the new set of locks opens in 2015, the definition of “Panamax” will
change to “New-Panamax” which will describe container vessels about 19
containers wide and 12,000 TEU.
The cargo shipping industry is trending towards these bigger
ships because of economies of scale for vessel construction and operations.
Even with the limiting width of the Canal, there are even larger ships
currently in play such as the Maersk Triple-E Class, which offer an enormous
18,000 TEU capacity and more than 1,300 feet of length.
For the ports, however, ever-larger container ships mean
upgrading vessel accommodations and making sure productivity is kept up. Bigger
ship dimensions mean longer working cycles for each container handled by a quay
crane, which in turn will have a significant effect on quay crane productivity.
A quay crane’s productivity is measured by how many cycles
or container moves it is able to do per hour. A typical quay crane cycle
consists of the spreader moving to a ship location, picking a container,
hoisting the container back to the wharf and setting the container down. For a
larger ship, the spreader would need to traverse a further distance to access
containers on the far side and would also have to travel further down in the
hold.
An initial crane simulation study was undertaken to test the
effects of vessel size, type of container and operator skill set, a quay crane
simulation software developed by AECOM and Liftech that measures the
uninterrupted productivity of a single quay crane. The CraneSim software takes
in crane specifications and dimensions, as well as vessel width and depth in containers.
The output is the theoretical maximum productivity of a specified crane working
to a predefined vessel. The factors influencing the output include crane drive
speeds, vessel size, location of container on vessel and wharf, type of
container and skill of the crane driver.
Simulations were run with the Panamax and New-Panamax size
vessels, each with single and twin picks for the type of container. Each set
was modeled with a range of pick and set times from ten to twenty seconds for
single picks and twenty to forty seconds for twin picks. These ranges represent
an operator skill set of very good to average.
The results of the initial study show that for a very
skilled operator working to just single picks, the maximum productivity could
be as high as 40 moves an hour for the New-Panamax and more than 45 moves an
hour for the Panamax ship. This productivity drops down to the thirties as the
pick and set times increase. For the twin picks, there are two containers being
lifted at a time, so the outcomes are almost double the productivity.
The constant factor with multiple pick and set times is the
period it takes to move the container across the vessel after picking and
before setting it down. For the Panamax ship, this is about 52 seconds and with
the New-Panamax it is 64 seconds.
Overall, for a larger vessel, the crane spreader has a
farther distance to travel and the productivity decreases. On average, for
single moves, the difference in productivity between vessel sizes is about five
moves per hour per quay crane. With four cranes serving one ship, it would be a
potential loss of twenty moves per hour. As ship size increases, the spreader
travel distance gets greater, and productivity per crane declines. This
decrease arrayed across all cranes on all ships would be a significant drop in
productivity.
Further simulations were done on the initial study with
sensitivities on crane spreader hoist speeds, container placement on the vessel
and container placement on the wharf. The conclusions from these can be
summarized as follows:
Big ships are more sensitive to crane speed because they
have more distance to cover. For example, with an increase in hoist speeds from
90 meters per minute to 135 meters per minute, the New-Panamax showed a three-
to five-percent increase in productivity as opposed to a one- to
one-and-a-half-percent increase with the Panamax.
Regardless of the size of the ship, there is a significant
difference in working to and from the upper half of the ship closest to the
wharf and below deck on the far side of the ship. On the Panamax, the
productivity went up 30 to 35 percent for the “easy” section of the vessel and
the New-Panamax showed a 25- to 33-percent increase. It is important to make
sure productivity is calculated from an average of container moves across the
ship so as not to skew the results.
Big ships are less sensitive to work position on the wharf
because the increase in trolley distance takes place at maximum trolley speed,
and because cranes can trolley and hoist simultaneously, big ships get more
“free” trolley time while hoisting is taking place. In an example comparison of
working between the legs of a crane versus the back reach, in the Panamax case,
the productivity drops six to nine percent but the difference for New-Panamax
ships is only about one percent
As the world industry standards for vessel size is
increasing, there is a greater need for ports to expand as well. Bigger ships
mean terminal changes, which will include acquiring better quay cranes to
accommodate the vessels and increasing the number of cranes per ship to keep
productivity levels same.
Ms. Le has worked on various marine terminal planning and
analysis projects and has experience in developing simulation modeling software
as well as discrete event simulation projects for the marine and oil sectors,
particularly in the areas of simulation model development and data analysis.
