Introduction
In order to optimize productivity on new facility construction, the input of
resources including men, materials and equipment, is varied according to the
planned timing and availability of the work. This applies on all but the smallest
construction jobs where minimal crew size may limit flexibility. However, even
on quite small "maintenance projects" this flexibility may be facilitated
by managing the manpower levels over several concurrent assignments. This optimizing
of productivity results in an initial period of build up, a period of peak loading,
followed by a period of progressive demobilizing. This typical profile, or curve,
when plotted cumulatively over time for a whole project, results in another typical
curve in the shape of the letter "S".
The purpose of this paper is to present some rules of thumb relating to these
curves which have resulted from experience on new civil and building construction
work. These rules of thumb suggest simple ways to draw first approximations for
cumulative resource or production curves over the life of the project. The first
relates to resource loading, i.e. men, materials, equipment or cash. A second
relates to the consequent production output. The two curves are closely related
and it is suggested that the difference can be accounted for by the effects of
learning. The phenomenon of learning itself is also explored to show how it may
be used for planning or tracking repetitive tasks on construction work.
These relationships have been found by the author to be most helpful for preliminary
project planning, for checking the validity of proposed plans, or for analyzing
the records of completed work. Since the author has used these techniques while
employed variously by owners, developers, and general contractors, it is hoped
that they will be seen as beneficial for anyone in similar positions.
In the following discussion, unless otherwise stated, the presumption is that
the project is or will be "well run". For the definition of a well-run
construction job, refer to Appendix 1.
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Abstract
