Original Theory
The phenomenon of "learning" was first expressed mathematically in
1936 by T. P. Wright. He observed in the aircraft industry that certain costs
per unit tend to decrease in a predictable pattern as the workers and their supervisors
become more familiar with the work. These decreasing costs are a function of
a learning process in which fewer and fewer man-hours are required to produce
a unit of work as more and more units are produced. The key elements of the theory
may be summarized as follows (Adrian 1987).
- The repetition of any task leads to an improvement in productivity as a result
of the experienced gained.
- This phenomenon is well established in the mass production industry as well
as in the construction industry under appropriate circumstances.
- The application of the theory (in the construction industry) assumes that
operatives start with the necessary basic skills as well as the required support
for the work to be accomplished.
- Productivity improvement then typically follows a constant ratio relationship
which is expressed as follows.
For every doubling of units, the cumulative average time per unit
is reduced by a constant ratio.
This relationship is illustrated in Table 1, showing
examples of Cumulative Average Time per Unit (Chellew 1974).
|
Number of Units
in Sequence
|
Cumulative Average Time per Unit
|
|
90% Ratio
|
80% Ratio
|
|
1
|
100.0
|
100.0
|
|
2
|
90.0
|
80.0
|
|
4
|
81.0
|
64.0
|
|
8
|
72.9
|
51.2
|
|
16
|
65.6
|
40.9
|
|
32
|
59.1
|
32.8
|
Table 1: Examples of Cumulative Average Time per Unit for Two Different Ratios
In Table 1, the time taken for the first unit is 100%.
At a 90% ratio, the average time taken for the first and second unit is 90%,
i.e., the actual time taken for the second unit is 80%. By the time the fourth
unit is reached the average time taken for all four units is 90%x90% = 81% and
so on.
These values can be plotted as curves as shown in Figure 9.
However, if the same data is plotted on log-log paper as shown in Figure
10, the result is a straight line which is more useful for manual analysis
or mathematical illustration.
Figure 9: Illustration of learning curves
Figure 10: Learning curves plotted on log-log scale
|
Learning
Curve vs. Experience Curve
