Published On:Sunday 27 November 2011
Posted by Muhammad Atif Saeed
Learning Curve (CIMA)
Learning Curve (CIMA)
“ The mathematical expression of the phenomenon that, when complex and labour intensive procedures are repeated, unit labour times tend to decrease at a constant rate. The learning curve models mathematically this reduction in unit production time.
Learning is the process of acquiring skill, Knowledge, and ability by an individual. According to learning curve theory the productivity of the worker increases with increase in experience due to learning effect. The learning theory suggests that the best way to master a task is to “learn by doing”. In other words, as people gain experience with a particular job or project they can produce each unit more efficiently than the preceding one.
The speeding up of a job with repeated performance is known as the learning effect or learning curve effect.
The cumulative average time per unit produced is assumed to fall by a constant percentage every time the total output is doubled. So generally learning effect is found in the multiples of 2
Learning formula Y= axb
Y= Cumulative average time taken per unit
a= time taken for the first unit
x = total number of units
b = index of learning
b = the log of learning
log of 2
Limitations of learning curve
1. All activities in manufacturing environment are not subject to learning effect e.g. work done by new and inexperienced worker.
2. There is considerable difficulty in obtaining valid data which can form basis of computation of learning effect.
3. The learning curve becomes obsolete even with slight change in circumstances.
4. It is unlikely that average time to manufacture a product will continue to decrease in the long run due to some unavoidable factors.
Information about two variables that are considered to be related in some way can be plotted on a scatter graph. In scatter graph is simply a graph on which historical data is plotted. By plotting cost level against activity level on a scattergraph the shape of the resulting figure might indicate whether or not relationships exist. The y axis represents cost and the x axis represents the output or activity level. If the points lie exactly on a straight line then the correlation is said to be perfect linear correlation.
Line of best fit
A scatter graph can be used to make an estimate of fixed and variable cost, by drawing a “line of best fit” through the band of points on the scatter graph, which best represents all the plotted points.
The amount of fixed cost can be found by looking at the point where the graph intercepts the y axis. In other words look at total costs when activity is zero. These must be fixed cost.
To calculate variable cost, take any other point on your line of best fit and record the total cost and the output level. Use these figures and your calculation of the fixed cost to estimate the variable cost per unit. The major disadvantage is that it calls for subjective judgment in drawing a line “by eye” which appears to suit all the point plotted. It is suitable where the amount of scatter is small, where the degree of accuracy of the prediction is not critical.
