Apply The Learning Curve Theory

Tricia Williamson

University of Phoenix

Apply the learning curve theory

The basic principle behind the learning curve theory is the development in performance process from repetitiveness of tasks completed by individuals or groups. The theory has three assumptions, which are:

1. The time needed for task completion decreases as it is repeated

2. The percentage of improvement decreases with corresponding increases in volume

3. The rate of improvement is predictable over a certain amount of time.

It has been shown that in the process of performance, production units are doubled in reduced amounts of time after certain periods of implementation. The slope of the curve is calculated by the difference between the rate of learning and numerical value of one hundred. If the timing between the doubling of units is decreased by 10%, then it will be a 90% learning curve.

The table for process performance data for the metric identified in the Pizza Store Simulation is in attachment one. Below is the plot for each week denoted by S.No. on the X-axis and Average wait-time in minutes on the Y-axis. Clear-cut improvement in average waiting time was shown. The wait time has lessened from 11.67 to 3.45 minutes after applying optimization strategy and eliminating the blockage in process. By doing the analysis of the curve, the average waiting time has lessened to almost half at the end of fourth week. The approximate slope of curve for week eight can be calculated by (11.67- 3.45)/(8–0) = 1.0272 meaning average waiting time is lessened by 1.0272/11.67 = 0.088~0.09. The rate of learning is nine percent that means it is a 91% learning curve.

[pic]

Similar analysis can be applied to the profit gained by the improvement in process. Below is the plot for each week denoted by S.No. on X-axis and Profit on Y-axis from the table below.

[pic]

A large improvement in profit from week one until week eight of the...

Tricia Williamson

University of Phoenix

Apply the learning curve theory

The basic principle behind the learning curve theory is the development in performance process from repetitiveness of tasks completed by individuals or groups. The theory has three assumptions, which are:

1. The time needed for task completion decreases as it is repeated

2. The percentage of improvement decreases with corresponding increases in volume

3. The rate of improvement is predictable over a certain amount of time.

It has been shown that in the process of performance, production units are doubled in reduced amounts of time after certain periods of implementation. The slope of the curve is calculated by the difference between the rate of learning and numerical value of one hundred. If the timing between the doubling of units is decreased by 10%, then it will be a 90% learning curve.

The table for process performance data for the metric identified in the Pizza Store Simulation is in attachment one. Below is the plot for each week denoted by S.No. on the X-axis and Average wait-time in minutes on the Y-axis. Clear-cut improvement in average waiting time was shown. The wait time has lessened from 11.67 to 3.45 minutes after applying optimization strategy and eliminating the blockage in process. By doing the analysis of the curve, the average waiting time has lessened to almost half at the end of fourth week. The approximate slope of curve for week eight can be calculated by (11.67- 3.45)/(8–0) = 1.0272 meaning average waiting time is lessened by 1.0272/11.67 = 0.088~0.09. The rate of learning is nine percent that means it is a 91% learning curve.

[pic]

Similar analysis can be applied to the profit gained by the improvement in process. Below is the plot for each week denoted by S.No. on X-axis and Profit on Y-axis from the table below.

[pic]

A large improvement in profit from week one until week eight of the...