Learning_Curves_lecture_note

Learning_Curves_lecture_note - 1Learning Curves...

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1 Learning Curves Introduction The concept of a learning curve is natural and intuitive. The idea that we become more efficient as we continue to do the same task repetitively is one that is readily grasped, because we have often seen it in our daily lives. An example is the grading of assignments or exams. It takes me much less time to grade the last 20 assignments in my stack than it does to grade the first 20. I begin to become aware of the types of errors most commonly made and their sources, allowing me to trace them through more readily. 1 Industry is also aware of learning and its effect on production efficiency. The aerospace industry, for example, has long planned for the effect of learning. New production lines or new shifts of workers will also experience learning, and this effect is anticipated and planned for. Setups or changeovers of equipment from one task to another are also procedures which improve over time. The sources of learning are varied. On an individual/worker level, the use of different work methods, regular training, the layout of the workplace, and even the motivational level (nothing succeeds like success) have all produced gains. At the organizational level, better product and process design, improved materials, new technology, and better scheduling and coordination can all produce learning curve effects. Measurements of these sorts of productivity gains often take on a regular shape of exponential decay. The chart below shows the time required to produce each of the first 32 unit from a process. The data is given below the chart. 1 Here we see that the time required to perform the task is decreasing, but as time goes on the effect is not as pronounced. For example, it is clear that the improvement achieved in terms of time to make the 2nd unit compared to time to make the 1st is greater than the improvement from the 31st to the 32nd unit.
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Yx 40 50 60 70 80 90 100 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 Yx 11 100 9 60.78 17 51.28 25 47.56 2 83.99 10 59.21 18 51.17 26 46.51 3 77.67 11 55.95 19 50.09 27 46.07 4 72.84 12 55.78 20 50.18 28 45.11 5 67.78 13 55.77 21 48.68 29 45.38 6 66.25 14 53.07 22 48.42 30 45.70 7 64.61 15 53.28 23 48.48 31 44.77 8 62.63 16 53.24 24 48.20 32 44.79 1 Since this often occurring exponential decay is a regular pattern, it is also predictable . We should be able to find a power equation that exhibits the same pattern and use it for prediction/planning purposes. In fact, such an equation does exist. The general form is: n x kx Y = where Y x = the time required to produce the x th unit, x = the ordinal number of the unit produced, k = the (predicted) time required to produce the 1st unit, and n = an exponent that identifies the rate of improvement.
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1 How to use the equation Using this equation, we can predict how long it will take to produce the 33rd unit (or any other unit for that matter). It is this ability to predict the time required to produce future units that makes the learning curve an effective tool for planning. Let's give it a try.
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This note was uploaded on 11/05/2010 for the course BUS F370 taught by Professor Tom during the Spring '10 term at Indiana Institute of Technology.

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Learning_Curves_lecture_note - 1Learning Curves...

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