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SUPPLEMENT TO CHAPTER 7: LEARNING CURVES Teaching Notes When dealing with learning curves there are four distinct areas which the decision-maker is concerned about: 1. Beginning point: This involves the initial time estimate of the process. Of course if the beginning point is lower time needed to complete the task (better), then less training is necessary to reach the same level of performance. 2. Shape of the curve and the rate of increase: In many cases the shape of the learning curve will be consistent with the traditional 70%, 80%, 90% learning curve. However, in some instances, the learning curve may be s-shaped and in rare instances, the shape of the learning curve may be a straight line. It is important to know the shape of the curve before assuming a certain shape and making predictions using that learning curve. Therefore, during the earlier stages of the process, the decision-maker must carefully study the shape by having different employees produce different quantities and recording the job completion times. The shape of the curve is a function of the specific job, rather than the individual worker. In addition, the faster (lower) the learning rate, the lower the training costs due to employees learning faster. 3. Steady state: At a certain point during the learning process, the employee will reach a steady state. This indicates the completion of the learning based on the given technology and the process. It represents the minimum time the job can be completed. Obviously the employee with the lowest steady state time is the most desirable employee. We can investigate the motions and actions of this employee to try to improve the job. 4. Quality of the product: As the learning is taken place, workers are working at a faster pace. We must make sure that the quality of the product is not compromised. This seems to be a topic that students readily grasp. The one area that some seem to have difficulties with is finding cumulative times (e.g., length of time for units 6 through 10). I find that reminding them of how they determine areas under the normal curve helps most overcome this difficulty. If they are currently taking statistics, or have recently completed their first course in statistics, comparing the process of finding cumulative learning curve amounts to the process of obtaining cumulative binomial or Poisson probabilities is another possibility. The advantage of these latter tables over the normal is that they are discrete instead of continuous, and students tend to equate these discrete probabilities tables more with the learning curve tables. Answers to Discussion and Review Questions 1. As the number of repetitions increases, the requisite “doubling” needed to achieve the rate improvement becomes larger and larger. For large volumes of output, as in mass production, the improvement per unit is extremely small. 2.
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This note was uploaded on 04/21/2011 for the course MGT 02 taught by Professor Gad during the Spring '11 term at Tanta University.

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