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Second Interim Report
Clair Brown, Editor

12. Enhancing the Rate of Learning by Doing Through Human Resource Management
Nile W. Hatch

12.5 Conclusions

In spite of hundreds of published studies on learning curves, surprisingly little is known about how learning by doing actually occurs. This study attempts to fill some of the gaps in our understanding of this phenomenon by analyzing how human resources influence learning by doing,. Empirical estimates show that yield improvements are a function of cumulative volume and cumulative engineering. In contrast to previous analysis, cumulative engineering is not included in the analysis as a rival proxy for manufacturing experience, but rather is one of the means by which yield improvements actually occur. Manufacturing volume provides information about yield losses that is analyzed by engineers to identify and eliminate sources of yield losses.

One of the most important implications of this finding is that learning by doing is not the incidental result of repetition during manufacturing. It is, rather, the product of deliberate, endogenous, activities that can be managed to improve learning by doing. Historically, little has been done to identify the sources of differences in the rate of learning between industries or firms. However, in the semiconductor industry, learning by doing differs across manufacturing facilities and even across manufacturing processes within the same plant. This study identifies two human resource management factors that are significant in explaining the observed- differences.

The key to yield improvements in semiconductor manufacturing is the ability to identify and permanently eliminate sources of yield loss. When the human capital of the workforce is sufficient to include operators in analytical activities for yield improvement, more information can be included in the analysis and more analysis can be performed than if it were done only by engineers. The result is a significant improvement in yields and manufacturing costs. The importance of human capital is seen most clearly by observing the effect of operator turnover on yields. Turnover results in a loss of training and knowledge of the equipment and manufacturing processes. The result is a significant loss of yields. In addition to that, the influence of engineering analysis is reduced, presumably because engineers are the only remaining qualified source of analysis and they are often required to devote attention to training and mistake prevention rather than formal yield analysis.

End of Chapter 12

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