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between these and crystalline cells is that rather than using crystalline silicon, these use chemical compounds to semiconduct. The chemical compounds are deposited on top of a substrate, that is to say a base for the solar cell. There are some formulations that do not require silicon at all, such as CIS (copper indium diselenide) and cadmium telluride. However, there is also a process called amorphous silicon, where silicon is deposited on a substrate, although not in a uniform crystal structure, but as a thin film. In addition, rather than being slow to produce, thin-film solar cells can be produced using a continuous process, which makes them much cheaper. However, the disadvantage is that while they are cheaper, thin-film solar cells are less efficient than their crystalline counterparts. Some different solar photovoltaic technologies are compared in Table 10-1. Figures are given for the efficiency of the cell technology, and the average area of cells required to generate 1 kW peak power when facing in the right direction! When looking at the merits of crystalline cells and thin-film cells, we can see that crystalline cells produce the most power for a given area. However, the problem with them is that they are expensive to produce and quite inflexible (as you are limited to constructing panels from standard cell sizes and cannot change or vary their shape).

gic focus areas. These items are transferred to House 2, becoming the next whats if more detail is needed. 5 The process continues until the ranked hows are speci c enough to assign strategic goals and measurements. Upon successful completion of this process, there will be a list of key focus areas, which can be assigned strategic goals and objective measures. This process provides con dence that project resources are focused on meeting critical needs of the business. The following are tips when creating the House of Quality:

The more speci c the processes the less time the process will require. Combine customer input with internal business strategies, employee needs, and

Index Contribution 7.5 11.25 12 6 4 3 3 4 9 8 67.75% 0.3893 25,956 3.44

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government regulations to obtain a comprehensive list of customer needs. Consider rst organizing all the whats into categories with similar detail, and then perform the iterative process, inserting new whats at the appropriate House level.

( xi x )( yi y )

By contrast, thin-film cells are cheap to produce, and the only factor limiting their shape is the substrate they are mounted on. This means that you can create large cells, and cells of different shapes and sizes, all of which can be useful in certain applications. We are now going to take a detailed look at making two different types of solar cell, one will be a crystalline solar cell, and the other a thin-film solar cell. Both of the experiments are designed to be illustrative, rather than to actually make a cell with a useful efficiency. The technology required to make silicon solar cells is out of the reach of the home experimenter, so we are going to illustrate the process of how a solar cell is made, using things you can find in your kitchen. For thin-film solar cells, we are going to make an actual solar cell, which responds to light with changing electrical properties; however, the efficiency of our cell will be very poor, and it will not be able to generate a useful amount of electricity.

i =1

( xi x ) 2

FIGURE 4-6.

n = number of observations S xx = ( xi x )2 S yy = ( yi y )2 S xy = ( xi x )( yi y )

In the preceding equations, is the slope of the regression line and s is an unbiased estimator of 2 (the population standard deviation). The variables Sxx, Syy, and Sxy are the sum of squares for x and y (Walpole and Myers, 1993).

In this section we are going to look at how photovoltaic cells (PV) are made. However, rather than taking a dull, textbook approach, we are going to make the whole process fun by doing some practical kitchen experiments that mimic the process that happens in solar cell factories all around the world.

There are ve major assumptions or ideal conditions for the estimation and inference in multiple regression models (Dielman, 1996). The ve assumptions are

The Measurements column identifies one or two key business indicators, and the Category Abbreviation column relates the measurement to the corresponding element of the Six Sigma Business Scorecard. The Category Significance column ranks the importance of each category. The Leadership and the Rate of Improvement categories, for example, are ranked highly significant because of their direct correlation with profitability. Leadership and profitability are weighed 30 percent, and the rate of management and improvement is ranked 20 percent. The Performance Against Plans column assesses a corporation s performance against its plans. For a company to rank well, it must have a sound plan, effective execution, and good results. The Index Contribution column includes the weighted contribution of each category determined by multiplying the Category Significance and Performance Against Plans values.

1 2 3 4 5

The relationship is statistically signi cant. 2 The residuals, ei , have constant variance e . The residuals are independent. The residuals are normally distributed. The explanatory variables are not highly correlated.

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