The Psychology of Quality and More

A Toolbook for Quality Improvement and Problem Solving (contents)

Histogram: Examples

The Quality Toolbook > Histogram > Examples

When to use it | How to understand it | Example | How to use it | Practical variations

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Example

A power engineer required a 10 ohm, 0.1% tolerance, high power resistor. The only resistors available were 10% tolerance. To achieve the higher tolerance, he uses a series of 100 resistors each of 0.1 ohm. The summing effect was expected to average out the low tolerance, as resistors over and under 0.1 ohm balanced each other out. When the resulting resistance started overheating, the engineer measured the value of each one and plotted a Histogram, as in Fig. 1.

The result showed that although the resistors were within specification, their distribution was not normal and not centered on 0.1 ohm (this was probably caused by selection from an off-center production system). The solution of a specially made resistor was significantly more expensive.

Fig. 1. Histogram shows selected sample

Other examples

• A poultry farmer measures the distribution of egg sizes to find if the most common sizes are also those which sell best. She then adjusts her chicken stock to change the distribution to suit their market.
• A sales department checks the distribution of orders by their value, and then analyzes the data further to determine the demographics of the high-value orders and thus improves its sales focus.
• A school checks the distribution of its examination results and streams students according to their position in the distribution. Students with marks outside the normal distribution are sent to special classes for high- or low-ability children.

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