Chapter 10

Data sets

To implement statistical quality control, we first need to understand the causes of variation in our process. We aim to identify and remove what is known as special cause variation and to keep common cause variation, to a minimum level. The next step is to establish that our process can meet the customer's specification, and that our product will continue to meet that specification during its design lifetime. Statistical quality control charts are used to monitor the process and so provide early warning of any new sources of special cause variation and any increase in the common cause variation.

• Example 10.2: Moisture content.
• Example 10.3: (Table 10.1) Tensile strengths.
• Example 10.4: (Table 10.2) Inter-laboratory trial.
• Table 10.3: Compressive strengths (MPa) of concrete cubes.
• Example 10.14: (Table 10.5) HV insulators.
• Example 10.15: (Table 10.6) Electrolytic capacitors.
• Example 10.16: Solar exploration vehicles.
• Example 10.17: Short wave radios.
• Example 10.18: (Table 10.7) Insulation.
• Example 10.22: Burners.
• Example 10.23: (Table 10.10) Concrete.
• Example 10.24: (Table 10.11) Windshields.
• Example 10.2: (Table 10.12) Components.
• Example 10.26: (Table 10.13) High voltage switch gear.
• Example 10.27: Bank Bottom Engineering - robot arms.
• μ
• Σ
• Exercise 10.7: Inter-laboratory trial.
• Exercise 10.10: (Table 10.14) Shewhart.
• Exercise 10.14: (Table 10.15) PSV.
• Exercise 10.17: Shewhart mean and range charts.
• Exercise 10.20: Autocorrelation.