Control Charts
Variable control charts are used to study a process when characteristics is a measurement, for example, cycle time, processing time, waiting time, highest, area, temperature, cost or revenue. Measurement data provides more information than attribute data: consequently, variables charts are more sensitive in detecting special cause variation than are attribute charts. Variable charts are typically used in pairs. One chart studies the variation in a process, and the other studies the process average. The chart that studies variability must be examined before the chart that studies the process average. This is so because the chart that studies the process average assumes that the process variability is stable over time. One of the most commonly employed pair of charts is the Xbar-chart and the R-chart. Through the use of control charts, similar gains can be realized in the manufacturing sector. Users of control charts report savings in scrap, including material and labor, lower rework costs, reduced inspections, higher product quality, more consistent part characteristics, greater operator confidence, lower trouble shooting, reduced completion time, faster deliveries and others Summers [8].
Figure 5 illustrates the XmR range chart obtained from Minitab for historical data and Figure 5 presenting new real life data.
Comparison between factory historical data and new real life data shows that the historical data is not accurate the reason for that is lack of precision in sampling process, inaccuracy in sampling size and sampling intervals. This contradict with a major objective of SPC is to quickly detect the occurrence of assignable causes of process shifts so that investigations of the process and corrective action may be undertaken before many nonconforming units are manufactured.
Figure 4: