Statistical Process Control for the Sawmill Industry

Abstract: In the sawmill industry, it can be very profitable to monitor the dimensions of sawn boards so that operators quickly can detect errors and take cor-rective action. In this master’s thesis project, Statistical Process Control (SPC) methods have been implemented to achieve this. SPC is a set of statistical methods whose purpose is to minimize the variations in an in-dustrial process. In particular, the SPC method used here is the control chart, which with an upper and lower control limit quantifies the bounds of natural variation. To find the most suitable control chart, five control charts monitoring the process mean, and two monitoring process variability were tested with help of both a simulation study and an empirical evaluation. The result of the evaluation was that the ”Average Moving Range” chart was regarded the most suitable for changes in process mean, and the Range chart was regarded as the best at detecting changes in process variability. Both charts are constructed for individual boards and not subgroups of boards (as is more common) due to compatibility reasons with the existing measurement practice. The two methods were deemed to be quite able to detect process changes, but some results indicate that the methods might work better for double arbour saw lines than single arbour ones.