Polyhedrika

  Statistical Process Control (SPC) is used to control a critical process output, acting on the factors affecting it, only when required. The purpose is to differentiate between a statistically significant change in the process, and common cause variation, because the actions required will be different. Process stability is a prerequisite for any further analysis. If a process is not stable, any conclusions you draw, can't be assumed to hold in the future. With SPC we check for process stability in the future. Control over-reaction A case of over-reaction is illustrated by the following example: Someone is shooting at a target, and based on the deviation of the impacts, he adjusts the gun site after each shot. The result will be an increase of the dispersion of the impacts; therefore, the adjustments will make the process worse. The correct way is, of course, to fire 5 or 6 shots without adjustments, and then decide if adjustment is required, based on the center of the impacts. ...

Design of Experiments is a useful methodology for process improvement. The purpose is to find a relationship between process variables we can control and key process outputs in order to increase process capability . You can use Excel statistical analysis tools, Solver, Pivot charts, etc. to plan and analyse the results of these experiments. The first approach is to look for a linear relationship as shown in:   Excel DOE But in some cases this relationship may not be linear, in which case we will try a quadratic model with Response Surface DOE . We will use an example in this Excel file you can download: Download file   ExcelResponseSurface.xlsm   from OneDrive to your PC. In this example we are trying to maximize process yield acting on the critical factors pH , Temperature and Time . We will run the experiments in the Experiments simulation sheet using coded values.   Code pH Temperature Time -1 2 120 7 1 12 150 15 Factorial Experiments We start by ru...