OEE is based on the 1870 version of quality. That is, it uses good vs bad, like the go/no-go gauges of old. Dr Shewhart showed a much better way to quality.
My previous post on OEE showed that OEE is a meaningless nonsense number. https://lnkd.in/gB6YYe3b The correct approach is to use The Operational Definition. This leads to Process Behavior Charts to monitor the variables.
Then you ask: “If we are supposed to use Process Behavior Charts, why not a single multivariable chart? Hotelling’s T**2 is very trendy. T**2 charts work for 2 or more variables.”
The first problem is that unlike Shewhart Charts, T**2 charts are very sensitive to normality. By contrast, both XmR and XbarR charts do NOT depend on a data model. They work well for ANY data distribution, without normalization or data manipulation.
While Process Behavior Charts look at each variable independently, T**2 charts look at the way the variables interact. They look for deviations in this interaction. For example, suppose we had a process where we were monitoring specific gravity and viscosity. We might expect viscosity to increase as specific gravity increased. A T**2 chart would indicate a point where this did not happen. For example, where specific gravity increased but viscosity decreased.
T**2 charts depend on a correlation to be present. The less the correlation, the less useful they are. In the case of OEE, there is no correlation at all. It is just a bunch of unrelated numbers tossed together. While a multivariable chart might seem appealing, it is of no use at all. Similarly, OEE itself is of no meaning or use.
Finally, Dr Wheeler advises: “Multivariable charts are way too complicated to let children play with them.” T**2 charts will quickly get you into deep water, out of your depth.
The message is KEEP IT SIMPLE.
by Dr Tony Burns BE (Hon 1) PhD (Chem Eng)