ABSTRACT
Every day, managers look at process production sheets, but the in-depth process variability analysis is rarely done. Every working shift supervisor looks at the behavior of process parameters, but the in-depth process variability analysis is too often kept silent. Every minute online analyzers and measurement systems send information about key process parameters to the control room where reactive action is taken when necessary, but there also, in-depth process variability analysis is too often beyond the knowledge of the monitoring operator. Several factors play a role in these observations:
High-level productivity does not allow much time for managers, supervisors, and operators to investigate process variability in depth.
Easy access to existing data is often a limiting factor.
The will to take time, reflect on existing data, and determine a creative course of action is weak at best.
Quality thinking and quality action-taking are often considered the enemies of economic productivity (Carrasco 81 ).
But, most often, it is a statistical methodology that is inappropriate, falling short of looking at process variability in terms of heterogeneity: this is exactly where the Theory of Sampling (TOS) makes a huge difference.
