The Integral Concepts article series

Statistical Process Control charts have been called the Voice of the Process.  Progressive manufacturers utilize control charts to “listen” to their processes so that potentially harmful changes will be quickly detected and rectified.  However, not all SPC programs deliver to their highest capability as there are many elements to get right to achieve maximum utility.  Highly effective SPC programs combine technical competencies, such as using an appropriate chart and sample size for the application, with effective management techniques such as enabling operator buy-in and involvement.  This article identifies ten keys that unleash the power of SPC.    [Read more…]

Process Stability and Process Capability are both extremely important aspects of any manufacturing process.  Often the concepts behind process stability and process capability and the relationship between them are misunderstood.  This article attempts to clarify both ideas and the relationship between them.   [Read more…]

When planning and designing an experiment, it may be tempting to try and accomplish all the objectives is a single experiment.  The thinking is often that experimentation is time consuming and expensive, so one experiment must be better than multiple experiments.

However, in general, it is a good idea to plan for multiple experiments which often is a much more efficient approach.  We like to think of experimentation as a methodology that is best implemented in phases.  We define experimental phases as: [Read more…]

Experimentation is frequently performed using trial and error approaches which are extremely inefficient and rarely lead to optimal solutions.  Furthermore, when it’s desired to understand theeffect of multiple variables on an outcome (response), “one-factor-at-a-time” trials are often performed.  Not only is this approach inefficient, it inhibits the ability to understand and model how multiple variables interact to jointly affect a response.  Statistically based Design of Experiments provides a methodology for optimally developing process understanding via experimentation.   [Read more…]