Good quality means controlling the important factors!
To improve quality, it is important to consider all factors that can be significant for product quality. Start with process mapping to identify variables that can affect product quality.
All processes are subject to variation, which may be classified as random / noise (common cause) or assignable cause variation (special cause).
Common cause variation is found in all processes and exhibits random yet stable variation that is predictable within calculated process control limits. Common cause variation is synonymous with natural variation, expected variation, or random variation.
Special cause variation, on the other hand, is unpredictable, sporadic, or unstable variation. It is the result of a specific assignable cause, for example Machine (Equipment), Man (Operator), Material, Method, Milieu (environment) & Measurement (referred to as 6M in a Fishbone).
Humidity is an example of specific assignable cause (Milieu) that can be controlled. The challenge of quality assurance is to identify the critical factors and control that the variation of them are within allowed tolerances.
Six Sigma involves statistical tool to understand variation and identify critical factors. It is important to know the critical factors of your processes to avoid spending time controlling non-important factors and failing to launch new products. Lean Tech has experienced both scenario's. In the last scenario, the variation of product quality was unacceptable for the customer. If critical factors are unknown it's hard to reduce variation.
What are the critical factors of your processes? Regression analysis, Component of Variation - CoV & Design of Experiment can help you decide the critical variables.
How do you control the variation of critical factors? Critical factors can be monitored using Statistical process control - SPC. Lean Tech has made a video about SPC application. Here is an example of implementation of online statistical process control - SPC (Norwegian article) at Axis-Shield.