Validation requires documented evidence that a process consistently conforms to requirements.
It requires that you first obtain a process that can consistently conform to requirements and then that you run studies demonstrating that this is the case. Statistical tools can aid in both tasks.
Balanced approach using mistake proofing and variation reduction tools.
Many nonconformities are not the result of errors, instead, they are the result of excessive variation and off-target processes
When pass/fail data is involved, acceptance sampling plans can be used to demonstrate conformance to specifications
Each unit of product differs to some small degree from all other units of product. These differences, no matter how small, are referred to as variation.
The goal is to optimize the average and reduce the variation.
Reducing variation requires the achievement of stable and capable processes.
Stable processes produce a consistent level of performance. The total variation is reduced. The process is more predictable.
Once a consistent performance has been achieved, the remaining variation must be made to safely fit within the specification limits.
In general, one must identify the key input variables, understand the effect of these inputs on the output, understand how the inputs behave
