6.
Process or Product Monitoring and Control
6.1.
Introduction
6.1.2.

What are Process Control Techniques?



Statistical Process Control (SPC)

Typical process control techniques

There are many ways to implement process control. Key monitoring
and investigating tools include:
All these are described in Montgomery (2000). This chapter will focus
(Section 3) on control chart methods,
specifically:

Underlying concepts 
The underlying concept of statistical process control is based on a
comparison of what is happening today with what happened previously.
We take a snapshot of how the process typically performs or build a model
of how we think the process will perform and calculate control limits for
the expected measurements of the output of the process. Then we collect
data from the process and compare the data to the control limits. The majority
of measurements should fall within the control limits. Measurements that
fall outside the control limits are examined to see if they belong to the
same population as our initial snapshot or model. Stated differently, we
use historical data to compute the initial control limits. Then the data
are compared against these initial limits. Points that fall outside of
the limits are investigated and, perhaps, some will later be discarded.
If so, the limits would be recomputed and the process repeated. This is
referred to as Phase I. Realtime process monitoring, using the limits
from the end of Phase I, is Phase II.


Statistical Quality Control (SQC)

Tools of statistical quality control

Several techniques can be used to investigate the product for defects
or defective pieces after all processing is complete. Typical tools of
SQC (described in section 2) are:
 Lot Acceptance sampling plans
 Skip lot sampling plans
 Military (MIL) Standard sampling plans

Underlying concepts of statistical quality
control 
The purpose of statistical quality control is to ensure,
in a cost efficient manner, that the product shipped to customers meets
their specifications. Inspecting every product is costly and inefficient,
but the consequences of shipping non conforming product can be significant
in terms of customer dissatisfaction. Statistical Quality Control is the
process of inspecting enough product from given lots to probabilistically
ensure a specified quality level.
