This section will briefly outline elementary statistical process control tools. There are three major techniques to achieve quality, the traditional approach, statistical process control, and the design of experiments. Traditional quality control consists of ineffective methods such as brute force inspection, management exhortation, delegation of quality responsibility to a detached quality control department, and even sampling plans. This statistical process control (SPC) approach typically utilizes control charts to understand process variability. These charts are useful to ensure that a process is and stays in control but are complex, costly, and almost useless their ability to solve chronic quality problems.
As shown in the “Contribution of Traditional, SPC, and DOE Tools to Quality Progress” figure the widespread use of design of experiments (DOE)has the biggest impact of the three methods on improving quality. This is because the object of DOE is to discover key variables in product and process design, to drastically reduce the variations a cause, and open up the tolerances to the lesser variables so as to reduce costs. This chapter will now highlight the SPC tools used in scale-up and production and DOE tools used in product design and scale-up.