DoE is a term used to describe a large set of statistically valid experimental structures or 'designs'.
Process optimization typically involves a class of designs known as screening designs that are used to determine the few critical inputs that control the output(s) of the process. Once the critical inputs are determined the inputs effect on the output(s) are modeled using various design structures collectively referred to as response surface methods.
As a starting point I recommend an article by Davis Balestracci entitled "
Using DoE as a Process Road Map" from the February 2006 issue of Quality Progress. (Clicking on the title will take you directly to the article...)
Three great primers on DoE and its various uses are:
"Quality Improvement Through Planned Experimentation" by Moen, Nolan and Provost
"Understanding Industrial Experimentation" by Dr. Donald Wheeler
"Statistical Engineering" by Steiner and MacKay
There is also a decent manual on Response Surface Methods: "RSM Simplified" by Anderson and Whitcomb