Study Cause and Effect: Experimental Design & Model Building
This posting continues the discussion of the seventh step, Study Cause and Effect, of the Hoerl-Snee Process Improvement Strategy. Tools that might be used in this step that were not summarized in the previous posting are:
- Experimental Design. A systematic planned variation of input factors for an actual process. The experimenter observes the effect of these variations on important quality characteristics. The 1/30/2008 posting mentions the use of designed experiments by an OEM manufacturer to determine an improved raw material composition. The 2/28/2008 posting discusses the effort by a company to reduce the rejection rate at one of its machine shops. Based on a Cause & Effect diagram, project members selected four factors for further analysis based on designed experiments. These factors were Feed Rate, Wheel Speed, Work Speed, and Wheel Grade. Analysis of the experimental results identified “optimum” levels for the four factors.
- Model Building. One could construct a model of a process that predicts quality performance based on input variables. The 2/18/2008 posting describes the actions of a Midwest manufacturing firm to reduce time delays experienced by customers contacting their order processing center. They constructed a simulation model of the order-taking process. Using the simulation model they determined the staffing level of customer service representatives by the hour of a work day to meet time-delay objectives. Why don’t software companies use simulation models to specify technical support personnel requirements?
Subsequent postings will illustrate the use of experimental design and model building to Study Cause and Effect.
