Control charts are simple but very powerful tools that can help you determine whether a process is in control or not. Follow along with the example below to learn how to choose the right control chart for your situation.
Socrates said, “The only true wisdom is in knowing you know nothing.” Another great mind, Ed Morse (in his keynote address at this past year’s Coordinate Metrology Society Conference), said, “Data is only as good as what you can do with it.” If you were so inclined to put these two thoughts together, you could see the current dilemma regarding Big Data.
I had a discussion recently with someone who, for three decades, had been performing a statistical function at a large manufacturing company. He couldn’t understand why, in spite of excellent job performance reviews, his company had furloughed him indefinitely.
Modern manufacturing relies on consistency, and tolerances are tighter than they’ve ever been. Production capabilities are up to the task, and CMM systems help ensure that completed or in-process parts are within tolerance. The real challenge comes when anything goes wrong.
Companies with robust quality programs often struggle to make sure that projects are on track and deliver results—and to aggregate data from thousands of projects so executives can see their overall impact.