Today’s software systems are advancing faster than any other time in history. Each is going in different directions. The competition is not necessarily with the software company that creates and sells a specific software such as a calibration or quality management solution—the real differences are the platforms behind the scenes.
How do you commit to realistic forecasts and timelines when resources are limited or gathering real data is too expensive or impractical? Can simulated data be trusted for accurate predictions? That’s when Monte Carlo simulation comes in.
Digital transformation is a competitive technology and business strategy that leverages data gathering to drive business efficiencies, new revenue growth, and new business models.
Turn Gage R into a tool for continuous quality improvement.
October 10, 2017
Many quality engineers don’t know the Gage Repeatability and Reproducibility, or Gage R&R, of their leak test. Many, frankly, don’t want to know because they fear how poor it may be.
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.
To produce a quality product--and continue to do so--you need data.
February 1, 2017
Quality is based on a series of facts and statistics collected together and analyzed. To produce a quality product—and continue producing a quality product—you need 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.
Analyzing and acting on data transformed the way Crayola does business and has enabled the company to concentrate resources where they'll have the biggest impact.