Data isn’t everything. But it’s perhaps the main thing standing between you and a successful project. Continuous improvement takes effort, but more than anything, it takes solid information and analysis. In other words, wouldn’t it be more helpful to use statistical process control to find out where your process is going wrong, rather than just a hunch?
ARaymond, an industrial supplier of fastening and assembling solutions, rose from humble beginnings. Founded in Grenoble, France in 1865, the family business “started out making fastening elements for the glove and footwear industry,” says Jake Fox, senior quality engineer at ARaymond’s Brunswick, Ohio location.
Manufacturing Intelligence Track Sessions Chock-full of Experts, Peers and Transformational Technologies for Users and Managers of Production Software.
Over a career that spans 40 years, Steve Gruler has struggled with the fact that quality seems to be a soft term. “Companies often say, ‘We’ve got great quality. We’ve got the best quality,’ and they’re looking at customer complaints and certification systems as their primary metrics,” he attests.
Statistical process control (SPC) charts are used in quality-focused facilities to monitor process output on a continual basis and alert process operators, managers and the support staff in real-time when the process is shifting towards an undesirable condition.
Quality engineers use statistical process control (SPC) to eliminate process variation and ensure that final products meet customer expectations. Their job includes rooting out problems during production and ideally preventing issues before products become rejects.
Each new journey begins with a single step. That common proverb applies to most aspects of life, including the decision to start a new business or organization. A company can look back fondly to that first bold and courageous decision to merely begin.