Two years ago, Process Engineer Bill Roberts and his team at Minnesota-based Roberts Automatic Products, Inc., were looking to improve the company’s statistical process control (SPC) and its overall data collection processes.
It is a fact. Every company experiences scrap, rework and downtime. Unfortunately, many companies still don’t know how to predict and manage the impact of these events on their time, budgets, and quality.
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.
To succeed in today’s global competitive manufacturing sector, businesses must thoroughly understand and manage their processes. Using Statistical Process Control (SPC) methodologies, organizations can use process data to get an accurate picture of how a process functions and what actions can be taken to improve it.
Are you considering usability as you evaluate your SPC software purchase? At Zontec, we look at usability in the context of how simple or difficult it is for a user to navigate the software while achieving the desired results within the manufacturing environment.
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.
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.
This goal is supported with a manufacturing process that functions in a consistent and predictable manner, a process that is not out of control or unpredictable. Understanding the variability in your process and being able to identify out of the ordinary events and what is causing them is the key to managing the process, reducing variability, improving your process, and, as a result, saving time and money.