InfinityQS
International, Inc. (InfinityQS), the
global authority on data-driven enterprise quality solutions, announces it has
empowered an international elevator company with real-time quality data for
immediate corrective action in production.
Equipped with the
ability to quickly spot quality issues and determine where to focus improvement
efforts, this manufacturer has improved the consistency of its elevator wall
panels, shortened production time, and reduced data analysis time from weeks to
minutes.
For this elevator
manufacturer, out-of-spec wall panels were causing job site construction
delays, costing significant time and money. Looking to improve control over the
panel machining process, the company implemented InfinityQS Statistical Process
Control (SPC) software for Quality Intelligence.
The quality data
collected by InfinityQS reveals if and where the process goes awry, enabling
shop-floor operators to take immediate action and ensuring that non-forming
materials never leave the factory.
Once it got its panel
machining process under control, the next focus aimed at shortening elevator
panel Takt time—the average time between the start of one production run and
the next. Using SPC data, this manufacturer reduced its wall panel production time
to just 2-3 minutes per run—a 40-60% time savings.
The company now
employs a combination of manual, semi-automated, and automated data collection
to quickly and easily track quality and process information. These data help
plant teams improve other onsite production processes, conduct faster and more
accurate audits, and perform detailed analysis across lines, shifts, and
machines in a matter of minutes.
“When manufacturers
can unify real-time information across lines, machines, products, shifts, and
even plants, they gain increased visibility and can make smarter business
decisions,” said Michael Lyle, President and CEO of InfinityQS.
“Many InfinityQS
customers cite visibility as their favourite product benefit, because it allows
them to rectify problems and expose which lines or plants perform better than
others.
"Understanding
why these differences exist enables continuous process improvement, making
quality data an invaluable asset to manufacturing operations at large.”
