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A Blueprint For Quality Improvement
Manufacturers are aware that quality is an increasingly significant problem. Fifty six percent of manufacturers say that improving quality and/or reducing scrap is a top challenge, a concern tied to reducing unplanned downtime.
But getting to the root causes of quality failures can be very difficult. If data is not unified, timely, or correctly analyzed, then the causes of problems can go undetected or unaddressed for a long time.
The solution is guided analytics. Guided analytics allow engineers to make process improvements ten times faster than with traditional monitoring systems, and provide intelligence that helps improve efficiency, maximize output quality, and minimize downtime.
The first step is defining your problems. Look at business cases and goals, and zero in on the specifics. How much money are you losing to quality failures? What would you do if you could increase throughput by 10%? What pain points can be solved the quickest, and what is the fastest way to improve quality and/or performance?
It’s extra critical when you’re making decisions around where to invest and what systems to use that you always work towards that Northstar of having the systems connected, and use data to help you make decisions. This makes quantifying ROI, or measuring the impact of a new tool, much more straightforward.
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