Every manufacturer wants to improve operations.  The most successful digital transformation use cases tackle specific problems –  reducing scrap, optimizing efficiency, speeding processes, lowering costs, and ultimately improving the bottom line. In this era of smart manufacturing, the best way to make these kinds of operational improvements is based on good data intelligence. The machines on the factory floor can provide a lot of valuable information – the key is figuring out how to effectively gather and make use of it to affect measurable change and ROI.

Overall Equipment Effectiveness (OEE) has emerged as a best practice for transforming data intelligence into real operational improvement. OEE is the gold standard for measuring manufacturing productivity. It’s really a simple math problem – availability x performance x quality = OEE.

Simply put – OEE indicates the percentage of time that manufacturing is truly productive. There are three parts to calculating or understanding OEE. 100% availability means there is no downtime and production is running as planned. 100% performance means goods are being produced as fast as possible. 100% quality means there are no defects, only good products.

The ability to effectively track and measure these three parts is what allows an organization to improve OEE. Many factories are collecting some equipment data that could be used to calculate OEE, but it is siloed or incomplete. Perhaps modern equipment is collected but not legacy, or maybe the data is trapped on the shop floor so the plant manager has to dig deep to access it and do some manual calculations.

In a smart factory, every asset on every production line is connected. As a result OEE can be calculated right there, at the edge, and then the dashboards can be shared with anyone in the organization. Litmus helps companies achieve a steady stream of OT data, then visualize and analyze the data with built-in KPIs for OEE. Just achieving a clear picture of current OEE status is a win for most companies. They can use that information to make adjustments at the machine.

Once they are ready, companies can take OEE improvement to another level by sending that data to IT systems to run data models in the cloud. Litmus can then run those models back on the factory floor and put them into production to continually learn and improve OEE scores – the ultimate goal.

Watch our recent webinar to see Litmus Edge in action and learn exactly how we can help you Improve OEE on the Factory Floor.