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Showing posts from June, 2023

Why Your Organization Needs an OEE Software Champion at the Heart of Your Efforts

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If you had to make a list of all the elements that contribute to a manufacturing organization's OEE tracking  success, accountability would be right at the top. It's easy to say to employees that you're having issues in terms of quality, availability, or overall performance. It's another thing entirely to explain what that means in a way that gets people to buy into it. In a way that helps them understand why any proposed changes are absolutely the right move to make at exactly the right time. Even the best OEE software  in the world won't necessarily do this on its own... but a digital champion for all of your Overall Equipment Effectiveness efforts can. A Champion Rises On the one hand, there is quite a bit that the right piece of OEE and machine downtime tracking software like Thrive can do for your business on its own. For starters, it can ingest the historical data that your business is creating in a way that makes it easy to see not only what you'r

So, You've Begun OEE Tracking. Now What?

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One of the most important things to understand about OEE (Overall Equipment Effectiveness) is that it isn't the "means to an end" that a lot of people assume it to be. Yes, understanding your manufacturing business' relationship between quality, performance, and availability is always important. But just because you're comfortable with your initial OEE score doesn't mean the journey is over. In many ways, it's just beginning. With the right OEE software by your side, this process can unlock a wealth of insight you wouldn't otherwise have access to. That's step one. Step two involves taking that insight and putting it into practice, capitalizing on opportunities for continuous improvement all the while. Machine Downtime Tracking: Your Next Steps For the sake of example, let's consider all this within the context of a pain point that most manufacturers share: unplanned equipment downtime. According to one recent study ,  when all factor