Real time analytics moves decision making to the operational or operator level so data can actually make a difference in your job.
When you use condition-based monitoring, you take a process or machine collecting data and interpret those signals meaningfully. This impacts your ROIs, specifically visibility and decision-making capabilities through real time, data-driven means shifts.
Your process and your machine controls can adapt to change and provide insight back to the operator about a dial that needs to be adjusted or a widget that should be modified.
On top of this, machine optimization analytics enable your machine to make changes on the fly, making your process that much better.
Let’s talk about the tactical approach: What do you need to use machine learning and where do you start?
Think about a small idea that could be scaled across the entire organization. Once you have something that you feel works, think about how fast you could scale it. As long as the data is being collected automatically, you can use process data, machine data, operator data, etc. to identify a problem and target a solution.
Maybe it’s a dimension. Maybe it’s a torque value. Maybe it’s a hole.
It doesn’t matter.
What matters is that you gather relevant data that can be interpreted and used to create a solution.