Machine Learning and advanced image analytics can improve predictive maintenance by eliminating human error and enhancing quality and consistency of operations. Join the virtual chat to learn more about real-world examples from Energy, Manufacturing and Transportation industries.
Real time data from IoT devices give businesses an unprecedented view into how their products are performing. It can help identify potential faults, troubleshoot from afar, and ultimately improve customer satisfaction.
Classification approach - predicts whether there is a possibility of failure in next n-steps. Regression approach - predicts how much time is left before the next failure. We call this Remaining Useful Life (RUL).
It can be extremely challenging to create a model that can accurately predict the lifetime of a machine. However, in reality, such a model is not needed. We can use risk based classification models to predict a failure within the next ’N’ days or cycles.
According to Gartner, Operations and Maintenance teams are faced with increasing pressures to managing Risk, minimizing costs and meet performance objectives. https://www.crowdchat.net/s/56657
The objective with any maintenance program is to reduce equipment failures. An unexpected failure interrupts a business process, usually for an extended period of time. Regular maintenance is designed to reduce the chance that failures like this from occurring.
The manufacturer “recommended” maintenance regiment has a lot of built-in assumptions (that many not apply to your conditions) and may not reflect your environment. Aka. you are doing more/less maintenance that is really required to reduce equipment failures. The real trick is
The real trick is to do the right amount of maintenance at the right time to get the least number of failures. Typical this is a trail and error process that takes quite a bit of time to create and is unique for each piece of equipment.
If you change from one manufacturer of say a pump to another, you may have to learn this process all over again. An unexpected failure takes time to diagnose, identify the root cause of the failure, replace the failed piece of equipment and then adjust your maintenance process.
All this translates to a loss of production and a huge amount of labor/ equipment costs which translates to a loss of profits. If this happens frequently, it can lead to a business’ failure. This risk of “failure” is what regular maintenance is designed to avoid when it is done.
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