RushikeshKothawade07/predictive-maintenance-ML
The project is a machine predictive maintenance application that uses machine learning (Random Forest) to classify whether a machine will experience failure or not based on various input parameters.
This tool helps maintenance engineers and operations managers anticipate machine breakdowns. You input various operational parameters like air temperature, rotational speed, and tool wear, and it tells you if a machine is likely to fail soon. This allows for proactive maintenance, preventing costly downtime and production disruptions.
No commits in the last 6 months.
Use this if you need a simple way to predict potential machine failures based on operational data, helping you schedule maintenance before problems occur.
Not ideal if you require predictions for a highly complex machine system with many interconnected failure modes or need to analyze the root cause of failure.
Stars
24
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6
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Aug 05, 2023
Commits (30d)
0
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