To develop a predictive maintenance system that uses machine learning to forecast machinery failures, reducing downtime and improving operational efficiency in industries.
Research predictive maintenance methodologies and sensors used in industries.
Collect historical machinery operation and failure data.
Apply machine learning models to predict possible breakdowns.
Develop an alert system to notify operators of predicted failures.
Create a dashboard to display equipment health metrics in real-time.
Simulate machinery operations and test predictive accuracy.
Analyze cost savings and operational efficiency improvements.
Document system design, algorithms, and evaluation results.
