AI/ML
Driven Engineering
Use Insights from
Process and Manufacturing Data
to drive Efficiency & Innovation.
Data Analytics for Process Improvement
Data Visualization
Process Modeling
Soft Sensor Development
Predictive Maintenance
Fault Diagnosis
AI/ML Model Development
Supervised & Unsupervised Models
Neural Network(ANN)
Reinforcement Models
Surrogate & Digital Twin Modeling
Data Driven Performance Monitoring
Process Monitoring
Quality Prediction
Process Fault Detection
Fault Classification
AI/ML Deployment
SAAS Platform
On-premise & Cloud deployment
Digital Twin deployment
Application of AI/ML
in Process Industry
Soft Sensing
Soft sensors or virtual sensors are models used to estimate the values of quality related process variables which are other-wise difficult to measure in real-time.
Process Monitoring
Process monitoring/fault detection/abnormality detection is among the most popular
application of ML in process industry.
Predictive Maintenance
Predictive maintenance models are built to determine the time to failure of any equipment or detect patterns in process data that could signal an impending process failure.
Potential of AI /ML impact
Increased
Efficiency
Higher
Performance
Optimal
Operations
Increased
Safety
​
Reduced
Downtime
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