You will get a predictive maintenance model and equipment health dashboard
Project details
I've spent 10+ years on the plant floor as a process engineer (glass manufacturing, oil & gas, chemical processing) before moving into data science. That combination means I don't just fit a model to your sensor data - I understand what a spike in vibration or a slow drift in pressure actually means for your equipment. I've built anomaly detection and predictive maintenance systems for pumps, compressors, and amine sweetening units, cutting one client's foaming events by 20%. This project brings that same approach to your equipment: physics-informed features, models that explain their predictions (SHAP), and a dashboard your team will actually open every day.
Machine Learning Tools
Azure Machine Learning, Microsoft Power BI, pandas, Python, Python Scikit-Learn, PyTorch, XGBoostWhat's included
| Service Tiers |
Starter
$150
|
Standard
$500
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 2 |
Number of Graphs/Charts | 1 | 5 | 10 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code | - | - |
Frequently asked questions
About Usama
Industrial Data Scientist | Predictive Maintenance | Python & ML
Lahore, Pakistan - 5:44 am local time
With 10+ years of hands-on process engineering experience (glass manufacturing, oil & gas, chemical processing) combined with advanced data science and machine learning, I bring something most data scientists can't — I understand your process, not just your data.
What I've delivered:
• Reduced foaming events by 20% using PyTorch and OPC sensor data in an Amine Sweetening Unit
• Built pump predictive maintenance models with real-time degradation tracking and RCA
• Developed membrane RUL (Remaining Useful Life) prediction with KPI dashboards
• Built financial forecasting models and interactive Power BI / data visualization dashboards
Tech Stack: Python (Pandas, NumPy, Scikit-Learn, PyTorch) | SQL | Power BI | Azure ML | Time Series Analysis | IoT/OPC Data
If your business runs on industrial processes and you need data-driven insights, let's talk.
Steps for completing your project
After purchasing the project, send requirements so Usama can start the project.
Delivery time starts when Usama receives requirements from you.
Usama works on your project following the steps below.
Revisions may occur after the delivery date.
Data audit, cleaning, and feature engineering
I review your data, clean and validate sensor signals, and engineer the physics-informed features the model will use.
Model build, dashboard, and handover
I train and validate the model, build your interactive dashboard, and walk you through how to use and maintain it.