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DCM Shriram Chemicals Tech Stack
Chlor-alkali manufacturer scaling ML and process optimization across India's chemical production
DCM Shriram Chemicals operates two state-of-the-art chlor-alkali plants and supplies core chemicals to 73 countries. The tech stack reveals a shift toward data-driven operations: Python, scikit-learn, XGBoost, and Azure ML sit alongside SCADA, PLC, and process simulation tools (Aspen Plus, HYSYS), indicating active development of yield prediction and process optimization models. Engineering-focused hiring (4 engineering, 1 data role) and projects centered on model deployment suggest the company is moving from traditional plant operations toward predictive analytics for downtime prevention and safety compliance.
Tech Stack 14 technologies
Core StackPython Pandas scikit-learn SageMaker SAP Pyomo XGBoost Azure Machine Learning DCS SCADA OPC UA Aspen Plus HYSYS PLC
What DCM Shriram Chemicals Is Building
◆Challenges
- Energy usage minimization
- Downtime prevention
- Yield prediction
- Managing project costs
- Statutory compliance
- Safety compliance
- Preventing catastrophic incidents
- Ensuring psm compliance
- Improving psm program effectiveness
- Minimizing downtime
▲Active Projects
- Yield prediction model development
- Process optimization model development
- Model deployment into production environments
- Major capital projects design consulting
- Process hazard analysis
- Process safety self-audits
- Continuous improvement projects to enhance plant reliability and efficiency
- Modification, installation, and commissioning of new instrumentation systems
- Energy conservation and productivity improvement schemes
Hiring Activity
5 roles · 2 in 30d
Department
Seniority
Company intelligence
