Project Overview

• Develop an AI-driven digital twin that tracks and predicts the environmental performance of a process unit in real time.
• Use process data and Life Cycle Assessment (LCA) modeling to calculate carbon and energy footprints and forecast sustainability KPIs to support eco-efficient operational decisions.

Deliverables

• Data pipeline connecting process data sources (historian or simulation) to sustainability models.
• Integrated LCA module for automated CO₂ and energy footprint computation.
• Machine learning model predicting future sustainability KPIs under changing operating conditions.
• Visualization dashboard displaying real-time and forecasted environmental metrics.
• Documentation & deployment guide describing model architecture, data flow, and usage instructions.
• Final technical report & presentation summarizing implementation, validation, and business impact.

Technical Scope & Keywords

• Focus areas include Digital Twin development, Process Optimization, AI/ML, Energy Efficiency, Carbon Footprint, and LCA.
• Work involves data engineering (process historian or simulation sources), LCA integration, ML modeling for forecasting, and dashboard visualization.

Application

• To apply, send your CV to careers@integrationobjects.com .
• Recommended to highlight experience in process data handling, LCA or sustainability assessment, ML forecasting, and dashboarding in the application.