🌟 Looking for an INDUSTRIAL Ph.D. at Universitat Politècnica de Catalunya? 🌟
Here in BeChained, we look for brilliant candidates.
👉 Energy Efficiency and Downtime Reduction System using AI and Optimization Techniques for Industrial Processes 👈
Develop a novel framework for improving energy efficiency and reducing downtime in industrial processes using advanced AI and optimisation techniques. Combine methods in optimization, including both mathematical and AI-driven approaches, with a focus on ✨ reinforcement learning ✨ and ✨ machine learning ✨ models geared to industrial applications.
Focus on the technical, economic, and environmental aspects of energy consumption and operational efficiency in industries such as
metal, paper, and food.
Create innovative approaches that optimise resource allocation, streamline production workflows, and lower operational costs.
🎯 Objective:
Maximise operational efficiency, economic sustainability, and environmental impact reduction in industrial processes.
👏 Enhanced AI optimisation techniques targeting energy consumption, downtime reduction, and emission mitigation. Ensure to meet economic & production goals, but also sustainability standards.
💡 Research Scope and Methodology
Develop and implement a set of advanced AI-driven optimization algorithms and mathematical models to enhance energy efficiency. Reduce downtime in a variety of industrial sectors. Incorporates real-time data analytics, RL, ML & optimisation techniques.
Combine them to monitor, anticipate, and optimise machine operations and energy consumption.
🎰 Create a system & connect with a wide range of industrial equipment, using real-time data.
🧠 By analyzing energy consumption patterns and production metrics, the system will autonomously identify optimal operational settings, thereby enhancing energy efficiency and minimizing downtime.
💘 Economically, the project will design cost-effective strategies that reduce energy expenses and maximize return on investment for stakeholders.
💚 Incorporate carbon reduction metrics, enabling companies to achieve environmental targets while maintaining operational efficiency.
🏭 Ensure robustness, experimental validations will be conducted in collaboration with industrial partners, facilitating the deployment of scalable
solutions adaptable to diverse industrial settings.
🎯 Results
Enhance energy efficiency and operational uptime in industrial processes, providing a benchmark for sustainability and cost savings in the sector. Demonstrate substantial reductions in energy costs and downtime, contributing to a more efficient, sustainable industrial ecosystem.
Make a flexible and scalable optimisation framework adaptable to various industrial environments (i.e. steel & metal, paper, food). Foster a future of smart, sustainable, and resilient industrial operations.
😍 For more information
https://lnkd.in/dDGZKCYk