The Circular Economy Model project aims to optimize resource usage and minimize waste in a product lifecycle by leveraging machine learning models for demand forecasting, predictive maintenance, supply chain optimization, and product design optimization.
This project provides a Python implementation of a Circular Economy Model, consisting of several machine learning models integrated into a cohesive framework. The key components include:
- Products: Representing various items within the circular economy system.
- Demand Forecasting: Predicting future demand for products.
- Predictive Maintenance: Anticipating maintenance needs for products.
- Supply Chain Optimization: Optimizing the supply chain processes.
- Product Design Optimization: Enhancing product design for sustainability.
- Python 3.x
- Required Python packages: numpy, scikit-learn, pandas
Ensure the following training data files are available:
- demand_training_data.csv
- maintenance_training_data.csv
- supply_chain_training_data.csv
- product_design_training_data.csv
This project is licensed under the MIT License.
- scikit-learn: Machine learning library for Python
- Kaushal Malpure
- Tejas Patil
- Vanshika Sharma