kishorkukreja/awesome-supply-chain/circular-economy

import numpy as np
import pandas as pd
class CircularityCalculator:
    """Calculate circularity metrics for products and systems"""
    def calculate_mci(self, virgin_input, recycled_input, product_mass,
                     waste_generated, product_lifespan_actual,
                     product_lifespan_industry_avg):
        """
        Calculate Material Circularity Indicator (Ellen MacArthur Foundation)
        MCI ranges from 0 (linear) to 1 (fully circular)
        Parameters:
        - virgin_input: kg of virgin material input
        - recycled_input: kg of recycled material input
        - product_mass: kg of final product
        - waste_generated: kg of waste in production + end-of-life
        - product_lifespan_actual: years product is used
        - product_lifespan_industry_avg: years average for product category
        """
        total_input = virgin_input + recycled_input
        # Linear Flow Index (LFI) - measures material losses
        # LFI = (Virgin input + Waste) / (2 × Product mass)
        lfi = (virgin_input + waste_generated) / (2 * product_mass) if product_mass > 0 else 1
        # Utility factor - accounts for product lifespan
        # Longer life = better circularity
        utility_factor = product_lifespan_actual / product_lifespan_industry_avg
        utility_factor = min(utility_factor, 5)  # Cap at 5x industry average
        # MCI calculation
        mci = (1 - lfi) * utility_factor
        # Ensure MCI is between 0 and 1
        mci = max(0, min(1, mci))
        return {
            'mci': round(mci, 3),
            'lfi': round(lfi, 3),
            'utility_factor': round(utility_factor, 2),
            'virgin_content_pct': round(virgin_input / total_input * 100, 1) if total_input > 0 else 0,
            'recycled_content_pct': round(recycled_input / total_input * 100, 1) if total_input > 0 else 0,
            'circularity_level': self._classify_mci(mci)
        }
    def _classify_mci(self, mci):
        """Classify circularity level"""
        if mci >= 0.9:
            return 'Highly Circular'
        elif mci >= 0.7:
            return 'Circular'
        elif mci >= 0.5:
            return 'Moderately Circular'
        elif mci >= 0.3:
            return 'Somewhat Circular'
        else:
            return 'Linear'
    def calculate_circularity_rate(self, cycled_materials, total_material_flow):
        """
        Calculate Circularity Rate
        Percentage of materials that are cycled back into the economy
        """
        circularity_rate = (cycled_materials / total_material_flow * 100) if total_material_flow > 0 else 0
        return {
            'circularity_rate_pct': round(circularity_rate, 1),
            'cycled_materials': cycled_materials,
            'total_material_flow': total_material_flow,
            'linear_materials': total_material_flow - cycled_materials
        }
    def calculate_r_strategies_impact(self, product_value, r_strategy,
                                     value_retention_rate):
        """
        Calculate value retention for different R-strategies
        R-strategies (9R framework):
        R0: Refuse, R1: Rethink, R2: Reduce
        R3: Reuse, R4: Repair, R5: Refurbish
        R6: Remanufacture, R7: Repurpose, R8: Recycle, R9: Recover
        """
        # Value retention rates by strategy (typical)
        retention_rates = {
            'refuse': 1.0,       # Prevent need
            'rethink': 1.0,      # Product-as-service
            'reduce': 1.0,       # More efficient use
            'reuse': 0.95,       # Direct reuse
            'repair': 0.90,      # Fix for same use
            'refurbish': 0.85,   # Restore to good condition
            'remanufacture': 0.80,  # Disassemble and rebuild
            'repurpose': 0.60,   # Different application
            'recycle': 0.40,     # Material recovery
            'recover': 0.20      # Energy recovery
        }
        default_retention = retention_rates.get(r_strategy, 0.5)
        actual_retention = value_retention_rate if value_retention_rate else default_retention
        retained_value = product_value * actual_retention
        return {
            'r_strategy': r_strategy,
            'original_value': product_value,
            'retention_rate': actual_retention,
            'retained_value': round(retained_value, 2),
            'value_lost': round(product_value - retained_value, 2)
        }
# Example usage
calculator = CircularityCalculator()
# Example 1: Calculate MCI for a product
mci_result = calculator.calculate_mci(
    virgin_input=8.0,       # kg virgin materials
    recycled_input=2.0,     # kg recycled materials
    product_mass=10.0,      # kg final product
    waste_generated=1.5,    # kg waste (production + end-of-life)
    product_lifespan_actual=8,  # years
    product_lifespan_industry_avg=5  # years
)
print("Material Circularity Indicator (MCI):")
print(f"  MCI Score: {mci_result['mci']}")
print(f"  Circularity Level: {mci_result['circularity_level']}")
print(f"  Virgin Content: {mci_result['virgin_content_pct']}%")
print(f"  Recycled Content: {mci_result['recycled_content_pct']}%")
print(f"  Utility Factor: {mci_result['utility_factor']}")
# Example 2: Circularity rate
circ_rate = calculator.calculate_circularity_rate(
    cycled_materials=3000,      # tonnes recycled/reused
    total_material_flow=10000   # tonnes total materials used
)
print(f"\nCircularity Rate: {circ_rate['circularity_rate_pct']}%")
# Example 3: R-strategy value retention
repair_value = calculator.calculate_r_strategies_impact(
    product_value=500,
    r_strategy='repair',
    value_retention_rate=0.90
)
print(f"\nRepair Strategy:")
print(f"  Original Value: ${repair_value['original_value']}")
print(f"  Retained Value: ${repair_value['retained_value']}")
print(f"  Value Retention Rate: {repair_value['retention_rate']*100}%")

class CircularDesignAssessment:
    """Assess product design for circularity"""
    def __init__(self, product_name):
        self.product_name = product_name
        self.assessment_criteria = {}
    def assess_design_for_disassembly(self, design_data):
        """
        Assess how easy product is to disassemble
        design_data: dict with design characteristics
        """
        score = 0
        max_score = 100
        feedback = []
        # Fastener type (0-20 points)
        fasteners = design_data.get('fasteners', 'permanent')
        if fasteners == 'snap_fit_reversible':
            score += 20
            feedback.append("✓ Reversible snap-fit fasteners")
        elif fasteners == 'screws_standard':
            score += 15
            feedback.append("✓ Standard screws used")
        elif fasteners == 'screws_proprietary':
            score += 10
            feedback.append("⚠ Proprietary fasteners (use standard)")
        else:
            score += 0
            feedback.append("✗ Permanent fasteners (welding, glue)")
        # Material variety (0-20 points)
        num_materials = design_data.get('num_material_types', 5)
        if num_materials <= 2:
            score += 20
            feedback.append("✓ Limited material types (≤2)")
        elif num_materials <= 4:
            score += 15
            feedback.append("⚠ Moderate material variety (3-4 types)")
        else:
            score += 5
            feedback.append("✗ High material variety (simplify)")
        # Material compatibility (0-20 points)
        incompatible_materials = design_data.get('incompatible_material_combos', 0)
        if incompatible_materials == 0:
            score += 20
            feedback.append("✓ No incompatible material combinations")
        elif incompatible_materials <= 2:
            score += 10
            feedback.append("⚠ Some incompatible combinations")
        else:
            score += 0
            feedback.append("✗ Many incompatible combinations")
        # Component labeling (0-15 points)
        if design_data.get('components_labeled', False):
            score += 15
            feedback.append("✓ Components labeled for recycling")
        else:
            score += 0
            feedback.append("✗ Components not labeled")
        # Modular design (0-25 points)
        modularity = design_data.get('modularity_level', 'none')
        if modularity == 'high':
            score += 25
            feedback.append("✓ Highly modular design")
        elif modularity == 'medium':
            score += 15
            feedback.append("⚠ Partially modular")
        else:
            score += 0
            feedback.append("✗ Not modular")
        return {
            'score': score,
            'max_score': max_score,
            'percentage': round(score / max_score * 100, 1),
            'rating': self._get_rating(score / max_score),
            'feedback': feedback
        }
    def assess_material_selection(self, material_data):
        """Assess material choices for circularity"""
        score = 0
        max_score = 100
        feedback = []