Automation
cwicr-material-procurement
Generate material
---
slug: "cwicr-material-procurement"
display_name: "CWICR Material Procurement"
description: "Generate material procurement lists from CWICR data. Calculate quantities with waste factors, group by supplier categories, and create purchase orders."
---
# CWICR Material Procurement
## Business Case
### Problem Statement
Material procurement needs accurate quantity lists:
- What materials are needed?
- How much of each with waste allowance?
- When are they needed on site?
- How to group for suppliers?
### Solution
Generate procurement lists from CWICR material data with waste factors, delivery scheduling, and supplier grouping.
### Business Value
- **Accurate quantities** - Based on validated norms
- **Waste included** - Industry-standard waste factors
- **Timely delivery** - Aligned with schedule
- **Cost optimization** - Bulk ordering opportunities
## Technical Implementation
```python
import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from datetime import datetime, timedelta
from enum import Enum
from collections import defaultdict
class MaterialCategory(Enum):
"""Material categories for procurement."""
CONCRETE = "concrete"
STEEL = "steel"
TIMBER = "timber"
MASONRY = "masonry"
FINISHES = "finishes"
MEP = "mep"
INSULATION = "insulation"
ROOFING = "roofing"
EARTHWORK = "earthwork"
OTHER = "other"
class ProcurementPriority(Enum):
"""Procurement priority levels."""
CRITICAL = 1
HIGH = 2
MEDIUM = 3
LOW = 4
@dataclass
class MaterialItem:
"""Single material item for procurement."""
material_code: str
description: str
category: MaterialCategory
unit: str
net_quantity: float
waste_factor: float
gross_quantity: float
unit_price: float
total_cost: float
lead_time_days: int
required_date: datetime
order_date: datetime
supplier: str = ""
work_item_codes: List[str] = field(default_factory=list)
@dataclass
class ProcurementList:
"""Complete procurement list."""
project_name: str
generated_date: datetime
total_items: int
total_cost: float
items: List[MaterialItem]
by_category: Dict[str, float]
by_supplier: Dict[str, List[MaterialItem]]
# Standard waste factors by material type
WASTE_FACTORS = {
'concrete': 0.05, # 5%
'reinforcement': 0.03, # 3%
'formwork': 0.10, # 10%
'masonry': 0.05, # 5%
'timber': 0.08, # 8%
'drywall': 0.10, # 10%
'tiles': 0.10, # 10%
'paint': 0.05, # 5%
'insulation': 0.05, # 5%
'pipes': 0.03, # 3%
'cables': 0.05, # 5%
'default': 0.05 # 5%
}
# Standard lead times by category (days)
LEAD_TIMES = {
'concrete': 1, # Ready-mix
'reinforcement': 7, # Steel delivery
'formwork': 3, # Standard forms
'masonry': 5, # Block delivery
'timber': 5, # Lumber
'structural_steel': 21, # Fabrication
'windows': 28, # Manufacturing
'doors': 14, # Standard doors
'mep': 14, # MEP equipment
'finishes': 7, # Standard finishes
'default': 7
}
class CWICRMaterialProcurement:
"""Generate procurement lists from CWICR data."""
def __init__(self, cwicr_data: pd.DataFrame,
resources_data: pd.DataFrame = None):
self.work_items = cwicr_data
self.resources = resources_data
self._index_data()
def _index_data(self):
"""Index data for fast lookup."""
if 'work_item_code' in self.work_items.columns:
self._work_index = self.work_items.set_index('work_item_code')
else:
self._work_index = None
def get_waste_factor(self, material_type: str) -> float:
"""Get waste factor for material type."""
material_lower = str(material_type).lower()
for key, factor in WASTE_FACTORS.items():
if key in material_lower:
return factor
return WASTE_FACTORS['default']
def get_lead_time(self, material_type: str) -> int:
"""Get lead time for material type."""
material_lower = str(material_type).lower()
for key, days in LEAD_TIMES.items():
if key in material_lower:
return days
return LEAD_TIMES['default']
def get_category(self, material_type: str) -> MaterialCategory:
"""Determine material category."""
material_lower = str(material_type).lower()
category_mapping = {
'concrete': MaterialCategory.CONCRETE,
'cement': MaterialCategory.CONCRETE,
'steel': MaterialCategory.STEEL,
'rebar': MaterialCategory.STEEL,
'reinforcement': MaterialCategory.STEEL,
'timber': MaterialCategory.TIMBER,
'wood': MaterialCategory.TIMBER,
'lumber': MaterialCategory.TIMBER,
'masonry': MaterialCategory.MASONRY,
'block': MaterialCategory.MASONRY,
'brick': MaterialCategory.MASONRY,
'paint': MaterialCategory.FINISHES,
'tile': MaterialCategory.FINISHES,
'floor': MaterialCategory.FINISHES,
'electrical': MaterialCategory.MEP,
'plumbing': MaterialCategory.MEP,
'hvac': MaterialCategory.MEP,
'insulation': MaterialCategory.INSULATION,
'roof': MaterialCategory.ROOFING
}
for key, cat in category_mapping.items():
if key in material_lower:
return cat
return MaterialCategory.OTHER
def extract_materials(self,
items: List[Dict[str, Any]],
schedule: Dict[str, datetime] = None) -> List[MaterialItem]:
"""Extract material requirements from work items."""
materials = defaultdict(lambda: {
'net_quantity': 0,
'work_items': [],
'required_date': None
})
for item in items:
code = item.get('work_item_code', item.get('code'))
qty = item.get('quantity', 0)
required_date = item.get('required_date')
if self._work_index is not None and code in self._work_index.index:
work_item = self._work_index.loc[code]
# Get material info from work item
material_desc = str(work_item.get('material_description',
work_item.get('description', '')))
material_unit = str(work_item.get('material_unit',
work_item.get('unit', '')))
material_norm = float(work_item.get('material_norm', 1) or 1)
material_cost = float(work_item.get('material_cost', 0) or 0)
# Calculate material quantity
material_qty = qty * material_norm
# Aggregate by material description
mat_key = f"{material_desc}|{material_unit}"
materials[mat_key]['net_quantity'] += material_qty
materials[mat_key]['work_items'].append(code)
materials[mat_key]['description'] = material_desc
materials[mat_key]['unit'] = material_unit
materials[mat_key]['unit_price'] = material_cost / material_norm if material_norm > 0 else 0
if required_date:
if materials[mat_key]['required_date'] is None:
materials[mat_key]['required_date'] = required_date
else:
materials[mat_key]['required_date'] = min(
materials[mat_key]['required_date'], required_date
)
# Convert to MaterialItem list
result = []
for mat_key, data in materials.items():
description = data['description']
waste_factor = self.get_waste_factor(description)
lead_time = self.get_lead_time(description)
net_qty = data['net_quantity']
gross_qty = net_qty * (1 + waste_factor)
unit_price = data.get('unit_price', 0)
required_date = data['required_date'] or datetime.now() + timedelta(days=30)
order_date = required_date - timedelta(days=lead_time)
result.append(MaterialItem(
material_code=mat_key.split('|')[0][:20],
description=description,
category=self.get_category(description),
unit=data['unit'],
net_quantity=round(net_qty, 2),
waste_factor=waste_factor,
gross_quantity=round(gross_qty, 2),
unit_price=round(unit_price, 2),
total_cost=round(gross_qty * unit_price, 2),
lead_time_days=lead_time,
required_date=required_date,
order_date=order_date,
work_item_codes=data['work_items']
))
return result
def generate_procurement_list(self,
items: List[Dict[str, Any]],
project_name: str = "Project") -> ProcurementList:
"""Generate complete procurement list."""
materials = self.extract_materials(items)
# Group by category
by_category = defaultdict(float)
for mat in materials:
by_category[mat.category.value] += mat.total_cost
# Group by supplier (placeholder - would use supplier mapping)
by_supplier = defaultdict(list)
for
... (truncated)
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