fix

src/calculation_time_constrains/flows.py

@@ -21,7 +21,7 @@ from .service import (create_calculation_result_service, create_param_and_data,
                       get_calculation_by_reference_and_parameter,
                       get_calculation_data_by_id, get_calculation_result,
                       get_corrective_cost_time_chart,
-                      get_overhaul_cost_by_time_chart, run_simulation)
+                      get_overhaul_cost_by_time_chart, run_simulation, run_simulation_with_spareparts)
 from src.database.core import CollectorDbSession
 
 
@@ -97,7 +97,7 @@ async def create_calculation(
     # results = await create_calculation_result_service(
     #     db_session=db_session, calculation=calculation_data, token=token
     # )
-    results = await run_simulation(
+    results = await run_simulation_with_spareparts(
         db_session=db_session, calculation=calculation_data, token=token, collector_db_session=collector_db_session
     )
 

src/calculation_time_constrains/schema.py

@@ -46,12 +46,15 @@ class CalculationTimeConstrainsParametersCreate(CalculationTimeConstrainsBase):
 
 
 class CalculationResultsRead(CalculationTimeConstrainsBase):
-    day: int
-    corrective_cost: float
     overhaul_cost: float
+    corrective_cost: float
     procurement_cost: float
-    procurement_details: Optional[Dict[str, Any]]
     num_failures: float
+    day: int
+    month: int
+    total_cost: float
+    procurement_details: Dict
+    sparepart_summary: dict
 
 
 class OptimumResult(CalculationTimeConstrainsBase):
@@ -74,14 +77,44 @@ class EquipmentResult(CalculationTimeConstrainsBase):
     is_included: bool
     master_equipment: Optional[MasterEquipmentBase] = Field(None)
 
+class FleetStatistics(CalculationTimeConstrainsBase):
+    total_equipment: int
+    included_equipment: int
+    excluded_equipment: int
+    equipment_with_sparepart_constraints: int
+    total_procurement_items: int
+    critical_procurement_items: int
+
+class OptimalAnalysis(CalculationTimeConstrainsBase):
+    optimal_month: int
+    planned_month: Optional[int]
+    timing_recommendation: str
+    optimal_total_cost: float
+    optimal_breakdown: Dict
+    cost_trend: str
+    months_from_planned: Optional[int]
+    cost_savings_vs_planned: Optional[float]
+    sparepart_impact: Dict
+
+class AnalysisMetadata(CalculationTimeConstrainsBase):
+    max_interval_months: int
+    last_overhaul_date: Optional[str]
+    next_planned_overhaul: str
+    calculation_type: str
+    total_equipment_analyzed: int
+    included_in_optimization: int
 
 class CalculationTimeConstrainsRead(CalculationTimeConstrainsBase):
     id: UUID
     reference: UUID
     scope: str
     results: List[CalculationResultsRead]
+    optimum_oh: int
+    optimum_oh_month: int
     equipment_results: List[EquipmentResult]
-    optimum_oh: Any
+    fleet_statistics: dict
+    optimal_analysis: dict
+    analysis_metadata: dict
 
 
 class CalculationTimeConstrainsCreate(CalculationTimeConstrainsBase):

src/calculation_time_constrains/utils.py

@@ -1,4 +1,7 @@
 import datetime
+import json
+
+import pandas as pd
 
 def get_months_between(start_date: datetime.datetime, end_date: datetime.datetime) -> int:
     """
@@ -34,8 +37,8 @@ def create_time_series_data(chart_data, max_hours=24096):
         
         # Add hourly data point
         hourly_data.append({
-            'hour': hour,
-            'flowrate': current_flow_rate,
+            'cumulativeTime': hour,
+            'flowRate': current_flow_rate,
             'currentEQStatus': current_eq_status
         })
     
@@ -88,3 +91,192 @@ def calculate_failures_per_month(hourly_data):
             })
     
     return result
+
+
+def analyze_monthly_metrics(timestamp_outs):
+    """
+    Analyze time series data to calculate monthly metrics:
+    1. Failure count per month
+    2. Cumulative failure count each month
+    3. Total out-of-service time per month  
+    4. Average flow rate per month
+    """
+    
+    # Check if timestamp_outs is None or empty
+    if timestamp_outs is None or not timestamp_outs:
+        # Return empty results with zero values
+        return {}
+    
+    # Convert to DataFrame for easier manipulation
+    df = pd.DataFrame(timestamp_outs)
+    
+    # Check if DataFrame is empty after creation
+    if df.empty:
+        return {}
+    
+    # Check if required columns exist
+    required_columns = ['cumulativeTime', 'currentEQStatus', 'flowRate']
+    missing_columns = [col for col in required_columns if col not in df.columns]
+    if missing_columns:
+        return {}
+    
+    # Assuming the simulation starts from a reference date (you can modify this)
+    # For this example, I'll use January 1, 2024 as the start date
+    start_date = datetime.datetime(2025, 10, 22)
+    
+    # Convert cumulative hours to actual datetime
+    df['datetime'] = df['cumulativeTime'].apply(
+        lambda x: start_date + datetime.timedelta(hours=x)
+    )
+    
+    # Extract month-year for grouping
+    df['month_year'] = df['datetime'].dt.to_period('M')
+    
+    # Calculate time duration for each record (difference between consecutive cumulative times)
+    df['duration_hours'] = df['cumulativeTime'].diff().fillna(df['cumulativeTime'].iloc[0])
+    
+    # Initialize results dictionary
+    monthly_results = {}
+    
+    # Track cumulative failures across all months
+    cumulative_failures = 0
+    cummulative_oos = 0
+    
+    # Group by month-year and ensure chronological order
+    for month_period, group in df.groupby('month_year'):
+        month_str = str(month_period)
+        monthly_results[month_str] = {}
+        
+        # 1. Count failures per month
+        # A failure is when currentEQStatus changes from "Svc" to "OoS"
+        status_changes = group['currentEQStatus'].shift() != group['currentEQStatus']
+        failures = ((group['currentEQStatus'] == 'OoS') & status_changes).sum()
+        monthly_results[month_str]['failures_count'] = int(failures)
+        
+        # 2. Add failures to cumulative count
+        cumulative_failures += failures
+        monthly_results[month_str]['cumulative_failures'] = int(cumulative_failures)
+        
+        # 3. Total out-of-service time per month (in hours)
+        oos_time = group[group['currentEQStatus'] == 'OoS']['duration_hours'].sum()
+        monthly_results[month_str]['total_oos_hours'] = float(oos_time)
+        
+        cummulative_oos += oos_time
+        monthly_results[month_str]['cummulative_oos'] = float(cummulative_oos)
+        
+        # 4. Average flow rate per month (weighted by duration)
+        # Calculate weighted average flow rate
+        total_flow_time = (group['flowRate'] * group['duration_hours']).sum()
+        total_time = group['duration_hours'].sum()
+        avg_flow_rate = total_flow_time / total_time if total_time > 0 else 0
+        monthly_results[month_str]['avg_flow_rate'] = float(avg_flow_rate)
+        
+        # Additional useful metrics
+        monthly_results[month_str]['total_hours'] = float(total_time)
+        monthly_results[month_str]['service_hours'] = float(
+            group[group['currentEQStatus'] == 'Svc']['duration_hours'].sum()
+        )
+        monthly_results[month_str]['availability_percentage'] = float(
+            (monthly_results[month_str]['service_hours'] / total_time * 100) if total_time > 0 else 0
+        )
+        
+    
+    return monthly_results
+
+def calculate_risk_cost_per_failure(monthly_results, birnbaum_importance, energy_price):
+    """
+    Calculate risk cost per failure for each month based on:
+    1. Equipment capacity contribution to system (flowrate * birnbaum_importance * availability)
+    2. Capacity lost to downtime per month
+    3. Energy price
+    
+    Parameters:
+    - monthly_results: Output from analyze_monthly_metrics()
+    - birnbaum_importance: Birnbaum importance factor for this equipment
+    - energy_price: Price per unit of energy/flow
+    
+    Returns:
+    - Dictionary with monthly risk costs and array of risk costs per failure
+    """
+    
+    risk_costs = {}
+    risk_cost_array = []
+    
+    for month, data in monthly_results.items():
+        # Extract monthly data
+        avg_flow_rate = data['avg_flow_rate']
+        availability = data['availability_percentage'] / 100  # Convert to decimal
+        total_oos_hours = data['total_oos_hours']
+        failures_count = data['failures_count']
+        
+        # 1. Calculate equipment capacity contribution to system
+        # Capacity = avg_flowrate * birnbaum_importance * availability
+        equipment_capacity = avg_flow_rate * birnbaum_importance * availability
+        
+        # 2. Calculate capacity lost to downtime per month
+        # Lost capacity = avg_flowrate * birnbaum_importance * downtime_hours
+        capacity_lost_to_downtime = avg_flow_rate * birnbaum_importance * total_oos_hours
+        
+        # 3. Calculate total risk cost for the month
+        # Risk cost = capacity_lost * energy_price
+        monthly_risk_cost = capacity_lost_to_downtime * energy_price
+        
+        # 4. Calculate risk cost per failure for this month
+        if failures_count > 0:
+            risk_cost_per_failure = monthly_risk_cost / failures_count
+        else:
+            # If no failures, set to 0 or use alternative approach
+            risk_cost_per_failure = 0
+        
+        # Store results
+        risk_costs[month] = {
+            'equipment_capacity': equipment_capacity,
+            'capacity_lost_to_downtime': capacity_lost_to_downtime,
+            'monthly_risk_cost': monthly_risk_cost,
+            'failures_count': failures_count,
+            'risk_cost_per_failure': risk_cost_per_failure
+        }
+        
+        # Add to array
+        risk_cost_array.append(risk_cost_per_failure)
+    
+    return {
+        'monthly_details': risk_costs,
+        'risk_cost_per_failure_array': risk_cost_array
+    }
+
+# Example usage:
+def get_monthly_risk_analysis(timestamp_outs, birnbaum_importance, energy_price):
+    """
+    Complete analysis combining monthly metrics with risk cost calculation
+    """
+    # Get monthly metrics
+    monthly_metrics = analyze_monthly_metrics(timestamp_outs)
+    
+    # Calculate risk costs
+    risk_analysis = calculate_risk_cost_per_failure(
+        monthly_metrics, 
+        birnbaum_importance, 
+        energy_price
+    )
+    
+    # Combine results for comprehensive view
+    combined_results = {}
+    for month in monthly_metrics.keys():
+        combined_results[month] = {
+            **monthly_metrics[month],
+            **risk_analysis['monthly_details'][month]
+        }
+    
+    return {
+        'monthly_data': combined_results,
+        'risk_cost_array': risk_analysis['risk_cost_per_failure_array']
+    }
+
+# Usage example:
+# birnbaum_importance = 0.85  # Example value
+# energy_price = 100  # Example: $100 per unit
+# 
+# results = get_monthly_risk_analysis(timestamp_outs, birnbaum_importance, energy_price)
+# risk_cost_array = results['risk_cost_array']
+# print("Risk cost per failure each month:", risk_cost_array)

src/logging.py

@@ -1,4 +1,5 @@
 import logging
+import sys
 
 from src.config import LOG_LEVEL
 from src.enums import OptimumOHEnum
@@ -30,3 +31,15 @@ def configure_logging():
 
     # sometimes the slack client can be too verbose
     logging.getLogger("slack_sdk.web.base_client").setLevel(logging.CRITICAL)
+
+
+def setup_logging(logger):
+    # Your logging configuration here
+    logger.setLevel(logging.DEBUG)
+    # Create formatter
+    formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
+    
+    # Create console handler
+    stream_handler = logging.StreamHandler(sys.stdout)
+    stream_handler.setFormatter(formatter)
+    logger.addHandler(stream_handler)

src/sparepart/service.py

@@ -1,4 +1,13 @@
 from typing import Optional
+import asyncio
+import logging
+from datetime import datetime, timedelta, date
+from typing import List, Dict, Optional, Tuple
+from collections import defaultdict
+from uuid import UUID
+import numpy as np
+from dataclasses import dataclass
+from enum import Enum
 
 from sqlalchemy import Delete, Select, text
 from sqlalchemy.orm import joinedload, selectinload
@@ -6,13 +15,13 @@ from sqlalchemy.orm import joinedload, selectinload
 from src.auth.service import CurrentUser
 from src.database.core import DbSession
 from src.database.service import CommonParameters, search_filter_sort_paginate
+from src.logging import setup_logging
+from src.overhaul_scope.service import get as get_scope
+from src.overhaul_scope.service import get_prev_oh
 
 
-# async def get(*, db_session: DbSession, activity_id: str) -> Optional[ActivityMaster]:
-#     """Returns a document based on the given document id."""
-#     result = await db_session.get(MasterActivity, activity_id)
-#     return result
-
+log = logging.getLogger(__name__)
+setup_logging(logger=log)
 
 async def get_all(db_session: DbSession):
     """
@@ -34,16 +43,20 @@ async def get_all(db_session: DbSession):
         h.issue_date as pr_issue_date,
         h.status as pr_status,
         pl.qty_ordered as pr_qty_ordered,
-        pl.description
+        pl.description,
+        pl.unit_cost,
+        pl.line_cost
     FROM public.maximo_sparepart_pr_po h
     JOIN public.maximo_sparepart_pr_po_line pl ON h.num = pl.num
     WHERE h.type = 'PR'
       AND h.issue_date IS NOT NULL
       AND h.num LIKE 'K%'
-    ORDER BY pl.item_num, TO_DATE(h.issue_date, 'YYYY-MM-DD') DESC
+    ORDER BY pl.item_num, h.issue_date DESC
 )
     SELECT DISTINCT ON (pr.item_num)
         pr.item_num,
+        pr.line_cost,
+        pr.unit_cost,
         pr.description,
         COALESCE(i.curbaltotal, 0) as current_balance_total,
         pr.pr_number,
@@ -55,7 +68,7 @@ async def get_all(db_session: DbSession):
         END as po_exists,
         COALESCE(po.qty_received, 0) as po_qty_received,
         COALESCE(po.qty_ordered, 0) as po_qty_ordered,
-        COALESCE(po.estimated_arrival_date, '') as po_estimated_arrival_date
+        po.estimated_arrival_date as po_estimated_arrival_date
     FROM latest_prs pr
     LEFT JOIN public.maximo_inventory i ON pr.item_num = i.itemnum
     LEFT JOIN LATERAL (
@@ -83,6 +96,8 @@ async def get_all(db_session: DbSession):
         spare_parts.append({
             "item_num": row.item_num,
             "description": row.description,
+            "line_cost": row.line_cost,
+            "unit_cost": row.unit_cost,
             "current_balance_total": float(row.current_balance_total) if row.current_balance_total is not None else 0.0,
             "pr_number": row.pr_number,
             "pr_issue_date": row.pr_issue_date,
@@ -97,35 +112,765 @@ async def get_all(db_session: DbSession):
 
 
 
-# async def create(*, db_session: DbSession, activty_in: ActivityMasterCreate):
-#     activity = MasterActivity(**activty_in.model_dump())
-#     db_session.add(activity)
-#     await db_session.commit()
-#     return activity
+class ProcurementStatus(Enum):
+    PLANNED = "planned"
+    ORDERED = "ordered"
+    RECEIVED = "received"
+    CANCELLED = "cancelled"
+
+@dataclass
+class SparepartRequirement:
+    """Sparepart requirement for equipment overhaul"""
+    sparepart_id: str
+    quantity_required: int
+    lead_time: int
+    sparepart_name: str
+
+@dataclass
+class SparepartStock:
+    """Current sparepart stock information"""
+    sparepart_id: str
+    sparepart_name: str
+    current_stock: int
+    unit_cost: float
+    location: str
+
+@dataclass
+class ProcurementRecord:
+    """Purchase Order/Purchase Request record"""
+    po_pr_id: str
+    sparepart_id: str
+    sparepart_name: str
+    quantity: int
+    unit_cost: float
+    total_cost: float
+    order_date: date
+    expected_delivery_date: date
+    status: ProcurementStatus
+
+class SparepartManager:
+    """Manages sparepart availability and procurement for overhaul optimization"""
+    
+    def __init__(self, analysis_start_date: date, analysis_window_months: int):
+        self.analysis_start_date = analysis_start_date
+        self.analysis_window_months = analysis_window_months
+        self.logger = log
+        
+        # Storage for sparepart data
+        self.sparepart_stocks: Dict[str, SparepartStock] = {}
+        self.equipment_requirements: Dict[str, List[SparepartRequirement]] = {}
+        self.procurement_records: List[ProcurementRecord] = []
+        
+        # Monthly projected stocks
+        self.projected_stocks: Dict[str, List[int]] = {}
+
+    def add_sparepart_stock(self, stock: SparepartStock):
+        """Add sparepart stock information"""
+        self.sparepart_stocks[stock.sparepart_id] = stock
+
+    def add_equipment_requirements(self, equipment_tag: str, requirements: List[SparepartRequirement]):
+        """Add sparepart requirements for equipment"""
+        self.equipment_requirements[equipment_tag] = requirements
+
+    def add_procurement_record(self, record: ProcurementRecord):
+        """Add procurement record (PO/PR)"""
+        self.procurement_records.append(record)
+
+    def _calculate_monthly_deliveries(self) -> Dict[str, Dict[int, int]]:
+        """Calculate expected deliveries for each sparepart by month"""
+        deliveries = defaultdict(lambda: defaultdict(int))
+        
+        for record in self.procurement_records:
+            if record.status in [ProcurementStatus.ORDERED, ProcurementStatus.PLANNED]:
+                # Skip records with no expected delivery date (e.g., still PR stage)
+                if not record.expected_delivery_date:
+                    continue
+
+                months_from_start = (
+                    (record.expected_delivery_date.year - self.analysis_start_date.year) * 12 +
+                    (record.expected_delivery_date.month - self.analysis_start_date.month)
+                )
+                
+                if 0 <= months_from_start < self.analysis_window_months:
+                    deliveries[record.sparepart_id][months_from_start] += record.quantity
+
+        return deliveries
+
+
+    def _project_monthly_stocks(self) -> Dict[str, List[int]]:
+        """Project sparepart stock levels for each month"""
+        projected_stocks = {}
+        monthly_deliveries = self._calculate_monthly_deliveries()
+        
+        for sparepart_id, stock_info in self.sparepart_stocks.items():
+            monthly_stock = []
+            current_stock = float(stock_info.current_stock)
+            
+            for month in range(self.analysis_window_months):
+                # Add any deliveries for this month
+                if sparepart_id in monthly_deliveries and month in monthly_deliveries[sparepart_id]:
+                    current_stock += float(monthly_deliveries[sparepart_id][month])
+                
+                monthly_stock.append(current_stock)
+                
+                # Note: We don't subtract usage here yet - that will be done during optimization
+            
+            projected_stocks[sparepart_id] = monthly_stock
+        
+        self.projected_stocks = projected_stocks
+        return projected_stocks
+
+    def check_sparepart_availability(self, equipment_tag: str, target_month: int, 
+                                   consider_other_overhauls: List[Tuple[str, int]] = None) -> Dict:
+        """
+        Check if spareparts are available for equipment overhaul at target month
+        
+        Args:
+            equipment_tag: Equipment location tag
+            target_month: Month when overhaul is planned (0-based)
+            consider_other_overhauls: List of (equipment_tag, month) for other planned overhauls
+        
+        Returns:
+            Dict with availability status and details
+        """
+        if equipment_tag not in self.equipment_requirements:
+            return {
+                'available': True,
+                'message': f'No sparepart requirements defined for {equipment_tag}',
+                'missing_parts': [],
+                'procurement_needed': [],
+                'total_procurement_cost': 0,
+                'can_proceed_with_delays': True,
+                'pr_po_summary': {
+                    'existing_orders': [],
+                    'required_new_orders': [],
+                    'total_existing_value': 0,
+                    'total_new_orders_value': 0
+                }
+            }
+        
+        requirements = self.equipment_requirements[equipment_tag]
+        missing_parts = []
+        procurement_needed = []
+        total_procurement_cost = 0
+        
+        # Calculate stock after considering other overhauls
+        adjusted_stocks = self._calculate_adjusted_stocks(target_month, consider_other_overhauls or [])
+        
+        existing_orders = self._get_existing_orders_for_month(target_month)
+        
+        pr_po_summary = {
+            'existing_orders': [],
+            'required_new_orders': [],
+            'total_existing_value': 0,
+            'total_new_orders_value': 0,
+            'orders_by_status': {
+                'planned': [],
+                'ordered': [],
+                'received': [],
+                'cancelled': []
+            }
+        }
+        
+        
+        for requirement in requirements:
+            sparepart_id = requirement.sparepart_id
+            needed_quantity = requirement.quantity_required
+            sparepart_name = requirement.sparepart_name
+            
+            current_stock = adjusted_stocks.get(sparepart_id, 0)
+            
+            existing_sparepart_orders = [order for order in existing_orders 
+                                   if order.sparepart_id == sparepart_id]
+            
+            total_ordered_quantity = sum(order.quantity for order in existing_sparepart_orders 
+                                   if order.status in [ProcurementStatus.PLANNED, ProcurementStatus.ORDERED])
+            
+            effective_stock = current_stock + total_ordered_quantity
+            
+            # if sparepart_id not in adjusted_stocks:
+            #     missing_parts.append({
+            #         'sparepart_id': sparepart_id,
+            #         'sparepart_name': requirement.sparepart_name,
+            #         'required': needed_quantity,
+            #         'available': 0,
+            #         'shortage': needed_quantity,
+            #         'criticality': "warning"
+            #     })
+            #     continue
+            
+            # available_stock = adjusted_stocks[sparepart_id]
+            
+            # if available_stock < needed_quantity:
+            #     shortage = needed_quantity - available_stock
+            #     missing_parts.append({
+            #         'sparepart_id': sparepart_id,
+            #         'sparepart_name': requirement.sparepart_name,
+            #         'required': needed_quantity,
+            #         'available': available_stock,
+            #         'shortage': shortage,
+            #         'criticality': "warning"
+            #     })
+                
+            #     # Calculate procurement needs
+            #     if sparepart_id in self.sparepart_stocks:
+            #         stock_info = self.sparepart_stocks[sparepart_id]
+            #         procurement_cost = shortage * stock_info.unit_cost
+            #         total_procurement_cost += procurement_cost
+
+                    
+            #         # Calculate when to order (considering lead time)
+            #         order_month = max(0, target_month - requirement.lead_time)
+                    
+            #         procurement_needed.append({
+            #             'sparepart_id': sparepart_id,
+            #             'sparepart_name': requirement.sparepart_name,
+            #             'quantity_needed': shortage,
+            #             'unit_cost': stock_info.unit_cost,
+            #             'total_cost': procurement_cost,
+            #             'order_by_month': order_month,
+            #             'lead_time_months': requirement.lead_time,
+            #             'criticality': "warning"
+            #         })
+            if effective_stock >= needed_quantity:
+            # Sufficient stock available (including from existing orders)
+                if existing_sparepart_orders:
+                    # Add existing order info to summary
+                    for order in existing_sparepart_orders:
+                        order_info = {
+                            'po_pr_id': order.po_pr_id,
+                            'sparepart_id': sparepart_id,
+                            'sparepart_name': sparepart_name,
+                            'quantity': order.quantity,
+                            'unit_cost': order.unit_cost,
+                            'total_cost': order.total_cost,
+                            'order_date': order.order_date.isoformat(),
+                            'expected_delivery_date': order.expected_delivery_date.isoformat(),
+                            'status': order.status.value,
+                            'months_until_delivery': self._calculate_months_until_delivery(order.expected_delivery_date, target_month),
+                            'is_on_time': self._is_delivery_on_time(order.expected_delivery_date, target_month),
+                            'usage': 'covers_requirement'
+                        }
+                        pr_po_summary['existing_orders'].append(order_info)
+                        pr_po_summary['total_existing_value'] += order.total_cost
+                        pr_po_summary['orders_by_status'][order.status.value].append(order_info)
+            else:
+                # Insufficient stock - need additional procurement
+                shortage = needed_quantity - effective_stock
+                
+                missing_parts.append({
+                    'sparepart_id': sparepart_id,
+                    'sparepart_name': sparepart_name,
+                    'required': needed_quantity,
+                    'current_stock': current_stock,
+                    'ordered_quantity': total_ordered_quantity,
+                    'effective_available': effective_stock,
+                    'shortage': shortage,
+                    'criticality': "warning",
+                    'existing_orders': len(existing_sparepart_orders),
+                    'existing_orders_details': [
+                        {
+                            'po_pr_id': order.po_pr_id,
+                            'quantity': order.quantity,
+                            'status': order.status.value,
+                            'expected_delivery': order.expected_delivery_date.isoformat(),
+                            'is_on_time': self._is_delivery_on_time(order.expected_delivery_date, target_month)
+                        } for order in existing_sparepart_orders
+                    ]
+                })
+                
+                # Calculate additional procurement needed
+                if sparepart_id in self.sparepart_stocks:
+                    stock_info = self.sparepart_stocks[sparepart_id]
+                    procurement_cost = shortage * stock_info.unit_cost
+                    total_procurement_cost += procurement_cost
+                    
+                    # Calculate when to order (considering lead time)
+                    order_month = max(0, target_month - requirement.lead_time)
+                    order_date = self.analysis_start_date + timedelta(days=order_month * 30)
+                    expected_delivery = order_date + timedelta(days=requirement.lead_time * 30)
+                    
+                    new_order = {
+                        'sparepart_id': sparepart_id,
+                        'sparepart_name': sparepart_name,
+                        'quantity_needed': shortage,
+                        'unit_cost': stock_info.unit_cost,
+                        'total_cost': procurement_cost,
+                        'order_by_month': order_month,
+                        'recommended_order_date': order_date.isoformat(),
+                        'expected_delivery_date': expected_delivery.isoformat(),
+                        'lead_time_months': requirement.lead_time,
+                        'criticality': "warning",
+                        'urgency': self._calculate_urgency(order_month, target_month),
+                        'reason': f'Additional {shortage} units needed beyond existing orders'
+                    }
+                    
+                    procurement_needed.append(new_order)
+                    pr_po_summary['required_new_orders'].append(new_order)
+                    pr_po_summary['total_new_orders_value'] += procurement_cost
+        
+        # Check for critical parts
+        critical_missing = [p for p in missing_parts if p['criticality'] == 'critical']
+        
+        # Generate comprehensive summary
+        availability_summary = self._generate_comprehensive_availability_message(
+            missing_parts, critical_missing, pr_po_summary
+        )
+        
+        return {
+            'available': len(critical_missing) == 0,
+            'total_missing_parts': len(missing_parts),
+            'critical_missing_parts': len(critical_missing),
+            'missing_parts': missing_parts,
+            'procurement_needed': procurement_needed,
+            'total_procurement_cost': total_procurement_cost,
+            'can_proceed_with_delays': len(critical_missing) == 0,
+            'message': availability_summary['message'],
+            'detailed_message': availability_summary['detailed_message'],
+            'pr_po_summary': pr_po_summary,
+            'recommendations': self._generate_procurement_recommendations(pr_po_summary, target_month)
+        }
+        
+    def _calculate_months_until_delivery(self, delivery_date: date, target_month: int) -> int:
+        """Calculate months from target month to delivery date"""
+        target_date = self.analysis_start_date + timedelta(days=target_month * 30)
+        months_diff = (delivery_date.year - target_date.year) * 12 + (delivery_date.month - target_date.month)
+        return months_diff
+
+    def _calculate_urgency(self, order_month: int, target_month: int) -> str:
+        """Calculate urgency level for new procurement"""
+        time_gap = target_month - order_month
+        
+        if time_gap <= 1:
+            return "URGENT"
+        elif time_gap <= 3:
+            return "HIGH"
+        elif time_gap <= 6:
+            return "MEDIUM"
+        else:
+            return "LOW"
+    
+    def _generate_procurement_recommendations(self, pr_po_summary: Dict, target_month: int) -> List[Dict]:
+        """Generate procurement recommendations based on analysis"""
+        recommendations = []
+        
+        # Check for late deliveries
+        late_orders = [order for order in pr_po_summary['existing_orders'] 
+                    if not order['is_on_time']]
+        
+        if late_orders:
+            recommendations.append({
+                'type': 'LATE_DELIVERY_WARNING',
+                'priority': 'HIGH',
+                'message': f"{len(late_orders)} existing orders will deliver late",
+                'details': [f"PO/PR {order['po_pr_id']} for {order['sparepart_name']}" 
+                        for order in late_orders],
+                'action': 'Expedite delivery or find alternative suppliers'
+            })
+        
+        # Check for urgent new orders
+        urgent_orders = [order for order in pr_po_summary['required_new_orders'] 
+                        if order['urgency'] == 'URGENT']
+        
+        if urgent_orders:
+            recommendations.append({
+                'type': 'URGENT_PROCUREMENT',
+                'priority': 'CRITICAL',
+                'message': f"{len(urgent_orders)} spareparts need immediate ordering",
+                'details': [f"{order['sparepart_name']}: {order['quantity_needed']} units" 
+                        for order in urgent_orders],
+                'action': 'Place orders immediately or consider expedited delivery'
+            })
+        
+        # Check for cancelled orders
+        cancelled_orders = pr_po_summary['orders_by_status'].get('cancelled', [])
+        if cancelled_orders:
+            recommendations.append({
+                'type': 'CANCELLED_ORDER_IMPACT',
+                'priority': 'MEDIUM',
+                'message': f"{len(cancelled_orders)} cancelled orders may affect availability",
+                'details': [f"Cancelled: PO/PR {order['po_pr_id']} for {order['sparepart_name']}" 
+                        for order in cancelled_orders],
+                'action': 'Review impact and place replacement orders if necessary'
+            })
+        
+        # Budget recommendations
+        total_investment = pr_po_summary['total_existing_value'] + pr_po_summary['total_new_orders_value']
+        if total_investment > 0:
+            recommendations.append({
+                'type': 'BUDGET_SUMMARY',
+                'priority': 'INFO',
+                'message': f'Total sparepart investment: ${total_investment:,.2f}',
+                'details': [
+                    f"Existing orders: ${pr_po_summary['total_existing_value']:,.2f}",
+                    f"Additional orders needed: ${pr_po_summary['total_new_orders_value']:,.2f}"
+                ],
+                'action': 'Ensure budget allocation for sparepart procurement'
+            })
+        
+        return recommendations
+    
+    def _is_delivery_on_time(self, delivery_date: datetime, target_month: int) -> bool:
+        """Check if delivery will arrive on time for target month"""
+        target_date = self.analysis_start_date + timedelta(days=target_month * 30)
+        del_time = delivery_date.date() if delivery_date else None
+        
+        return del_time <= target_date if del_time else False
+
+    def _calculate_adjusted_stocks(self, target_month: int, other_overhauls: List[Tuple[str, int]]) -> Dict[str, int]:
+        """Calculate stock levels after considering consumption from other planned overhauls"""
+        adjusted_stocks = {}
+        
+        for sparepart_id, monthly_stocks in self.projected_stocks.items():
+            if target_month < len(monthly_stocks):
+                stock_at_month = monthly_stocks[target_month]
+                
+                # Subtract consumption from other overhauls happening at or before target month
+                for other_equipment, other_month in other_overhauls:
+                    if other_month <= target_month and other_equipment in self.equipment_requirements:
+                        for req in self.equipment_requirements[other_equipment]:
+                            if req.sparepart_id == sparepart_id:
+                                stock_at_month -= req.quantity_required
+                
+                adjusted_stocks[sparepart_id] = max(0, stock_at_month)
+        
+        return adjusted_stocks
+    
+    def _get_existing_orders_for_month(self, target_month: int) -> List[ProcurementRecord]:
+        """Get existing PR/PO orders that could supply spareparts for target month"""
+        target_date = self.analysis_start_date + timedelta(days=target_month * 30)
+        
+        relevant_orders = []
+        for record in self.procurement_records:
+            date_expected_delivery = record.expected_delivery_date.date() if record.expected_delivery_date else None
+            # Include orders that deliver before or around the target month
+            # and are not cancelled
+            if (record.status != ProcurementStatus.CANCELLED and date_expected_delivery and
+                date_expected_delivery <= target_date):  # 15 days buffer
+                relevant_orders.append(record)
+        
+        return relevant_orders
+    
+    def _generate_comprehensive_availability_message(self, missing_parts: List[Dict], 
+                                               critical_missing: List[Dict], 
+                                               pr_po_summary: Dict) -> Dict:
+        """Generate comprehensive availability message with PR/PO details"""
+        
+        if not missing_parts:
+            if pr_po_summary['existing_orders']:
+                message = f"All spareparts available through {len(pr_po_summary['existing_orders'])} existing orders"
+                detailed_message = f"Total existing order value: ${pr_po_summary['total_existing_value']:,.2f}"
+            else:
+                message = "All spareparts available from current stock"
+                detailed_message = "No additional procurement required"
+        else:
+            if critical_missing:
+                message = f"CRITICAL: {len(critical_missing)} critical spareparts missing. Overhaul cannot proceed."
+                detailed_message = f"Additional procurement required: ${pr_po_summary['total_new_orders_value']:,.2f}"
+            else:
+                message = f"WARNING: {len(missing_parts)} spareparts missing, but no critical parts."
+                if pr_po_summary['total_new_orders_value'] > 0:
+                    detailed_message = f"Additional procurement required: ${pr_po_summary['total_new_orders_value']:,.2f}. "
+                else:
+                    detailed_message = ""
+                
+                if pr_po_summary['existing_orders']:
+                    detailed_message += f"Existing orders cover some requirements (${pr_po_summary['total_existing_value']:,.2f})."
+        
+        return {
+            'message': message,
+            'detailed_message': detailed_message
+        }
+
+    def _generate_availability_message(self, missing_parts: List[Dict], critical_missing: List[Dict]) -> str:
+        """Generate human-readable availability message"""
+        if not missing_parts:
+            return "All spareparts available"
+        
+        if critical_missing:
+            return f"CRITICAL: {len(critical_missing)} critical spareparts missing. Overhaul cannot proceed."
+        
+        return f"WARNING: {len(missing_parts)} spareparts missing, but no critical parts. Overhaul can proceed with procurement."
+
+    def optimize_procurement_timing(self, planned_overhauls: List[Tuple[str, int]]) -> Dict:
+        """
+        Optimize procurement timing for multiple equipment overhauls
+        
+        Args:
+            planned_overhauls: List of (equipment_tag, planned_month) tuples
+        
+        Returns:
+            Optimized procurement plan
+        """
+        procurement_plan = []
+        total_procurement_cost = 0
+        
+        # Sort overhauls by month
+        sorted_overhauls = sorted(planned_overhauls, key=lambda x: x[1])
+        
+        # Track cumulative procurement needs
+        processed_overhauls = []
+        
+        for equipment_tag, target_month in sorted_overhauls:
+            availability = self.check_sparepart_availability(
+                equipment_tag, target_month, processed_overhauls
+            )
+            
+            for procurement in availability['procurement_needed']:
+                procurement_plan.append({
+                    'equipment_tag': equipment_tag,
+                    'target_overhaul_month': target_month,
+                    **procurement
+                })
+                total_procurement_cost += procurement['total_cost']
+            
+            processed_overhauls.append((equipment_tag, target_month))
+        
+        # Group by order month for better planning
+        procurement_by_month = defaultdict(list)
+        for item in procurement_plan:
+            procurement_by_month[item['order_by_month']].append(item)
+        
+        return {
+            'total_procurement_cost': total_procurement_cost,
+            'procurement_plan': procurement_plan,
+            'procurement_by_month': dict(procurement_by_month),
+            # 'summary': self._generate_procurement_summary(procurement_plan)
+        }
+
+    def _generate_procurement_summary(self, procurement_plan: List[Dict]) -> Dict:
+        """Generate procurement summary statistics"""
+        if not procurement_plan:
+            return {'message': 'No procurement needed'}
+        
+        critical_items = [p for p in procurement_plan if p['criticality'] == 'critical']
+        total_items = len(procurement_plan)
+        total_cost = sum(p['total_cost'] for p in procurement_plan)
+        
+        # Group by supplier
+        by_supplier = defaultdict(list)
+        for item in procurement_plan:
+            by_supplier[item['supplier']].append(item)
+        
+        return {
+            'total_items': total_items,
+            'critical_items': len(critical_items),
+            'total_cost': total_cost,
+            'unique_spareparts': len(set(p['sparepart_id'] for p in procurement_plan)),
+            'suppliers_involved': len(by_supplier),
+            'by_supplier': {
+                supplier: {
+                    'item_count': len(items),
+                    'total_cost': sum(i['total_cost'] for i in items)
+                }
+                for supplier, items in by_supplier.items()
+            }
+        }
+
+    def get_monthly_procurement_schedule(self) -> Dict[int, List[Dict]]:
+        """Get procurement schedule by month"""
+        if not hasattr(self, '_monthly_schedule'):
+            self._monthly_schedule = {}
+        return self._monthly_schedule
+
+    def update_projected_stocks_with_consumption(self, equipment_overhauls: List[Tuple[str, int]]):
+        """Update projected stocks considering sparepart consumption from overhauls"""
+        # Create a copy of projected stocks
+        updated_stocks = {}
+        
+        for sparepart_id, monthly_stocks in self.projected_stocks.items():
+            updated_stocks[sparepart_id] = monthly_stocks.copy()
+        
+        # Apply consumption from overhauls
+        for equipment_tag, overhaul_month in equipment_overhauls:
+            if equipment_tag in self.equipment_requirements:
+                for requirement in self.equipment_requirements[equipment_tag]:
+                    sparepart_id = requirement.sparepart_id
+                    quantity_needed = requirement.quantity_required
+                    
+                    if sparepart_id in updated_stocks:
+                        # Reduce stock from overhaul month onwards
+                        for month in range(overhaul_month, len(updated_stocks[sparepart_id])):
+                            updated_stocks[sparepart_id][month] = max(
+                                0, updated_stocks[sparepart_id][month] - quantity_needed
+                            )
+        
+        return updated_stocks
+
+
+# Integration functions for database operations
+async def load_sparepart_data_from_db(scope, prev_oh_scope, db_session) -> SparepartManager:
+    """Load sparepart data from database"""
+    # You'll need to implement these queries based on your database schema
+    # Get scope dates for analysis window
+    # scope = await get_scope(db_session=db_session, overhaul_session_id=overhaul_session_id)
+    # prev_oh_scope = await get_prev_oh(db_session=db_session, overhaul_session=scope)
+    
+    analysis_start_date = prev_oh_scope.end_date
+    analysis_window_months = int(((scope.start_date - prev_oh_scope.end_date).days / 30) * 1.5)
+    
+    sparepart_manager = SparepartManager(analysis_start_date, analysis_window_months)
+    
+    # Load sparepart stocks
+    # Example query - adjust based on your schema
+    query = text("""
+                 SELECT 
+                    mi.id,
+                    mi.itemnum,
+                    mi.itemsetid,
+                    mi."location",
+                    mi.curbaltotal,
+                    mi.avgcost,
+                    mspl.description
+                FROM public.maximo_inventory mi
+                LEFT JOIN public.maximo_sparepart_pr_po_line mspl 
+                    ON mi.itemnum = mspl.item_num
+                 """)
+    log.info("Fetch sparepart")
+    sparepart_stocks_query = await db_session.execute(query)
+    
+    for stock_record in sparepart_stocks_query:
+        stock = SparepartStock(
+            sparepart_id=stock_record.itemnum,
+            sparepart_name=stock_record.description,
+            current_stock=stock_record.curbaltotal,
+            unit_cost=stock_record.avgcost,
+            location=stock_record.location or "Unknown",
+        )
+        sparepart_manager.add_sparepart_stock(stock)
+    
+    # Load equipment sparepart requirements
+    # You'll need to create this table/relationship
+    query = text("""WITH oh_workorders AS (
+    -- First, get all OH work orders
+    SELECT DISTINCT
+        wonum,
+        asset_location
+    FROM public.wo_staging_maximo_2
+    WHERE worktype = 'OH' AND asset_location IS NOT NULL
+),
+sparepart_usage AS (
+    -- Get sparepart usage for OH work orders
+    SELECT 
+        oh.asset_location,
+        mwm.itemnum,
+        mwm.itemqty,
+        mwm.wonum
+    FROM oh_workorders oh
+    INNER JOIN public.maximo_workorder_materials mwm 
+        ON oh.wonum = mwm.wonum
+),
+location_sparepart_stats AS (
+    -- Calculate average usage per sparepart per location
+    SELECT 
+        asset_location,
+        itemnum,
+        COUNT(DISTINCT wonum) as total_wo_count,
+        SUM(itemqty) as total_qty_used,
+        AVG(itemqty) as avg_qty_per_wo,
+        MIN(itemqty) as min_qty_used,
+        MAX(itemqty) as max_qty_used
+    FROM sparepart_usage
+    GROUP BY asset_location, itemnum
+),
+pr_po_combined AS (
+    -- Combine PR and PO data by num to get issue_date and estimated_arrival_date
+    SELECT 
+        mspl.item_num,
+        mspl.num,
+        MAX(CASE WHEN mspo.type = 'PR' THEN mspo.issue_date END) as issue_date,
+        MAX(CASE WHEN mspo.type = 'PO' THEN mspo.estimated_arrival_date END) as estimated_arrival_date
+    FROM public.maximo_sparepart_pr_po_line mspl
+    INNER JOIN public.maximo_sparepart_pr_po mspo 
+        ON mspl.num = mspo.num
+    WHERE mspo.type IN ('PR', 'PO')
+    GROUP BY mspl.item_num, mspl.num
+),
+leadtime_stats AS (
+    -- Calculate lead time statistics for each item
+    SELECT 
+        item_num,
+        ROUND(AVG(
+            EXTRACT(EPOCH FROM (estimated_arrival_date - issue_date)) / 86400 / 30.44
+        ), 1) as avg_leadtime_months,
+        ROUND(MIN(
+            EXTRACT(EPOCH FROM (estimated_arrival_date - issue_date)) / 86400 / 30.44
+        ), 1) as min_leadtime_months,
+        COUNT(*) as leadtime_sample_size
+    FROM pr_po_combined
+    WHERE issue_date IS NOT NULL 
+        AND estimated_arrival_date IS NOT NULL
+        AND estimated_arrival_date > issue_date
+    GROUP BY item_num
+),
+item_descriptions AS (
+    -- Get unique descriptions for each item (optimized)
+    SELECT DISTINCT
+        item_num,
+        FIRST_VALUE(description) OVER (
+            PARTITION BY item_num 
+            ORDER BY created_at DESC NULLS LAST
+        ) as description
+    FROM public.maximo_sparepart_pr_po_line
+    WHERE description IS NOT NULL
+)
+SELECT 
+    lss.asset_location,
+    lss.itemnum,
+    COALESCE(id.description, 'No description available') as item_description,
+    lss.total_wo_count,
+    lss.total_qty_used,
+    ROUND(lss.avg_qty_per_wo, 2) as avg_qty_per_wo,
+    lss.min_qty_used,
+    lss.max_qty_used,
+    COALESCE(lt.avg_leadtime_months, 0) as avg_leadtime_months,
+    COALESCE(lt.min_leadtime_months, 0) as min_leadtime_months,
+    COALESCE(lt.leadtime_sample_size, 0) as leadtime_sample_size
+FROM location_sparepart_stats lss
+LEFT JOIN item_descriptions id ON lss.itemnum = id.item_num
+LEFT JOIN leadtime_stats lt ON lss.itemnum = lt.item_num
+ORDER BY lss.asset_location, lss.itemnum;""")
+    
+    equipment_requirements_query = await db_session.execute(query)
+    
+    equipment_requirements = defaultdict(list)
+    for req_record in equipment_requirements_query:
+        requirement = SparepartRequirement(
+            sparepart_id=req_record.itemnum,
+            quantity_required=float(req_record.avg_qty_per_wo),
+            lead_time=float(req_record.avg_leadtime_months),
+            sparepart_name=req_record.item_description
+            
+        )
+        equipment_requirements[req_record.asset_location].append(requirement)
+    
+    for equipment_tag, requirements in equipment_requirements.items():
+        sparepart_manager.add_equipment_requirements(equipment_tag, requirements)
+    
+    
+    # Load procurement records (PO/PR)
+    procurement_query = await get_all(db_session=db_session)
     
     
-# async def update(
-#     *,
-#     db_session: DbSession,
-#     activity: MasterActivity,
-#     activity_in: ActivityMasterCreate
-# ):
-#     """Updates a document."""
-#     data = activity_in.model_dump()
+    for proc_record in procurement_query:
+        procurement = ProcurementRecord(
+            po_pr_id=proc_record["pr_number"],
+            sparepart_id=proc_record["item_num"],
+            sparepart_name=proc_record["description"],
+            quantity=proc_record["pr_qty_ordered"],
+            unit_cost=proc_record["unit_cost"],
+            total_cost=proc_record["line_cost"],
+            order_date=proc_record['pr_issue_date'],
+            expected_delivery_date=proc_record['po_estimated_arrival_date'],
+            status=ProcurementStatus("ordered"),
+        )
+        sparepart_manager.add_procurement_record(procurement)
     
-#     update_data = activity_in.model_dump(exclude_defaults=True)
+    # Calculate projected stocks
+    sparepart_manager._project_monthly_stocks()
     
-#     for field in data:
-#         if field in update_data:
-#             setattr(activity, field, update_data[field])
+    return sparepart_manager
 
-#     await db_session.commit()
 
-#     return activity
 
    
-# async def delete(*, db_session: DbSession, activity_id: str):
-#     """Deletes a document."""
-#     activity = await db_session.get(MasterActivity, activity_id)
-#     await db_session.delete(activity)
-#     await db_session.commit()