diff --git a/src/calculation_time_constrains/service.py b/src/calculation_time_constrains/service.py
index f407211..cf4d3f9 100644
--- a/src/calculation_time_constrains/service.py
+++ b/src/calculation_time_constrains/service.py
@@ -84,7 +84,7 @@ def get_corrective_cost_time_chart(material_cost: float, service_cost: float, da
     daily_failure_rate = np.clip(daily_failure_rate, 0, None)  # Ensure failure rate is non-negative
 
     # Calculate cumulative failures
-    failure_counts = np.cumsum(daily_failure_rate, axis=1)
+    failure_counts = np.cumsum(daily_failure_rate)
 
     # Calculate corrective costs based on cumulative failures and combined costs
     cost_per_failure = material_cost + service_cost
@@ -244,11 +244,7 @@ async def create_calculation_result_service(
     
     calculation_data = await get_calculation_data_by_id(db_session=db_session, calculation_id=calculation.id)
 
-    overhaul_cost_points = get_overhaul_cost_by_time_chart(
-        calculation_data.parameter.overhaul_cost, 
-        days=days,
-        numEquipments=len(equipments)
-    )
+    
     
 
     # Store results for each equipment
@@ -265,6 +261,12 @@ async def create_calculation_result_service(
             numEquipments=len(equipments)
         )
         
+        overhaul_cost_points = get_overhaul_cost_by_time_chart(
+            calculation_data.parameter.overhaul_cost, 
+            days=days,
+            numEquipments=len(equipments)
+    )
+        
         # Calculate individual equipment optimum points
         equipment_total_cost = corrective_costs + overhaul_cost_points
         equipment_optimum_index = np.argmin(equipment_total_cost)