Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
日本語の概要は準備中です。原文の説明を表示しています。
Manage construction equipment fleet. Track utilization, maintenance, and assignments.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
import pandas as pd
from datetime import date, timedelta
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum
class EquipmentStatus(Enum):
AVAILABLE = "available"
IN_USE = "in_use"
MAINTENANCE = "maintenance"
REPAIR = "repair"
RETIRED = "retired"
class EquipmentType(Enum):
CRANE = "crane"
EXCAVATOR = "excavator"
LOADER = "loader"
FORKLIFT = "forklift"
GENERATOR = "generator"
COMPRESSOR = "compressor"
SCAFFOLDING = "scaffolding"
OTHER = "other"
@dataclass
class MaintenanceRecord:
record_id: str
equipment_id: str
maintenance_type: str
scheduled_date: date
completed_date: Optional[date]
cost: float
notes: str = ""
@dataclass
class Assignment:
assignment_id: str
equipment_id: str
project: str
location: str
start_date: date
end_date: Optional[date]
operator: str = ""
@dataclass
class Equipment:
equipment_id: str
name: str
equipment_type: EquipmentType
make: str
model: str
year: int
status: EquipmentStatus
hourly_rate: float
daily_rate: float
current_hours: float = 0
last_maintenance: Optional[date] = None
next_maintenance_hours: float = 500
assignments: List[Assignment] = field(default_factory=list)
class EquipmentFleetManager:
def __init__(self, company_name: str):
self.company_name = company_name
self.equipment: Dict[str, Equipment] = {}
self.maintenance_records: List[MaintenanceRecord] = {}
self._equip_counter = 0
self._assign_counter = 0
def add_equipment(self, name: str, equipment_type: EquipmentType,
make: str, model: str, year: int,
hourly_rate: float, daily_rate: float) -> Equipment:
self._equip_counter += 1
equip_id = f"EQ-{self._equip_counter:04d}"
equip = Equipment(
equipment_id=equip_id,
name=name,
equipment_type=equipment_type,
make=make,
model=model,
year=year,
status=EquipmentStatus.AVAILABLE,
hourly_rate=hourly_rate,
daily_rate=daily_rate
)
self.equipment[equip_id] = equip
return equip
def assign_equipment(self, equip_id: str, project: str, location: str,
start_date: date, operator: str = "") -> Assignment:
if equip_id not in self.equipment:
return None
self._assign_counter += 1
assign_id = f"ASN-{self._assign_counter:04d}"
assignment = Assignment(
assignment_id=assign_id,
equipment_id=equip_id,
project=project,
location=location,
start_date=start_date,
end_date=None,
operator=operator
)
self.equipment[equip_id].assignments.append(assignment)
self.equipment[equip_id].status = EquipmentStatus.IN_USE
return assignment
def return_equipment(self, equip_id: str, hours_used: float):
if equip_id in self.equipment:
equip = self.equipment[equip_id]
equip.status = EquipmentStatus.AVAILABLE
equip.current_hours += hours_used
if equip.assignments:
equip.assignments[-1].end_date = date.today()
def schedule_maintenance(self, equip_id: str, maintenance_type: str,
scheduled_date: date, cost: float):
if equip_id not in self.equipment:
return
record_id = f"MNT-{len(self.maintenance_records) + 1:04d}"
record = MaintenanceRecord(record_id, equip_id, maintenance_type,
scheduled_date, None, cost)
self.maintenance_records[record_id] = record
def get_available_equipment(self, equipment_type: EquipmentType = None) -> List[Equipment]:
available = [e for e in self.equipment.values()
if e.status == EquipmentStatus.AVAILABLE]
if equipment_type:
available = [e for e in available if e.equipment_type == equipment_type]
return available
def get_utilization_report(self) -> Dict[str, Any]:
in_use = sum(1 for e in self.equipment.values()
if e.status == EquipmentStatus.IN_USE)
total = len(self.equipment)
return {
'total_equipment': total,
'in_use': in_use,
'available': sum(1 for e in self.equipment.values()
if e.status == EquipmentStatus.AVAILABLE),
'maintenance': sum(1 for e in self.equipment.values()
if e.status == EquipmentStatus.MAINTENANCE),
'utilization_rate': round(in_use / total * 100, 1) if total > 0 else 0
}
def export_fleet(self, output_path: str):
data = [{
'ID': e.equipment_id,
'Name': e.name,
'Type': e.equipment_type.value,
'Make/Model': f"{e.make} {e.model}",
'Year': e.year,
'Status': e.status.value,
'Hours': e.current_hours,
'Daily Rate': e.daily_rate
} for e in self.equipment.values()]
pd.DataFrame(data).to_excel(output_path, index=False)
fleet = EquipmentFleetManager("ABC Construction")
crane = fleet.add_equipment("Tower Crane #1", EquipmentType.CRANE,
"Liebherr", "280 EC-H", 2020, 150, 1200)
assignment = fleet.assign_equipment(crane.equipment_id, "Office Tower",
"Site A", date.today(), "John Smith")
report = fleet.get_utilization_report()
print(f"Utilization: {report['utilization_rate']}%")
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze 5000+ IFC and Revit projects at scale for patterns, benchmarks, and insights. Big data analysis for construction.
日本語の概要は準備中です。原文の説明を表示しています。
Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrate multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI.
日本語の概要は準備中です。原文の説明を表示しています。
Create Apache Airflow DAGs for construction data pipelines. Orchestrate ETL, validation, and reporting workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Automate as-built documentation and digital handover for construction. Compile project records, generate O&M manuals, create asset databases, and ensure complete project closeout.
日本語の概要は準備中です。原文の説明を表示しています。