Skill 详情

ifc-qto-extraction

Automates quantity takeoff from IFC and Revit construction models.

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来源datadrivenconstruction/ddc_skills_for_ai_agents_in_construction外部来源
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SKILL.md

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---
name: "ifc-qto-extraction"
description: "Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting."
homepage: "https://datadrivenconstruction.io"
metadata: {"openclaw":{"emoji":"📐","os":["darwin","linux","win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"],"anyBins":["IfcConvert","ifcopenshell"]}}}
---

# IFC Quantity Takeoff Extraction

Extract structured quantity data from BIM models (IFC, Revit) for cost estimation, material ordering, and progress tracking.

## Business Case

**Problem**: Manual quantity takeoff is:
- Time-consuming (40-80 hours for medium project)
- Error-prone (human counting mistakes)
- Not repeatable (changes require full rework)
- Disconnected from design (no live updates)

**Solution**: Automated QTO from BIM that:
- Extracts all quantities in minutes
- Groups by type, level, zone
- Updates instantly with model changes
- Exports to Excel for pricing

**ROI**: 90% reduction in QTO time, near-zero counting errors

## DDC Tools Used

```
┌──────────────────────────────────────────────────────────────────────┐
│                      QTO EXTRACTION PIPELINE                          │
├──────────────────────────────────────────────────────────────────────┤
│                                                                       │
│   INPUT                 CONVERT                 ANALYZE               │
│   ┌─────────┐          ┌─────────┐            ┌─────────┐            │
│   │ .rvt    │          │ DDC     │            │ Python  │            │
│   │ .ifc    │─────────►│Converter│───────────►│ pandas  │            │
│   │ .dwg    │          │         │            │         │            │
│   └─────────┘          └─────────┘            └─────────┘            │
│                              │                      │                 │
│                              ▼                      ▼                 │
│                        ┌─────────┐            ┌─────────┐            │
│                        │ .xlsx   │            │ Grouped │            │
│                        │ raw data│            │ QTO     │            │
│                        └─────────┘            └─────────┘            │
│                                                    │                  │
│   OUTPUT                                           ▼                  │
│   ┌─────────────────────────────────────────────────────────────┐   │
│   │  QTO Report                                                  │   │
│   │  • Element counts by type                                    │   │
│   │  • Areas (m², ft²)                                           │   │
│   │  • Volumes (m³, ft³)                                         │   │
│   │  • Lengths (m, ft)                                           │   │
│   │  • Weights (kg, tons)                                        │   │
│   │  • Grouped by level/zone/system                              │   │
│   └─────────────────────────────────────────────────────────────┘   │
│                                                                       │
└──────────────────────────────────────────────────────────────────────┘
```

## CLI Commands

### Revit to Excel (with BBox for volumes)

```bash
# Basic extraction
RvtExporter.exe "C:\Models\Building.rvt"

# Full extraction with bounding boxes (for volume calculations)
RvtExporter.exe "C:\Models\Building.rvt" complete bbox

# Include schedules (Revit's built-in QTO)
RvtExporter.exe "C:\Models\Building.rvt" complete bbox schedule
```

### IFC to Excel

```bash
# Extract IFC data
IfcExporter.exe "C:\Models\Building.ifc"

# Output: Building.xlsx with all IFC entities
```

### DWG to Excel (2D areas)

```bash
# Extract DWG blocks and areas
DwgExporter.exe "C:\Drawings\FloorPlan.dwg"
```

## Python Implementation

```python
import pandas as pd
import numpy as np
from pathlib import Path
import subprocess
from typing import Lis
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