ifc-to-excel

IFC から Excel への変換

ビジネスケース

問題提起

IFC（Industry Foundation Classes）はオープンな BIM 標準ですが、次の課題があります。

• IFC の読み取りには専用ソフトウェアが必要です
• プロパティの抽出にはプログラミングの知識が必要です
• バッチ処理は手作業で、時間がかかります
• 分析ツールとの統合は複雑です

解決策

IfcExporter.exe は IFC ファイルを構造化された Excel データベースに変換し、分析、検証、レポート作成に BIM データを活用できるようにします。

ビジネス価値

• オープン標準 - あらゆる IFC ファイルを処理できます（2x3、4x、4.3）
• ライセンス不要 - BIM ソフトウェアなしでオフライン動作します
• データ抽出 - すべてのプロパティ、数量、材料を抽出します
• 3D ジオメトリ - Collada DAE 形式にエクスポートします
• パイプライン対応 - ETL ワークフローに統合できます

技術的な実装

CLI 構文

IfcExporter.exe <input_ifc> [options]

対応する IFC バージョン

バージョン	スキーマ	説明
IFC2x3	MVD	最も一般的な交換形式
IFC4	ADD1	拡張されたプロパティ
IFC4x1	Alignment	インフラストラクチャに対応
IFC4x3	Latest	インフラストラクチャに全面対応

出力形式

出力	説明
.xlsx	要素とプロパティを含む Excel データベース
.dae	ID が一致する Collada 3D ジオメトリ

オプション

オプション	説明
bbox	要素の境界ボックスを含めます
-no-xlsx	Excel エクスポートをスキップします
-no-collada	3D ジオメトリのエクスポートをスキップします

例

# Basic conversion (XLSX + DAE)
IfcExporter.exe "C:\Models\Building.ifc"

# With bounding boxes
IfcExporter.exe "C:\Models\Building.ifc" bbox

# Excel only (no 3D geometry)
IfcExporter.exe "C:\Models\Building.ifc" -no-collada

# Batch processing
for /R "C:\IFC_Models" %f in (*.ifc) do IfcExporter.exe "%f" bbox

Python との統合

import subprocess
import pandas as pd
from pathlib import Path
from typing import List, Optional, Dict, Any, Set
from dataclasses import dataclass, field
from enum import Enum
import json


class IFCVersion(Enum):
    """IFC schema versions."""
    IFC2X3 = "IFC2X3"
    IFC4 = "IFC4"
    IFC4X1 = "IFC4X1"
    IFC4X3 = "IFC4X3"


class IFCEntityType(Enum):
    """Common IFC entity types."""
    IFCWALL = "IfcWall"
    IFCWALLSTANDARDCASE = "IfcWallStandardCase"
    IFCSLAB = "IfcSlab"
    IFCCOLUMN = "IfcColumn"
    IFCBEAM = "IfcBeam"
    IFCDOOR = "IfcDoor"
    IFCWINDOW = "IfcWindow"
    IFCROOF = "IfcRoof"
    IFCSTAIR = "IfcStair"
    IFCRAILING = "IfcRailing"
    IFCFURNISHINGELEMENT = "IfcFurnishingElement"
    IFCSPACE = "IfcSpace"
    IFCBUILDINGSTOREY = "IfcBuildingStorey"
    IFCBUILDING = "IfcBuilding"
    IFCSITE = "IfcSite"


@dataclass
class IFCElement:
    """Represents an IFC element."""
    global_id: str
    ifc_type: str
    name: str
    description: Optional[str]
    object_type: Optional[str]
    level: Optional[str]

    # Quantities
    area: Optional[float] = None
    volume: Optional[float] = None
    length: Optional[float] = None
    height: Optional[float] = None
    width: Optional[float] = None

    # Bounding box (if exported)
    bbox_min_x: Optional[float] = None
    bbox_min_y: Optional[float] = None
    bbox_min_z: Optional[float] = None
    bbox_max_x: Optional[float] = None
    bbox_max_y: Optional[float] = None
    bbox_max_z: Optional[float] = None

    # Properties
    properties: Dict[str, Any] = field(default_factory=dict)
    materials: List[str] = field(default_factory=list)


@dataclass
class IFCProperty:
    """Represents an IFC property."""
    pset_name: str
    property_name: str
    value: Any
    value_type: str


@dataclass
class IFCMaterial:
    """Represents an IFC material."""
    name: str
    category: Optional[str]
    thickness: Optional[float]
    layer_position: Optional[int]


class IFCExporter:
    """IFC to Excel converter using DDC IfcExporter CLI."""

    def __init__(self, exporter_path: str = "IfcExporter.exe"):
        self.exporter = Path(exporter_path)
        if not self.exporter.exists():
            raise FileNotFoundError(f"IfcExporter not found: {exporter_path}")

    def convert(self, ifc_file: str,
                include_bbox: bool = True,
                export_xlsx: bool = True,
                export_collada: bool = True) -> Path:
        """Convert IFC file to Excel."""
        ifc_path = Path(ifc_file)
        if not ifc_path.exists():
            raise FileNotFoundError(f"IFC file not found: {ifc_file}")

        cmd = [str(self.exporter), str(ifc_path)]

        if include_bbox:
            cmd.append("bbox")
        if not export_xlsx:
            cmd.append("-no-xlsx")
        if not export_collada:
            cmd.append("-no-collada")

        result = subprocess.run(cmd, capture_output=True, text=True)

        if result.returncode != 0:
            raise RuntimeError(f"Export failed: {result.stderr}")

        return ifc_path.with_suffix('.xlsx')

    def batch_convert(self, folder: str,
                      include_subfolders: bool = True,
                      include_bbox: bool = True) -> List[Dict[str, Any]]:
        """Convert all IFC files in folder."""
        folder_path = Path(folder)
        pattern = "**/*.ifc" if include_subfolders else "*.ifc"

        results = []
        for ifc_file in folder_path.glob(pattern):
            try:
                output = self.convert(str(ifc_file), include_bbox)
                results.append({
                    'input': str(ifc_file),
                    'output': str(output),
                    'status': 'success'
                })
                print(f"✓ Converted: {ifc_file.name}")
            except Exception as e:
                results.append({
                    'input': str(ifc_file),
                    'output': None,
                    'status': 'failed',
                    'error': str(e)
                })
                print(f"✗ Failed: {ifc_file.name} - {e}")

        return results

    def read_elements(self, xlsx_file: str) -> pd.DataFrame:
        """Read converted Excel as DataFrame."""
        return pd.read_excel(xlsx_file, sheet_name="Elements")

    def get_element_types(self, xlsx_file: str) -> pd.DataFrame:
        """Get element type summary."""
        df = self.read_elements(xlsx_file)

        if 'IfcType' not in df.columns:
            raise ValueError("IfcType column not found")

        summary = df.groupby('IfcType').agg({
            'GlobalId': 'count',
            'Volume': 'sum' if 'Volume' in df.columns else 'count',
            'Area': 'sum' if 'Area' in df.columns else 'count'
        }).reset_index()

        summary.columns = ['IFC_Type', 'Count', 'Total_Volume', 'Total_Area']
        return summary.sort_values('Count', ascending=False)

    def get_levels(self, xlsx_file: str) -> pd.DataFrame:
        """Get building level summary."""
        df = self.read_elements(xlsx_file)

        level_col = None
        for col in ['Level', 'BuildingStorey', 'IfcBuildingStorey']:
            if col in df.columns:
                level_col = col
                break

        if level_col is None:
            return pd.DataFrame(columns=['Level', 'Element_Count'])

        summary = df.groupby(level_col).agg({
            'GlobalId': 'count'
        }).reset_index()
        summary.columns = ['Level', 'Element_Count']
        return summary

    def get_materials(self, xlsx_file: str) -> pd.DataFrame:
        """Get material summary."""
        df = self.read_elements(xlsx_file)

        if 'Material' not in df.columns:
            return pd.DataFrame(columns=['Material', 'Count'])

        summary = df.groupby('Material').agg({
            'GlobalId': 'count'
        }).reset_index()
        summary.columns = ['Material', 'Element_Count']
        return summary.sort_values('Element_Count', ascending=False)

    def get_quantities(self, xlsx_file: str,
                       group_by: str = 'IfcType') -> pd.DataFrame:
        """Get quantity takeoff summary."""
        df = self.read_elements(xlsx_file)

        if group_by not in df.columns:
            raise ValueError(f"Column {group_by} not found")

        agg_dict = {'GlobalId': 'count'}

        # Add numeric columns for aggregation
        numeric_cols = ['Volume', 'Area', 'Length', 'Width', 'Height']
        for col in numeric_cols:
            if col in df.columns:
                agg_dict[col] = 'sum'

        summary = df.groupby(group_by).agg(agg_dict).reset_index()
        return summary

    def filter_by_type(self, xlsx_file: str,
                       ifc_types: List[str]) -> pd.DataFrame:
        """Filter elements by IFC type."""
        df = self.read_elements(xlsx_file)
        return df[df['IfcType'].isin(ifc_types)]

    def get_properties(self, xlsx_file: str,
                       element_id: str) -> Dict[str, Any]:
        """Get all properties for specific element."""
        df = self.read_elements(xlsx_file)
        element = df[df['GlobalId'] == element_id]

        if element.empty:
            return {}

        # Convert row to dictionary, excluding NaN values
        props = element.iloc[0].dropna().to_dict()
        return props

    def validate_ifc_data(self, xlsx_file: str) -> Dict[str, Any]:
        """Validate IFC data quality."""
        df = self.read_elements(xlsx_file)

        validation = {
            'total_elements': len(df),
            'issues': []
        }

        # Check for missing GlobalIds
        if 'GlobalId' in df.columns:
            missing_ids = df['GlobalId'].isna().sum()
            if missing_ids > 0:
                validation['issues'].append(f"{missing_ids} elements missing GlobalId")

        # Check for missing names
        if 'Name' in df.columns:
            missing_names = df['Name'].isna().sum()
            if missing_names > 0:
                validation['issues'].append(f"{missing_names} elements missing Name")

        # Check for zero quantities
        for col in ['Volume', 'Area']:
            if col in df.columns:
                zero_qty = (df[col] == 0).sum()
                if zero_qty > 0:
                    validation['issues'].append(f"{zero_qty} elements with zero {col}")

        # Check for duplicate GlobalIds
        if 'GlobalId' in df.columns:
            duplicates = df['GlobalId'].duplicated().sum()
            if duplicates > 0:
                validation['issues'].append(f"{duplicates} duplicate GlobalIds")

        validation['is_valid'] = len(validation['issues']) == 0
        return validation


class IFCQuantityTakeoff:
    """Quantity takeoff from IFC data."""

    def __init__(self, exporter: IFCExporter):
        self.exporter = exporter

    def generate_qto(self, ifc_file: str) -> Dict[str, pd.DataFrame]:
        """Generate complete quantity takeoff."""
        xlsx = self.exporter.convert(ifc_file, include_bbox=True)
        df = self.exporter.read_elements(str(xlsx))

        qto = {}

        # Walls
        walls = df[df['IfcType'].str.contains('Wall', case=False, na=False)]
        if not walls.empty:
            qto['Walls'] = self._summarize_elements(walls, 'Type Name')

        # Slabs
        slabs = df[df['IfcType'].str.contains('Slab', case=False, na=False)]
        if not slabs.empty:
            qto['Slabs'] = self._summarize_elements(slabs, 'Type Name')

        # Columns
        columns = df[df['IfcType'].str.contains('Column', case=False, na=False)]
        if not columns.empty:
            qto['Columns'] = self._summarize_elements(columns, 'Type Name')

        # Beams
        beams = df[df['IfcType'].str.contains('Beam', case=False, na=False)]
        if not beams.empty:
            qto['Beams'] = self._summarize_elements(beams, 'Type Name')

        # Doors
        doors = df[df['IfcType'].str.contains('Door', case=False, na=False)]
        if not doors.empty:
            qto['Doors'] = self._summarize_elements(doors, 'Type Name')

        # Windows
        windows = df[df['IfcType'].str.contains('Window', case=False, na=False)]
        if not windows.empty:
            qto['Windows'] = self._summarize_elements(windows, 'Type Name')

        return qto

    def _summarize_elements(self, df: pd.DataFrame,
                            group_col: str) -> pd.DataFrame:
        """Summarize elements by grouping column."""
        if group_col not in df.columns:
            group_col = 'IfcType'

        agg_dict = {'GlobalId': 'count'}
        for col in ['Volume', 'Area', 'Length']:
            if col in df.columns:
                agg_dict[col] = 'sum'

        summary = df.groupby(group_col).agg(agg_dict).reset_index()
        summary.rename(columns={'GlobalId': 'Count'}, inplace=True)
        return summary

    def export_to_excel(self, qto: Dict[str, pd.DataFrame],
                        output_file: str):
        """Export QTO to multi-sheet Excel."""
        with pd.ExcelWriter(output_file, engine='openpyxl') as writer:
            for sheet_name, df in qto.items():
                df.to_excel(writer, sheet_name=sheet_name, index=False)


# Convenience functions
def convert_ifc_to_excel(ifc_file: str,
                         exporter_path: str = "IfcExporter.exe") -> str:
    """Quick conversion of IFC to Excel."""
    exporter = IFCExporter(exporter_path)
    output = exporter.convert(ifc_file)
    return str(output)


def get_ifc_summary(xlsx_file: str) -> Dict[str, Any]:
    """Get summary of converted IFC data."""
    df = pd.read_excel(xlsx_file, sheet_name="Elements")

    return {
        'total_elements': len(df),
        'ifc_types': df['IfcType'].nunique() if 'IfcType' in df.columns else 0,
        'levels': df['Level'].nunique() if 'Level' in df.columns else 0,
        'total_volume': df['Volume'].sum() if 'Volume' in df.columns else 0,
        'total_area': df['Area'].sum() if 'Area' in df.columns else 0
    }

出力構造

Excel シート

シート	内容
Elements	すべての IFC 要素とプロパティ
Types	要素タイプの概要
Levels	建物の階データ
Materials	材料の割り当て
PropertySets	IFC プロパティセット

要素の列

列	型	説明
GlobalId	string	IFC GUID
IfcType	string	IFC エンティティタイプ
Name	string	要素名
Description	string	要素の説明
Level	string	建物の階
Material	string	主な材料
Volume	float	体積（m³）
Area	float	表面積（m²）
Length	float	長さ（m）
Height	float	高さ（m）
Width	float	幅（m）

クイックスタート

# Initialize exporter
exporter = IFCExporter("C:/DDC/IfcExporter.exe")

# Convert IFC to Excel
xlsx = exporter.convert("C:/Models/Building.ifc", include_bbox=True)

# Read elements
df = exporter.read_elements(str(xlsx))
print(f"Total elements: {len(df)}")

# Get element types
types = exporter.get_element_types(str(xlsx))
print(types)

# Get quantities by type
qto = exporter.get_quantities(str(xlsx), group_by='IfcType')
print(qto)

一般的なユースケース

1. モデルの検証

exporter = IFCExporter()
xlsx = exporter.convert("model.ifc")
validation = exporter.validate_ifc_data(str(xlsx))

if not validation['is_valid']:
    print("Issues found:")
    for issue in validation['issues']:
        print(f"  - {issue}")

2. 数量拾い

qto_generator = IFCQuantityTakeoff(exporter)
qto = qto_generator.generate_qto("building.ifc")

for category, data in qto.items():
    print(f"\n{category}:")
    print(data.to_string(index=False))

3. 材料表

xlsx = exporter.convert("building.ifc")
materials = exporter.get_materials(str(xlsx))
print(materials)

DDC パイプラインとの統合

# Full pipeline: IFC → Excel → Validation → Cost Estimate
exporter = IFCExporter("C:/DDC/IfcExporter.exe")

# 1. Convert IFC
xlsx = exporter.convert("project.ifc", include_bbox=True)

# 2. Validate data
validation = exporter.validate_ifc_data(str(xlsx))
print(f"Valid: {validation['is_valid']}")

# 3. Generate QTO
qto = IFCQuantityTakeoff(exporter)
quantities = qto.generate_qto("project.ifc")

# 4. Export for cost estimation
qto.export_to_excel(quantities, "project_qto.xlsx")

リソース

• GitHub: cad2data パイプライン
• IFC 標準: buildingSMART
• DDC 書籍: 第 2.4 章 - CAD/BIM データ抽出