BIM Validation Report Generator
Business Case
Problem Statement
BIM models often have quality issues:
- Missing required properties
- Invalid or inconsistent data
- Non-compliant with project standards
- Incomplete model information
Solution
Automated BIM validation system that checks models against configurable rules and generates detailed compliance reports.
Business Value
- Quality assurance - Catch issues early
- Standards compliance - Meet project requirements
- Automation - Reduce manual QC effort
- Transparency - Clear validation results
Technical Implementation
import pandas as pd
from datetime import datetime
from typing import Dict, Any, List, Optional, Callable
from dataclasses import dataclass, field
from enum import Enum
class ValidationSeverity(Enum):
"""Validation issue severity."""
ERROR = "error"
WARNING = "warning"
INFO = "info"
class ValidationStatus(Enum):
"""Overall validation status."""
PASSED = "passed"
PASSED_WITH_WARNINGS = "passed_with_warnings"
FAILED = "failed"
class RuleCategory(Enum):
"""Validation rule categories."""
REQUIRED_PROPERTIES = "required_properties"
DATA_FORMAT = "data_format"
NAMING_CONVENTION = "naming_convention"
GEOMETRIC = "geometric"
CLASSIFICATION = "classification"
RELATIONSHIPS = "relationships"
@dataclass
class ValidationRule:
"""Single validation rule."""
rule_id: str
name: str
category: RuleCategory
description: str
severity: ValidationSeverity
check_function: Callable
applicable_categories: List[str] = field(default_factory=list)
enabled: bool = True
@dataclass
class ValidationIssue:
"""Single validation issue."""
issue_id: str
rule_id: str
rule_name: str
element_id: str
element_name: str
element_category: str
severity: ValidationSeverity
message: str
details: Dict[str, Any] = field(default_factory=dict)
def to_dict(self) -> Dict[str, Any]:
return {
'issue_id': self.issue_id,
'rule_id': self.rule_id,
'rule_name': self.rule_name,
'element_id': self.element_id,
'element_name': self.element_name,
'element_category': self.element_category,
'severity': self.severity.value,
'message': self.message
}
@dataclass
class ValidationReport:
"""Complete validation report."""
project_name: str
model_name: str
validated_at: datetime
status: ValidationStatus
total_elements: int
elements_with_issues: int
issues: List[ValidationIssue]
rules_checked: int
summary_by_severity: Dict[str, int]
summary_by_category: Dict[str, int]
class BIMValidationEngine:
"""BIM model validation engine."""
def __init__(self, project_name: str, model_name: str):
self.project_name = project_name
self.model_name = model_name
self.rules: List[ValidationRule] = []
self.issues: List[ValidationIssue] = []
self._issue_counter = 0
# Load default rules
self._load_default_rules()
def _load_default_rules(self):
"""Load standard validation rules."""
# Required properties rules
self.add_rule(ValidationRule(
rule_id="REQ-001",
name="Element Name Required",
category=RuleCategory.REQUIRED_PROPERTIES,
description="All elements must have a name",
severity=ValidationSeverity.ERROR,
check_function=lambda e: bool(e.get('name'))
))
self.add_rule(ValidationRule(
rule_id="REQ-002",
name="Level Assignment Required",
category=RuleCategory.REQUIRED_PROPERTIES,
description="Elements must be assigned to a level",
severity=ValidationSeverity.WARNING,
check_function=lambda e: bool(e.get('level')),
applicable_categories=["Walls", "Floors", "Doors", "Windows"]
))
self.add_rule(ValidationRule(
rule_id="REQ-003",
name="Material Required",
category=RuleCategory.REQUIRED_PROPERTIES,
description="Structural elements must have material defined",
severity=ValidationSeverity.ERROR,
check_function=lambda e: bool(e.get('material')),
applicable_categories=["Structural Columns", "Structural Framing", "Floors"]
))
# Naming convention rules
self.add_rule(ValidationRule(
rule_id="NAM-001",
name="No Special Characters",
category=RuleCategory.NAMING_CONVENTION,
description="Names should not contain special characters",
severity=ValidationSeverity.WARNING,
check_function=self._check_no_special_chars
))
self.add_rule(ValidationRule(
rule_id="NAM-002",
name="Name Length Check",
category=RuleCategory.NAMING_CONVENTION,
description="Names should be between 3 and 100 characters",
severity=ValidationSeverity.INFO,
check_function=lambda e: 3 <= len(e.get('name', '')) <= 100
))
# Classification rules
self.add_rule(ValidationRule(
rule_id="CLS-001",
name="Classification Code Present",
category=RuleCategory.CLASSIFICATION,
description="Elements should have classification code",
severity=ValidationSeverity.WARNING,
check_function=lambda e: bool(e.get('classification_code') or e.get('uniformat'))
))
# Geometric rules
self.add_rule(ValidationRule(
rule_id="GEO-001",
name="Non-Zero Volume",
category=RuleCategory.GEOMETRIC,
description="3D elements must have non-zero volume",
severity=ValidationSeverity.ERROR,
check_function=lambda e: float(e.get('volume', 0)) > 0,
applicable_categories=["Walls", "Floors", "Structural Columns", "Structural Framing"]
))
self.add_rule(ValidationRule(
rule_id="GEO-002",
name="Valid Bounding Box",
category=RuleCategory.GEOMETRIC,
description="Elements must have valid bounding box",
severity=ValidationSeverity.ERROR,
check_function=self._check_valid_bbox
))
def _check_no_special_chars(self, element: Dict[str, Any]) -> bool:
"""Check name for special characters."""
import re
name = element.get('name', '')
return bool(re.match(r'^[\w\s\-\.]+$', name))
def _check_valid_bbox(self, element: Dict[str, Any]) -> bool:
"""Check for valid bounding box."""
try:
min_x = float(element.get('min_x', 0))
max_x = float(element.get('max_x', 0))
min_y = float(element.get('min_y', 0))
max_y = float(element.get('max_y', 0))
min_z = float(element.get('min_z', 0))
max_z = float(element.get('max_z', 0))
return max_x > min_x and max_y > min_y and max_z > min_z
except (ValueError, TypeError):
return False
def add_rule(self, rule: ValidationRule):
"""Add validation rule."""
self.rules.append(rule)
def add_custom_rule(self, rule_id: str, name: str, category: RuleCategory,
check_function: Callable, severity: ValidationSeverity = ValidationSeverity.WARNING,
description: str = "", categories: List[str] = None):
"""Add custom validation rule."""
rule = ValidationRule(
rule_id=rule_id,
name=name,
category=category,
description=description,
severity=severity,
check_function=check_function,
applicable_categories=categories or []
)
self.add_rule(rule)
def validate_element(self, element: Dict[str, Any]) -> List[ValidationIssue]:
"""Validate single element against all rules."""
issues = []
element_category = element.get('category', '')
for rule in self.rules:
if not rule.enabled:
continue
# Check if rule applies to this category
if rule.applicable_categories and element_category not in rule.applicable_categories:
continue
try:
passed = rule.check_function(element)
if not passed:
self._issue_counter += 1
issue = ValidationIssue(
issue_id=f"ISS-{self._issue_counter:05d}",
rule_id=rule.rule_id,
rule_name=rule.name,
element_id=str(element.get('element_id', '')),
element_name=str(element.get('name', '')),
element_category=element_category,
severity=rule.severity,
message=rule.description
)
issues.append(issue)
except Exception as e:
# Rule check failed
self._issue_counter += 1
issue = ValidationIssue(
issue_id=f"ISS-{self._issue_counter:05d}",
rule_id=rule.rule_id,
rule_name=rule.name,
element_id=str(element.get('element_id', '')),
element_name=str(element.get('name', '')),
element_category=element_category,
severity=ValidationSeverity.ERROR,
message=f"Rule check error: {str(e)}"
)
issues.append(issue)
return issues
def validate_model(self, elements_df: pd.DataFrame) -> ValidationReport:
"""Validate entire BIM model."""
self.issues = []
elements_with_issues = set()
for _, row in elements_df.iterrows():
element = row.to_dict()
element_issues = self.validate_element(element)
if element_issues:
elements_with_issues.add(element.get('element_id'))
self.issues.extend(element_issues)
# Calculate summaries
summary_by_severity = {
'error': sum(1 for i in self.issues if i.severity == ValidationSeverity.ERROR),
'warning': sum(1 for i in self.issues if i.severity == ValidationSeverity.WARNING),
'info': sum(1 for i in self.issues if i.severity == ValidationSeverity.INFO)
}
summary_by_category = {}
for issue in self.issues:
cat = issue.element_category
summary_by_category[cat] = summary_by_category.get(cat, 0) + 1
# Determine overall status
if summary_by_severity['error'] > 0:
status = ValidationStatus.FAILED
elif summary_by_severity['warning'] > 0:
status = ValidationStatus.PASSED_WITH_WARNINGS
else:
status = ValidationStatus.PASSED
return ValidationReport(
project_name=self.project_name,
model_name=self.model_name,
validated_at=datetime.now(),
status=status,
total_elements=len(elements_df),
elements_with_issues=len(elements_with_issues),
issues=self.issues,
rules_checked=len([r for r in self.rules if r.enabled]),
summary_by_severity=summary_by_severity,
summary_by_category=summary_by_category
)
def export_report(self, report: ValidationReport, output_path: str):
"""Export validation report to Excel."""
with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
# Summary sheet
summary_data = {
'Metric': ['Project', 'Model', 'Validated At', 'Status',
'Total Elements', 'Elements with Issues', 'Rules Checked',
'Errors', 'Warnings', 'Info'],
'Value': [report.project_name, report.model_name,
report.validated_at.isoformat(), report.status.value,
report.total_elements, report.elements_with_issues,
report.rules_checked, report.summary_by_severity['error'],
report.summary_by_severity['warning'], report.summary_by_severity['info']]
}
pd.DataFrame(summary_data).to_excel(writer, sheet_name='Summary', index=False)
# Issues sheet
issues_df = pd.DataFrame([i.to_dict() for i in report.issues])
if not issues_df.empty:
issues_df.to_excel(writer, sheet_name='Issues', index=False)
# By Category sheet
cat_df = pd.DataFrame([
{'Category': k, 'Issue Count': v}
for k, v in report.summary_by_category.items()
])
if not cat_df.empty:
cat_df.to_excel(writer, sheet_name='By Category', index=False)
return output_path
def generate_validation_report(elements_df: pd.DataFrame,
project_name: str,
model_name: str,
output_path: str = None) -> ValidationReport:
"""Quick function to generate validation report."""
engine = BIMValidationEngine(project_name, model_name)
report = engine.validate_model(elements_df)
if output_path:
engine.export_report(report, output_path)
return reportQuick Start
# Load BIM elements
elements = pd.read_excel("bim_elements.xlsx")
# Run validation
report = generate_validation_report(
elements,
project_name="Office Tower",
model_name="Architectural Model v3.2",
output_path="validation_report.xlsx"
)
print(f"Status: {report.status.value}")
print(f"Errors: {report.summary_by_severity['error']}")
print(f"Warnings: {report.summary_by_severity['warning']}")Common Use Cases
1. Custom Validation Rules
engine = BIMValidationEngine("Project", "Model")
# Add custom rule
engine.add_custom_rule(
rule_id="CUSTOM-001",
name="Fire Rating Required",
category=RuleCategory.REQUIRED_PROPERTIES,
check_function=lambda e: bool(e.get('fire_rating')),
severity=ValidationSeverity.ERROR,
categories=["Walls", "Doors"]
)2. Filter Issues
# Get only errors
errors = [i for i in report.issues if i.severity == ValidationSeverity.ERROR]
# Get issues for specific category
wall_issues = [i for i in report.issues if i.element_category == "Walls"]3. Automated QC Pipeline
report = engine.validate_model(elements)
if report.status == ValidationStatus.FAILED:
send_notification("BIM validation failed", report.summary_by_severity)Resources
- DDC Book: Chapter 4.3 - BIM Validation
- Reference: ISO 19650, buildingSMART IDS