delay-analysis

这段内容是审核时保存的快照。外部来源才是完整且最新的版本。

---
name: "delay-analysis"
description: "Analyze construction schedule delays for claims and recovery. Perform time impact analysis, identify delay causes, calculate damages, and document for disputes."
homepage: "https://datadrivenconstruction.io"
metadata: {"openclaw": {"emoji": "⏱️", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}}
---
# Delay Analysis

## Overview

Analyze construction schedule delays for project recovery and claims. Perform time impact analysis (TIA), identify concurrent delays, calculate delay damages, and prepare documentation for dispute resolution.

> "Proper delay analysis is essential for fair resolution of construction disputes" — DDC Community

## Delay Analysis Methods

```
┌─────────────────────────────────────────────────────────────────┐
│                    DELAY ANALYSIS METHODS                        │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  As-Planned vs As-Built    │    Time Impact Analysis (TIA)      │
│  ─────────────────────     │    ────────────────────────────    │
│  Compare original to       │    Insert delay events into        │
│  actual schedule           │    schedule to measure impact      │
│                            │                                     │
│  Windows Analysis          │    Collapsed As-Built              │
│  ────────────────          │    ─────────────────               │
│  Divide project into       │    Remove delays from as-built     │
│  time periods              │    to find "but-for" completion    │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘
```

## Technical Implementation

```python
from dataclasses import dataclass, field
from typing import List, Dict, Optional, Tuple
from datetime import datetime, timedelta
from enum import Enum
from collections import defaultdict

class DelayType(Enum):
    EXCUSABLE_COMPENSABLE = "excusable_compensable"      # Owner caused - time + money
    EXCUSABLE_NON_COMPENSABLE = "excusable_non_compensable"  # Neither party - time only
    NON_EXCUSABLE = "non_excusable"                      # Contractor caused - no relief
    CONCURRENT = "concurrent"                            # Both parties - complex

class DelayCause(Enum):
    OWNER_CHANGE = "owner_change"
    LATE_INFORMATION = "late_information"
    DIFFERING_CONDITIONS = "differing_conditions"
    PERMIT_DELAY = "permit_delay"
    WEATHER = "weather"
    LABOR_SHORTAGE = "labor_shortage"
    MATERIAL_DELAY = "material_delay"
    SUBCONTRACTOR = "subcontractor"
    COORDINATION = "coordination"
    ACCESS = "access"
    FORCE_MAJEURE = "force_majeure"

@dataclass
class DelayEvent:
    id: str
    description: str
    cause: DelayCause
    delay_type: DelayType
    start_date: datetime
    end_date: datetime
    affected_activities: List[str]
    responsible_party: str
    documented: bool = True
    supporting_docs: List[str] = field(default_factory=list)
    calculated_impact: int = 0  # days
    concurrent_with: List[str] = field(default_factory=list)

@dataclass
class ScheduleVersion:
    version_id: str
    version_type: str  # baseline, update, as-built
    data_date: datetime
    completion_date: datetime
    activities: Dict[str, Dict]  # activity_id -> {start, finish, duration}

@dataclass
class WindowPeriod:
    window_id: str
    start_date: datetime
    end_date: datetime
    planned_progress: float
    actual_progress: float
    delay_days: int
    delay_events: List[str]
    responsible_parties: Dict[str, int]  # party -> delay days

@dataclass
class DelayAnalysisReport:
    project_name: str
    analysis_date: datetime
    original_completion: datetime
    actual_completion: datetime
    total_delay: int
    excusable_delay: int
    non_excusable_delay: int
    concurrent_delay: int
    del