Schedule Quality Analyzer

Automated EPC Schedule Assessment & Analysis Application

📋 Overview

The Schedule Quality Analyzer is a web-based application designed to automate the assessment and analysis of EPC (Engineering, Procurement, Construction) project schedules against industry best practices. It implements DCMA 14-Point Schedule Assessment and GAO Schedule Assessment Guide methodologies, providing project managers and schedulers with instant, data-driven insights into schedule quality, risks, and improvement opportunities.

✨ Key Features

• ✅ Automated Schedule Analysis - DCMA 14-Point and GAO compliance checking
• 📊 Interactive Dashboards - Real-time metrics with visualizations
• 📄 Professional Reports - Generate DOCX and Excel reports
• 🔍 Schedule Comparison - Track quality improvements across versions
• 👥 Multi-User Access - Role-based permissions (Admin/Viewer)
• 💡 Smart Recommendations - Prioritized, actionable improvement suggestions
• 🎯 Health Score - Composite 0-100 metric for schedule quality

🚀 Quick Start

Prerequisites

• Python 3.11 or higher
• pip package manager
• Git

Installation

1. Clone the repository

git clone https://github.com/drogoXX/ScheduleAss.git
cd ScheduleAss

2. Install dependencies

pip install -r requirements.txt

3. Run the application

streamlit run app.py

4. Access the application

• Open your browser to http://localhost:8501
• Login with demo credentials (see below)

Demo Credentials

Admin Account:

• Username: admin
• Password: admin123

Viewer Account:

• Username: viewer
• Password: viewer123

📖 User Guide

Uploading a Schedule

1. Navigate to Upload Schedule page
2. Select an existing project or create a new one
3. Upload your P6 CSV export file
4. Click Upload and Analyze
5. Wait for analysis to complete (10-30 seconds)

Viewing Analysis

1. Go to Analysis Dashboard
2. Select a schedule from the dropdown
3. Explore different tabs:
   • Overview: Health score and key metrics
   • Detailed Metrics: In-depth analysis with charts
   • Issues: Identified problems by severity
   • Recommendations: Prioritized improvement actions
   • Activities: Searchable activity list

Generating Reports

1. Visit Reports page
2. Select a schedule
3. Choose report type:
   • DOCX: Executive summary for stakeholders
   • Excel: Detailed analysis for technical teams
4. Click Generate and download

Comparing Schedules

1. Navigate to Comparison page
2. Select two schedule versions
3. View side-by-side metrics
4. Analyze improvements or regressions

🏗️ Project Structure

ScheduleAss/
├── app.py                          # Main application entry point
├── requirements.txt                # Python dependencies
├── .streamlit/
│   └── config.toml                # Streamlit configuration
├── src/
│   ├── auth/
│   │   └── auth_manager.py        # Authentication logic
│   ├── parsers/
│   │   └── schedule_parser.py     # CSV parser for P6 exports
│   ├── analysis/
│   │   ├── dcma_analyzer.py       # DCMA metrics calculator
│   │   ├── metrics_calculator.py  # CPLI, BEI, health score
│   │   └── recommendations.py     # Recommendations engine
│   ├── database/
│   │   └── db_manager.py          # Data storage manager
│   ├── reports/
│   │   ├── docx_generator.py      # DOCX report generator
│   │   └── excel_generator.py     # Excel report generator
│   └── utils/
│       └── helpers.py             # Utility functions
├── pages/
│   ├── 1_Upload_Schedule.py       # Upload interface
│   ├── 2_Analysis_Dashboard.py    # Main dashboard
│   ├── 3_Comparison.py            # Schedule comparison
│   ├── 4_Reports.py               # Report generation
│   └── 5_Settings.py              # Settings and profile
├── data/
│   └── sample_schedule.csv        # Sample P6 export
└── README.md                      # This file

📊 Supported CSV Format

The application expects Primavera P6 CSV exports with the following columns:

Required Columns

• Activity ID
• Activity Name
• Activity Status
• Start
• Finish
• Total Float
• Duration Type

Optional Columns (Recommended)

• WBS Code
• At Completion Duration
• Free Float
• Predecessors / Predecessor Details
• Successors / Successor Details
• Primary Constraint
• Activity Type
• Resource Names

Example P6 Export Settings

When exporting from P6:

1. File → Export → Spreadsheet
2. Select "Activity" layout
3. Include all columns listed above
4. Export as CSV format

🔍 Analysis Metrics

DCMA 14-Point Assessment

Metric	Description	Target
Negative Lags	Activities with lead relationships	0
Positive Lags	Percentage of relationships with lags	≤5%
Hard Constraints	Activities with mandatory dates	≤10%
Missing Logic	Activities without predecessors/successors	0
Long Durations	Activities exceeding 20 days	Minimize
High Float	Excessive total float activities	Review

Performance Indices

• CPLI (Critical Path Length Index)

  • Formula: (Critical Path + Total Float) / Critical Path
  • Target: ≥ 0.95
  • Measures schedule compression risk

• BEI (Baseline Execution Index)

  • Formula: Completed Tasks / Planned Tasks
  • Target: ≥ 0.95
  • Measures schedule adherence

• Health Score

  • Composite metric (0-100)
  • Based on DCMA compliance
  • Ratings: Excellent (90-100), Good (75-89), Fair (60-74), Poor (40-59), Critical (0-39)

🔐 Security & Authentication

User Roles

Role	Permissions
Admin	Upload schedules, run analysis, generate reports, delete data, manage users
Viewer	View dashboards, access reports (read-only)

Session Management

• 30-minute inactivity timeout
• Password-based authentication
• Session state isolation
• Audit logging for all actions

🛠️ Technology Stack

Component	Technology
Frontend	Streamlit 1.28+
Backend	Python 3.11+
Database	Session-based (upgradeable to Pocketbase)
Data Processing	Pandas, NumPy
Visualization	Plotly, Altair, Matplotlib
Reports	python-docx, openpyxl
Authentication	Streamlit Session State

📈 Performance

• CSV Parsing: <10 seconds for 1000-1500 activities
• Analysis Execution: <30 seconds for full DCMA assessment
• Dashboard Rendering: <5 seconds for all visualizations
• Report Generation: <15 seconds for DOCX and Excel

🚧 Troubleshooting

Common Issues

"Missing required columns" error

• Verify P6 export includes all required fields
• Check column names match expected format

"Failed to parse CSV" error

• Ensure file is valid CSV format
• Remove special characters or formatting issues
• Try re-exporting from P6

Analysis takes too long

• Large schedules (>5000 activities) may take longer
• Check system resources (RAM, CPU)
• Try with smaller schedule first

Login not working

• Verify correct username/password
• Try refreshing the page
• Clear browser cache

🔄 Deployment

Streamlit Community Cloud

1. Push code to GitHub repository
2. Visit streamlit.io/cloud
3. Connect your GitHub account
4. Deploy from repository
5. Configure secrets (if needed)

Local Deployment

# Production mode
streamlit run app.py --server.port 8501 --server.address 0.0.0.0

Docker Deployment (Coming Soon)

# Dockerfile example
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["streamlit", "run", "app.py"]

🗺️ Roadmap

Phase 1 ✅ (Current)

• ✅ Basic authentication
• ✅ CSV parser
• ✅ DCMA analysis engine
• ✅ Dashboards and visualizations
• ✅ Report generation (DOCX & Excel)
• ✅ Schedule comparison

Phase 2 🚧 (Planned)

• Pocketbase integration
• Advanced user management
• Monte Carlo risk analysis
• Critical path visualization
• Email notifications
• Custom metric thresholds

Phase 3 🔮 (Future)

• Direct XER file import
• Resource loading analysis
• Portfolio dashboard
• RESTful API
• Mobile app
• Machine learning predictions

🤝 Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

📧 Contact

For questions, issues, or suggestions:

• GitHub Issues: Create an issue
• Email: [Your email]
• Documentation: See in-app help sections

🙏 Acknowledgments

• DCMA - For the 14-Point Schedule Assessment framework
• GAO - For Schedule Assessment Guide best practices
• Streamlit - For the amazing web framework
• Community - For feedback and contributions

📚 References

• DCMA 14-Point Assessment
• GAO Schedule Assessment Guide
• Primavera P6 Documentation
• Streamlit Documentation

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Built with ❤️ for EPC Project Teams

Version 1.0.0 - November 2025