Science Laboratory Inventory Management System (SLIMS)

A comprehensive inventory management system designed specifically for scientific research environments, featuring advanced tracking capabilities, role-based access control, and intelligent recommendation algorithms.

Features

Core Functionality

• Complete Inventory Management: Track chemicals, equipment, glassware, and consumables with detailed metadata
• Location Tracking: Organize inventory by location with capacity monitoring
• Transaction History: Full audit trail of item movements and usage
• Order Management: Request and track orders from suppliers
• Reporting & Analytics: Generate insights from inventory and usage data

Advanced Features

• Personalized Recommendation Engine: Context-aware item suggestions based on:
  • Personal usage patterns (50% weight)
  • Department relevance (20% weight)
  • Role-specific patterns (30% weight)
  • Stock availability and category adjustments
• Role-Based Access Control: Permissions tailored to different laboratory roles:
  • Admin: Full system access
  • Lab Manager: Inventory management and reporting
  • Researcher: Usage tracking and ordering
  • Student: Limited viewing and basic transactions
• Safety Compliance: Track safety data, hazard classifications, and storage requirements

Technical Highlights

• Three-Tier Architecture:
  • Frontend: HTML/CSS/JavaScript with Bootstrap for responsive design
  • Backend: Python Flask framework
  • Database: SQLite for persistent storage
• RESTful API: Enables integration with other laboratory systems
• Barcode/RFID Ready: Support for scanning technology

Getting Started

Prerequisites

• Python 3.x
• Flask and related packages
• Modern web browser
• Internet connection for external API features

Installation

1. Clone the repository
2. Install required Python packages:

   pip install -r requirements.txt
   

3. Initialize the database:

   python app.py init_db
   

4. Start the application:

   python run.py
   

Default Credentials

• Admin: username: admin, password: admin123
• Lab Manager: username: manager, password: manager123
• Researcher: username: researcher, password: researcher123
• Student: username: student, password: student123

Usage Guide

Navigation

• Dashboard: Overview of key metrics and personalized recommendations
• Inventory: Direct access to item management
• Management: Access locations, suppliers, and reports
• Orders: Track and manage purchase orders
• Recommendations: View all personalized item suggestions

Key Workflows

1. Adding New Items: Inventory → Add Item
2. Checking Out Items: Inventory → View Item → Check Out
3. Placing Orders: Orders → New Order
4. Viewing Reports: Management → Reports
5. Managing Locations: Management → Locations

Recommendation Algorithm

The system uses a sophisticated weighted scoring system to generate personalized inventory recommendations:

• Personal Usage Score (0-5 points, 0.5 weight multiplier)

  • Based on frequency and recency of personal use

• Department Relevance (0-3 points, 0.2 weight multiplier)

  • Based on department-wide usage patterns

• Role Patterns (0-4 points, 0.3 weight multiplier)

  • Based on typical usage for user's role

• Adjustments:

  • Low stock: -1 point
  • Role-category match: +2 points for relevant categories

The system stores up to 15 recommendations with the top 3 displayed on the dashboard.

Security and Permissions

• Role-Based Access Control: Different permissions for various user types
• Transaction Logging: All actions are recorded for audit purposes
• Data Validation: Input validation to prevent security vulnerabilities

License

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

Acknowledgements

• Bootstrap for responsive UI components
• Flask framework for backend functionality
• SQLite for database storage

Build by AAKASH