• Developed a Production Data Acquisition (PDA) System to monitor and analyze real-time machine performance and operational data.• Built backend logic to process data from industrial sensors, capturing key metrics like vibration, temperature, motion, and cycle counts for detailed machine execution insights.• Implemented a robust pipeline using Kafka to stream real-time sensor data, storing it efficiently in a PostgreSQL database with timestamp-based indexing.• Designed and integrated a ticketing system, enabling users to log queries, attach images for context, and track resolution statuses directly within the platform.• Developed notification systems to alert users about machine anomalies, state changes, and ticket updates, improving response times and operational efficiency.• Created interactive dashboards to visualize real-time and historical machine states, production metrics, and user inputs, ensuring actionable insights for operators and management.Key Features:• Real-time monitoring of machine states such as Stopped, Idle, Operating, Producing, and Off.• Background task processing: Used Dramatiq with Redis to handle asynchronous tasks like data aggregation, notification generation, and machine state calculations.• Scheduler Integration: Automated pre-collection processes to ensure timely and efficient data retrieval. Real-time notifications: Implemented using Socket.IO, delivering updates instantly for machine events, ticket status changes, and shift transitions.• Comprehensive ticketing system with image attachment support, enabling detailed issue documentation and faster resolution.