AWS Cloud-based Data Pipeline for Industry 4.0 Insights

Overview

An Industry 4.0 solution provider faced the challenge of processing vast amounts of machine-generated data for manufacturing insights. JashDS developed an AWS cloud-based data pipeline that ingested data from multiple devices, calculated fact tables, and provided API access, enabling real-time business insights and future data science applications.

About the Client

An Industry 4.0 solution provider serving the manufacturing industry

The Challenge

The client needed to develop a comprehensive solution for manufacturing companies to gain business insights and enable data science applications. Multiple machines in manufacturing facilities were generating vast amounts of data points using Industry 4.0 devices and posting them to an MQTT endpoint. The challenge was to create an AWS cloud-based data pipeline to ingest this data and calculate fact tables for dashboard visualization and future data science purposes.

Key Results

Developed an AWS cloud-based data pipeline capable of processing data from multiple (100k+) Industry 4.0 devices sending messages every second
Created a scalable system to populate multiple fact tables for generating business insights at various organizational levels and time intervals
Implemented data APIs to provide seamless access to the data warehouse for a third-party application layer

Our Solution

The team implemented a comprehensive AWS-based solution to address the client's needs:

Utilized Confluent Kafka MQTT proxy to listen to MQTT messages from Industry 4.0 devices, mapping each MQTT topic to a universal Kafka topic
Developed multiple data pipelines using Python:A pipeline to ingest raw data from Confluent Kafka MQTT proxy into a PostgreSQL database
A pipeline to process historical data and populate fact tables with business insights at various levels (hourly to yearly, machine to organization)
A pipeline to synchronize master data from the application layer to the data warehouse
Created data APIs using Flask to provide requested data in JSON format, enabling the third-party team to generate violations and dashboards
Deployed the entire solution on AWS EC2 instances, with AWS Lambda functions for automated shutdown and restart to optimize cost management

Technologies Used

AWS (EC2, Lambda)Confluent Kafka MQTT proxyPythonPostgreSQLFlaskMQTT

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