WHY APACHE KAFKA IN MANUFACTURING AND INDUSTRY 4.0?
Companies that want to modernize their manufacturing processes have one or more objectives in common:
1. Bring the agile software delivery into factories.
2. Faster mean time to recover by reducing downtime of equipment with predictive maintenance and automating software updates.
3. Enable centralized command and control to visualize the overall manufacturing process in one plant or across multiple factories.
4. Implement a consistent and flexible software architecture.
Event Streaming with Apache Kafka plays a key role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way. Industry 4.0 is all about processing high volumes of data in real-time.
Here are a few reasons why Apache Kafka gets more and more adoption in Industry 4.0 projects:
Real-time messaging (at scale, mission-critical)
Global Kafka (edge, data center, multi-cloud)
Cloud-native (open, flexible, elastic)
Data integration (legacy + modern protocols, applications, communication paradigms)
Data correlation (real-time + historical data, omni-channel)
Real decoupling (not just messaging, but also infinite storage + replayability of events)
Real-time monitoring
Transactional data (MES, ERP, CRM, SCM, …)
Applied machine learning (model training and scoring)
Cybersecurity
Cutting edge technology (3D printing, augmented reality, …)
These are not new characteristics and requirements. Real-time messaging solutions exist for many years. Hundreds of platforms exist for data integration (including ETL and ESB tooling or specific IIoT platforms such as OSIsoft PI). SCADA systems monitor plants for decades in real-time. And so on.
The significant difference is that Kafka combines all the above characteristics in an open, scalable, and flexible infrastructure to operate mission-critical workloads at scale in real-time.
