Browsing Tag

manufacturing

9 posts
Automotive and Manufacturing Landscape for Apache Kafka
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Apache Kafka Landscape for Automotive and Manufacturing

Apache Kafka is the central nervous system of many applications in various areas related to the automotive and manufacturing industry for processing analytical and transactional data in motion across edge, hybrid, and multi-cloud deployments. This article explores the event streaming landscape for automotive including connected vehicles, smart manufacturing, supply chain optimization, aftersales, mobility services, and innovative new business models.
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Unidirectional Kafka Gateway for Zero Trust and Air Gapped Environments
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  • 10 minute read

Kafka for Cybersecurity (Part 5 of 6) – Zero Trust and Air-Gapped Environments

This blog series explores use cases and architectures for Apache Kafka in the cybersecurity space, including situational awareness, threat intelligence, forensics, air-gapped and zero trust environments, and SIEM / SOAR modernization. This post is part five: Zero trust and air-gapped environments.
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Apache Kafka for Industrial IoT and Manufacturing 4.0

This post explores use cases and architectures for processing data in motion with Apache Kafka in Industrial IoT (IIoT) across verticals such as automotive, energy, steel manufacturing, oil&gas, cybersecurity, shipping, logistics. Use cases include predictive maintenance, quality assurance, track and track, real-time locating system (RTLS), asset tracking, customer 360, and more. Examples include BMW, Bosch, Baader, Intel, Porsche, and Devon.
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MQTT and Kafka for Manufacturing and Industrial IoT
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Apache Kafka and MQTT (Part 3 of 5) – Manufacturing 4.0 and Industrial IoT

Apache Kafka and MQTT are a perfect combination for many IoT use cases. This blog series covers the pros and cons of both technologies. Various use cases across industries, including connected vehicles, manufacturing, mobility services, and smart city are explored. The examples use different architectures, including lightweight edge scenarios, hybrid integrations, and serverless cloud solutions. This post is part three: Manufacturing, Industrial IoT, and Industry 4.0.
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Apache Kafka in Aviation Industry including Airlines Airports Manufacturing Retail GDS
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Apache Kafka in the Airline, Aviation and Travel Industry

Aviation and travel are notoriously vulnerable to social, economic, and political events, as well as the ever-changing expectations of consumers. Coronavirus is just a piece of the challenge. This post explores use cases, architectures, and references for Apache Kafka in the aviation industry, including airline, airports, global distribution systems (GDS), aircraft manufacturers, and more.
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Building a Smart Factory with Apache Kafka and 5G Campus Networks

The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology. 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. Learn about the relationship between Apache Kafka and modern telco infrastructures leveraging private 5G campus networks for Industrial IoT (IIoT) and edge computing.
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Real-Time Locating : Tracking System (RTLS) with Apache Kafka and Event Streaming
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Real Time Locating System (RTLS) with Apache Kafka for Transportation and Logistics

Real-Time Locating System (RTLS) enables identifying and tracking the location of assets or people in real-time. This blog post explores the use cases for RTLS, the challenges of existing implementations, and an open, scalable RTLS architecture based on Apache Kafka.
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IoT and Supply Chain Optimization with Apache Kafka and Machine Learning
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Apache Kafka and Machine Learning for Real Time Supply Chain Optimization in IIoT

Apache Kafka and Machine Learning for Real Time Supply Chain Optimization: Integrate in real time with the legacy world and proprietary IIoT protocols (like Siemens S7, Modbus, Beckhoff ADS, OPC-UA, et al). You can process the data at scale and then ingest it into a modern database or analytic / machine  learning framework.
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