Cargotec picks Cloudera to give data-driven services a lift
Cargotec picks Cloudera to give data-driven services a lift

Cargotec picks Cloudera to give data-driven services a lift

Cargotec is using big data technology from Cloudera to give its machinery a digital services makeover.

Cargotec, a Finnish company that makes cargo-handling machinery for ships, ports, terminals and local distribution centres, has implemented the IoT to give its machinery a digital boost. It is also using big data technology from Cloudera to underpin predictive maintenance and other data-driven services.

To support Cargotec’s IoT plans, Cloudera, together with Tata Consultancy Services (TCS), built a cloud-based analytics framework for sensor data. Here, data streams are collected, stored, analyzed and combined with data from internal, external and third-party data sources.

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Data ingestion

The analytics and machine learning platform, based on Cloudera’s Enterprise Data Hub, will ingest data from equipment and fleet management, pull in weather patterns and forecasts, and contrast geography – to perform key analyses for remote monitoring, predictive equipment maintenance and anomaly detection – all in real-time.

Cargotec expects that this platform will allow it to offer new types of intelligent services and solutions with embedded artificial intelligence to customers, along with its machines. Once collected, enriched data will be used for driving and boosting new types of ecosystems by exposing the data through APIs [application programming interfaces] for other companies to use.

Using the hub, Cargotec can glean intelligence on fuel efficiency and route optimisation that end users, such as ports or shipping companies, can purchase to improve their operational efficiencies. This, in turn, should create new revenue streams for Cargotec.

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Data scientists at work

Additionally, the Cargotec data science team is using Cloudera Data Science Workbench, a collaborative hub and integrated development environment. This is where developers can build queries, reports and analytic applications in Python, R or Scala, with support for Apache Spark to build machine learning solutions.

“It is our goal to be a leader in intelligent cargo handling by 2020,” said Soili Mäkinen, chief information officer at Cargotec. “With our scalable IoT platform, we can offer our customers data-based insights that many of these industrial companies have never seen before.”

“We use IoT data and machine learning to help customers recognise how their cargo handling equipment are performing in different weather conditions, understand how usage relates to failure rates, and even detect anomalies in transport systems,” she added.

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