Using Google Cloud Platform tools, we created scitis.io together with Achenbach Buschhütten GmbH to bring data together from the entire lifecycle of industrial products, creating a pan-industrial platform that breaks through the limitations of proprietary technology.
“Our industry involves a lot of mechanics and a lot of automation,” explains André Barten, CEO of Achenbach. “And like products in many industries, aluminium passes through machines at several companies, in several locations, on its way from being molten aluminium to becoming the finished product. That means manufacturing data is decentralised, and it’s why we decided to create a way to pool data and use it to optimise productivity, quality and efficiency.”
Achenbach engineers discussed the issue with our manufacturing software experts. We knew that Google Cloud Platform tools would be able to collect and analyse the dispersed data in real-time, cost-effectively and at scale.
Rapidly, together with Achenbach we recognised the potential of our project for optimising almost any industrial and manufacturing process. From our collaboration, scitis.io was born: an independent digital platform to collect, connect and analyse live data from industrial machinery.
The machines scitis.io connects to can be 100 years old, and the PLCs (programmable logic controllers) that operate them only have to be renewed every 10 to 15 years. If a factory were to choose a proprietary system to stream data, they would be compelled to buy a new, proprietary PLC, which might cost close to $1 million, Thanks to Google Cloud Platform, scitis.io delivers connectivity without the need to replace PLCs or other equipment, so the overall cost is peanuts in comparison.
Big data from heavy machinery
In manufacturing and heavy industry, the production process from raw materials to finished product is very data heavy. In the past you were never able to compare or analyse live data between plants or to create a full history of data due to capacity limits on local computers. Cloud enables that, so we can have all data centrally without dialing in or sending hard drives around the world.
With CloudPlug, we had already developed a system to draw information from PLCs and deliver it to the cloud. The next step for scitis.io was to leverage that data and make it available for analysis.
To do that, scitis.io is built on Google App Engine and uses Google BigQuery to store, parse and interrogate data. To present that information, scitis.io uses Tableau run on Google Compute Engine instances. Because these Google Cloud Platform tools can be scaled up and down at speed, scitis.io customers can deploy the solution to new mills without enlisting additional help from technicians or fiddling with hardware. Unusually within heavy industry, that also means customers can use the system on a trial basis without being tied into a commitment.
Sharing across companies with the cloud
With Achenbach, scitis.io went from proof of concept to full first release in 20 months. For Achenbach, each PLC uses CloudPlug to deliver data on speed, thickness, flatness, breakages and waste in the aluminium rolling process. That data enables the company to assess the effectiveness of different work shifts or diagnose faulty equipment and order spare parts with minimal disruption to production. Where previously it was only possible to look at data from the last three months from a single machine, now Achenbach can take live and historical data from its 300 mills worldwide to analyse macro trends in minute detail.
Because of Google’s open tools, Achenbach can also look at data from machinery from other companies involved in the process, such as those operating furnaces and grinding machines. “With scitis.io we can go beyond Achenbach machinery,” explains André. “Because now we can look at the machines in the process before and after our devices and really see the whole supply chain.”
“Neither scitis.io or Google Cloud Platform are tied to proprietary technology in heavy industry, so we can work with any PLC and we don’t have to defend our legacy on the ground,” says André. “Meanwhile leveraging Google’s technology and scalability means we can set up a solution very quickly. That all keeps costs down, because our upfront investment is low, investment in new machinery is kept to a minimum, and we don’t have to defend multimillion dollar investments into automation.”
Teaching old machines new tricks
SOTEC is a Google Cloud IoT Core partner, with access to the private beta version of Google’s new managed service to easily and securely connect, manage, and ingest data from globally dispersed devices. Integrating Cloud IoT Core with the scitis.io solution is a natural next step, as is applying Google Cloud AI to the expansive datasets collected from new partnerships. Meanwhile scitis.io continues to build new associations with new clients, convincing them that Google Cloud Platform’s ISO/IEC 27017 compliant data centers will deliver the security they demand.
Learn more about scitis.io:
Read full case study: