Manufacturing as an industry has always been at the forefront of squeezing value from data. Instrumentation, highly connected systems, and automation have been part and parcel of manufacturing organisations for decades. Constrained by the state of technology more than cost, process optimisation was always achieved by making clever use of the data available and has given rise to completely new disciplines and applications.
Yet many manufacturers now feel they’ve bumped up against a ceiling. Data volumes from both inside as well as outside the manufacturing process continue to grow. The makeup of data changes too, and is more and more unstructured. Analyst firms like Ovum identify that there is a proliferation of machines and sensors, industrial IoT, each spewing forth torrents of data, disrupting the manufacturing industry with near certainty. Getting a handle on these flows of information becomes cost prohibitive with the current approaches. In order to innovate, to remain competitive and differentiate, manufacturing organisations must break through and fundamentally change their approach to managing their data. It will lay the foundation that they need in order to gain data-driven insight: an actionable view of their operations, products, customers, and supply chain.
A whole new world
What if manufacturers were no longer constrained in terms of the data at their disposal? What if the boundaries for innovation and insight were no longer set by the sliver of historical data on offer or the processing power available?
There would be no limit to the questions to be asked, simulations run, or alternatives evaluated. Manufacturing can move from working with approximations to insight based on actual data, as it happens. Overall performance would be improved through better forecasts of product demand and production, through the understanding of plant operations across multiple metrics, and by being able to provide service and support to customers faster.
Enabling tomorrow today
Data is what delivers that future vision in the present. Transformed, contextualised and analysed, it shows a clear way forward. However, to do so, organisations must not only fundamentally rethink their data management strategy but also transition to a platform that is optimised for the scale and complexity the data problem presents. A modern platform based on open source. A platform that helps companies find patterns and trends in their data by applying machine learning, where business users can analyse not just their structured data in the one or two silos they have access to, but all data relevant to the business problem they are trying to solve. Last but not least, a platform that’s enterprise-grade and can be scaled up or down on hybrid infrastructures.
The value that plant data holds is significant even for organisations where the manufacturing process is well understood. Take Tenaris, a manufacturer of both welded and seamless steel tubes. Their biggest operational cost is energy: tremendous electric currents are required for both welding as well as melting the metal; gigawatts on an annual basis.
As Tenaris uses their gigawatts in production, they also gather gigabytes of data on a daily basis from their manufacturing process. Thousands of furnace sensors gather key measurements like temperature, pressure and electrical consumption at sub-second rates. Not only is the data used to drive higher product quality, it’s also made available to Tenaris’ team of data scientists. Using Cloudera’s platform, they deliver insights in a couple of days rather than the weeks it took before, and are able to improve energy consumption by being able to predict demand. At gigawatt scale, even the smallest of efficiency gains has a tremendous impact on operating costs.
Manufacturing data: how do you use yours?
If you had all your manufacturing data in its original fidelity both as it is happening and as it has happened, what insights would you be able to get? Cloudera, the modern platform for machine learning and analytics, optimised for the cloud, makes it possible.
Learn more about Tenaris’ success and watch the video.