Making data operational
One of our targets is to “make data operational”. In other words, in addition to building reporting analytics, the target is to make data a real-time decision-making tool. This is particularly important with OT (operational technology) data, which comes right out of machines. This data has valuable use in process optimisation, predictive maintenance (as in Kone projects) and for example general OEE overview.
We have a long and strong track of cross-disciplinary combining our businesses (CoDa, Dev, Cloud and Strategy & Design). These combinations have led to more and more wide results and roles e.g. with Ponsse. In recent years, our activities are also gathered around domains, such as industrial. The industrial domain is already significant for us, bringing approximately 1/3 of private sector sales. It’s forecasted to steadily grow also in the future – and that’s why we decided to launch an internal development program for industrial domain, called Solita Industrial Data Hothouse.
Hothouse curriculum
With an open internal call for applications, 19 participants from all six Solita countries and all four business units were selected to participate in Industrial Data Hothouse. The 3,5-week program content was balanced between invited partner and internal speakers, exercise assignment on imaginative frying pan factory data and time reserved for reflection.
Important themes covered in Hothouse were for example:
- How to retrieve and contextualise industrial data
- Different modern factory floor integration platforms and data platforms
- Edge devices and combining edge to cloud (with Nokia MXIE as example)
- Cybersecurity
- Publish layer, visualisation and service design
- Enhancing operative data processes with data analytics (check as well the Crash Course by Tuomas Asikainen and Tero Honko on this topic)
With wide curriculum, we brought various approaches to give a wide overview of industrial data in rather short period of time.
Conclusion – OT and IT converging
Traditionally, data platforms have served for enterprise and master data, the data in IT systems. OT data has been residing in its own separate environment, close to automation, available for local visualisation and trending needs. Now the tools are getting more and more mature for combining these two worlds. Streaming process data can be e.g. seamlessly connected to product data and equipment hierarchy.
An important fact to emphasise is that modern industrial data solutions need appropriate underlying infrastructure. As Hothouse keynote speaker Dave Griffith of Manufacturing HUB mentioned – even though these opportunities of Industry 4.0 (digital technologies and cloud computing) are already here, in many plants and mills it’s essential to first update the underlying technology to Industry 3.0 (automation). This means making sure that process automation, PLC’s, buses, connectivity and interfaces are modern enough to enable further use of data.
To me, one of the most interesting facts about industrial data projects is that they are essentially different from large IT system projects. With large IT system projects, the price tag can be tens of millions of euros, and when the project is ready, ready is as well a firm vendor lock-in. Industrial data projects are much more agile and easier to get started with. It is possible to combine different platforms and technology building blocks, taking a more explorative approach without the risk of ending up to vendor lock-in. Nevertheless, it pays off to first focus on underlying architecture – so that the base is solid for these explorations.
We are ready to take on upcoming industrial challenges and help on these various aspects – by combining the competences of concept/architecture, connectivity, data and design.