The Internet of Things gives companies digital access to thousands of individual objects. But the real power of the approach will come from the whole, not just the sum of the parts. Benefiting from even greater connectivity of the data you have access to, will help to optimise the processes you rely on to ensure operational performance and profitability.
For engineers, IoT technologies promise to simplify a lot of challenging problems. They can install sensors to collect more data on the condition of assets or the status of production processes. They can automate more tasks with connected actuators and flexible machines, and they can do all these things remotely across reliable, inexpensive networks that are easy to build, operate and extend.
Those digital connections enable assets to work in smarter, more efficient ways. Systems can move from traditional reactive methods of control and analysis to new predictive ones. A simple thermostat tells a building’s heating control system how well it has been doing at maintaining a comfortable temperature for the occupants, for example. Using other data sources – like weather forecast information from the Internet, or building occupancy data – the system can predict the amount of heating or cooling energy required up front. That helps it make smarter decisions, cutting energy consumption and reducing operating costs.
Linking together once disparate systems and data sources in this way is hugely powerful, but it’s only a small part of the true potential of the Internet of Things. Emerging machine learning and analytics technologies are leading to the creation of systems that don’t just allow companies to manage cause-and-effect relationships they already understand, they also reveal previously hidden interactions and opportunities for performance improvement.
In manufacturing, for example, smart analytics systems can comb through terabytes of data looking for correlations between the historical process conditions and quality deviations. That can lead to unexpected insights, like the sensitivity of a particular machine to external humidity, or an increase in energy consumption that acts a as tell-tale indicator of wear in a critical asset.
Those kinds of insights can transform operational performance, allowing companies to solve longstanding quality problems, drive up asset reliability or boost productivity.
Building the right infrastructure to deliver those insights isn’t straightforward, however. It requires aggregation and storage systems that can cope with high volumes of complex data from multiple sources. It requires integration technologies than can bring that data together in a meaningful way. It requires analytics tools that can uncover those hidden relationships. And it requires new data presentation and visualisation systems that can make them visible to the user.
Until recently, any organisation that wanted those things had to build them itself. That limited the application of these exciting technologies to big companies with deep pockets and lots of in-house expertise. That’s starting to change. The development of new general purpose IoT platforms, like PTC’s Thingworx, and analytical systems like Glassbeam, are dramatically reducing the cost and complexity of the approach.
We are already applying these technologies to solve challenging problems for customers operating in diverse industries, from the energy (power generation) sector to the automotive industry.
Are you interested in demonstrating real business value from Industry 4.0 in your organisation? For more information about the points discussed in this article get in touch with our Capula Futures team.