Even though the early adoption of industrial Ethernet has shown marginal productivity gains (+22%) and reduction in maintenance costs (-40%), System Integrators and Plant Engineers are still hesitant for its all-out implementation. But why? Today, traditional control systems can use only 3% of data from plant assets, and are unable to cater for the dynamic business requirements. Out of date systems often run into problems due to limited capabilities, and are always at risk to security loopholes. Therefore, in order to gain an edge over the competition and retain productivity levels, it is essential that companies start moving towards the direction of software-defined machines that are smart enough to adapt to varying process outputs.
Optimization through Predictive Models
Traditionally, a controller was only able to run a single application at a time, but recent advancements have brought new features to the table, one of which is the ability to simultaneously run multiple applications. Examples of such applications include predictive modelling packages that can collect data from various processes and feed it into a real-time optimizer to ensure assets are running in the most efficient manner possible.
But this also means that more processing power and greater connectivity would have to be established to ensure these applications run smoothly without hindering the controller’s primary tasks. To cater for such requirements, advanced control systems are being introduced, and these rely heavily on the capabilities of industrial internet to run at optimum levels.
Cloud-computing is also making its way into the industrial market as a viable way to meet the high level of compute resources required by advanced analytics applications. Machines hosted on the cloud provide a perfect platform for assets connected to the internet to relay their information into a central repository, on which engineers can perform operations remotely.
In addition, the advent of Big Data Analytics and the availability of cloud based pay-as-you-go Data Warehouse Services mean industries are more likely to benefit from real-time analytics if their resources are hosted already on the cloud, eliminating the need to go through the tedious processes of migration.
Suppose an automation and controls company offers a cloud platform capable of running analytics and similar applications. The platform acts as a repository for machines, analyzes trends and provides insights to its clients as to how the plant floor can operate at maximum efficiency. The entire feature set is provided as a service therefore companies no longer need to set up separate infrastructure for each process and inter-link them.
The new era of controls provides a much needed boost to the industrial economy while opening new avenues of growth. As machines and humans become increasingly interconnected, machines could also be programmed to make use of apps the same way consumers do, something that would improve as Artificial Intelligence and Artificial Neural Networks make headway.
Conclusively, with industrial internet-enabled controllers, intelligence can be imparted and interfaced within equipment and control systems, improving the overall efficiency and reliability of the system, from the commercial aspect right down to the machine level.