Beyond SCADA Systems: Consolidating Your OT with an IIoT Platform

Along with MES and IoT technology, SCADA systems are today’s most widely used tool in manufacturing facilities. Industrial enterprises use SCADA as a process control system to monitor data acquisition processes and oversee various related workflows. The data coming from OT devices is taken in by the SCADA system and integrated into the ecosystem as applications covering a range of use cases for the shop floor. So why does an industrial IoT platform still make sense here? 

One downside of traditional SCADA systems, in contrast to IoT solutions, is that they are not made for rapid scaling. They do not accommodate change so easily. Most of the time, the processes are slow and inflexible. Further, the data collection processes, though robust, have their limitations. As an industrial control system, SCADA software is usually only suited for monitoring, supervisory control, and sending out alerts at best. More sophisticated analytics or use cases based on machine learning are out of reach for the SCADA solution.

Another challenge comes from the Operational Technology (OT) devices as such. OT stands for the hardware-and-software bundle within an organisation that takes care of monitoring and control. It encompasses devices, processes, and pre-defined key events on the shop floor. Each organisation has a wide range of industrial assets, most of them highly heterogeneous. So the greatest quandary is consolidating these and making them all work in concert. Preferably, this takes place from within a single venue that can serve as the organisation’s data hub and a single source of truth for insight delivery.

SCADA systems vs IoT Platforms: The Bottom Line

Unlike cloud-based IoT, SCADA systems do not respond well to the challenges of scaling. One answer to this is an overarching IIoT platform solution that gives companies a solid foundation for iterative industrial processes and enables both industrial automation and seamless scalability to thousands of devices. At Record Evolution, we make it a priority to ensure a smooth journey from connecting heterogeneous IoT devices and systems, ingesting and processing the IoT data, all the way to building machine learning models and visualising complex insights in custom dashboards across multiple sites.

Specifically, industrial enterprises are best positioned to collect and consolidate IoT data from multiple field devices. Further, they can reliably store the data coming from various IoT systems. This approach safeguards organisation-wide data accessibility at all times and sets the ground for complex analytics and sophisticated artificial intelligence solutions.

Beyond the SCADA application scenarios, this means more access to consolidated real time data for better data analytics without significant change in the critical infrastructure. In turn, more and better data translates into refined remote monitoring and predictive maintenance solutions, and ultimaltely more insight into industrial operations.

How Do You Consolidate All Your Industrial Assets? 

Consolidating industrial assets and safeguarding transparency across different OT units is the very foundation of streamlined operations on the shop floor. The industrial IoT platform by Record Evolution helps you get there. The IIoT system abstracts all the complexity of the process and allows you to scale fast. Starting with connecting the OT assets, you benefit from a hardware-independent infrastructure. This allows you to reach sensors, IIoT devices, control systems, IPCs, data acquisition systems, practically anything at the level of the IoT gateway and any piece of equipment thanks to container technology.  

Solving Typical OT Challenges

Unlike SCADA technology, the platform effectively overcomes the most typical challenges when it comes to tying up the loose ends within an organisation and unifying OT (and IT along the way):

• Brownfield integration. Full inclusion of any brownfield assets including legacy devices, systems, and industrial equipment by different vendors.
• Data collection from multiple heterogeneous sources. The ability to tap into IoT data coming from any data source and harmonise that data, effectively combating data silos. 
• Edge data management capabilities. Processes in place to securely extract, load, and store the incoming IoT data, making it available where it is needed. 
• Complete integration within the existing infrastructure. Eliminating the need for complex system integration scenarios. 
• Full transparency and collaborative capabilities, allowing effective knowledge exchange within and across manufacturing sites. 

This makes for a fully consolidated OT layer, providing a solid basis for building applications and perfecting existing use cases. Once on the platform, the collected IoT data is readily available to various functions within the organisation. Data can be consumed immediately to serve different departments as their needs dictate.  

Record Evolution combines data democratisation with a hardware-agnostic, any-protocol, any-programming language approach to device connectivity. 

The data collected from edge devices is stored securely, with device logs ensuring a transparent audit trail at all times. Raw or processed, data can be stored in the cloud thanks to a comprehensive data studio with advanced visualisation capabilities. The platform’s RESTful API enables integration with a wealth of additional services and BI tools. This translates into even more sophisticated infographics, data transformation tasks, and algorithm building. 

The Next Step: Achieving Seamless Scalability

An effective IIoT platform can enhance existing OT capabilities. But it can also start from scratch, bringing together isolated assets and putting the high availability of enterprise data at the forefront. The first step towards scalability is connecting to each and every data-generating asset to the platform. 

From Data to Process

The data is then extracted, unified, and stored securely on the platform. This way, it can be immediately consumed and used for a variety of tasks. These may range from instant visualisations or performing queries on the data all the way to building IoT apps based on sophisticated machine learning models. The apps can be rolled out back to the IoT edge to serve a variety of functions. These may span from simple monitoring and control tasks, reporting on key parameters, overseeing that specific KPIs are met, and ultimately improving overall operational efficiency. 

Taking it from here, you build an iterative process where you continually improve on the existing cycle to realise more ROI faster. This is how you build a robust process starting with feeding the relevant IoT data into the IIoT platform engine.

 Expanding across Multiple Sites

Record Evolution makes it easy to not simply implement the established cycles within one manufacturing site but also expand across multiple locations, creating an even larger network of connected assets streaming IoT data. This level of transparency makes it possible for teams to glean insights and respond to outliers faster, bringing forth improvements and anticipating where change is needed. 

Thanks to its robust edge management capabilities, the IIoT platform by Record Evolution delivers device monitoring and control across manufacturing sites, app management with instant deployments and OTA updates, and a solid data management capability that allows enterprises to collect and unify data from multiple locations.