Beyond SCADA: Consolidating Your OT With an IIoT Platform

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 SCADA systems and integrated into the SCADA 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 SCADA is that these systems 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. They are usually only suited for monitoring, supervision, and sending out alerts at best. More sophisticated analytics or use cases based on machine learning are out of reach. 

Another challenge comes from the operational technology (OT) devices. OT stands for the hardware-and-software bundle that takes care of monitoring and control. It encompasses devices, processes, and pre-defined key events on the shop floor. Each organization 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 organization’s data hub and a single source of truth for insight delivery.

The Bottom Line

One answer to this is an overarching IIoT platform solution that gives companies a solid foundation for iterative processes and enables seamless scalability to thousands of devices. The platform, ideally, is built to deliver a smooth journey from connecting heterogeneous edge devices and systems, ingesting and processing the IoT data, all the way to building machine learning models, and visualizing complex insights in custom dashboards. 

This way, industrial enterprises are best positioned to collect IoT data from any asset. Further, they can reliably store that data. This approach safeguards organization-wide data accessibility at all times and sets the ground for complex analytics. 

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. Industrial IoT platforms abstract all the complexity of the process and allow you to scale fast. Starting with connecting the OT assets, you benefit from a hardware-independent infrastructure. This allows you to reach any device, IPC, system, and piece of equipment thanks to container technology. 

Solving Typical OT Challenges

This way, the platform effectively overcomes the most typical challenges when it comes to tying up the loose ends within an organization 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 harmonize that data, effectively combating data silos. 
• Edge data management capabilities. Processes are in place to securely extract, load, and store 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 organization. Data can be consumed immediately to serve different departments as their needs dictate.  

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 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 visualizations 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 realize 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

Moving forward, you do 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. With robust edge management capabilities, you will have device monitoring and control across manufacturing sites, app management with instant deployments and OTA updates, and data management capabilities that make it possible to collect and unify data from multiple locations. 

The level of transparency delivered by the platform makes it possible for teams to glean insights and respond to outliers faster, bringing forth improvements and anticipating where change is needed.