Automation systems and a huge number of smart sensors are producing vast amounts of data that can, ideally, be used to improve business outcomes. But only if the data can be accessed and analyzed. For a surprising number of reasons, both technical and commercial, however, valuable data remains inaccessible and stranded in the industrial landscape.
In a recent white paper on liberating stranded data, we discuss how data gets stranded and some of the new architectures that are changing this predicament by combining flexible and capable edge computing with a cloud computing model, making it not only feasible, but practical to analyze this data, gain new insights and make the results available to stakeholders. Getting control of stranded data is core to Industrial IoT (IIoT) concepts and essential for Digital Transformation.
Until recently, most manufacturing data was sourced from PLCs, HMIs, SCADA and historian systems running in the operations technology (OT) domain. Within the OT environment, data sources appear to be open, but in reality, they are quite difficult to access for applications outside the OT environment, where the data can be more easily analyzed. In addition, many potentially valuable sources of data – such as environmental conditions, condition-monitoring information and utility consumption – are not needed for production or equipment control and are therefore not collected by the automation systems. This results in a number of different kinds of stranded data:
- Isolated – with no network access
- Ignored – due to lack of immediate need, limited storage, etc.
- Under-sampled – assets generating data but sampled at an insufficient data rate
- Inaccessible – due to inaccessible format, etc.
- Non-digitalized – data on paper, clipboards and white boards
When an end-user or OEM can liberate stranded data from traditional data sources and transmit this to cloud-hosted applications and services, this creates many opportunities including remote monitoring, predictive diagnostics and root cause analysis, planning across machines, plants and facilities, long-term data analytics, like-for-like asset analysis within and across multiple plants, fleet management, cross-domain data analysis and analytics (deep learning), insights into production bottlenecks, and identifying where process defects are originating, even if they are not detected until further in the production process.
Edge solutions can be an integral part of automation systems or installed in parallel to monitor data not needed by the automation systems. Many users prefer the latter approach, because they can obtain the necessary data without impacting existing production systems or invalidating equipment warranties. However, the key is that these new digital capabilities can connect with all previously identified forms of stranded data.
Edge connectivity solutions take many forms, including compact or large PLCs ready to connect with industrial PCs (IPCs) running SCADA or edge software suites, edge controllers that are `edge-enabled’ and running SCADA or edge software suites, and IPCs running SCADA or edge software suites. Hardware deployed at the edge may need wired I/O and/or industrial communication protocol capabilities to interact with all sources of edge data. Once the data is obtained, it may need to be pre-processed, transformed, reduced and/or organized by adding context. Maintaining context is particularly important in manufacturing environments where there are hundreds or thousands of discrete sensors monitoring and driving mechanical and physical machinery actions. Finally, the data must be transmitted to higher-level systems, using protocols like MQTT or OPC UA.
A cloud architecture fits particularly well with the needs of organizations when implementing IIoT data projects. Hosting software in the cloud offers a range of benefits, including reduced costs, with the user paying only for what they use and avoiding investment in purchasing and managing IT infrastructures. The cloud is the enabling infrastructure of many IIoT projects, and the combination of cloud with edge technologies enables innovative interactions among humans, objects and machines, giving birth to new business models based on intelligent products and services.
Where does your organization still have stranded data?