Contributing AWS Authors: Krishna Doddapaneni, Thomas Cummins and Rajesh Gomatam
With the emergence of Industry 4.0 and the Industrial Internet of Things (IIoT), industrial enterprises have access to a wealth of data generated by equipment throughout their operations. This idea of the connected factory has promised smarter, data-driven decisions that maximize productivity, increase equipment availability, and save costs.
For example, condition monitoring and predictive analytics enable plants to optimize equipment maintenance schedules, improve asset performance, and reduce the costs of lost productivity by avoiding unexpected downtime.
Unfortunately, many of these enterprises have yet to realize the full value of IIoT technology because even though there is no shortage of data, that data is not necessarily usable. In fact, 95% of data generated by industrial companies is currently unusable due to siloed infrastructure, poor or inconsistent data quality, and lack of strong data governance.
According to a recent McKinsey & Company report, “Connecting the two worlds of IT and OT would offer a truly end-to-end digital enterprise...But unfortunately for far too many organizations, sharing data between these two worlds can be a struggle, because their network infrastructures are neither up to date nor sufficiently connected” (Leveraging Industrial IoT and Advanced Technologies for Digital Transformation).
When IT and OT teams operate with different objectives and manage their data in disparate systems, the result is fragmented, disconnected data that lacks the context needed to generate real-world value from the organizations’ IoT ecosystem. Worse still, incorrect or incomplete data may be used to make critical business decisions. Unified data management is essential to maximize the value of your IoT investments while mitigating the risk of bad data.
Element Unify is a trusted IT/OT data management solution that integrates critical metadata in the AWS Industrial Machine Connectivity (IMC) kit. This integration makes it even easier for companies to seamlessly provision their IIoT technology stack.
The following illustration shows the architecture of an end-to-end integration between OT data platforms, IT data sources, Element Unify, and AWS services, including AWS IoT SiteWise and Amazon S3 industrial data lake.
Element Unify ingests tag definitions, templates, and existing data models exported from applications like Ignition, KepServerEx and Asset Framework (AF). There is no need to manually parse the information; the software does all of the processing for you. Simply upload an exported JSON file from Ignition or KepServerEx into Amazon S3, which serves as a staging area to load files directly into Element Unify’s Dataset Catalog. Within a few seconds, the files are available in Element Unify for data transformation and are ready to be published in AWS IoT SiteWise.
Element Unify integrates, contextualizes, and governs metadata from various sources, including time-series data, factory edge applications, EAM applications and P&IDs, for single-site, multi-site, and multi-instance deployments. This enables cross-application modeling that allows users to unlock valuable insights while reducing complexity across the entire enterprise.
Element Unify allows industrial enterprises to transform their metadata in more meaningful ways with little-to-no additional coding. This no-code / low-code data transformation makes it easy to deploy Element Unify alongside existing technology architecture and accelerates time to insight—with little to no delays in implementation.
Users who already have data models built out in AWS IoT SiteWise can import them into Element Unify, adding context from other data sources or reshaping them. Enriched models automatically publish back to AWS IoT SiteWise, keeping those models and hierarchies up-to-date as the underlying source data changes.
Element Unify, through the P&ID Productivity Tool, automatically extracts text from Piping and Instrumentation Diagrams (P&IDs) in bulk, enabling the quick association of instruments to equipment, adding additional context to data models in Unify. This reduces mapping errors and saves valuable time in the mapping validation cycle.
The integration with AWS IoT SiteWise includes built-in template and attribute mapping and other purpose-built transformations and functions that make it easy to create or reshape data models that power AWS IoT SiteWise, as well as other applications including Amazon SageMaker and Amazon QuickSight. Model once and consume anywhere in the AWS stack.
AWS customers or partners interested in extensibility have the option to develop custom connectors for other IT and OT systems in their ecosystem, enabling any tag definitions, structures, or relational information from these systems to connect to Element Unify.
Element Unify enables real-world use cases like condition monitoring, predictive analytics and maintenance, and Overall Equipment Effectiveness (OEE). Additionally, companies can benefit from improved alignment and collaboration between IT and OT teams as they share context rich, standardized data across the organization. Read more about this integration on the AWS for Industrial blog.
We will be discussing unifying IT/OT data during a webinar on June 30; 10:00 AM PDT / 1:00 PM EDT. Register to join us.