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Empower Data-Driven Decisions

by embracing the modern historian

A modern smart factory reaches well outside the four walls of a traditional plant. The rise in cloud technology and remote workforces during the past several years has shifted the location of many operational experts from the factory floor to off-premises sites. These remote workers need a modern historian that provides fast, reliable access to the same information available to their colleagues working inside the plant to increase visibility on operations.

Making production data available to everyone is no longer optional. Process experts need access to operational data for a variety of business solutions. These include advanced industrial analytics software; machine learning workbenches; MES systems; and shift logs. Next generation cloud services can support IT/OT teams by offering a faster way to roll out the data to these users.

One of the ways industrial companies have been able to access operational data is by using cloud sources to store it. These robust solutions, such as AWS IoT SiteWise, Amazon Timestream, or Microsoft ADX, provide instant access to time-series data from anywhere in the world. Furthermore, they allow companies to scale complementary solutions—such as advanced industrial analytics—to a global, remote workforce.

Fast rollouts & scalable solutions

Cloud storage data sources help make large-scale deployments possible. For example, IT departments can roll out timeseries storage and analytics solutions up to 30% faster using a cloud service. They also can collect data from sites that did not previously have a historian. 

As part of our digital strategy, we adopted our cloud-first approach to store our industrial data. This allowed us to connect 20 additional plants with cloud data storage and advanced analytics. As a result, hundreds of our workers were given the opportunity to make data-driven decisions.

These cloud-first solutions offer more people access to information. Companies also can break down data silos and get a global overview of all company data. Even with rapid mergers and acquisitions, bringing in the data silos from new plants and exposing them to corporate solutions becomes more manageable.

The result is empowered production teams where engineers improve production quality, overall equipment efficiency, energy usage, and overall production/asset performance of manufacturing processes. And optimizations and value created from analysis can be repeated easily and deployed at scale to global sites and across equipment. 

The existing market leaders in data historians are also transforming their offerings. AWS and GE Digital, for example, collaborated to bring the Proficy Historian into cloud infrastructure. Aveva, which acquired Wonderware and OSIsoft, is launching Aveva Data Hub that brings its historian product to the cloud. The data warehouse solution uses internal and third-party data by importing traditional historian data into the cloud. 

 

Cloud Considerations

Companies do not necessarily have to move all their data to the cloud at once. A cloud-first strategy employed as a solution at newer plants can operate in tandem with on-premises historians or in a hybrid environment that pulls data from multiple sources. Modernizing your historian landscape also can include moving existing historians to cloud infrastructure or making the historian data that is needed available in a cloud database or data warehouse.

Among the considerations for moving data storage to the cloud is the ability to analyze operational data to find opportunities for improvement. While companies can use the trend viewers that are included with historians, these typically are slow and unintuitive. Companies more advanced along their digitalization journey use advanced industrial analytics software to learn more about process behavior over time. These solutions offer the benefit of being able to connect to cloud sources instead of an on-premises historian.

Moving OT data to the cloud and making data available for analytics has not been a straightforward journey. The rise of data lakes created some false expectations on speed and suitability for BI and real-time analytics use cases. The introduction of IoT/Industrial specific cloud services has made it easier to find data in the right place so that it does not end up in a data swamp.

Equipment and their sensors traditionally report data to their own on-premises historian. To explore data, vendorspecific trend clients had to be used. The next step often is to apply other tools to explore the data. The result is an infrastructure that relies on multiple vendors and multiple protocols. Advanced industrial analytics helps ease that complexity by providing a plant integration component for accessing data across networks and vendors. In a cloud-first blueprint, multiple sites can connect to a single cloud service, which provides clearer ways to integrate to thirdparty tools as well.

Concluding Thoughts

By moving to cloud solutions and choosing a modern historian landscape, process manufacturers can bring advanced industrial analytics to the next level. Both time-series data and time-stamped data (such as events) are directly accessible for analyzing production processes. Engineers can tackle more complex use cases. Direct access to the data allows operational experts to solve more and more complex cases.

The modernized historian also provides a unified location for central and local teams to work better together on use cases where machine learning is needed. Finally, the combination of a modernized historian with advanced industrial analytics offers a firm basis for developing operational insights via analytics-driven dashboards. It also provides reports to all stakeholders across the enterprise and in each layer.

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