Making Sense of IoT Data with Visualizations

IoT and Factory Automation
December 03, 2020

The Internet of Things (IoT) is an emerging technology whose impact will be felt across all industries—especially where business leaders need to maximize value from older production plants.

Taking over a legacy production plant, or a brownfield, means bringing old equipment and infrastructure up-to-speed with the organization’s more modern operations management systems. Brownfields are a challenge to flip as they are typically under-digitalized.

The impact of IoT will be especially felt in the oil and gas industry, where brownfields make up an astounding 80% of the market (Greenfields—new capital investments—make up the rest). However, the amount of data that the IoT is predicted to generate on a typical work site will remain unactionable without an application that provides context to it. How can IoT help drive the most value out of these brownfield investments?

Digitalizing Brownfields

Historical data in the existing plant is usually filed away on paper. So, the first step in modernizing a brownfield is to take control of all of the plant’s existing data by digitalizing it. Once digitalized, the brownfield can plug into the data management initiatives that are taking place across the rest of the business. Existing service buses can capture data stores, and data management systems are able to scale with the existing network infrastructure. Workflow digitalization is the first, crucial step toward achieving operational efficiency.

But plants still run the risk of gathering too much IoT data. In an example, experts predict that new volume-measurement sensors from HP would produce at least 10 exabytes of IoT data, if Shell would have deployed these sensors in combination with new fiber-optic network infrastructure across its 10,000 oil wells. In comparison, all the words ever spoken in the world only amounts to around 5 exabytes, according to one estimate. That is a lot of data to sift through and manage.

To help manage such large datasets, Shell partnered with DreamWorks Animation and IBM to create 3-D and 4-D renderings of the oil wells. These digital maps of the IoT data would give the plant teams more intuition over oil and gas levels in their reservoirs than the raw data would alone.

New visualization technology, like Shell’s 3-D and 4-D maps, will make sense out of these huge caches of IoT data and make them relevant and manageable.

IoT Data and Visualizations

New IoT Visualizations: Digital Twins

A brownfield could take yet another bold move into IoT: creating a full, 3-D point-cloud model of the physical plant. New, affordable 3-D laser scanning technology can scan brownfields and create these 3-D models, to create digital twins of the physical plants. Using the digital twin, administrators could link equipment to the data and show it to the user, either in the field with smart glasses, when combined with augmented reality technology, or in the back office, for training using virtual reality.

By partnering with experts in Geographic Information System (GIS) mapping, 3-D modelling and augmented reality, digitalized Control of Work (CoW) processes can be implemented in brownfields. Visualizations in a CoW solution can show 3-D models with real-time plant data in a geospatial system.

Leveraging IoT Visualizations for CoW and Process Safety Management

When designing isolations in a production plant, IoT could speed up the process of point confirmation and issuing work permits. Using GIS, two people can simultaneously track isolation point confirmations, saving redundant trips to the field for the visual cross-check. By the same token, 3-D models of the plant could allow an operator in the back office to gather all the information they need about a piece of equipment, to aid in authorizing a permit. The operator saves travel time by performing his calculations in the back office to determine if a plant visit is necessary or not.

IoT can also help visualize the plant’s state-of-fitness in a 2-D plot plan, in real-time. For example, an interactive piping and instrumentation diagram (P&ID) can be set up to present real-time data from a process valve.

The next step would be to take all of the 3-D point cloud models into augmented reality. The augmented data is laid out directly over the equipment, keeping the operator’s focus directly on the work in front of him. This helps avoid incidents by preventing him from looking away from the equipment while working.

The Evolving Digital Roadmap

Quickly adaptable software creates endless possibilities for leveraging IoT data, to achieve operational efficiency. With the right software, it would be possible to link tag numbers directly to the equipment, within the 3-D models, and predict failure before it happens—and if failures will be safety critical—by using machine learning to leverage big data.

Likewise, wearable devices could feed a combined EHS, operational risk and process safety platform with real-time information over the location and status of field operators. When further combined with mobile gas detectors and extra monitors in the field, the platform could leverage the entire set of IoT data to strengthen a barrier management system.

All IoT data enriches the real-time cumulative risk visualization of the plant. This sets the stage for both back-office and operations teams to implement a predictive risk framework in order to avoid major incidents in the future.

Coming back to the question of brownfields: how can IoT drive the most value out of these aging assets? Given the right way to visualize IoT data, setting up brownfields to capture and analyze digital datasets can lead to boundless gains in efficiency and productivity. With adaptable software and a combined digital platform, business leaders can discover information and put it to use—at the right place and the right time.

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Author

Tina Amirtha

Tina Amirtha

Product Manager at Wolters Kluwer | Enablon