Digital Plant Engineering Plant Engineers Shake Hands with the Cyber–Age

Author / Editor: Bhupinder Singh, Anne-Marie Walters* / Dominik Stephan

The age of digital engineering has just began: As operation, information and technology are about to merge, engineering enters a new era — Digital engineering models and actual operational data don’t have much in common — or have they? The Internet of Things and intelligent field devices are about to usher in a new era, in which the boundaries between cyberspace and on-site production blur. It is up to us to harness the technological change and reap its benefits.

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As operations technology (OT) leverages the Industrial Internet of Things (IIoT) with sensors and assets producing an enormous volume of big data, there is a need for improved security, information sharing and data management. This, in turn, is driving an unprecedented convergence with IT.

However, organizations are struggling to make use of the data from their OT and IT systems, causing them to miss opportunities to improve performance. This is due, in part, to the fact that the digital models developed during the engineering phase of capital projects, are typically not playing a role in operations.

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From Digital Model to Business Results

What if owner-operators could use these models in operations? Imagine how a digital engineering model — the engineering technology or ET of an asset — could help operations and maintenance staff forecast problems, do better planning, and improve performance.

It is now possible for companies to converge their IT, OT and ET — and seamlessly integrate process and information flows between them. This enables asset performance modeling to deliver actionable intelligence for decision support through an immersive environment for visual operations.

The Information is There

For many years, engineering departments have been using advanced modeling and simulation applications that focus on the process of design and construction of an infrastructure asset in a way that improves project delivery and asset performance. Better project delivery enables companies to optimize Capex — through both the depth of information modeling and the breadth of information mobility for collaboration during design and construction.

There’s a staggering amount of information related to assets — detailed component specifications, precise geo-location, configuration management, fabrication details, cost information, predicted lifetimes, recommended maintenance and repair information. Today’s engineering technology makes it possible to bring all this information together within the federated digital engineering model, making it possible to track, access and share with others.

The technology also enables engineers to model projects in a 3D virtual setting for design integration and construction work packaging, so that when the project is actually constructed, the project teams and stakeholders are able to minimize unforeseen situations.

The Coming Convergence

Ideally, all of this information flows between applications and project teams for better project delivery, which is the key to better Capex, and flows through to operations and maintenance systems across the entire asset lifecycle, which is key to reducing Opex. For example, when companies can integrate 3D models for each discipline in a project, it improves information mobility.

Disciplines can more effectively communicate critical design details, detect clashes earlier in the design phase and before construction starts, share updates during engineering and construction and hand over accurate and complete information to ensure successful start-up and operations.

How the IIoT Converges with Real-World Engineering

The Industrial Internet of Things (IIoT) is driving a convergence between operational technology and information technology. Digital engineering models can accelerate this convergence and add the visual representation of the real world needed to aid decision making; this can have far-reaching impacts on the safety, productivity, efficiency and operations of industries worldwide.

For example, South Australia Water is currently using predictive and real-time operational analytics to forecast water demand and improve customer service while reducing operational costs. To create a demand forecasting tool, they needed to pull information from both the operational and IT sides of the organization in real time.

Bentley’s predictive analytics software was chosen as the operational intelligence platform due to its real-time ability to connect and capture data from a wide variety of sources, its ability to perform complicated calculations and analysis, and its impressive visualization capabilities. Bringing data from sensors, equipment and external sources together has resulted in huge benefits, including improved performance, enhanced understanding of interrelationships and better decision-making as well as more accurate predictions of short- and long-term demand.

We are witnessing an exciting convergence: The ability to work in a comprehensive modeling environment, leveraging technologies, and connecting with the Industrial Internet of Things through asset management and predictive analytics, gives companies the chance to converge their information, operational and engineering technology — and seamlessly integrate processes and information between them.

The next generation of engineers — digital natives — will no doubt find ways to exploit this convergence in unprecedented ways. But we can already realize immediate benefits today by using these technologies to make more informed decisions regarding when to repair, retire, or replace assets so that they are safer, more reliable and maximally efficient.

* * The authors are Chief Production Officer (Singh) and Global Marketing Director (Walters) at Bentley.

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