As operations technology (OT) leverages the Industrial Internet of Things (IIoT) with sensors on operating equipment 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 asset performance. This is due, in part, to the fact that the digital engineering models developed during the engineering phase of capital projects are typically not playing a role in operations.
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 people 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 – to enable asset performance modelling to deliver actionable intelligence for decision support through an immersive environment for visual operations.
The Digital Engineering Model
For many years, engineering departments have been using advanced modelling and simulation applications that focus on the process of design and construction of an infrastructure asset – a plant, bridge, highway, railway or utility network – in a way that improves project delivery and asset performance. Better project delivery enables companies to optimize CAPEX – through both the depth of information modelling 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 of this information together within the federated digital engineering model, making it possible to track, access, and share with others collaborating on the project. 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 in the real world, the project teams and stakeholders are able to minimize unforeseen situations and keep the project on track.
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 the 3D models for each discipline involved in a project, it improves information mobility. Disciplines can more effectively communicate critical design details for operations, detect clashes earlier in the design phase and before construction starts, share updates during the engineering and construction phases, and hand over accurate and complete information to ensure successful start-up and ongoing operations.
As operations technology (OT) leverages the Industrial Internet of Things (IIoT) with sensors on operating equipment 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 asset performance. This is due, in part, to the fact that the digital engineering models developed during the engineering phase of capital projects are typically not playing a role in operations.
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 people 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 – to enable asset performance modelling to deliver actionable intelligence for decision support through an immersive environment for visual operations.
The Digital Engineering Model
For many years, engineering departments have been using advanced modelling and simulation applications that focus on the process of design and construction of an infrastructure asset – a plant, bridge, highway, railway or utility network – in a way that improves project delivery and asset performance. Better project delivery enables companies to optimize CAPEX – through both the depth of information modelling 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 of this information together within the federated digital engineering model, making it possible to track, access, and share with others collaborating on the project. 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 in the real world, the project teams and stakeholders are able to minimize unforeseen situations and keep the project on track.
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 the 3D models for each discipline involved in a project, it improves information mobility. Disciplines can more effectively communicate critical design details for operations, detect clashes earlier in the design phase and before construction starts, share updates during the engineering and construction phases, and hand over accurate and complete information to ensure successful start-up and ongoing operations.
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