Endless data blown in like a jarring arctic blast from multiple, siloed systems, each requiring interaction with different isolated tools. This is among the major business challenges facing most industries in general today. With downstream operations, any singular piece or type of equipment at a facility may have thousands of associated points of critical information – and each facility can host thousands, if not tens of thousands, of pieces of equipment requiring data management to operate effectively. Aggregating this flurry of data is only part of the solution.
There are potentially millions of documents, schedules, records, operating metrics, and more, which all exist without context. The solution lies in being able to quickly parse all that data to be used in a meaningful way and to make highly informed – often critical – decisions post haste.
This business need for optimal decision making, always and in all places, should be an evergreen objective and how operators should be thinking of their business. It is the primary ambition and promise of adopting a Digital Performance Model (DPM) and with digital twin as an enabler for this operational transformation.
Let’s review some common pain points addressed by digital twins and how adopting a robust Digital Performance Model helps overcome these challenges.
How much are you losing due to unplanned downtime? There is a complex web of systems, applications, workflows, and human behaviors affecting reliability. Distributed Control Systems (DCS), Emergency Shutdown Systems (ESD), Alarm Management Systems (AMS), Operator Training Simulators (OTS), historical data from unplanned events (Historians), manual logging workflows (Operator Rounds), just to name a few, along with a multitude of dashboards from disparate applications.
On average, refineries experience 2-3 often costly unscheduled shutdowns in a year, typically lasting between 2-5 days. One major cause for this is an inability to access actionable data or insights from the many siloed systems in use, and too many manual workflows which affect your ability to act promptly.
A DPM provides contextualized, actionable data, enabling operators to make informed decisions and prevent unscheduled downtime.
Digital twins analyze sensor data and integrate various Systems of Records (SoRs) to identify anomalies indicating potential failures. This proactive approach transforms maintenance from reactive to predictive, minimizing costly downtimes.
Digital twins can save millions by predicting failures and scheduling maintenance during planned downtimes. The key lies in integration—combining IoT technology, advanced analytics, and machine learning (ML) within a cohesive system and improved digital workflows to respond with speed. Digital twins create this foundation, enabling organizations to unlock data's full potential at scale, improving operational efficiency and reliability.
To optimize production output and fully realize return on asset investment, companies often rely on costly, experienced personnel to aggregate and analyze field production data scattered across numerous systems. This approach can prove to be inefficient, yielding limited operational benefits.
A digital twin automates data aggregation and contextualization, providing insights from a centralized, unified platform.
Digital twins revolutionize production by mirroring physical assets in a digital environment. These autonomous systems aggregate and contextualize real-time data from sensors and various sources, enabling faster, more precise decision-making.
For example, a digital twin detecting a pressure anomaly doesn’t just send an alert; it pinpoints the issue, suggests causes, and predicts production impacts. This autonomy reduces manual labor, improves efficiency, and enhances safety by minimizing field visits to hazardous locations. Digital twins empower organizations to transition to a digital, data-driven approach, optimizing production with unprecedented speed and accuracy.
A common challenge across the energy value chain is finding where data exists in multiple, siloed systems which are often localized to physical sites.
A digital twin centralizes and secures data in the cloud, providing remote access to asset information from anywhere in the world.
Digital twins consolidate asset information into a single, secure, cloud-based (and, if required, on-premise) repository. This democratizes data access, ensuring that everyone—from field operators to decision-makers—can retrieve the right information at the right time.
With built-in security features, digital twins maintain data integrity while enabling real-time insights. By integrating advanced analytics and AI, these systems predict maintenance needs, refine performance, and allow organizations to move from reactive responses to strategic planning. The result is seamless collaboration and enhanced operational efficiency, regardless of location.
Manual inspection planning and work package development often involve paper-based documentation, fragmented processes, and outdated coordination methods. At one refinery, this cumbersome approach led to delays, increased operational risks, and suboptimal decision-making. Critical inspection needs were often overlooked, and insights from inspection data were challenging to extract.
A digital twin enables proactive and predictive inspection planning, streamlining work packages and optimizing resource utilization.
Digital twins simulate scenarios in a risk-free environment, predicting failures and optimizing inspection routes based on past data and future projections. This transition from reactive to proactive inspections reduces downtime, improves efficiency, and lowers costs.
Moreover, digital twins evolve with every inspection, refining their predictions through continuous learning. This creates a dynamic system that grows smarter over time, reducing routine inspections and unexpected breakdowns while allowing teams to focus on high-value activities.
Learn more here about our downstream technology and our dynamic digital twin platform, Kognitwin. Discover how adopting a robust DPM can help unlock new efficiencies and realize greater return on asset performance and productivity in your downstream operations.
