Optimizing Operations and Reducing Downtime

Overcoming business challenges in the energy industry—such as cybersecurity threats, a complex regulatory environment, inflation, and supply chain bottlenecks—requires thinking outside the box. Forecasting strategies that worked for industry leaders several years ago may not be as effective today amidst rapid technological advancement and evolving geopolitical and economic circumstances. 

That’s where innovative approaches like digital twins help businesses in the energy industry make well-informed decisions to stay ahead of these complex challenges. Digital twin technology has unique benefits for energy companies, which rely heavily on data to make improvement decisions, identify safety risks, or enhance production efficiency.

Below, we’ll explore what digital twins are and how they help energy companies optimize their operations and reduce asset downtime.

What is a Digital Twin?

In the context of the energy industry, a digital twin is a “virtual replica” of an asset or process that helps operators at these businesses simulate scenarios, make decisions, and optimize assets and processes. By modeling assets or processes in various scenarios across their lifecycles, industry leaders can identify which work best for a business’ challenges.

For instance, oil terminals can leverage digital-twin technology to determine which end-to-end processes in their operations enforce bottlenecks. Factors like delays in loading or unloading shipping vessels, gaps in forecasting the terminal’s monthly capacity, or shortcomings in conducting asset maintenance may unknowingly contribute to operational and productivity gaps.

Adopting a digital twin approach helps these companies improve their agility and resilience because the models they use to simulate operational scenarios and make decisions based on them are driven by real-world data. That increases the likelihood of these models performing successfully, unlike theoretical models, which are conceptual at best.

And that’s critical when energy companies are dealing with fast-changing industry demands.

Higher Global Energy Demands Require Faster, More Adaptable Operations

Replacing energy transmission infrastructure in the United States will cost an estimated $10 billion annually, depending on how and where these lines were initially constructed. Energy demands have skyrocketed since the ’70s, requiring suppliers to determine how to accommodate the growing use of electric vehicles, automated industrial equipment, and other factors.

The same goes for oil and gas suppliers that must keep up with the increasing demands of consumers who depend on these fuels to heat their homes or keep their cars running. These challenges increase operational costs and place higher demands on existing asset infrastructure, meaning business leaders must find innovative ways to plan for the future, optimize operations, and reduce asset downtime.

With a digital-twin strategy, these companies can virtually represent internal and external conditions at their facilities to anticipate operational risks and mitigate them early on. Doing so helps prevent disruptions to the global supply of energy consumables. 

Digital Twins Mitigate Safety Risks and Asset Downtime

Let’s consider the case of an oil or gas supplier whose main concern is the effect of gas leaks on a facility’s production or safety.

When that company installs Internet of Things (IoT) sensors to detect gas leaks, they can use the information collected by these sensors to model potential safety scenarios. Using a digital twin model, the oil or gas supplier can determine the minimum thresholds at which areas of an energy-producing facility might be at risk for adverse events like explosions or asset failures. 

Based on these thresholds, engineering and safety teams can implement appropriate processes like shutdowns to minimize damage to assets or personnel working in the facility. 

Digital Twins Improve Operational Speed and Efficiency

Similarly, digitally twinning automated processes can help guide R&D in improving various automations applied across a facility. For instance, some robot versions may work faster at manufacturing facilities than in shipping facilities, making them more reliable and efficient in the former context. 

A digital twin model helps capture the differences between these scenarios, enabling process owners to realize greater efficiency across their processes. As process owners apply these improvements, they can further optimize and scale for efficiency.

Optimize Your Digital Twin Strategy with Altira

Understanding how a digital replica of end-to-end processes works will help any company in the energy industry optimize its workflows. Adopting a digital twin strategy helps reduce operational risks and increases production output while enabling constant improvement across each process’ lifecycle.

At Altira, we provide venture capital funding and expertise to help innovators in today’s energy industry solve modern, complex challenges. By leveraging IOTA’s digital twin technology, we can enhance real-time data integration and improve operational efficiency. Whether you’re an entrepreneur or you run a portfolio company, our team can help you translate innovative ideas into high-demand offerings for oil and gas customers. With over 20 years of energy technology experience, we can help you commercialize these novel ideas.

Contact us to learn more about implementing digital twins in your business.

Sources: 

CNBC. Why America’s Outdated Energy Grid Is a Climate Problem. https://www.cnbc.com/2023/02/17/why-americas-outdated-energy-grid-is-a-climate-problem.html

Gallagher Specialty. Energy Firms Face Up to New Generation of Operational Risks.  https://specialty.ajg.com/energy/energy-firms-face-up-to-new-generation-of-operational-risks?

McKinsey. What is Digital-Twin Technology? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-digital-twin-technology

NVIDIA. What Is a Digital Twin? https://blogs.nvidia.com/blog/what-is-a-digital-twin/
S&P Global. IEA Sees Major Oil Capacity Glut by 2030 as Demand Peaks. https://www.spglobal.com/commodityinsights/en/market-insights/latest-news/oil/061224-iea-sees-major-oil-capacity-glut-by-2030-as-demand-peaks