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Digital Twin is most commonly defined as a software representation of a physical asset, system or process designed to detect, prevent, predict and optimize through real time analytics to deliver business value. At GE Digital, we’re focused on how Digital Twins can help our customers across three core areas: Asset, Network and Process.
From Aviation, Oil & Gas, Power Generation, to Electrical Grids and Manufacturing Operations – our Digital Twin software apply machine learning and advanced analytics to real-time monitoring of vast quantities of industrial data: from HMI/SCADA systems, time series, alarms, events, as well as weather and ambient temperature readings.
But what types of Digital Twins does GE Digital specialize in, and how are industrial companies using them to realize value? What kind of outcomes can industrial companies expect?
Covered by our Asset Performance Management (APM) technology, this mission-critical software solution creates Digital Twins based on operational / fleet data of components (like pumps or compressors), critical assets (like turbines) or systems of assets (like an entire power station). Key markets are Power Generation and Oil & Gas, but it spans across industries as diverse as Mining, Metals, and Manufacturing.
Cost savings with Asset Digital Twins are significant. To date, we’ve saved our customers $1.5BN through Digital Twins real-time monitoring capabilities, and currently have 1.2m Digital Twins of jet engines, wind-farms, off-shore oil rigs, power generation equipment, pumps, compressors, chillers, and more. GE Digital currently has over 330 different Digital Twin ‘blueprints’ available for customers in its analytics catalog – meaning it’s easier than ever for industrial companies to rapidly get value from their digital twin investments.
Oil & Gas company, Chevron Energy Technology, is using Asset Digital Twin software to fix small issues before they become big problems. Through continuous monitoring with GE Digital’s Industrial Managed Services (IMS) and Digital Twin software, it uses data, analytics and knowledge to increase availability, reliability, efficiency and profitability. Asset Digital Twins are used to quickly and efficiently expand the company’s predictive diagnostics footprint. By applying predictive diagnostics, Chevron will decrease downtime and decrease maintenance costs by deploying the right amount of service to the right asset at the right time, maximizing the company’s return on investment.
This type of Digital Twin is an increasingly common tool for operators of large equipment to optimize their maintenance schedules and to predict and avoid unplanned downtime. Operators and owners in these industries are now looking for easier, faster ways to get to value from their Digital Twin investments and understand how they can get Digital Twin assets to ‘communicate’ with other systems at the plant level.
Electrical grids are the world’s largest and most complex machines. In addition to keeping the lights on with reliable, available and affordable electricity, grid operators need to manage the impact of increasingly extreme weather, aging infrastructure, and the growing use of renewables on the grid. Network Digital Twin can help by helping operators create virtual models to better operate, analyze and optimize how the grid responds to these challenges.
Network Digital Twins can produce cost reductions of up to 30%, planning time reductions of up to 20% and reduction in new build and internal process costs up to 7%. Companies can also look to field inspection and back office productivity improvements by as much as 8% as well as improved network asset analysis and data accuracy.
Using a combination of operational data from across the network, GE Digital’s ADMS and GIS technologies help grid operators create a Network Digital Twin, which provides a connected view of the end-to-end network of assets, based on real operational data. It includes as-is, to-be, and real-time views of the network and enables all departments to contribute and consume data that help deliver better outcomes. Network Digital Twins allows teams from the control center to the field to make smarter, faster decisions that help to ensure that the lights stay on regardless of the challenges on the ground.
In Australia, Energy Queensland integrated its Advanced Distribution Management Solution (ADMS) and its Geographic Information System (GIS) to deliver a single source of truth across the enterprise. This Network Digital Twin provides a consistent and shared network model representing the as-built and as-operated status of the company’s grid.
Process Digital Twins help manufacturers meet the challenges of fast-changing consumer demand, regulatory requirements and looming generation knowledge gap. Process Digital Twins create models of ‘the best way’ to run a process in a given environment – often referred to as ‘the golden batch’. By identifying the most optimal process to manufacture a given product, plant operators can ensure they are consistently delivering against quality, cost and volume objectives.
Most customers have continuous improvement teams driving initiatives to improve product quality, reduce manufacturing process variation and costs.
And while 90% of manufacturers are already investing or planning to invest in predictive capabilities in the next five years, and 75% are investing in machine learning, Process Digital Twins are very early in their application compared to Network and Asset twins. This is due in part to the high variability of manufacturing processes (equipment, scale, environment, complexity and poor data quality).
Through our CSense Operations Performance Management solutions, GE Digital has already delivered Process Digital Twins in multiple industries, including Mining, Food & Beverage, Oil & Gas and Power Generation, and Water & Wastewater industries.
Competitive Power Ventures (CPV) uses Operations Performance Management (OPM) software to drive significant operational production gains. CPV increased use of the gas turbine’s peak fire service by 10x without impacting its maintenance interval and has improved the accuracy of Day Ahead capacity predictions by 2%. Manual Excel-based processes have been replaced with AI/ Machine Learning algorithms, enabling CPV to compile weather data and plant status to more accurately predict the hourly capacity and heat rate of their plants.
OPM software creates Process Digital Twins of processes and assets to help team members more accurately predict day-ahead and intraday plant capacity and heat rate. This helps CPV to make the most profitable use of that capacity through improved commitment preparation, fuel nomination and dispatch planning.
Digital Twin software is helping industrial companies to adapt to an increasingly challenging landscape, impacted by regulatory, market and technological trends. Today, we are seeing industrial companies move from Digital Twin as a pilot or as a use case to Digital Twin at scale, transforming whole organizations at incredible speed and scale.
We will see the development of easy-to-use tools and out-of-the-box analytics on data, including sensor health, predictive product quality, and batch process control that leverage real world Digital Twin experiences and Digital Lean technologies to drive expected outcomes.
The key is to make sure companies engage with an experienced vendor who can size the technology for that company’s particular application. At GE Digital, we’re investing in making Digital Twins more accessible and more powerful by combining waste elimination concepts from Lean with advanced analytics.
Our Industrial Managed Services team monitors over 7000 assets around the world. See how others in your industry are saving real money in real time with Digital Twin technology and Industrial Managed Services from GE Digital.
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