How Digital Twin are Reshaping Maintenance Strategies?

In 2002, when Dr. Michael Grieves moved to the University of Michigan, little did he know that he was laying the foundation of a futuristic technology called ‘Digital twining.’

Imagine if you could have a granular view of the maintainable assets; wouldn’t it increase your efficiency? Or, if you have a 24/7 view of your equipment, wouldn’t it augment your preventive maintenance strategies to the next level?

Digital twin technology creates a digital simulation of a physical object. This technology can replicate your physical devices, infrastructures, or assets to monitor their operation. The technology additionally helps you make more informed decisions on when to replace or upgrade parts and reduce downtime by providing notifications for preventative maintenance, thus helping you in more efficient maintenance budget planning.

Digital twin technology can potentially disrupt your management strategies in a better way. How? Let us understand in this article.

Digital Twins Magnifies Predictive Maintenance Efforts

Digital twins help you create virtual replicas of your physical assets and continuously gather real-time data from the embedded sensors. The predictive capability helps schedule maintenance tasks more efficiently, minimizing costs and maximizing asset lifespan. You can utilize this data to have a comprehensive view of your asset’s current condition and also identify anomalies or potential issues.

This technology also enables a shift from traditional scheduled maintenance to condition-based maintenance. Instead of following pre-fixed schedules, your maintenance activities can be triggered automatically based on your asset’s actual condition and performance; hence, you can have a more optimized resource allocation strategy. You will also be able to minimize unnecessary maintenance.

Predictive analytics implies the usage of advanced analytics and machine learning algorithms. When this combination is applied to the data generated by digital twins, it can forecast potential failures more accurately. Hence, your maintenance teams can take proactive measures, such as replacing components or scheduling repairs, before a breakdown occurs.

Predictive maintenance further enables prioritization of tasks based on criticality, resource availability, and urgency of the detected issues, resulting in more efficient use of time and resources. Additionally, addressing issues proactively tends to be less resource-intensive and less expensive than emergency repairs conducted after a breakdown.

With the augmented power of predictive analytics, you can analyze the data collected from the digital twin and detect patterns and trends that indicate when maintenance might be required. Based on the collected insights, the maintenance teams can figure out and address potential problems before they escalate, reducing the likelihood of unplanned downtime.

Digital twins facilitate the collection of historical maintenance data and performance metrics over time. Analyzing this data with the combined assistance of maintenance planning software allows organizations to refine predictive models, improving their accuracy and enhancing their overall maintenance strategies.

Leverage Digital Twin to Monitor and Diagnose Assets Remotely

With the assistance of digital twin technology, your maintenance teams can remotely monitor assets’ performance and diagnose issues without physically inspecting them. Digital twinning technology as they create virtual replicas of your assets, can continuously collect and transmit real-time data through the sensors and IoT (Internet of Things) devices installed in the equipment.

The gathered data can be used to gain a comprehensive view of an asset’s performance and condition, further allowing your teams to monitor it from anywhere in the world. The maintenance team can also analyze the real-time data and compare it against established benchmarks or models; experts can identify potential problems, deviations, or anomalies. With this technology in place, your business will save time and resources by allowing experts to analyze data, identify problems, and even simulate solutions without being on-site.

Remote monitoring, coupled with predictive analytics, enables the identification of patterns or trends that might indicate future issues. Imbibing this proactive approach in your business will enable the responsible teams to anticipate maintenance needs in advance, assess risks, and take preventive actions before problems escalate.

With the capability of conducting remote diagnostics experts can analyze data and provide guidance to on-site personnel, optimizing the allocation of resources. Hence, teams can focus on critical tasks based on the severity and urgency of issues identified through remote monitoring. This not only saves time but also reduces travel costs and minimizes downtime by enabling faster identification and resolution of issues.

You can also use digital twin technology to facilitate collaboration among experts regardless of their physical location. Multiple stakeholders can collaborate, share insights, and collectively work on diagnosing and solving problems through shared access to the virtual replica and real-time data.

Furthermore, the data collected from remote monitoring and diagnostics contributes to ongoing improvements in predictive models and maintenance strategies. Organizations can improve their ability to predict, diagnose, and solve issues effectively by analyzing past data and outcomes. This helps them refine their approach and work more efficiently.

Digital Twin Solution Optimized Performance of Assets:

Organizations can optimize the performance of their assets by analyzing data gathered from the digital twin of the original asset. For example, can simulate different scenarios, tweak parameters, and test changes in the virtual environment before implementing them in the real world. Let us explain it in detail; Digital twins allow for the simulation and testing of different scenarios in a virtual environment.

Maintenance teams can, hence, experiment with adjustments, upgrades, or changes to operational parameters without affecting the physical asset. With this capability, your team can assess the potential impact of modifications on performance before implementing them in reality.

Real-time data collected by digital twins provides comprehensive insights into asset performance. By analyzing this data, maintenance teams can identify inefficiencies, areas for improvement, or deviations from optimal performance. They can then make informed decisions to fine-tune operations and improve overall efficiency.

Advanced algorithms applied to the data from digital twins can optimize asset performance by continuously adjusting operational parameters based on real-time data. These algorithms can fine-tune processes, such as production schedules or energy usage, to maximize efficiency while meeting operational objectives.

Some digital twin systems can employ adaptive control mechanisms. These systems adjust operations in real-time based on changing conditions or demands, ensuring that assets operate at peak efficiency under varying circumstances. Digital twins not only predict maintenance needs but also predict performance trends. By forecasting potential performance issues or bottlenecks, maintenance strategies can proactively address these concerns before they impact operations, ensuring continuous optimization.

Additionally, this technology facilitates a continuous iterative cycle. By constantly analyzing performance data and outcomes, organizations can refine their models, algorithms, and operational strategies to achieve higher performance and efficiency over time.

As facilitated by digital twins, optimized performance leads to better resource utilization. It helps in reducing waste, optimizing energy consumption, improving production output, and maximizing the utilization of assets, ultimately leading to cost savings and improved sustainability.

Streamline Lifecycle Management of Assets with Digital Twin Technology

Digital twins cover the entire lifecycle of an asset, from design and production to operation and maintenance. The technology can have a tremendous influence early in your asset’s lifecycle by assisting in the design and development phases. They virtually enable simulation and testing of various design iterations, which helps create more robust and efficient assets from the outset.

For example, during the production phase, digital twins facilitate real-time monitoring and optimization of manufacturing processes. They ensure that the production aligns with the initially designed parameters, leading to higher-quality products and reducing defects.

Digital twins continue to provide value during the operational phase. By creating virtual replicas of physical assets, they enable real-time monitoring of performance, predictive maintenance, and remote diagnostics, as discussed earlier. This prolongs asset lifespan and ensures optimal operational efficiency.

This technology also provides value during the operational phase. Creating virtual replicas of physical assets enables real-time monitoring of performance, predictive maintenance, and remote diagnostics, as discussed earlier. This prolongs asset lifespan and ensures optimal operational efficiency. Throughout the asset’s life cycle, digital twins help in assessing and mitigating risks. Organizations can proactively implement strategies to reduce risks and enhance asset reliability and safety by simulating scenarios and predicting potential failures or risks.

The data collected and analyzed by digital twins contribute to informed decision-making at every stage of the asset’s life cycle. It allows for data-driven strategies and adjustments to optimize performance, reduce costs, and ensure compliance with regulations. Digital twins support continuous improvement by providing a feedback loop of data and insights. Organizations can use this information to innovate, refine processes, and develop better-performing assets for future life cycles.


According to a study by IBM in 2022, the global digital twin market is expected to grow rapidly and reach a staggering value of USD 73.5 billion by 2027. Hence, we can anticipate that digital twins are already widely used in various industries, and their demand will likely continue increasing in the foreseeable future. As a result, the technology is expected to revolutionize maintenance management strategies in several ways.

Digital technology has prompted maintenance professionals to consider adopting digital transformation in their existing structure. Creating a digital twin model based on digital information can help you make smarter decisions at the right time, increase efficiency, and achieve a high return on investment.

FieldCircle can help you augment your existing maintenance infrastructure with its experienced teams and innovative technology. To know more, get in touch with us today!


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