Businesses can make model-driven decisions using digital twins, which are virtual/digital replicas of physical items like devices, people, processes, or systems.
FREMONT, CA: Digital twin technology is gaining traction. According to a Deloitte report, the global market for digital twins is predicted to rise at a 38 percent compound annual growth rate to reach $16 billion by 2023, accelerated by the expansion of IoT technologies.
A digital twin is a digital representation of a physical entity such as equipment, a person, a process, or a system that enables organizations to make model-driven decisions. Digital twins are transforming how work is done in various industries and for a variety of commercial applications. Understanding those applications enables firms to integrate digital twins into their operations. Consider the following examples of digital twin applications:
A digital twin can assist construction businesses in determining how a building performs in real-time, allowing them to maximize performance and efficiency. The information gathered from the digital twin can be utilized to plan and construct future buildings.
Digital twins can assist healthcare professionals in virtualizing the patient experience to maximize care, cost, and performance. In healthcare, use cases are classified into two categories:
● Enhancing healthcare operations' efficiency
By developing a digital twin of a hospital, operational plans, capacity, personnel, and care models, healthcare professionals can assess the organization's operational success.
● Enhancing the level of individualized care
Additionally, healthcare practitioners and pharmaceutical businesses can employ digital twins to model individuals' genomes, physiological traits, and lifestyles to deliver individualized care, such as different medications for each patient.
The manufacturing industry is the most prevalent application of digital twins. Manufacturing relies on expensive technology that creates a large amount of data, facilitating the creation of digital twins. The following are examples of digital twin applications in manufacturing:
● Development of new products
Engineers can use digital twins to validate the viability of new products before launching. Engineers begin production or refocus their efforts on developing a viable product based on test results.
● Customization of the design
Businesses can use digital twins to create numerous product variants to offer customized products and services to their clients.
● Enhancement of shop floor performance
A digital twin can monitor and analyze end products, allowing engineers to identify which products are defective or perform below expectations.
● Predictive maintenance
Manufacturers use digital twins to forecast potential machine downtime, enabling firms to reduce non-value-adding maintenance procedures and increase total machine efficiency by personnel intervening before a fault occurs.
However, deploying digital twins for predictive maintenance duties is not scalable since they are machine-specific virtual replicas that require expensive data science talent to construct and maintain.