Product development is a multi-stage, complex process that begins with preliminary design and progresses to the developed product before arriving at the final performance prototype. At each stage, multiple types of research and data analysis such as liquid dynamics, mechanical, thermoelectric, and control systems are used to harden the design elements. The current design method cannot predict the product’s final course of action. Physical development necessitates more time, human effort, space, and money, as well as potentially hazardous environmental consequences.
Modifications to complex products, such as aeronautics equipment, subsequent generations of commercial aircraft, building construction, and software-based vehicles, are difficult to track. A new aspect of managing a tangible product’s smart context is required. So software applications are taking shape in engineering, construction, manufacturing, architecture, and many more industries. Technology like Digital Twin is emerging as a solution to numerous challenges. The worldwide Digital Twin market was worth USD 3.1 billion in 2020, and it anticipates expanding to USD 48.2 billion by 2026. During the forecast period, it is predicted to grow at a CAGR of 58 percent.
A virtual/digital mockup of a physical entity, such as a gadget, person, procedure, or framework, helps businesses prototype decisions. Digital twins transformed the way consumers work across a wide range of industries and business applications. Recognizing those applications can allow the business to integrate digital twins into their processes.
Global manufacturers today work with both physical and virtual products. The link between the two products has yet to be established. Because of digital twins, we can now work with both of them at the same time. More advanced manufacturers can now simulate the manufacturing process digitally.
The Digital Twin Market is based on technology, such as IoT, Blockchain, Machine Learning, Artificial Intelligence, Virtual Reality, Augmented Reality, Mixed Reality, Big Data Analytics, and 5G. Its integration with various IoT sensors and all digital technologies for virtualizing the physical object, results in expanding connectivity. So, the risks of security, compliance, data protection, and regulations must be consider. The incorporation of these technologies makes the Digital Twin a more reliable and consistent technological solution.
Implementation and benefit of the digital twin:
Design and development: Businesses can use digital twins to validate the viability of new products before they are released. Based on the test results, industries begin production or shift their focus to developing a viable product.
Design capabilities: Businesses can use digital twins to create multiple product scenarios in order to provide customized solutions and services to their customers.
Market mapping: A digital twin can be used to evaluate and monitor end-products, assisting companies in determining which products are defective or perform below aspirations.
Machine maintenance: Industries use digital twins to forecast machines’ unplanned downtime, enabling businesses to cut non-value-added maintenance activities to enhance overall machine efficiency by taking action before a failure occurs.
Packaging of product: With the aid of digital twins, businesses can understand that how different packaging conditions affect product delivery and ensure the fastest delivery of the product and minimize the damage to product delivery to the end consumer
Inventory management: A digital twin of a transport system contains data about traffic, road layout, and construction. Companies can design distribution routes and inventory storage locations using this knowledge.
Customer simulations and modeling: Businesses got the solution to improve the customer experience by creating digital twins of customer personas.
The digital twinning process can create an artificial model, or “twin,” of any physical entity in order to accelerate, optimize, and establish the underlying sustainable physical process. It intends to improve operational efficiency and enable predictive maintenance. It also avoids disruptions and lowering operating costs.
A digital twin is a physics-based mathematical model that can predict the behavior of a portion in service under a given array of environmental and operational parameters. Although expert opinion is important in the development of such models, statistics and interpretation approaches are now being used to limit human intervention in the development of physics-based models. Environmental data such as location, configuration, or service records are captured by digital twins, which can then provide observations into everything from development and historical transactions to forecasting repair and maintenance. These models, along with the insights gained from them, form the foundation of a digital twin.
The digital twin is acting as the best solution for the listed challenges:
- Increasing the efficiency with which physical assets and manufacturing processes are operated and maintained
- Obtaining real-time visibility into products in use
- Using a digital thread to connect disparate systems and promote traceability
- Remote monitoring and troubleshooting of equipment
- Virtual tests use to simulate a variety of what-if scenarios.
- Predicting the behaviour of equipment in various environments, conditions, and situations;
- Using digital twins in the design phase to reduce development costs and improve product reliability;
- Clarifying equipment specifications with suppliers and optimizing the final design for production;
- Validating the final product’s quality by comparing it to its digital twin;
- Obtaining performance information and generating usage insights;
- Experimenting with new data without interrupting production or jeopardizing the safety
- Processes are virtually refined prior to implementation.
- Training new employees and minimizing the impact of human error on the physical system
- Preventing downtime through data analysis and monitoring systems.
As a business leader, you’ll discover that if you’re already collecting data from your products, processes, or people, setting up a basic digital twin model requires only a small investment. You may even have improved front-ends and analytical capabilities in place, in addition to the necessary digital thread connecting interconnected data silos. A digital twin is the best option for businesses looking for real-world insights to improve product design. Digital twins use simulation technology of virtual models to discover and estimate the imaginary environment and come up with ways, constantly enhance human’s innovative thinking, and continue to seek optimization and progress, which are the modern manufacturing industry’s innovations.