Impact of Digital Twins on Product Development
Aug 7, 2024
For companies that develop products, digital-twin technologies arrived to accelerate development processes, and enhance product quality. Creating digital replicas of physical products helps companies simulate and refine their designs in a virtual environment, which leads to faster and efficient product development. This article explores the current use of digital twins, their benefits, and the future potential of this impactful technology.
The Market for Digital Twins Grows
Product development is costly and takes a long time. Anything that can speed the process and ensure a better quality is a big pro for any company. The ability to rapidly develop and launch new products is crucial these days, especially with so much competition that is speeding ahead. Over the next five years, approximately $30 trillion in corporate revenues will depend on products that have not yet reached the market. But developing successful new products is a great challenge mainly due to the need for complex integrations, sustainability considerations, and the pressure to minimize R&D costs.
To address the challenges, companies have no other choice than turn to any helpful strategy. Those who can afford it, are turning to digital-product-development technologies, particularly digital twins. Using digital replicas to simulate the characteristics and behaviors of physical products offers an efficient and risk-free way to explore, test, and refine designs.
What is a Digital Twin?
A digital twin is a virtual representation of a product, process, or system, created using digital models that process data from various sources. On the contrary to the traditional simulation methods, digital twins are a more accurate approximation of real objects, because they combine multiple types of models and connect them to the real-world data. This way products can be modified in a virtual space, which has many advantages over physical prototypes.
Key characteristics of digital twins
Varying complexity — Ranges from basic data linking to advanced predictive analytics and automated design refinement.
Scope — It can cover individual components, entire systems, or full products.
Value chain inclusion — Covers engineering, production, and service stages of a product's lifecycle.
Current Applications of Digital Twins
Digital twins are already making a significant impact in various industries, from aerospace to automotive. Companies are leveraging this technology to optimize designs, improve performance, and reduce costs.
Examples of Digital Twin Applications
Automotive — Modeling software and hardware configurations to simulate and refine design improvements before customer delivery.
Industrial Equipment — Developing real-time wear prediction and performance optimization models for turbines.
Aerospace — Using machine-learning-based geometry optimization to enhance weight savings and aerodynamic performance.
Medical Devices — Creating multiphysics models of the human heart to support drug and medical-device development.
Benefits of Digital Twins
The adoption of digital twins offers several key benefits, including:
Risk-free environment – Enables design and engineering teams to explore more design options without the costs associated with physical prototypes.
Better testing and validation – Allows new solutions to be evaluated in lifelike scenarios, including extreme conditions.
Deeper insights – Provides detailed monitoring and analysis of product behavior and interactions.
Real-world data integration – Uses operational data to inform and optimize product designs.
Digital twins have been shown to reduce total development times by 20 to 50 percent and decrease the number of expensive pre-production prototypes needed. Products developed using digital twins also tend to have much fewer quality issues and higher customer satisfaction, which leads to increased sales and revenue from value-added services.
The Phased Adoption Approach
Implementing digital-twin technology can be problematic, mainly in terms of integration into existing IT infrastructure and developing new processes and working practices associated with the twin. A phased approach to adoption can be a solution for companies to navigate the challenge effectively:
1. Competitive intelligence and scoping – Identify available digital-twin solutions and estimate their potential value.
2. Architecture design and software stack definition – Define the necessary software components and design a suitable architecture.
3. Software development capability – Develop the processes and capabilities required to launch the digital-twin platform.
Looking ahead, digital twins are expected to evolve alongside advancements in AI and IoT. Future digital twins may proactively search for new insights, refine their own models using real-world data, and even interact with other digital twins to simulate complex environments. Ultimately, they could become autonomous systems capable of identifying opportunities and suggesting product improvements independently.
Takeaway
Digital twins are revolutionizing product development, enabling companies to create better products faster and at lower costs. As this technology continues to advance, it holds the promise of further transforming industries by offering new ways to innovate, optimize, and deliver value. Embracing digital-twin technology can position companies at the forefront of their markets, driving growth and success in an increasingly competitive landscape.