A Deep Dive into Product Digital Twin Development

Custom product digital twin development offers a practical solution, optimizing operations, enhancing decision-making, and improving product performance through real-time data analysis and predictive capabilities. These virtual replicas provide a faster, simpler, and safer alternative to real-world manipulation than the traditional "create first, then optimize" approach. 

 

The Onix team recently developed a digital twin of a flashlight to enhance its presentation on our client's website. 

 

In this article, our experts share valuable insights from hands-on experience building a digital twin.

 

Continue reading for:

 

• clear explanations of complex concepts
• practical advice for digital twin product development
• case studies showcasing successful product digital twin applications
• inspiration for innovation and optimization in your projects.

Example of how Onix created a digital twin of a flashlight

Business Opportunities and Use Cases of Product Digital Twins

You might wonder, "Why should I invest in digital twin development?" We'll help you answer this question by explaining the business opportunities various types of digital twins offer across industries and demonstrating how they can be implemented.

 

Manufacturing

A digital twin in manufacturing offers a powerful tool for optimizing operations, improving quality, and driving innovation.

 

Notably, the manufacturing sector dominates the global digital twin market.

By leveraging this technology effectively, manufacturers can enhance productivity, reduce costs, and gain a competitive edge in the marketplace.

 

• Predictive maintenance. By creating a digital twin of manufacturing equipment, machinery, or factories, manufacturers can predict potential failures, schedule proactive maintenance, and minimize unplanned downtime by monitoring key performance indicators and analyzing real-time sensor data.

 

The tech giant Siemens utilized digital twin software development to establish a smart factory at its Chinese subsidiary. Leveraging real-time data from assembly lines, Siemens devised strategies to eliminate production constraints and optimize resource usage.

 

Through digital flow and layout optimization, SNC enhanced machine utilization rates, reduced space requirements by 40% for the same output compared to the old factory, and avoided the need for a second production line investment.

 Siemens’ digital native factory in Nanjing, China

 

Yu Rong Zhou, General Manager of Siemens Numerical Control, remarked, "This digital factory is truly advancing our digital transformation efforts. We've reduced time to market by 200% and expanded manufacturing capacity by 200%, boosting productivity by 20%."

 

• Process optimization. Digital twin creation allows manufacturers to simulate manufacturing processes, optimize workflows, reduce cycle times, and increase productivity by analyzing virtual production line models. This streamlines operations, minimizes waste, and maximizes output.

 

• Remote monitoring and control. Manufacturers can access virtual replicas of their facilities from anywhere in the world, enabling them to monitor production in real-time, diagnose issues remotely, and make adjustments to optimize performance and efficiency.

 

The leading manufacturing company Kaeser transitioned from offering air compression devices to delivering a comprehensive service encompassing installation, maintenance, and monitoring of their products. This transformation was driven by leveraging digital twin technology.

 

Among their notable accomplishments, Kaeser monitored their device's lifecycle and performance, leading to product enhancement and service optimization.

 

Additionally, this technology enabled a strategic shift in their pricing model from product-based charges to energy usage-based fees, resulting in a 30% reduction in commodity costs and the adoption of digital twins by nearly half of all major vendors.

 

E-commerce

By leveraging digital twin technology, e-commerce companies can stay ahead of the competition, enhance the shopping experience, and drive business growth in a rapidly evolving digital world.

 

• Personalized product recommendations. Implementing digital twins to create virtual replicas of customer preferences and behaviors. E-commerce platforms can analyze these virtual models to generate personalized product recommendations based on individual shopping histories, preferences, and browsing patterns.

 

This enhances the shopping experience, increases customer engagement, and drives sales.

 

• A more comprehensive view of your product. Enhance customer engagement by integrating 3D visualizations into your marketing approach, offering a dynamic and immersive view of your products. This enables customers to interact with your offerings from various angles, enhancing their understanding and appreciation of your products.

 

Recently, Onix transformed a client's product presentation on their website, enhancing engagement and effectiveness. 

 

Our team developed a captivating 3D animation to bring the product to life. We proposed to create a scene that would go beyond conventional approaches and utilize visual storytelling techniques to convey a compelling message about the product's exceptional quality.

Illustration of Onix's creation of a digital twin for a flashlight

 

• Supply chain optimization. E-commerce companies can create virtual representations of their warehouses, distribution centers, and transportation networks to visualize the entire supply chain in real-time. This enables them to improve inventory management, reduce shipping costs, and ensure timely delivery of products to customers.

 

Healthcare

The healthcare digital twins market is expected to expand at a CAGR of 25.6% from 2023 to 2030, reaching a significant global scale.

Digital twins allow the healthcare industry to transform patient care, drive innovation, and improve operational efficiency. By harnessing this technology effectively, healthcare providers can deliver higher quality care, reduce costs, and enhance patient healthcare experience.

 

• Comprehensive medical research. In medical research, digital twin technology simulates scenarios economically and safely before real-life testing. This aids in identifying illness patterns, modeling therapy effects, and pinpointing areas for further study in living subjects. 

 

Researchers compare medical twins created through digital twin technology to assess treatment options for individuals with similar characteristics, aiding in identifying biological indicators for disorders.

Source: MDPI

 

• Medical device development and testing. Using digital twins to simulate medical device performance allows manufacturers to virtually test prototypes, analyze functionality, and detect design flaws or performance issues before physical testing. This speeds up development, cuts costs, and ensures device safety and efficacy.

 

Read also: Implementing VR & AR in Medicine and Medical Training

 

• Drug discovery and development. Pharmaceutical companies can use virtual models to predict drug effectiveness, identify potential side effects, and optimize drug formulations. This speeds up the drug discovery process, reduces the need for costly clinical trials, and brings new treatments to market more quickly.

 

Recognizing the growing demand for drugs and vaccines, Atos, GlaxoSmithKline, and Siemens have partnered to revolutionize pharmaceutical manufacturing.

 

Traditionally, pharmaceutical companies assessed product quality post-production, risking wastage if standards weren't met. Digital twins enable real-time quality evaluation during manufacturing, facilitating immediate operational adjustments to maintain standards.

 

This collaboration allowed Atos to implement a digital twin to monitor each stage of the vaccine manufacturing process. This digital twin significantly enhanced product quality, reduced costs, and shortened time to market. The pharmaceutical company can also simulate production changes and assess their impact on the final product.

Digital twin for pharmaceutical manufacturing

 

Retail

Digital twins offer immense potential for retailers to optimize operations, improve efficiency, and enhance the customer experience.

 

• Better and faster shopping experience. Through digital twins, retailers can create virtual replicas of their physical stores, enabling them to optimize layout designs, product placements, and customer flow.

 

By analyzing data collected from sensors, cameras, and other IoT devices embedded in the store environment, retailers can identify customer preferences, predict shopping patterns, and personalize the shopping journey. 

 

Kroger, the largest grocery chain in the United States, partners with Nvidia to incorporate digital twins into its operations.

 

Utilizing simulation and digital twins, they revolutionize the in-store shopping experience by creating a precise digital replica of their physical stores, enabling real-time synchronization.

 

Kroger’s partnership to integrate digital twins in retail stores has allowed stores to:

 

• overcome in-store challenges such as shrinkage and labor loss
• reduce customer friction and stock losses at self-service checkouts 
• optimize customer shopping experiences
• operate efficiently 

 

 

• Product placement and merchandising. Retailers can analyze customer behavior and preferences to strategically place products for maximum visibility and appeal, ultimately driving sales and revenue.

 

Lowe’s, a leading American home goods retailer, has introduced the concept of "virtual stores" — digital replicas of physical shops. These stores utilize AI avatars created from historical data to estimate walking distances for frequently purchased items.

 

This aids employees in optimizing product placement to enhance the customer and associate experience.

 

 

• Customer personalization. Retailers can create virtual profiles of customers based on their purchase history, preferences, and demographics. This data allows for personalized marketing, product recommendations, and tailored promotions, enhancing customer loyalty.

 

L’Oréal integrated scannable QR codes into its products, linking consumers to digital twins for comprehensive information and enhanced experiences.

 

These QR codes, now present on cosmetic items, offer customers detailed insights directly on their smartphones, eliminating the need for customer service assistance. Users can conveniently access information such as product ingredients, visual representation of results, and usage tutorials.

 

 

Automotive

Digital twins offer the automotive industry a powerful tool for driving innovation, improving efficiency, and enhancing vehicle quality and performance:

 

• Vehicle design and prototyping. Using digital twins to create virtual replicas of vehicle designs and components allows automotive engineers to simulate design iterations, test aerodynamics, and analyze performance virtually before physical prototyping. This accelerates design, cuts development costs, and enhances vehicle performance.

 

Volvo Trucks North America utilized virtual experience digital twin technology to enhance their baseline model's aerodynamic design significantly.

 

By employing virtual 3D design and multi-physics CFD simulation, they could conduct extensive experimentation in a "Digital Wind Tunnel," testing thousands of variations in a fraction of the time and cost required for physical prototypes.

 

Ultimately, they achieved:

 

• a 40% reduction in overall aerodynamic drag, resulting in a 20% improvement in fuel economy.

 

• downsizing the engine from a 13L 485HP to an 11L 425HP model reduced vehicle weight and decreased engine cooling demands, leading to further efficiency gains and a more streamlined vehicle design.

 

Volvo trucks analysis

 

• Predictive maintenance. Creating digital twins of vehicle components and systems enables proactive maintenance by analyzing real-time sensor data to predict potential failures. This minimizes unplanned downtime and allows automotive manufacturers and service providers to schedule maintenance proactively.

 

For instance, BMW utilizes a Digital Vehicle File to track each car's lifespan, detailing every component and any changes made during production or servicing. This comprehensive record enables predictive maintenance, comparing component age and mileage to fleet-wide data to anticipate and address potential failures proactively.

An example of BMW's Digital Vehicle File that generates a digital twin for its vehicles.

 

• Connected car technologies. Automotive companies can create virtual models of vehicles and their onboard systems to simulate connectivity features, such as infotainment systems, telematics, and vehicle-to-vehicle communication. This allows them to optimize user experiences, ensure interoperability, and enhance vehicle safety and functionality.

 

Aviation

By leveraging digital twin technology, aerospace companies can enhance aircraft design, manufacturing, maintenance, and operations, ultimately improving safety, reliability, and cost-effectiveness in the aviation sector.

 

• Aircraft design and prototyping. Aerospace engineers can simulate different design configurations, test aerodynamics, and analyze performance virtually before physical prototyping. This enables them to accelerate the design process, reduce development costs, and optimize aircraft performance.

 

How the Digital Twin helps the aerospace industry soar

 

Boeing was among the pioneers in aerospace to adopt Digital Twins, leveraging the technology to enhance the quality and safety of their commercial and military aircraft. This innovation has notably boosted the first-time quality of aircraft parts and systems by 40% during production.

 

• Predictive maintenance. Creating digital twins of aircraft components and systems to monitor performance and predict maintenance needs. Aerospace companies can analyze real-time data from sensors embedded in aircraft to identify potential failures before they occur. 

 

This enables proactive maintenance scheduling, minimizes unplanned downtime, and enhances aircraft reliability and safety.

 

For example, Airbus employs digital twins to simulate and optimize numerous aircraft design and production aspects. Utilizing predictive models derived from real-time sensor data collected across the production line aids in forecasting the production process and preemptively identifying potential issues.

 

Through digital twin simulation, Airbus 

 

• can simulate 120,000 failures and their ramifications to determine the ideal replacement age. For instance, they discovered that one of their machines could run much longer in production than previously expected.

 

• has set the groundwork for their new approach, with 80% of decisions now data-driven.

 

• predicts a potential 15% decrease in their overall costs.

A digital twin of an aircraft (Image credit)

 

• Efficient airport operations. Digital twins can simulate the layout of terminals, runways, taxiways, and other facilities to identify bottlenecks, optimize traffic flow, and improve passenger experience.

 

For example, digital twins can analyze passenger movement patterns to determine the most efficient layout for security checkpoints, gates, and boarding areas, thereby reducing congestion and wait times.

 

Furthermore, digital twins can optimize airspace utilization, reduce flight delays, and enhance safety by simulating air traffic patterns, weather conditions, and aircraft movements.

 

Digital twin for airports

 

Energy 

Digital twins provide the energy industry with a powerful tool to boost asset performance, optimize resource utilization, and address the increasing need for sustainable and dependable energy solutions.

 

• Asset performance monitoring and maintenance. Creating digital twins of energy infrastructure assets such as power plants, wind turbines, and solar farms. Energy companies can monitor the performance of these assets in real-time, analyze operational data, and predict maintenance needs.

 

This enables proactive maintenance scheduling, minimizes downtime, and extends the lifespan of critical assets.

 

GE is a world energy leader providing equipment, solutions, and services across the energy value chain from generation to consumption. They created a 3D virtual model of the Haliade 150-6 wind turbine's rotary engines, allowing employees to monitor internal currents and predict motor temperatures.

 

 

This custom digital twin development enables GE to assess machine efficiency and optimize engine speed adjustments.

 

• Grid optimization and management. Energy utilities can create virtual replicas of power grids to analyze grid performance, predict demand fluctuations, and identify potential congestion points. This allows them to optimize grid operations, improve reliability, and ensure efficient energy delivery to consumers.

 

• Renewable energy resource assessment. Energy companies can create virtual models of geographical regions to simulate wind patterns, solar radiation, and other environmental factors. This enables them to identify optimal locations for deploying renewable energy projects, maximize energy generation, and optimize resource utilization.

 

How to Build a Digital Twin: Tips from Onix Experts

The Onix team combines extensive AR and VR experience with strong ML and 3D modeling skills to turn your digital twin concept into a high-quality solution.

 

In this section, our team is excited to share our firsthand experience with this technology and provide valuable insights on how to implement a digital twin effectively.

 

Identify the type of digital twin

Digital twins can be broken down into three broad types of digital twins:

 

1. Product twin

A product twin is a digital representation of a physical product, mirroring its design, structure, and behavior. It allows for virtual testing, analysis, and optimization throughout the product lifecycle.

 

2. Process twin

A process twin is a digital model of an industrial process or system, providing real-time monitoring, analysis, and optimization capabilities. It replicates materials, energy, and information flow within a production environment.

 

3. System twin

A system twin is a holistic digital replica of an entire system comprising interconnected components, processes, and entities. It represents the dynamic interactions and dependencies within complex infrastructures.

 

Types of Digital Twins

 

Evaluate process enhancement opportunities for your business

During this phase, it's crucial to determine the scope of your digital twin solution. 

 

We prepared a list of the key questions that will help you at this stage:

 

• Are you replicating an entire system or device, or just specific components?
• Will your employees or end users be responsible for operating the digital twin?
• Will users access it remotely or on-site?
• Which functions do you plan to replicate within the digital twin?

 

By the end of this assessment, you should clearly understand the desired functionality of the digital twin platform and the objectives you aim to accomplish.

 

 

Select the right technology stack

When selecting the right technology for digital twin product design, we consider such factors as:

 

• scalability to support future growth
• data exchange and interoperability
• robust data management capabilities
• built-in security features to protect sensitive product data
• advanced analytics and AI capabilities
• intuitive visualization tools (Unity, Houdini, Blender)
• compatibility with a wide range of sensors and IoT devices

 

Creating digital twin solutions involves leveraging cloud computing, data analytics, and IoT.  As a digital twin development company, our technical experts place particular emphasis on the following technologies:

 

Cloud computing

Cloud computing enables organizations to store and process large volumes of data efficiently, which would be challenging to manage on-premises. Digital twin data is securely stored in the cloud and accessed from anywhere.

 

Onix offers comprehensive cloud computing services, including consulting, migration, and data engineering. Our technology stack includes:

 

• Database building: Microsoft SQL Server, MySQL, PostgreSQL, MongoDB, Redis, Azure Cosmos DB, Azure Table Storage, Amazon DynamoDB.

 

• Infrastructure services: Amazon Web Services, Microsoft Azure, Google Cloud Platform, Docker, Kubernetes, Firebase.

 

• Web backend: Node.js, ASP.NET, Java, Django/Python.

 

• Frontend development: HTML/CSS, JavaScript & jQuery, TypeScript, React/Vue, A-Frame.

 

Data Collection & Analytics

Digital twin development requires capturing, storing, and analyzing vast amounts of data to create synchronous simulations and predict object behavior. Data analytics algorithms are essential for deriving insights from raw data, which decision-makers should understand.

 

Our experts leverage 2D and 3D visualizations and immersive technologies to create visual data representations for informed decision-making. Our tech stack includes the following:

 

• 3D engines: Unity, PlayCanvas, Babylon.js, three.js.

 

• Desktop and standalone VR kits: Steam VR, HTC Vive, Oculus VR, Windows Mixed Reality.

 

• Mobile VR experiences: Google VR.

 

• Mobile AR: Apple AR Kit, Google AR, CoreVuforia.

 

IoT Sensors

IoT plays a crucial role in creating digital simulations by connecting objects to sensors. These sensors capture performance data, which is then processed by AI and ML algorithms. The insights derived are presented in a user-friendly visual format.

 

• Languages: Python, MATLAB.

 

• Frameworks: TensorFlow, PyTorch, SciKit-Learn, SciPy.

 

• Algorithms: Supervised Learning, Unsupervised Learning, Statistical Learning, Deep Learning, Clustering.

 

• Visualization. Seaborn, Pillow, Matplotlib, Keras, Fastai.

 

Data collection

When building a digital twin, data collection is crucial for accurately replicating and simulating the behavior of the physical asset or system. 

 

Below, our experts share some ways of how they gather data effectively:

 

• Identify key parameters. We determine the critical parameters that influence the operation and performance of the physical asset or system. This may include temperature, pressure, speed, vibration, energy consumption, and environmental conditions.

 

• Utilize sensors. Our experts install sensors strategically to capture real-time data on the identified parameters. Sensors can range from simple temperature or pressure sensors to more complex sensors like accelerometers, flow meters, or cameras, depending on the nature of the asset.

 

• IoT integration. IoT devices enable connectivity and communication between sensors and the digital twin platform, allowing for seamless data transfer and analysis.

 

• Data logging. We implement data logging mechanisms to record historical data over time. This historical data provides valuable insights into trends, patterns, and anomalies, essential for predictive maintenance and optimization.

 

• Remote monitoring. Our specialists enable remote monitoring capabilities to access real-time data from the physical asset or system, regardless of location.

 

• Data fusion. Data fusion integrates information from sensors, historical records, external databases, and other relevant sources to view the asset or system comprehensively.

 

• Privacy and security. We ensure data privacy and security measures are in place to protect sensitive information collected from the physical asset or system. Implement encryption, access controls, and other security protocols to safeguard data integrity and confidentiality.

 

Developing the digital twin

Leveraging the gathered data, our software engineers build a virtual representation of the product, carefully mirroring its structure and functionality. This digital replica incorporates all collected sensor data and faithfully reproduces not just the physical layout of the product but also its operational behavior and efficiency.

 

The model can simulate external factors like environmental variables or market demands in more sophisticated setups.

 

Establish a data governance framework

We recommend establishing a robust data governance framework to manage data within the digital twin environment, ensuring integrity, security, and compliance throughout the data lifecycle.

 

Below, our experts share some essential steps to do it:

 

• Data ownership. Identify stakeholders responsible for collecting, managing, and using the data throughout its lifecycle.

 

• Data policies and standards. Create comprehensive data policies and standards outlining how data should be collected, stored, processed, and shared within the digital twin environment.

 

• Data security measures. Implement robust data security measures to safeguard sensitive information from unauthorized access, breaches, or cyber threats.

 

• Data lifecycle management. Define clear guidelines for managing the lifecycle of data within the digital twin, including data acquisition, storage, processing, analysis, archival, and disposal.

 

• Data sharing and collaboration. Enable secure data sharing and collaboration among authorized users and stakeholders within the digital twin ecosystem.

 

Choose the required archetypes for integrating digital twin technology

• Separate business unit. It is solely dedicated to creating a distinct portfolio of digital assets alongside physical ones. 

 

• Existing business unit. Integrating the digital-twin team into an existing business unit allows for developing and maintaining digital-twin applications associated with its products. This approach is suitable for gaining experience with digital twins or in cases of limited synergies between units.

 

• Separate center. Lastly, the digital-twin team can function as a separate center of excellence, supporting application development across existing business units, and enabling rapid scaling with consistent processes and technology components.

 

Read more: Best practices for outsourcing software development

 

 

Onix's Experience in Digital Twin Development

Our client sought to strengthen their online presence in the professional and extreme enthusiast lighting niche. 

 

Traditional methods failed to convey the lights' unique advantages, features, and quality. So, we delivered 3D rendering and modeling services based on the existing light design, creating precise digital representations for various purposes, including visualization and marketing.

 

We offered the following solutions:

 

• Comprehensive 3D modeling. Our team carefully recreated each component and detail of the lights in a virtual environment, ensuring precise accuracy and fidelity to the original design.

 

• Realistic texture selection. We chose realistic textures to enhance the visual fidelity of the lights in our 3D modeling and rendering process.

 

• Dynamic 3D animation. We created a captivating 3D animation to breathe life into the product, showcasing its durability and strength through dynamic sequences.

 

• Visual metaphor. We employed a visual metaphor of the ground crumbling beneath the flashlight, symbolizing its sturdiness and resilience, thus compellingly showcasing its exceptional quality.

Example of how Onix created a digital twin of a flashlight

 

As a result, the digital twin solution set the product apart in the market, driving increased interest and interaction from clients and end-users.

 

 

Conclusion

Product digital twins offer many business opportunities across industries, from optimizing manufacturing processes to enhancing retail experiences and revolutionizing healthcare.

 

By effectively leveraging digital twin technology, businesses can expedite development processes, improve product outcomes, and drive growth.

 

To maximize the benefits of digital twins, it's essential to approach development with clear objectives, utilize appropriate tools and resources, and continually iterate based on feedback and insights.

 

With the right approach, digital twins can become invaluable tools for businesses seeking to stay competitive and meet the evolving needs of their customers.

 

FAQ

 

Who needs to be part of the team to develop digital twins?

To develop reliable digital twins, a team typically requires professionals with expertise in software development, data analytics, IoT integration, and specialists in 3D modeling and simulation.

 

However, since each project is unique, all specifics and details are typically addressed during the initial client consultation.

 

What are Onix's areas of expertise in digital twin development?

Onix specializes in digital twin development across various industries, offering expertise in:

 

• Creating highly accurate virtual models of physical assets or systems.
• Integrating IoT sensors and data analytics for real-time monitoring and analysis.
• Implementing advanced visualization techniques for immersive user experiences.
• Developing predictive maintenance algorithms for optimizing asset performance.
• Providing end-to-end solutions, from data collection to model deployment and maintenance.

 

What is the digital twin development cost?

The cost of digital twin development can vary widely depending on complexity, scale, and customization requirements. Small-scale projects may start at a few thousand dollars, while more complex implementations can range into the millions.