With the vast possibilities within Industry 4.0, digital twin technology is a tool that can bring the Industry 4.0 vision to life. One of the promising impacts of this technology is in manufacturing medical devices. A digital twin is a digital replica of a physical entity, created using real-time data and advanced simulation models. The gap between physical and digital worlds is reduced providing the path to optimization of design, production and maintenance of medical devices. Through this article we will review the concept of digital twin technology, its impact in the manufacturing of medical devices and the potential benefits and challenges with its implementation. Digital twins represent a growing global marketplace valued at over $8.6 billion in 2022 and forecasted to reach $138 billion by 2030.

Digital Twin Technology

A digital twin is a virtual representation of an object or system designed to reflect a physical object accurately. It spans the object’s lifecycle, is updated from real-time data and uses simulation, machine learning and reasoning to help make decisions. The key components of a digital twin include:

  1. Physical Entity: The physical medical device being replicated.
  2. Digital Model: A virtual representation that simulates the physical entity’s characteristics and behaviors. Advanced CAD/CAM/CAE software such as Siemens NX, Ansys Twin Builder are perfect example tools to assist in designing, simulating, validating and deploying digital twin model.
  3. Data Connectivity: Sensors and IoT devices that collect real-time data from the physical entity. Examples of these devices are temperature sensors, vibration sensors, pressure sensors, etc. Data acquisition systems (DAQ) like National Instruments DAQ systems and software platforms like LabVIEW are commonly used. Microsoft Azure IoT, AWS IoT Core, and Google Cloud IoT are popular cloud platforms used for integrating data from digital twins.
  4. Analytics and Simulation: There are advanced algorithms and models that analyze the data and simulate different scenarios. A digital twin framework can simulate “what-if” scenarios to evaluate the impact of different conditions. For example, they can simulate the effects of changing production parameters or assist with Design of Experiments (DOE). Tools like COMSOL Multiphysics simulate interactions between different physical phenomena (e.g., thermal, electrical, mechanical) to provide a comprehensive understanding of the entity’s behavior.
  5. User Interface: These are the platforms that allow users to interact with the digital twin and extract actionable insights. Platforms that offer 3D Modeling Solutions such as PTC Creo/Siemens NX as well as augmented reality (AR) and virtual reality (VR) technologies are the promising tools to be used as a user interface within the digital twin framework.

Applications of Digital Twin in Manufacturing Medical Devices

Integration of digital twin technology in medical device manufacturing provides potential to improve device performance, optimize production processes and reduce quality defects. Some applications of this framework include:

  1. Predictive Maintenance:
    The digital twin framework can assist in predicting potential failures and maintenance needs of the manufacturing equipment used within the manufacturing process of the respective medical device. For example, injection molding machine is one of the highly used manufacturing equipment within the medical device industry. Symptoms such as slow or erratic machine movements, leaks and/or overheating could predict the need for replacing oil and filters on the hydraulic lines of the injection molding machine.
  2. Design Optimization:
    The digital twin framework can assist in optimizing the design of medical devices by simulating various design iterations and testing their performance virtually. In the design of orthopedic implants, a digital twin can simulate different materials and structural configurations to identify the optimal design that offers the best performance and longevity.
  3. Quality Control:
    The digital twin framework can enable real-time monitoring and analysis of the manufacturing process characteristics resulting in improved quality control. To produce injection molded components, a digital twin can monitor environmental conditions and process parameters. This is currently being done at a machine level in the industry but utilizing this framework, the monitoring can be expanded to multi-process monitoring.
  4. Supply Chain Optimization:
    The digital twin framework can optimize the supply chain by providing real-time visibility into inventory levels, production schedules, delay notification and demand forecasts. In the production of disposable medical devices, a digital twin can help manage raw material inventories, track production progress, and predict future demand, ensuring efficient just-in-time (JIT) deliveries/shipments.
  5. Regulatory Compliance:
    The digital twin framework can reduce the time and cost associated with clinical trials and regulatory approvals by simulating regulatory testing environments and reviews. Medical device manufacturers can use this framework to simulate the performance of a new device under various conditions, ensuring compliance with safety standards such as IEC 60601 before the device undergoes physical testing and regulatory review.

Benefits of Digital Twin Technology in Manufacturing of Medical Devices

The adoption of digital twin technology in the manufacturing of medical devices brings several advantages that can revolutionize the MedTech Industry:

  1. Improved Reliability and Safety:
    Continuous monitoring and predictive analytics ensures that manufacturing equipment/medical device operates reliably, reducing the risk of malfunctions and improving product safety.
  2. Cost Efficiency:
    Predictive maintenance and optimized production processes lowers operational costs, reducing the cost of the medical devices, which will eventually benefit the hospitals and patients.
  3. Improved Product Quality:
    Real-time monitoring and quality control ensures that medical devices meet high standards, leading to better patient outcomes and higher satisfaction.
  4. Streamlined Operations:
    Digital twins facilitate efficient resource management, reducing downtime and improving the overall efficiency of manufacturing facilities.
  5. Accelerated Innovation:
    By providing a virtual testing environment, digital twins accelerate the development and deployment of new medical devices and therapies, fostering innovation in the MedTech Industry.

Challenges

With the potential to positively impact medical device manufacturing leveraging the digital twin framework, there are several significant risks to be overcome:

  1. Data Security and Privacy:
    The collection and transmission of sensitive manufacturing data raises concerns about data security and intellectual property protection. Robust cybersecurity measures and strict compliance with data protection regulations such as General Data Protection Regulation (GDPR) and California Consumer Privacy ACT (CCPA) are essential. Multi-factor authentication (MFA), Role-based access control (RBAC), AES (Advanced Encryption Standard) etc., are some of the tools that can be used to ensure data security.
  2. Interoperability:
    Ensuring seamless integration and communication between different manufacturing systems, digital platforms, and supply chains is critical for the effective implementation of digital twins. By adopting open standards such as Open Platform Communications Unified Architecture (OPC UA) and utilizing Application Programming Interfaces (APIs)/ Software Development Kits (SDKs), manufacturers can create a cohesive digital twin framework that results in efficiency and innovation.
  3. Complexity and Cost:
    Developing and maintaining digital twins can be complex and costly, requiring significant investment in technology, infrastructure, and expertise. This caters from the complexity of bringing several systems together and their cost such as sensors/IoT devices, simulation tools, cloud platforms, technical experts, etc. There will be significant initial development cost and then recurring maintenance cost.
  4. Regulatory Hurdles:
    Navigating the regulatory landscape for digital twin technology in medical device manufacturing can be challenging, with stringent requirements for validation, safety, and efficacy. U.S. FDA (Food and Drug Administration) and EMA (European Medicines Agency) are some of the regulatory agencies which will need to be engaged by the medical device manufacturers and work together to explore the guidance on incorporating the digital twin framework into the regulatory approval process.
  5. Standardization:
    Establishing industry-wide standards for digital twin development and implementation is necessary to ensure consistency and interoperability across different systems and applications. ISO/TC 184 technical committee, within the International Organization of Standardization (ISO), is actively leading the standardization efforts for digital twins. ISO 23247 is the series of standards that has been developed with the goal of providing guidance on digital twin framework. This series of standards was published in 2021.

Conclusion

The digital twin framework is a revolutionizing concept that will change several industrial verticals including medical device manufacturing. Utilizing digital replicas of physical entities, this framework will facilitate predictive maintenance, optimization of designs, quality control, supply chain optimization, etc. These improvements will then result in improved reliability/safety, reduced costs, improved product quality, etc. As this framework evolves, several challenges such as data security and standardization will need to be addressed head on.