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The Rise of Digital Twins in Manufacturing

Posted by IndustryNet on Tuesday, November 14, 2023

 The Rise of Digital Twins in Manufacturing

Manufacturing is a complex and dynamic process that involves a dazzling range of materials, machines, processes, and environments. To optimize their performance, manufacturers need to understand how these variables interact and affect the quality, efficiency, and sustainability of their products. This is where digital twins come in.

What is a Digital Twin?

A digital twin is a virtual replica of a physical system, such as a product, a production line, or a supply chain, that can simulate its behavior and performance under different conditions. By using data from sensors, simulations, and analytics, a digital twin can provide valuable insights into the current and future state of the system, enabling manufacturers to test, monitor, and improve their operations.

Digital twins are not a new concept, but they have become more powerful and accessible in recent years, thanks to advances in computing, artificial intelligence, and the internet of things.

According to a report by McKinsey, almost 75 percent of companies in advanced industries have already adopted digital-twin technologies that have achieved at least medium levels of complexity.

The global market for digital-twin technologies is expected to grow at about 60 percent annually over the next five years, reaching $73.5 billion by 2027. The concept of digital twins has started to take off, with the market for digital-twin technology and tools growing by 58 percent annually to reach $48 billion by 2026, up from $3.1 billion in 2020.

These statistics suggest that digital twins are becoming increasingly popular and valuable in the manufacturing industry.

Digital Twins in Manufacturing: Tranformative Applications & Real-World Examples

From expediting product development to enhancing product quality, operational efficiency, and even inspiring innovative business models, digital twins are reshaping the industry. Here are just a few benefits of digital twins and manufacturing and how they are being used in the real world. 

Faster and cheaper product development. Digital twins can help manufacturers design and test new products in a virtual environment, reducing the need for physical prototypes and experiments. For example, Raytheon Technologies, an aerospace and US defense technology provider, has been using digital twins to simulate almost every aspect of a missile-interceptor test. The company’s engineering team used artificial intelligence and machine learning to put a Standard Missile-3 Block IIA missile through digital testing ahead of a flight test demonstration.

The company also used digital twins to design a new air-launched cruise missile. The developers of the missile have been flying their digital design 6 million miles every night, generating troves of test data that would be impractical to replicate in the real world. The use of digital twins has enabled Raytheon to find ways to work smarter and faster, and to identify models that are really useful for decision-making.

Improved product quality and reliability. Digital twins can help manufacturers detect and correct defects, errors, and failures in their products before they reach the market or cause problems for customers.

We can look to the stars for one thrilling real-world example of this. Siemens and NASA’s Jet Propulsion Laboratory used a digital twin of the Mars Science Laboratory on the Curiosity rover to solve heat dissipation problems caused by the radioisotope power generator.

Enhanced operational efficiency and flexibility. Digital twins can help manufacturers optimize their production processes, equipment, and resources, as well as adapt to changing customer demands and market conditions.

For instance, Absolut Vodka uses Siemens Digital Industries’ Opcenter to create a dynamic platform as the digital conductor, able to switch to digital control and line configuration of the five production lines running in their facilities. The use of digital twins and a comprehensive automated machine-to-machine communication and control is a crucial factor in enhancing operational efficiency .

New business models and services. Digital twins can help manufacturers create new value propositions and revenue streams for their customers, such as performance-based contracts, predictive maintenance, and personalized offerings.

A great example of this is seen in how Bridgestone, a leading tire manufacturer, has been using digital twins to simulate the performance of its tires using data from actual vehicles. The company has been able to develop a price-per-kilometer service in Europe, which allows fleet managers to pay for tires based on usage rather than upfront costs.

The use of digital twins has enabled Bridgestone to increase product quality, drive efficiency, and increase productivity, leading to much healthier profit and loss accounts. The technology is proving particularly beneficial on OEM programs, helping Bridgestone exchange virtual representations of a product with its automotive partners for analysis and approval.

As digital twins become more widespread and sophisticated, manufacturers will be able to leverage them for more applications and benefits, such as improving sustainability, enhancing customer experience, and fostering innovation. However, to realize the full potential of digital twins, manufacturers will need to overcome some challenges, such as ensuring data quality and security, integrating different systems and platforms, and developing the right skills and capabilities.

Key Considerations for Implementing Digital Twins

Digital twins are a powerful tool for manufacturers to optimize their operations, improve their products, and create new value propositions for their customers. However, implementing digital twins requires careful planning, preparation, and execution to ensure their accuracy, relevance, and value. Here are some key considerations, common pitfalls, and tips for success when implementing digital twins in manufacturing. Next, we’ll take a look at some key considerations when when implementing digital twins in manufacturing.

Defining clear objectives and scope for the digital twin project is essential to ensure that it aligns with the strategic goals and values of the organization. This involves identifying the key performance indicators (KPIs) that the digital twin will measure, monitor, and optimize, as well as the assets, processes, and systems that it will simulate and analyze.

Establishing a cross-functional team that includes experts from different domains, such as engineering, IT, and operations, is critical to ensure that the digital twin project is well-designed, well-implemented, and well-maintained. This team should have a clear understanding of the business requirements, technical capabilities, and operational constraints of the digital twin, as well as the data sources, analytics tools, and simulation models that it will use.

Assessing the technology requirements and capabilities of the digital twin is necessary to ensure that it can handle the complexity, variability, and uncertainty of the manufacturing environment. This involves evaluating the data quality, quantity, and variety of the data sources, as well as the scalability, reliability, and security of the analytics tools and simulation models.

Developing and integrating the digital twin into the existing manufacturing operations management architecture, such as MES, ERP, and PLM systems, is crucial to ensure that it can leverage the data, processes, and workflows of the organization. This involves designing the interfaces, APIs, and protocols that enable the digital twin to communicate, exchange, and synchronize data with other systems.

Monitoring and refining the digital twin over time is essential to ensure that it remains accurate, relevant, and valuable to the organization. This involves validating the data quality, consistency, and completeness of the digital twin, as well as the performance, usability, and accessibility of the analytics tools and simulation models.

Common Pitfalls to Avoid in Digital Twin Implementation

With any new technology implementation, there are pitfalls. One stumbling block is a lack of adequate preparation and planning, leading to fuzzy goals, impractical expectations, and insufficient resources. To sidestep this challenge, it's crucial for manufacturers to clearly define the project's scope, objectives, and requirements. Equally important is establishing the roles, responsibilities, and timelines for the team members.

Another potential snag lies in the realm of insufficient data quality and security. This pitfall may result in incomplete, inaccurate, or biased data, coupled with inadequate cybersecurity measures. Manufacturers can avert this risk by ensuring the reliability, consistency, and relevance of data sources. Additionally, robust measures should be implemented to protect, encrypt, and audit the data.

Poor integration and interoperability present yet another hurdle. This pitfall can manifest as incompatible systems, data silos, and a lack of standards. Manufacturers can steer clear of this obstacle by designing the digital twin to be modular, scalable, and extendable. Leveraging open standards, APIs, and microservices further ensures seamless integration.

Resistance to change and adoption emerges as a fourth potential stumbling block, often rooted in cultural, organizational, and technical barriers. A dearth of training and communication compounds the issue. To navigate this challenge, manufacturers should actively involve the workforce and stakeholders in the digital twin project. Offering comprehensive training, soliciting feedback, and providing incentives are key strategies to encourage a smoother transition and adoption process.

Summing Up

In the modern manufacturing world, digital twins have emerged as a transformative technolgoy, deciphering the complexities of materials, machinery, and processes. Evolving from a concept to a dynamic force, digital twins are set to accelerate product development, fortifying quality, and fostering innovative business models.

As U.S. manufacturing advances, IndustryNet stands as your trusted ally. Discover a vast network of suppliers, streamline your sourcing process, and leverage a platform designed for the future of manufacturing. Search, source & quote for free today!

 

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