92% of enterprises are stuck halfway: Why is it difficult to implement digital twin?
Most enterprises mistakenly regard digital twin as "3D graphic presentation", while in fact it is a virtual "digital life form".
In high - complexity manufacturing industries such as aerospace, automotive, and consumer electronics, digital twin is evolving from a technological concept to a core competency. It is regarded as a key means to address the challenges of increasing product complexity, faster market launch, intelligent upgrading, global supply chain competition, and sustainable development pressure.
However, there is a huge gap between the ideal and the reality. Many enterprises misunderstand digital twin as 3D modeling or graphic visualization, with isolated systems and fragmented data, making it difficult to support the closed - loop collaboration from design to manufacturing and then to operation and maintenance. According to research data from the Digital Twin Consortium, only about 8% of global enterprises have achieved the in - depth integration of digital twin in product lifecycle, production processes, and performance analysis. 92% of enterprises still remain in the "partial visualization" stage and have difficulty in releasing systematic value.
A fundamental question then emerges: Why can't digital twin form a complete picture?
8% Breakthrough and 92% Predicament
In a traditional shipyard, the information fragmentation between complex processes and links has long troubled the entire enterprise. For example, during the design stage, designers build ship plans through 3D modeling, but what is delivered to the shipyard is 2D drawings. The drawings are converted into 3D models again before construction for hull structure planning and then restored to 2D drawings at the production front - line for workers to operate. When a new ship is delivered, the customer still receives a paper manual, even though these materials are enough to fill a truck.
In order to completely break this inefficient and fragmented model, the shipyard decided to introduce a digital twin system based on a "single platform" to achieve a high - degree coupling of people, processes, and information. In this system, the design, simulation, manufacturing, and delivery stages are organically connected. Any change in one link can be transmitted to the downstream in real - time. All participants "contribute" to a single digital model, breaking the barrier of "inconsistent language" and forming a dynamic closed - loop of simultaneous design, construction, and experience.
Digital twin maps real - world objects, systems, and processes into the virtual space through digital technology to generate an interactive and evolvable "digital clone". It significantly reduces repetitive labor and improves collaboration efficiency through "linking the real and virtual", and gives rise to a deeper - level "shift - left engineering" revolution.
Problems are often found in the later stage of traditional manufacturing processes, leading to rework, delays, and a sharp increase in costs. Through digital twin, engineering verification is "advanced" to the early design stage. Thousands of performance tests and process verifications can be completed in the virtual world, potential risks can be identified and corrected in the early stage, and the high cost of physical trial - and - error can be avoided.
From aerospace, consumer electronics to the automotive industry, digital twin is becoming the "cornerstone" of high - complexity manufacturing industries. For example, JetZero uses it to verify the next - generation blended - wing - body aircraft, and the Oracle Red Bull F1 team uses it to adjust racing car parameters in real - time. It is not just an efficiency tool for a single link but a systematic platform that supports organizational change and innovation capabilities.
However, as shown by the "8% and 92%" contrast in the research data of the Digital Twin Consortium, behind it lies the structural challenges that enterprises face in the implementation process of digital twin.
Most enterprises mistakenly regard digital twin as an "advanced presentation of 3D graphics" rather than a "digital life form" that encompasses design, simulation, verification, optimization, manufacturing, and service, where the real and virtual coexist. The real comprehensive digital twin is a self - evolving closed - loop system that can continuously absorb real data and drive business evolution throughout the entire lifecycle.
Take Siemens' Nanjing factory as an example. Its planning and construction process was completed in the digital twin. Through the simulation engine, the team pre - rehearsed multiple extreme scenarios and completed multiple rounds of verification and optimization of the factory layout, process flow, and data flow path in the virtual space. After the factory was put into operation, all operation data was fed back to the twin in real - time for continuous adjustment and performance improvement, truly building an "intelligent nervous system" for the factory.
As pointed out by the Harvard Business Review: "The closed - loop optimization ability is the core value anchor point of industrial digital transformation." And comprehensive digital twin is the embodiment of this ability.
The key to promoting this closed - loop system lies not in the deployment of a single tool but in connecting the "system breakpoints" between design (CAD), management (PLM), manufacturing execution (MES), and enterprise resources (ERP) to build a "digital thread" with unified logic and connected data. Due to the high requirements for system capabilities and the large collaboration threshold, most enterprises have difficulty in breaking through the local pilot stage and stop at "tool stacking".
Why Can't It Form a Complete Picture?
The essence of comprehensive digital twin is not "tool stacking" but the reshaping of the system architecture. If an enterprise wants to truly enter the digital twin stage, it must first answer a question: Why can't it form a complete picture?
In real - world enterprises, the decentralized management of multi - domain bills of materials (BOM) is serious. Design BOM, engineering BOM, and manufacturing BOM operate independently. Mechanical, electrical, and software teams use different tools and formats, and it is difficult to connect the systems. Data dispersion, frequent conversion of multiple formats, manual synchronization, and lack of traceability lead to information lag, error accumulation, and even induce design defects and compliance risks.
More importantly, the isolated architecture suppresses advanced technologies such as AI and machine learning that require large - scale data to be effective, blocking the path for enterprises to achieve high - level intelligence.
Siemens' solution is to build a data "neural network" that runs through the entire product lifecycle - the digital thread. It integrates tools, data, processes, and systems, connects the upstream and downstream of design, simulation, manufacturing, and service, and allows them to flow and "coexist" on the same main line. The engineering team can share and call core data on a unified platform, changes are synchronized in real - time, and simulation and decision - making are based on global insights.
The digital thread is not just a simple data pipeline but a platform - level capability. Teamcenter, as the core platform of Siemens' digital thread, is equivalent to the enterprise's "collaboration brain".
During the conceptual design and analysis stage, it supports parallel development in multiple fields such as mechanical, electrical, and software, and can maintain precise linkage through the key data alignment mechanism.
The multi - domain engineering bill of materials (EBOM) is the core hub of the digital thread. Although engineers are responsible for product design, the complete definition and specification of the product are finally solidified in the EBOM. Therefore, the EBOM is usually the largest, most user - intensive, and most complex system within the enterprise. By seamlessly integrating the EBOM data flow into the product lifecycle management (PLM) system, the enterprise establishes a complete and unified product definition, ensuring that every configuration and change can be traced and audited.
The digital thread also extends to the manufacturing and service stages. Seamless collaboration can be achieved between engineering, manufacturing, process planning, and service, and changes are automatically synchronized.
This concept has been verified in the practice of OPmobility. The company customized Teamcenter as the backbone system for its product lifecycle management. Félicie Burelle, the managing director of the company, said: "We used Siemens Teamcenter X to deploy a standardized and unified PLM solution in our global R & D network. It not only helps improve team efficiency and results but also speeds up the product launch time, which is beneficial to both OPmobility's products and customers."
It is precisely because of this systematic ability that Siemens won the 2023 Digital Twin Technology Leadership Award from Frost & Sullivan. The organization pointed out that "Siemens provides a truly comprehensive approach by connecting traditional isolated product and production processes through an integrated digital thread", and this is Siemens' "ultimate weapon" in leading the digital twin field.
Reshaping the Manufacturing Paradigm
The digital thread opens up the data path for comprehensive digital twin and eliminates system fragmentation, but it alone is not enough. To convert data into business value, enterprises also need an "execution engine" to carry the entire process of model building, simulation, testing, and feedback. Simcenter is Siemens' key layout in this regard.
As the core platform of Siemens' comprehensive digital twin, Simcenter deeply integrates engineering simulation, performance prediction, and virtual verification, enabling products to have the "behavior pre - rehearsal ability" that is precise and controllable from the very beginning of design.
With Simcenter, based on the data opened up by the digital thread, a digital mapping model of the product under different working conditions, extreme environments, and even throughout the entire lifecycle can be built to achieve predictive verification, performance optimization, and real - time feedback, thus supporting true closed - loop manufacturing.
One of its core technologies is the manufacturing master data model (MDM) and the common plant model (CPM). Through the product bill of materials (BOM) and the bill of process (BOP), design modeling, process planning, production execution, and equipment management are completed on a "single platform", forming a comprehensive intersection of product twin, process twin, and equipment twin. This system has been widely applied in practice.
In the battery manufacturing field, the first 80% of battery charging is usually very fast, while the last 20% takes longer, partly due to the heat generated during the charging process. Through digital twin modeling of the shunt with Simcenter, the air flow distribution is optimized, resulting in a 22% improvement in cooling performance and a 50% reduction in design time.
In the transportation field, the California startup Natilus is committed to solving the problem of high air freight costs. With the digital twin system, customers and developers can have an "immersive" experience and comprehensively explore design details. They adopted a blended - wing - body design, increasing the freight capacity by 1.5 times, reducing fuel consumption by half, and shortening the time to market by 50%. The RV manufacturer Hymer, when designing the concept RV VisionVenture, used comprehensive digital twin, reducing physical prototypes by 80% and shortening the development time of personalized variants by 65%.
In the consumer - grade product and personalized manufacturing field, the prosthetic manufacturing enterprise Unlimited Tomorrow uses digital twin and 3D printing to achieve personalized design and manufacturing, reducing the cost of prosthetics from $80,000 to $8,000, shortening the delivery cycle from up to one year to a few weeks, and reducing the weight of prosthetics from 4 pounds to 1 pound, providing customers with affordable, lightweight, and high - quality prosthetics.
In a more challenging case of production conversion, Vietnam's VinFast completed the conversion from car - making to ventilator - making in just three weeks. It was achieved through the rapid deployment of Siemens' digital twin solution, and the monthly production capacity was finally increased to 55,000 units. This responsiveness is the key competitiveness that the comprehensive digital twin system endows enterprises with.
At the same time, digital twin is deeply integrated with AI, the industrial metaverse, and sustainable manufacturing to create a dynamic and evolvable system. In the optimization of the battery robot fixture, AI - assisted design achieved an 80% reduction in structure weight and a 90% reduction in carbon emissions. The AI - driven configuration application significantly shortens the design cycle and cost through topological optimization.
From these practices, it can be seen that when an enterprise truly opens up the digital thread, builds a simulation platform, and extends it to the factory, processes, and the customer front - line, comprehensive digital twin is not just a technological ability but a structural force that drives product evolution, process re - engineering, and organizational change. It not only improves efficiency and quality but also expands the boundaries of product definition and delivery. Ultimately, it enables enterprises to make quick decisions, respond agilely, and operate sustainably in a complex and ever - changing environment.
Comprehensive digital twin is a new production logic and organizational ability. It reshapes the product design paradigm, rewrites the manufacturing rhythm, and defines the core competitiveness of future industrial enterprises.
The real future of industry does not belong to enterprises with the most tools but to those that can drive evolution with data and support decision - making with simulation. In this paradigm shift from "tool stacking" to "system reconstruction", comprehensive digital twin is becoming the dividing line that determines the fate of enterprises.
This article is from the WeChat official account "Digital Intelligence Frontline" (ID: szqx1991), written by Zhao Yanqiu, edited by Niu Hui, and published by 36Kr with authorization.