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The digital twin has long since established itself in industry, where it’s revolutionizing processes along the entire value chain. As a virtual representation of a product, production process, or performance, it enables the individual process stages to be seamlessly linked. This creates a consistent improvement in efficiency, minimizes failure rates, shortens development cycles, and opens up new business opportunities: In other words, it creates a lasting competitive edge.
For these very reasons, IT analysis and market research institute Gartner expects half of all major industrial companies to be using digital twins by 2021, increasing their effectiveness by ten percent (link to the whole study can be found in the related link section). To leverage the full potential of the digital twin, however, real systems in the future don’t just need to be networked with each other: They also need to develop the ability to “think” and act autonomously. Development is trending in the direction of artificial intelligence, from simple mutual perception and interaction to communication and independent optimization. This also requires integrated information systems that permit a continuous exchange of information.
Developing digital twins calls for powerful software systems that can implement them along the whole value chain – for planning and designing products, machines, and plants and operating products and production systems. This allows users to act much more flexibly and efficiently and to customize their manufacturing.
The digital twin of the product is created as early as the definition and design stage of a planned product. This allows engineers to simulate and validate product properties depending on the respective requirements: for example, is the product stable, and is it intuitive to use? Does the car bodywork offer the lowest possible air resistance? Do the electronics operate reliably? Whether it involves mechanics, electronics, software, or system performance, the digital twin can be used to test and optimize all of these elements in advance.
The same applies to the digital twin of production. It involves every aspect, from the machines and plant controllers to entire production lines in the virtual environment. This simulation process can be used to optimize production in advance with PLC code generation and virtual commissioning. As a result, sources of error or failure can be identified and prevented before actual operation begins. This saves time and lays the groundwork for customized mass production, because even highly complex production routes can be calculated, tested, and programmed with minimal cost and effort in a very short time.
In turn, the digital twin of performance is constantly fed with operational data from products or the production plant. This allows information like status data from machines and energy consumption data from manufacturing systems to be constantly monitored. In turn, this makes it possible to perform predictive maintenance to prevent downtime and optimize energy consumption. And some companies use data-driven services to develop new business models, as shown in the example of mechanical engineering firm Heller. At the same time, data-driven knowledge about systems like MindSphere – the open, Cloud-based IoT operating system from Siemens – can be fed back into the entire value chain all the way to the product system. This generates a completely closed decision-making loop for the continuous optimization process.
The Siemens Digital Enterprise Suite offers perfectly coordinated and integrated software and automation solutions to create a comprehensive approach: A central data platform is used to digitalize industry’s entire value-added process. Intelligent industrial communication networks provide for simple data exchanges within the different production modules and collect operational data on an ongoing basis.
The Defense-in-Depth strategy from Siemens ensures that companies are positioned to deal with growing industrial security requirements, and that industrial plants are effectively protected from both internal and external attacks. Standard-compliant security mechanisms – from password protection to continuous security monitoring – provide reliable and customized protection for the digital factory.
MindSphere also serves as a platform for developing new digital business models for industrial companies, and it completes the Siemens portfolio of data-driven digital services for the industrial environment. It offers state-of-the-art security functions for data acquisition in the field and for transferring and storing this data in the cloud (see this interview for more details).
With the Siemens Digital Enterprise Suite, customers can begin investing today in future-proof solutions for the step-by-step implementation of Industrie 4.0. For example, special-purpose machine manufacturer Bausch + Ströbel uses digitalization as a key to consistency in its engineering. The company is expecting an increase in efficiency of at least 30 percent by 2020 thanks to the time saved during engineering alone.
Likewise, Schunk – the world market leader in clamping technology and gripping systems – is already using digitalization solutions for its electrically controlled gripping system components. This new engineering process will lead to significantly shorter project timelines, faster commissioning, and a substantial increase in efficiency when building similar plants.
Networking machines with each other and with higher-level systems enables resources and production data to be centrally managed. This ensures cost benefits in procurement and operation, – meaning that order data is available throughout the entire company, and it’s possible to identify optimal strategies for allocating orders to the various production sites within the organization. In addition, material stock, logistics processes, and tool availability can be seen at a glance and efficiently coordinated.
Thanks to improved documentation of manufacturing processes and production parameters, the potential offered by the digital twin in the area of quality management is just as exciting. If manufacturers know exactly what component has been installed, with what features, in what products, and how it was installed, they can provide a targeted response to potential problems and optimize their processes. In its Simatic production facility in Amberg , Germany, Siemens is already using a comprehensive documentation and evaluation system and has achieved an extremely low error rate in production.
And in the process industry, too, the digital twin is ensuring greater efficiency and productivity: With the step from Integrated Engineering to Integrated Operations, Siemens enables companies in the process industry to build a comprehensive data model from plant engineering to operation. In this field as well, digitalization ensures a shorter time to market, greater flexibility, and increased efficiency. This gives companies the opportunity to respond successfully to the volatility and diversity of global markets and to increase their productivity as well as energy and resource efficiency.
Picture credits: Electra Meccanica, Siemens AG
There is tremendous value gained from performing "what if" scenarios and predicting future performance with the digital twin. The ultimate goal of the digital twin is in the closed loop connection between the virtual world of product development and production planning with the physical world of production system and product performance. Through this connection actionable insight is gained from the physical world for informed decisions throughout the lifecycle of products and production operations.
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