Implementing the Digital Twin culture, which includes real-world and virtual product-life-cycle management software, significantly reduces design cycle time, testing, and improves yields. These manufacturing improvements occur with a reasonable reduction in maintenance and product costs.
Sound attractive? Over the last few years, businesses have seen the Industry 4.0 Industrial Internet of Things (IIoT) migrate to Digital Twins. This strategy, along with Siemens solutions, pulls the numerous traditional 20th-century sequential islands of excellence into cohesive start-to-finish applications of predictive maintenance, process planning and optimization, and product design and virtual prototyping.
With these benefits, Digital Twin projects capture the attention of those who desire actual zero failures and continued acceleration of process excellence. Digital Twins’ heart is the combination of a real-time bridge between the real and digital world.
What is Digital Twin?
A Digital Twin concept creates a highly complex exact-counterpart virtual model of a physical item from inception to the product’s end of life. The ‘item’ can be the next generation of manufacturing or product, with planning, designing, building, supporting, and item life closure as the five major development phases. The Digital Twin process connects the entire operation by capturing data to predict futurism with simulation software (Figure 1).
technology” alt=”The Digital Twin Concept and How It Works”>Figure 1: This efficient production floor utilizes Digital Twin technology to connect all operations from beginning to end. (Image Source: Analog Devices)
In Figure 1, the process monitors use data to predict the final item outcome for the end-user. Digital Twin leverages the implementation of these phases with the company’s workforce as its most significant competitive advantage. The Digital Twin version of Industry 4.0 promises to make it easier for manufacturers to produce appropriate products in the marketplace while attracting and retaining the new engineering talent found in the incoming Generation Z.
How does Digital Twin work?
Connected sensors on the physical asset collect data that maps onto the virtual model. Anyone looking at the Digital Twin sees crucial information about the physical item’s planning, creation, and real-world application. In this manner, Digital Twins help understand the present and predict the future. At the front end, process simulation determines the Digital Twin product (Figure 2).
Figure 2: Digital Twins help understand the present and predict the future. (Image Source: Siemens)
At the second stage (Figure 2), the process automation and process quality support the performance data during the Digital Twin production. At this point, it is important to note that simulation and data collection continue to occur. The production of the real product happens at the last stage, although previous simulations predict the characteristics of the real product ahead of time.
One of the most significant pieces of the Digital Twin personal and software technical debt is the elimination of the walls (virtual and real) that create silos between departments. For example, an Industry 3.0 product’s design details are practically inaccessible outside the walls of engineering. It is difficult for manufacturing, procurement, sales, and service teams to do their jobs effectively and give feedback to the other groups to improve the product and process. For example, shop floor technicians don’t know what the outcome should look like once it’s fully assembled. The service teams page through virtual PDFs to try and figure out how to service a part they’ve never seen. Sales teams sell feature options, and supply chain managers only know part numbers. Not only is it challenging for each team member to do their work, but it also means that engineers don’t get critical input to improve their designs. If companies can make designs more accessible, innovation will happen sooner, and the workforce will be more engaged in the process.
Digital Twin construction
Digital Twin technology provides unprecedented visibility into products and assets to find bottlenecks, streamline operations, and innovate product development. The three primary Digital Twins are predictive maintenance, process planning and optimization, and product design and virtual prototyping.
Companies instantly find operation anomalies and deviations in the view of equipment health and performance. Proactively planned maintenance and spare part replenishment minimizes service time and avoids costly resource failures. Digital Twins’ predictive maintenance provides new service-based revenue streams while helping improve product reliability for OEMs.
Process planning and optimization
A comprehensive analysis of critical Key Performance Indicators (KPIs), such as product rates and scrap counts, comes from a digital footprint with sensor and Enterprise Resource Planning (ERP) data. This process diagnoses the root cause of inefficiencies and throughput losses, and this diagnosis can optimize yields and reduce wastes. Additionally, equipment historical data, processes, and environments improve production scheduling by enabling downtime forecasting.
Product design and virtual prototyping
Virtual product models provide insights into usage patterns, degradation points, workload capacity, incurring defects, etc. Understanding product characteristics and failure modes allow designers and developers to evaluate product usability and improve future component design. Similarly, OEMs can deliver customized offerings for different groups of customers based on specific user behaviors and product implementation contexts. Digital Twin technology additionally aids in developing virtual prototypes and running robust stimulants for feature testing based on empirical data.
Real-world use cases
In the real world, it is critical to have the capability to test products, processes, or facilities before introducing them in the production line. Digital Twins accomplishes this purpose. Globally, companies use Digital Twins to improve processes, supply chains, facilities management, and more. Here are examples of how Digital Twin technology transforms a range of different industries.
Smarter shipment packaging with Siemens’ SIMATIC
Siemens’ SIMATIC technology is at the heart of many solutions in innovative packaging machines. These projects show how the SIMATIC T-CPU (CPU à schematic technology) helps machines achieve simpler and leaner processes, better quality, and optimum performance in every respect.
TMG company produces packaging machines for food and beverage, cosmetic, and chemical packaging (Figure 3).
Figure 3: TMG’s packing machine. (Image Source: Siemens)
In their system, the seven SINAMICS S120 drives and format change-over takes very little time. Siemens’ PROFINET network integrates the SIMATIC S7-1500TF CPU, comfort panels, S120 and G120 drives to develop automation, motion control, and safety in a single Total Integrated Automation (TIA) portal environment. Thanks to an integrated and versatile solution with SIMATIC S7-1500TF and SINAMICS drive technologies, the TMG scores high in configuration efficiency, high-performance, and new format conversion simplicity.
Artificial intelligence meets motion control (147)
Wittmann Battenfeld’s handling systems grip and insert parts for injection molding machines and then reinsert them into another machine. The equipment freely moves and rotates the corresponding object to give the handling system five axes – three for movement in space and two more to rotate the inserts in any direction. The handling systems increase productivity by completing this complex task with fast cycle times, allowing the process to be as flexible as possible. SIMATIC, the Siemens solution for automation, provides mapping all functions in one controller – motion control, image recognition, and automation. Wittmann Battenfeld implements this function with the help of the Handling Standard Application from Siemens, which supports engineering motion control tasks and visualization modules. The package also includes a trace function where Wittmann Battenfeld developers track the gripper movement with a 3D model.
Figure 4: The SIMATIC controller commands the gripper that grips the inserts on the vibrating table. The AI module processes the camera data. (Image Source: Siemens)
Critical considerations for Digital Twins deployment
Digital Twin is a new paradigm from the 20th-century manufacturing model. Finances impact the factory’s turn to the Digital Twin model. However, there is a return on the Digital Twin investment with the equipment’s and production line’s increased reliability. The Digital Twin technology improves Overall Equipment Effectiveness (OEE) through downtime reduction and improved productivity and performance. The connection of virtual models to reality reduces risk in various areas, including product availability and marketplace reputation.
The Digital Twin is a virtual representation of the as-designed, as-built, and as-maintained physical product in manufacturing. This virtual representation mirrors real-time process data and analytics based on the physical product, production systems, or equipment configurations. A further advantage is that Digital Twin allows engineers to test concepts and hypotheses before applying them to a physical machine.
Digital Twin and Siemens’ digital imitation is part of the industrial automation revolution. How has Digital Twin impacted the industry? This digital imitation continuously influences physical assets, operations, and frameworks that produce data. Digital Twin is at the core of Industry 4.0 development, which enfolds automation, data exchange, and manufacturing processes, creating endless opportunities for industries to grow.
- Video Insights: Pioneering Digital Twins, Oct. 6, 2021, A conversation with Dr. Michael Grieves, inventor of the digital twin concept.
- TMG: more performance, less time video, Siemens.
- Artificial Intelligence meets motion control: Taking technology a step further, Siemens.