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Digital twins for Smart Manufacturing

Smart manufacturing is the future of manufacturing, and it is made possible by the Internet of Things (IoT). It’s a way of making things that combines the power of digital technology with the knowledge and expertise of human workers to create smarter, more efficient processes that improve product quality, reduce waste and cost, and help companies stay competitive in an increasingly globalized marketplace.

IoT development companies play an important role in implementing these smart manufacturing practices. One of the key tools in smart manufacturing is digital twins, which are digital replicas of real-world items. These digital twins can be used by IoT development companies to evaluate various designs and component performance, and optimize the manufacturing process.

Applications for digital twins in manufacturing include all functional areas of a manufacturing enterprise, including pre-production, production, and post-production. By using digital twins, IoT development companies can help businesses improve product quality, reduce waste and cost, and stay competitive in the marketplace.

In this article, we’ll take a look at five real-life examples of how companies are using digital twins to boost their smart manufacturing efforts.

Digital Twin in Manufacturing Outline

Digital twins, enabled by the power of the Internet of Things (IoT) technology, are like virtual doppelgangers of physical objects, they are digital replicas that can mimic the behavior and characteristics of their real-world counterparts.

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They can perform a variety of tasks, from simply capturing data for future reference to simulating hypothetical scenarios and identifying potential issues before they happen, providing an advanced level of insight and control.

Applications for digital twins in manufacturing include all functional areas of a manufacturing enterprise, including:

  •         Pre-production: Digital twins are a tool that businesses can use to evaluate various designs and component performance.
  •         Production: Manufacturers can arrange the manufacturing process and discover the perfect production run with the aid of digital twins.
  •         Post-production: Customers might acquire equipment training or preventative maintenance from businesses. Even obsolete spare parts might be provided by the manufacturers. They can also offer product-as-a-service business concepts.

Let’s examine five use cases for digital twin manufacturing using actual examples from the real world.

Pre-production. Error Prevention in the Design Process

A physical prototype in conventional product development goes through a build-test-redesign-retest cycle. This implies that the prototype is initially tested in a lab which will highlight any design issues that need to be fixed. The issue with this cycle-style development is that it adds to expenses and lengthens the timeline.

Digital twins aid in the elimination of pointless loops during design optimization. Companies may evaluate product design in a virtual environment using this technology. They can therefore arrive to the ideal design much more quickly.

Consider the following example. Norwegian machine manufacturer, Tronrud Engineering intended to create a new packaging gear that could operate twice as fast as the present model. To do so, they needed to transition from pneumatic to fully electric operation which meant significant design adjustments.

The firm employed a digital twin to build and test the product in a virtual environment. This enabled their designers, engineers, and programmers to collaborate on the project at the same time. Consequently, the time spent on programming, design, and assembly was cut in half. The firm also avoided costly design changes.

Pre-production. Identifying the “Perfect Production Run”

Finding an optimal manufacturing run that can serve as a template is a difficult task. Materials, equipment, labor, space, and costs are all factors that influence output. That’s why businesses must pay close attention to how these factors interact in order to identify their “golden batch.”

A digital twin is an ideal buy for such activities. Companies can use them to simulate multiple variables until they discover the ideal combination for production, allowing companies to prevent quality difficulties and rejected batches.

One pharmaceutical company was hunting for a “golden batch” of its new medicines. They built up machines by hand, and as a result, more than 10,000 pills were rejected in each experiment. They also had to pay for the disposal of the discarded pills

Employing Digital twin, this company was able to identify the ideal machine configuration for their production. Their operators used simulations to acquire the appropriate tablet weight, thickness, and hardness. As a consequence, the organization reduced waste and cut expenditures. They also cut the operator’s time setting up equipment by 70%.

Production. Optimizing the Manufacturing Process’s Timetable

Manufacturing scheduling may appear to be simple. However, it is more than merely entering data into the system. A variety of factors influence the timetable, including material delays, equipment breakdowns, and shifting supplier priorities.

Some businesses rely on their ERP system and Excel spreadsheets for data entry. Because adjusting data in Excel spreadsheets is a time-consuming manual operation, exporting it is always a challenge. A digital twin, in contrast to traditional planning systems, is a system that is constantly updated.

Lagor manufactures power transformer ferromagnetic cores. Each core may be up to eight tons in weight. Materials are kept on steel pallets throughout the manufacturing process. These pallets are transported between workstations by roller or shuttle conveyors. Even if the pallets are empty, they are never removed from the line.

Initially, they manually planned manufacturing lines. This led to cases when items on the manufacturing line caused bottlenecks. The manufacturer had to unload the cores by crane and restart the entire line to remove them. But when they decided to increase output, it was time for a change.

This is why the firm chose to utilize a digital twin. It was used to simulate various core kinds, production cycles, and production strategies. This enabled them to minimize needless moves that resulted in congestion. As a result, manufacturing became more efficient and faster.

Post-production. Predictive Maintenance

Companies typically maintain their equipment too often which results in budget waste. Of course, manufacturers set the periods at which their devices must be serviced. However, various maintenance regimens are required for equipment that operates under varied circumstances. This makes it difficult to create an accurate manufacturing schedule. If a machine requires more frequent maintenance and this goes undiscovered, it might result in downtime and, as a result, expenditures.

With the use of sensors, digital twins can determine the system’s health while also continually monitoring the functionality of the equipment. Digital twins can forecast how the system will act in the future by using AI. This information might help businesses optimize their maintenance procedures. This helps to save expenses because parts are only changed when necessary. Additionally, businesses may avoid overly frequent maintenance tasks and keep their equipment running for extended periods of time.

Post-production. Providing Customer Training

Employee training in a real-world scenario is likely to be costly for your client if you manufacture complicated equipment. However, as it takes longer for the equipment to become operational, this results in disruptions to their primary business. Also, new personnel will always require training.

Consider helping your clients complete training while the equipment is still being manufactured. This is made feasible by digital twins since they imitate the actual equipment. They can also simulate emergency circumstances, something real-world equipment cannot do.

ThyssenKrupp Marine Systems manufactures surface ships and submarines. They develop a training environment for their customers using a digital twin.

The company created a virtual ship that is identical to the actual ship and it helps sailors enhance their spatial knowledge on board by allowing them to practice operating the ship in real-world scenarios. Businesses can also simulate crises, such as an automation system breakdown.

This technology not only increases the teams’ ability to operate under extreme stress and time constraints, it also allows training to take place without the use of a real vessel. This is useful whether the ship is at sea or in the manufacturing process.

Wrap Up

Digital twins can assist businesses at every level of the production process. They can prevent expensive mistakes during the design process. They can prevent bottlenecks and product rejection during manufacturing. They can generate profits in the post-production stage by providing services to clients.

A digital twin is a powerful tool for manufacturers, but it’s not just about the technology. It’s about how you use that technology to create a better business.

If you’re looking to boost your smart manufacturing efforts, consider these five real-life examples of how companies are using digital twins to improve their operations and make a difference in the world.

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