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The global Industry 4.0 market was worth US$116 billion in 2021 and is projected to grow to US$337 billion by 2028. Many technologies are contributing to the incredible growth of Industry 4.0, but digital twin solutions stand out among them. In particular, digital twins are now being deployed to significantly improve warehouse automation operations, with the end goal of increasing efficiency and reducing downtime.
Digital twins can provide virtual representations of a physical environment – which is proving extremely useful for the warehousing industry. With a digital twin, new improvements and efficiencies can be tested virtually without downtime or physical asset rearrangements.
Warehouse processes are becoming increasingly complex. Inventory is more diverse as the massive expansion of e-commerce has led to an increase in the proliferation of SKUs. Logistics solutions are under pressure as customers now expect lightning-fast processing. The technology is more complex as innovative new automation systems emerge and managers must analyze the new systems to introduce the ones that will bring the greatest benefit to their warehouse operations.
To stay ahead of the competition, smart companies are now building digital twins of their warehouse operations and using them to address operational complexities and performance improvements.
Visualization and design made easy
With digital twins, companies can try out new floor plans and test new workflows virtually. They can introduce new variables and configuration parameters into the virtual model of their operations and assess the impact. Every aspect of operations can be monitored and optimized, including SKU mix, ordering and shipping, and demand spikes. Automation efforts can be tested and their impact reviewed. In short: the storage performance can be increased much faster and more cost-effectively than before.
Digital twins are also valuable when designing new automation systems. With a traditional automation system, thousands of hours are invested in configuring and customizing the software that runs the system. One size doesn’t fit all. For each system, the different materials and processes of each customer must be taken into account. But what if it was possible to skip all of the coding of these customer specs? It is a digital twin of the physical system in which a machine learning algorithm can run experiments. It typically takes up to a year to build and install a system; But in that time, machine learning can do its experiments and the physical system can be optimal on the day of launch.
Digital twins can also help companies adapt to changing requirements or other disruptions. How far can you push your business during the busy holiday season with Christmas shopping? What happens if customer buying behavior changes? How does your system react to equipment downtime? A warehouse or distribution center equipped with digital twin technology can run hundreds of possible scenarios in a very short time. This provides key insights into average performance over time and identifies areas where you can strengthen your system’s ability to meet short- and long-term challenges. It also allows for much quicker decisions about when to service, upgrade, or replace the system.
Robot systems are going digital
The digitization of robotic systems continues to enable next-generation automation in the warehouse area. The synthetic models that provide intelligence to the algorithm train the internal data set to replicate it into a digital twin and show the end user the best performance scenarios. The extension of these processes gives the robotic systems the optimal path for project completion. In previous applications, these technological processes corresponded to months of implementation in the warehouse. With the data from the digital twin, these processes are now reduced to weeks. Increased investments and research and development in machine learning will further optimize operations to increase efficiency and reduce downtime.
Future-oriented companies use digital twins today as a central tool for their digital transformation. Your operations and maintenance teams gain valuable new insights from digital twins to make more timely and relevant decisions. They synchronize digital twins with their real-world environments to analyze and improve the performance of their current processes. With integrated process and plant data combined with predictive analytics, they reach a new level of productivity and can better identify impending problems. They increase performance, efficiency, yield and uptime.
There is now an intense focus on digital transformation initiatives and industrial IoT – and digital twins are playing an important role. They significantly improve performance and ROI by enabling much more efficient, faster and cheaper analysis and decision making.
Thomas H. Evans, Ph.D. is CTO of Robotics at Honeywell.
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