Integrating automated guided vehicles and robotic systems into digital twin models increase accuracy and enhance simulation results. Simio software provides enterprises with the opportunity to digitize logistic systems and complex autonomous processes to receive applicable insights from them.
Industrial and manufacturing markets currently account for approximately 45% of the autonomous vehicles (AGVs) and robots currently deployed across the world. The increasing reliance on AGVs and robots are driven by the need to increase efficiency levels, reduce waste, and eliminate accidents from occurring within a facility’s logistics systems.
During their operations, AGVs and robots rely on data such as mapping data, shop floor topology, and obstacle dimensions which may affect the accuracy of their performance. Also, these automated shop floor assets produce their own data which could be the distance traveled during deliveries, the relationship between load weight and transportation safety, delivery timelines, and transportation speed. The data produced by AGVs also provide more insight into the material handling and logistics activities that occur on the shop floor.
Other robotic systems that deliver precision guidance or track production processes also rely on shop floor data such as inventory lists and workstation availability. These systems also produce their fair share of data that define the manufacturing or industrial process occurring on the shop floor. Thus, making robots and AGVs integral components in industrial automation and Industry 4.0.
Automating every process in large industrial facilities is a complex task. This is because of the multiple subsystems that communicate in complex patterns when achieving a common goal. This is what the digital twin excels at. It provides a comprehensive digital environment where the varying relationships among subsystems within a facility can be discovered, monitored, and enhanced. The use of AGVs and robotic systems are examples of such subsystems and the digital twin can be used to extract important industrial insights from these systems, as well as, their relationship with an entire facility.
The data automated assets and processes provide can be analyzed to enhance shop floor performance and the accuracy of logistics systems. With the data collected from these automated processes, the logistics chain within a facility can be modeled into a digital twin and analyzed in real-time. Complex relationships such as the one between customer demand, inventory list, and the automated logistics system can also be integrated into a digital twin. Thus enhancing the integrity of the analytical results produced from the digital twin of any facility. The benefits of using digital twin ecosystems to manage AGVs and robotic systems include:
Simio’s digital twin software provides an intuitive and 3D-capable interface for digitizing your facility and its varying subsystems including its logistics system. With accurate data and representations of the assets that define supply chains, a digital twin consisting of AGVs and robotic systems can be modeled using Simio.
Within this digital twin, your enterprise can choose to monitor its logistics system in real-time and run simulations on the effects of different scenarios on industrial operations. Manufacturers and industrial enterprises interested in automation can also analyze the complex relationships between automated processes and the more traditional or manual process occurring within a facility. The end result can be applied to developing business cases where automated and manual processes function in harmony.