Data utilization pilot in industrial environment started

The Data for Efficiency, Productivity and Competitiveness project is implementing a pilot project with Aurolahti Automation, part of the Aurolahti Group, that utilizes Internet of Things (IoT) sensor technology. The pilot project aims to collect information on pallet throughput times and test several potential solution models and new sensors.
"Aurolahti Automation networked through the Robocoast EDIH network, bringing interesting solution needs and ideas to the project," says Veli-Matti Tornikoski, project manager for the Data for Efficiency, Productivity and Competitiveness project.

The project investigates various interfaces between an IoT sensor device and a data collection system, and later between factory information systems. The goal is to utilize the collected data as input data in automation, layout design, and simulation solution scenarios.
"We are interested in investigating how we can utilize IoT sensors and data processing in warehouse and intralogistics simulation. The goal is to "quickly obtain input data" on the current state of the automation system and potential bottlenecks," says Kalle Määttä, Business Manager at Aurolahti Automation.

Simulation software enables the pre-design, optimization and validation of industrial processes using 3D models and virtual environments. Digital design tools and platforms combine advanced rendering technologies and generative artificial intelligence with the simulation needs of industry and robotics. In addition, the simulation and analysis of production and logistics processes help optimize material flows and resource use.

Aurolahti Automation offers simulation services for optimizing various industrial processes and warehouse logistics. Digital Twin operating models enable the simulation of moving parts of processes and virtual driving on pallets, conveyors and lifts. This allows, for example, to optimize conveyor speeds in a high-bay warehouse. Simulation can also be used to evaluate warehouse performance and optimize resources, such as the number of elevators, loading bays, personnel and forklifts.