Simulation-assisted optimisation is particularly relevant in the fields of industry and Industry 4.0, artificial intelligence, and automation. This is a modern approach that uses computer models to improve processes or products before they are tested in the real world. This saves time, money, and resources.<\/p>\n
Instead of conducting \u201etrial and error\u201c in live operation, virtual twins of machines, production processes, or even entire factories are created. In the simulation, different settings or changes can then be safely tested. The optimal solution is found based on the results from numerous test runs. <\/p>\n
A simple example: A company wants to make its production line more efficient. Using simulation-driven optimisation, a digital replica of the plant is created. In this virtual environment, an algorithm tests different ways of arranging the machines or planning the processes. The best-performing option tested can then be implemented in reality without risk and significantly faster. <\/p>\n
Simulation-assisted optimisation helps companies to remain more competitive and avoid errors in advance. Especially in times of digitalisation, this method is an important building block for greater efficiency and innovation.<\/p>","protected":false},"excerpt":{"rendered":"