Manufacturing Simulation Optimization
Getting the best results from a manufacturing model requires understanding how changes will impact efficiency at individual stages of production and the larger chain as a whole. Experimenting with changes in the safety of a virtual environment removes the risk of disrupting operations, but figuring out the best paths for optimization and then deploying them into action still presents a unique set of challenges.
Manufacturing simulations equipped with Pathmind offer more insight than those using basic trial-and-error testing and outperform models relying on traditional optimizers. Pathmind AI often reveals paths for optimization that might not be evident with traditional testing and can help manufacturers deploy new ideas for more efficient production. The Pathmind platform also makes it easier to explore how each stage of production can be optimized and how those changes impact the operation as a whole.
Reveal New Optimization Strategies
Determining better choices for optimization within a manufacturing simulation model can be a major time investment and may tie up resources that are needed elsewhere. Pathmind frees up those hours and equipment by automatically running experiments in the cloud with no need for close monitoring. Policies generated by Pathmind are also more likely to reveal strategies that are not evident in traditional testing, which is limited by the experiences of the tester.
Improve Performance at Each Production Stage
Manufacturing facilities are a complex network of equipment and processes. Figuring out how to get the best performance from each stage of production while also understanding how each stage works as part of the larger facility is key to optimization. Pathmind AI is a powerful resource for tackling these complicated problems and revealing how changes will impact each step of production.
Manufacturing Use Cases
Discover New Paths for Optimization
Contact us to see how Pathmind reinforcement learning can strengthen your optimization strategy.