Digital twins are empowering small and medium enterprises (SMEs) to simulate and optimize complex multivariable problems using AI, reducing the costs associated with physical experimentation. A five-step process involves defining business objectives, mapping processes, identifying data, building digital models, and iterating through testing and implementation.
Digital twins enable businesses to repeatedly simulate and optimize complex multivariable problems, cutting the learning costs that come with experimenting in the physical world. Once the exclusive province of big business, small and medium enterprises can now use AI to advanced digital twins that enable them to repeatedly simulate and optimize complex multivariable problems.
A strategy’s execution is its riskiest moment because it is the point when any miscalculations have a tangible cost. One way to reduce that risk is to repeat a process over and over in an experimental setting improving it just a little bit more each time. It’s the type of thing Toyota’s continuous improvement systems are famous for. But this can be difficult as it involves continuously monitoring data and making many micro decisions in response..
Digital Twins AI Business Optimization Smes Simulation
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