Digital twins are enabling small and medium enterprises (SMEs) to simulate and optimize complex problems, reducing costly trial-and-error in the physical world. The five-step process of creating a digital twin involves defining a clear business objective, outlining the process, identifying data needs, building the digital model, and testing, implementing, and iterating. This approach allows for continuous improvement, similar to Toyota's lean manufacturing principles, by repeatedly testing and refining strategies in a risk-free environment.
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 Smes Optimization Strategy
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