GE Digital Twin vs. Analytic Solver

Employing advanced analytics and machine learning methodologies is vital for reducing operational costs and alleviating risks. Digital twins, a key element of the digital transformation journey, offer exact virtual models of physical assets, systems, and objects that aim to improve productivity, streamline processes, and boost profitability. Generally, a digital twin is seen as a software representation of a tangible asset or system designed to identify, prevent, forecast, and enhance operations through real-time data analysis, ultimately providing considerable advantages for businesses. At GE Digital, we focus on utilizing digital twin software to support our clients across three essential areas: Asset, Network, and Process. By adeptly overseeing, simulating, and controlling an asset or process, organizations can greatly improve system performance. Moreover, it is imperative to prioritize the health and safety of employees and the environment while pursuing business objectives, which entails reducing incidents associated with assets and processes and avoiding unexpected downtimes, thus nurturing a more robust operational structure. The adoption of digital twin technology not only boosts efficiency but also opens doors for innovation across numerous industries. As organizations embrace this technology, they position themselves for sustained growth and competitive advantage in an ever-evolving marketplace.

Analytic Solver Optimization provides full compatibility with the Excel Solver and is adept at tackling various traditional optimization problems without uncertainty, regardless of their size or complexity. Its distinguishing feature lies in its ability to algebraically analyze the structure of your model while harnessing the complete processing power of multiple cores available on your computer. This tool can efficiently solve nonlinear models that are up to ten times larger and linear models that can be forty times larger than those manageable by the Excel Solver, resulting in significantly quicker solutions and the ability to incorporate Solver Engines capable of handling millions of variables. Furthermore, Analytic Solver Simulation offers a highly intuitive yet powerful platform for conducting Monte Carlo simulations, performing risk analysis, creating decision trees, and optimizing simulations, all while utilizing Frontline’s advanced Evolutionary Solver. With an extensive selection of 60 probability distributions, including compound distributions, automatic fitting, rank-order correlations, and copula-based correlations, as well as 80 statistical measures, various risk assessments, Six Sigma functions, and the potential for multiple parameterized simulations, it emerges as a comprehensive resource for intricate analytical requirements. This rich array of features guarantees that users can conduct thorough analyses efficiently and accurately, solidifying its status as an essential tool in both optimization and simulation fields. Ultimately, the versatility and power of Analytic Solver make it a go-to choice for professionals seeking to enhance their analytical capabilities.