Engineers traditionally use deterministic modeling in their tasks, but challenges for developing and optimizing products and processes inspire us to venture beyond deterministic to probabilistic or stochastic modeling. The melding of engineering modeling with probabilistic thinking empowers engineers to develop confidence for ourselves, our customers and regulatory agencies that our products are likely to be successful and that we will flawlessly meet or exceed expectations over a comprehensive range of use conditions. Predictive engineering starts from measurable system level requirements, exploration and documentation of use conditions, and expanding on deterministic models with probabilistic modeling using Monte Carlo Simulation or Bayesian Networks to optimize the design and process. Probabilistic and stochastic modeling has provided competitive advantages for enterprises, for products, and for both experienced engineers and engineers early in their careers.
Event is organized by IEEE Hawaii YP, IAS, and WIE and co-hosted with several other organizations. Depending on the level of interest in this event, a follow on series with Six Sigma certification is possible.
Speaker(s): Eric Maass, PhD
Virtual: https://events.vtools.ieee.org/m/382000
Predictive Engineering
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