Manufacturing companies require systems that can respond to disruptions and be reconfigured quickly. The use of simulation to improve efficiency is particularly common; however, realistic and accurate simulations are computationally expensive. To save on computational expense, a facility manager can make use of a computationally efficient surrogate model that approximates the response of the simulation. This work implements a novel method of approximating throughput of a simulated manufacturing environment using Non-Uniform Rational B-splines (NURBs) as the basis for surrogate models. In three scenario studies, NURBs-based surrogates accurately approximate simulation outputs, with surrogate model query times ranging from 2 to 4 orders of magnitude faster than estimated evaluation times for corresponding simulations. These findings indicate that NURBs-based surrogates are a promising method of approximating manufacturing simulations for performance forecasting.
Applying NURBs-Based Surrogate Models for Performance Forecasting in Manufacturing Systems
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Anderson, D, & Turner, CJ. "Applying NURBs-Based Surrogate Models for Performance Forecasting in Manufacturing Systems." Proceedings of the ASME 2015 International Mechanical Engineering Congress and Exposition. Volume 11: Systems, Design, and Complexity. Houston, Texas, USA. November 13–19, 2015. V011T14A042. ASME. https://doi.org/10.1115/IMECE2015-51862
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