ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2103.13881
35
7
v1v2v3v4 (latest)

Advanced Manufacturing Parameters Configuration using Sample-efficient Batch Bayesian Optimization

25 March 2021
Xavier Guidetti
Alisa Rupenyan
L. Fassl
M. Nabavi
John Lygeros
ArXiv (abs)PDFHTML
Abstract

Recent work has shown constrained Bayesian optimization to be a powerful technique for the optimization of industrial processes. We adapt this framework to the set-up and optimization of atmospheric plasma spraying processes. We propose and validate a Gaussian process modeling structure to predict coatings properties. We introduce a parallel acquisition procedure tailored on the process characteristics and propose an algorithm that adapts to real-time process measurements to improve reproducibility. We validate our optimization method numerically and experimentally, and demonstrate that it can efficiently find input parameters that produce the desired coating and minimize the process cost.

View on arXiv
Comments on this paper