2 citations · 5 across the 7 of their papers we have counts for
7 papers
Practical Implementation of an End-to-End Methodology for SPC of 3-D Part Geometry: A Case Study
Yulin An, Xueqi Zhao, Enrique del Castillo
Del Castillo and Zhao (2020, 2021, 2022, 2024) have recently proposed a new methodology for the Statistical Process Control (SPC) of discrete parts whose 3-dimensional (3D) geometr…
Registration-free localization of defects in 3-D parts from mesh metrology data using functional maps
Xueqi Zhao, Enrique del Castillo
Spectral Laplacian methods, widely used in computer graphics and manifold learning, have been recently proposed for the Statistical Process Control (SPC) of a sequence of manufactu…
A Registration-free approach for Statistical Process Control of 3D scanned objects via FEM
Xueqi Zhao, Enrique del Castillo
Recent work in on-line Statistical Process Control (SPC) of manufactured 3-dimensional (3-D) objects has been proposed based on the estimation of the spectrum of the Laplace-Beltra…
Optimal Design of Experiments on Riemannian Manifolds
Hang Li, Enrique Del Castillo
The theory of optimal design of experiments has been traditionally developed on an Euclidean space. In this paper, new theoretical results and an algorithm for finding the optimal…
Generalized Sparse Precision Matrix Selection for Fitting Multivariate Gaussian Random Fields to Large Data Sets
Sam Davanloo Tajbakhsh, Necdet Serhat Aybat, Enrique del Castillo
We present a new method for estimating multivariate, second-order stationary Gaussian Random Field (GRF) models based on the Sparse Precision matrix Selection (SPS) algorithm, prop…
Analysis and Optimal Targets Setup of a Multihead Weighing Machine
Enrique del Castillo, Alessia Beretta, Quirico Semeraro
Multihead weighing machines (MWMs) are ubiquitous in industry for fast and accurate packaging of a wide variety of foods and vegetables, small hardware items and office supplies. A…
On the Theoretical Guarantees for Parameter Estimation of Gaussian Random Field Models: A Sparse Precision Matrix Approach
Sam Davanloo Tajbakhsh, Necdet Serhat Aybat, Enrique Del Castillo
Iterative methods for fitting a Gaussian Random Field (GRF) model via maximum likelihood (ML) estimation requires solving a nonconvex optimization problem. The problem is aggravate…