Year: 2026
Type: article
Abstract: Additive manufacturing (AM) requires process-comparison tools that remain practical when sample generation and testing are costly. We propose a univariate, nonparametric workflow for comparing a candidate AM process to a stable reference process by testing distributional equivalency for a single response variable. The method discretizes the reference distribution into empirical percentile-defined bins and combines this representation with a sequential sampling protocol designed to reduce unnecessary sampling when evidence for equivalency or non-equivalency becomes sufficient. Simulation studies were used to evaluate operating characteristics across experimental settings, and a validation case study based on geometric measurements of laser based powder bed fusion plate scans correctly classified a candidate process expected to be equivalent to the reference while identifying a non-equivalent process at the first sampling step. The workflow is most appropriate for low-sample, high-cost, or throughput-constrained settings, and is best viewed as a tool for process comparability, change control, calibration, and requalification support rather than as a standalone replacement for qualification standards. The full workflow is implemented in the open-source AMEquivalency package to support reproducible analysis.
DOI: 10.3390/jmmp10040134
Institutions: Arizona State University, The University of Texas at El Paso
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,172
Award: G254279804
OpenAlex ID: W7154784480
FWCI:
Cites:
Cited by:
Related to: