So sánh phương pháp

	Thiết kế phân đoạn hỗ trợ mô phỏng	Thiết kế thí nghiệm có hỗ trợ mô phỏng
Lĩnh vực	Thiết kế thí nghiệm	Thiết kế thí nghiệm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	FFD: 1950s; simulation integration: 1980s–2000s	1970s–1990s (formalized with computer experimentation growth)
Người khởi xướng	Box, Hunter & Hunter (FFD basis); Kleijnen and others (simulation integration)	Multiple contributors; systematized by Jack P.C. Kleijnen and Thomas J. Santner et al.
Loại	Experimental design with computational augmentation	Hybrid experimental-computational method
Công trình gốc	Kleijnen, J. P. C. (2008). Design and Analysis of Simulation Experiments. Springer. ISBN: 978-0387718125	Santner, T. J., Williams, B. J., & Notz, W. I. (2003). The Design and Analysis of Computer Experiments. Springer. ISBN: 978-0387954202
Tên gọi khác	SA-FFD, virtual fractional factorial design, computer-aided fractional factorial design, simulation-based FFD	Simulation-based DoE, Virtual DoE, Computer-aided DoE, SA-DoE
Liên quan	4	5
Tóm tắt	Simulation-assisted fractional factorial design (SA-FFD) combines the statistical efficiency of fractional factorial experimentation with computerized simulation models to screen and estimate factor effects when physical experiments are too costly, hazardous, or time-consuming. A carefully chosen subset of factor-level combinations — the fractional factorial array — is executed inside a validated simulation model instead of (or alongside) a real process, dramatically reducing resource requirements while preserving the ability to identify main effects and low-order interactions.	Simulation-assisted design of experiments (SA-DoE) integrates computational simulation tools — such as finite element analysis (FEA), computational fluid dynamics (CFD), or discrete-event simulation — with classical DoE principles to systematically explore the factor space of a system. Rather than running costly or hazardous physical trials, researchers execute a structured set of virtual experiments across selected factor combinations, then fit a surrogate model to the simulation outputs to understand main effects, interactions, and optimal settings.