So sánh phương pháp

	Ứng dụng công nghiệp của Phương pháp Bề mặt Đáp ứng	Thiết kế Box-Behnken
Lĩnh vực	Thiết kế thí nghiệm	Thiết kế thí nghiệm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1951 (origin); widespread industrial adoption from 1980s onward	1960
Người khởi xướng	George E. P. Box & K. B. Wilson; industrialized by Douglas Montgomery and colleagues	George E. P. Box and Donald W. Behnken
Loại	Empirical optimization technique	Response surface design (incomplete three-level factorial)
Công trình gốc	Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (4th ed.). Wiley. ISBN: 978-1118916018	Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.
Tên gọi khác	Industrial RSM, RSM for manufacturing, process optimization RSM, industrial response surface analysis	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
Liên quan	5	3
Tóm tắt	Industrial Applications Response Surface Methodology (RSM) applies the classical Box-Wilson response surface framework to manufacturing and process engineering problems. It builds an empirical polynomial model linking controllable process inputs — such as temperature, pressure, feed rate, or catalyst concentration — to one or more quality responses, then mathematically locates the input settings that optimize those responses. It is the de-facto standard statistical tool for process characterization and optimization in chemical, mechanical, food, materials, and pharmaceutical manufacturing.	The Box-Behnken design (BBD) is an efficient response surface methodology design that fits a full second-order polynomial model using three levels of each factor. Introduced by Box and Behnken in 1960, it places experimental points at the midpoints of the edges of a hypercube and at the center, avoiding the corner points where all factors are simultaneously at their extreme levels. This structure makes BBD particularly attractive when extreme-level combinations are physically impossible, costly, or unsafe to test.