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| Response Surface Methodology (RSM) Aplikasi Industri× | Box-Behnken Design× | |
|---|---|---|
| Bidang | Reka Bentuk Eksperimen | Reka Bentuk Eksperimen |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 1951 (origin); widespread industrial adoption from 1980s onward | 1960 |
| Pengasas≠ | George E. P. Box & K. B. Wilson; industrialized by Douglas Montgomery and colleagues | George E. P. Box and Donald W. Behnken |
| Jenis≠ | Empirical optimization technique | Response surface design (incomplete three-level factorial) |
| Sumber perintis≠ | 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. DOI ↗ |
| Alias | Industrial RSM, RSM for manufacturing, process optimization RSM, industrial response surface analysis | BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design |
| Berkaitan≠ | 5 | 3 |
| Ringkasan≠ | 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. |
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