পদ্ধতির তুলনা করুন

	ঝুঁকি-ভিত্তিক সেন্ট্রাল কম্পোজিট ডিজাইন	বক্স-বেঙ্কেন ডিজাইন
ক্ষেত্র	পরীক্ষামূলক নকশা	পরীক্ষামূলক নকশা
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1951 (CCD); risk-based integration emerged in applied engineering literature from the 1990s onward	1960
প্রবর্তক	Foundational CCD: George E. P. Box & K. B. Wilson (1951); risk integration adapted from engineering risk analysis traditions	George E. P. Box and Donald W. Behnken
ধরন	Experimental design with integrated risk assessment	Response surface design (incomplete three-level factorial)
মৌলিক উৎস	Box, G. E. P., & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society: Series B, 13(1), 1–45.	Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475.
অপর নাম	Risk-informed CCD, CCD with risk assessment, Uncertainty-aware central composite design, Risk-integrated RSM	BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design
সম্পর্কিত	5	3
সারসংক্ষেপ	Risk-based Central Composite Design (Risk-based CCD) integrates formal risk identification and uncertainty quantification into the classical CCD framework. By coupling the rotatable second-order experimental structure of CCD with probabilistic risk metrics, engineers and scientists can simultaneously optimize process responses and characterize the risk of unacceptable outcomes — making it particularly valuable in regulated industries such as pharmaceuticals, chemical engineering, and advanced 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.