পদ্ধতির তুলনা করুন

	বহু-প্রতিক্রিয়া প্রক্রিয়া সক্ষমতা বিশ্লেষণ	পরীক্ষা নকশা
ক্ষেত্র	পরীক্ষামূলক নকশা	পরীক্ষামূলক নকশা
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1993–1994 (foundational multivariate indices)	1935
প্রবর্তক	Taam, Subbaiah & Liddy (multivariate capability); Hubele, Shahriari & Cheng (MCpm)	Ronald A. Fisher
ধরন	Quantitative quality / process assessment method	Experimental planning framework
মৌলিক উৎস	Taam, W., Subbaiah, P., & Liddy, J. W. (1993). A note on multivariate capability indices. Journal of Applied Statistics, 20(3), 339–351.	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
অপর নাম	MRPCA, multivariate process capability, multi-characteristic capability analysis, vector process capability	DOE, experimental design, factorial experimentation, planned experimentation
সম্পর্কিত	6	3
সারসংক্ষেপ	Multi-response process capability analysis extends classical single-response capability indices (Cp, Cpk) to situations where a process must simultaneously satisfy specification limits on two or more correlated quality characteristics. Rather than evaluating each response in isolation, it assesses the joint probability that all characteristics fall within their respective tolerance regions, yielding a more realistic picture of overall process performance in multi-characteristic manufacturing and engineering settings.	Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences.