পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| বহু-প্রতিক্রিয়া প্রক্রিয়া সক্ষমতা বিশ্লেষণ× | বহু-প্রতিক্রিয়া পরীক্ষণ নকশা× | |
|---|---|---|
| ক্ষেত্র | পরীক্ষামূলক নকশা | পরীক্ষামূলক নকশা |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1993–1994 (foundational multivariate indices) | 1980 (desirability function formalization); DoE roots from Fisher, 1920s–1930s |
| প্রবর্তক≠ | Taam, Subbaiah & Liddy (multivariate capability); Hubele, Shahriari & Cheng (MCpm) | Derringer & Suich (desirability function); Montgomery (systematic DoE integration) |
| ধরন≠ | Quantitative quality / process assessment method | Experimental optimization methodology |
| মৌলিক উৎস≠ | Taam, W., Subbaiah, P., & Liddy, J. W. (1993). A note on multivariate capability indices. Journal of Applied Statistics, 20(3), 339–351. link ↗ | Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219. DOI ↗ |
| অপর নাম | MRPCA, multivariate process capability, multi-characteristic capability analysis, vector process capability | Multi-response DoE, Multiple-response optimization, Multi-objective DoE, MRDoE |
| সম্পর্কিত≠ | 6 | 4 |
| 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. | Multi-response Design of Experiments (MRDoE) extends classical DoE to situations where several response variables must be optimized simultaneously. Rather than tuning factors for a single output, the experimenter fits separate regression or response-surface models for each response, then combines them — most often via Derringer and Suich's desirability function — into a single composite score that guides the search for factor settings satisfying all response targets at once. |
| ScholarGateডেটাসেট ↗ |
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