Statistical Process Optimization
Statistical Process Optimization is a systematic methodology that employs statistical models and experimental design principles to identify optimal operating conditions and enhance performance in bioprocesses by quantitatively analyzing the relationships between input variables and critical quality or productivity outcomes.
1K
Publications
43.2K
Citations
3.4K
Authors
1.1K
Institutions
Publications per year
2017–2026
384
1K
Response Surface Methodology: 1966-1988
Raymond H. Myers, André I. Khuri, Walter H. Carter et al. · Technometrics · 1989 · 598 citations
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3.4K
City of Scientific Research and Technological Applications, Egypt
9 publications · 504 citations
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8
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7
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7
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6
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1–5 of 3.4K
1.1K

University of Delhi
New Delhi, India
14 h-index
43 publications
3K citations
City of Scientific Research and Technological Applications
Alexandria, Egypt
14 h-index
26 publications
1.3K citations
National Research Centre
Giza, Egypt
12 h-index
45 publications
1.1K citations
Pohang University of Science and Technology
Pohang, South Korea
11 h-index
27 publications
826 citations

King Saud University
Riyadh, Saudi Arabia
11 h-index
18 publications
1K citations

Universiti Sains Malaysia
George Town, Malaysia
11 h-index
27 publications
2.2K citations
Carnegie Mellon University
Pittsburgh, United States
10 h-index
17 publications
1.2K citations
University of Technology Malaysia
Johor Bahru, Malaysia
9 h-index
27 publications
930 citations
1–8 of 1.1K
23 publications · 1.6K citations
22
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30 publications · 2.4K citations
22
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16 publications · 1K citations
14
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19 publications · 1.2K citations
14
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13 publications · 657 citations
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