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Process Optimization: A Statistical Approach Enrique del Castillo

• Authors : Myers, Donald E.

• Source: SIAM Review, 2008 Sep 01. 50(3), 615-620.

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Advancing Monoclonal Antibody Manufacturing: Process Optimization, Cost Reduction Strategies, and Emerging Technologies

• Authors : Ranbhor,Ranjit

Subjects: Biologics: Targets and Therapy

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Machine learning in gel-based additive manufacturing: from material design to process optimization

• Authors : Zhang, Zhizhou; Wang, Yaxin; Wang, Weiguang

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Enzymatic Routes for Chiral Amine Synthesis: Protein Engineering and Process Optimization

• Authors : Vikhrankar,Sayali; Satbhai,Seema; Kulkarni,Priyanka

Subjects: Biologics: Targets and Therapy

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Diverse Approaches in Wet-Spun Alginate Filament Production from the Textile Industry Perspective: From Process Optimization to Composite Filament Production

• Authors : Var, C.; Palamutcu, S.

Subjects: alginate filament; textile; wet spinning

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Enhancing microalgal lipid accumulation for biofuel production

• Authors : Zhu, Zhi, Author; Sun, Jing, Author; Fa, Yun, Author ...

Subjects: microalgae; lipid enhancement; biofuel production

• Source: Frontiers in Microbiology. 13

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Data Analytics and Machine Learning: Navigating the Big Data Landscape.

• Authors : Sloboda, Brian W.

Subjects: MACHINE learning; BIG data; BUSINESS analytics

• Source: International Statistical Review; Apr2025, Vol. 93 Issue 1, p179-182, 4p

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Current approaches to digital twins in additive manufacturing:a systematic literature review

• Authors : Tudorache, Leonard; Babur, Önder; Lucas, Sandra S.

Subjects: Digital twin; 3D printing; Additive manufacturing

• Source: Tudorache, L, Babur, Ö, Lucas, S S & van den Brand, M G J 2025, 'Current approaches to digital twins in additive manufacturing : a systematic literature review', Progress in Additive Manufacturing,

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Upcycling and recycling of spent battery waste for a sustainable future: Progress and perspectives

• Authors : Bin Abu Sofian, Abu Danish Aiman; Majid, S. R.; Kang, Kisuk ...

Subjects: LITHIUM-ION BATTERIES; VALUABLE METALS; HYDROMETALLURGICAL PROCESS

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Data-driven CFRP machining performance prediction and optimization: advances, challenges and future prospects

• Authors : Ge, Jia; Zhang, Jiduo; Xu, Moran

Subjects: CFRP machining; data-driven method; defects prediction

• Source: Ge, J, Zhang, J, Xu, M, Wu, M, Yao, Z, Fu, G, Zhang, W, Falzon, B G, Catalanotti, G, Xu, J, Jin, Y & Sun, D 2025, 'Data-driven CFRP machining performance prediction and

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