Statistical Approaches With Emphasis on Design of Experiments Applied to Chemical Processes

10.5772/65616 ◽  
2018 ◽  
Keyword(s):  
Design Of Experiments ◽  
Chemical Processes ◽  
Statistical Approaches

scholarly journals Optimal Design of Laboratory and Pilot-plant Experiments using Multiobjective Optimization

2021 ◽  
Author(s):  
Esther Forte ◽  
Erik von Harbou ◽  
Jakob Burger ◽  
Norbert Asprion ◽  
Michael Bortz
Keyword(s):  
Experimental Design ◽  
Optimal Design ◽  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Pilot Plant ◽  
Pareto Frontier ◽  
Trade Offs ◽  
Interesting Part ◽  
Conflicting Objectives ◽  
Statistical Approaches

Performing an experimental design prior to the collection of data is in most circumstances important to ensure efficiency. The focus of this work is the combination of model‐based and statistical approaches to optimal design of experiments. The knowledge encoded in the model is used to identify the most interesting range for the experiments via a Pareto optimization of the most important conflicting objectives. Analysis of the trade‐offs found is in itself useful to design an experimental plan. This can be complemented using a factorial design in the most interesting part of the Pareto frontier.

scholarly journals Optimal Design of Laboratory and Pilot-plant Experiments using Multiobjective Optimization

2018 ◽  
Author(s):  
Ester Forte ◽  
Erik von Harbou ◽  
Jakob Burger ◽  
Michael Bortz ◽  
Norbert Asprion
Keyword(s):  
Experimental Design ◽  
Optimal Design ◽  
Multiobjective Optimization ◽  
Design Of Experiments ◽  
Pilot Plant ◽  
Pareto Frontier ◽  
Trade Offs ◽  
Interesting Part ◽  
Conflicting Objectives ◽  
Statistical Approaches

Performing an experimental design prior to the collection of data is in most circumstances important to ensure efficiency. The focus of this work is the combination of model‐based and statistical approaches to optimal design of experiments. The knowledge encoded in the model is used to identify the most interesting range for the experiments via a Pareto optimization of the most important conflicting objectives. Analysis of the trade‐offs found is in itself useful to design an experimental plan. This can be complemented using a factorial design in the most interesting part of the Pareto frontier.

Design of experiments in liquid chromatography (HPLC) analysis of pharmaceuticals: analytics, applications, implications and future prospects

2017 ◽  
Vol 36 (3) ◽  
Author(s):  
Saurabh B. Ganorkar ◽  
Atul A. Shirkhedkar
Keyword(s):  
Liquid Chromatography ◽  
Design Of Experiments ◽  
Pharmaceutical Analysis ◽  
High Performance ◽  
Hplc Analysis ◽  
Future Prospects ◽  
Statistical Approaches ◽  
Statistical Designs ◽  
Fine Tune

AbstractThis review presents the essential brief annals, crucial analytics, precise applications and noteworthy implications of design of experiments which enrouted to liquid chromatography (LC) in the midst of utmost focus on high-performance liquid-chromatography (HPLC) and broadened its impressions on allied techniques in pharmaceutical analysis. Being most widely applied statistical methodologies for such purpose, its use was started in 1970 and heightened after Fischer’s precious input in 1981. The persistent use of statistical approaches one after another led to the efficient attention of pharmaceutical analysts. Hence, in order to fine-tune the trail impressed by the cumulative trends, the use of statistical designs in HPLC analysis has been reviewed and efforts were made to recognize its relative impact and corresponding future prospects. Applications of precise methodologies have been reassessed with respect to the need established by recent regulatory perspectives with a fanatical and the consequent stance on prominent historical advancements and concrete purposes. An effort was also made to state an arbitrary classification of diverse design types and succinct line of application in LC and associated analyses.

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