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Modern methods are optimization-based, using for example Mixed Integer Non-Linear Programming (MINLP) formulation to optimize a process superstructure.
The problem of how to optimize a process based on many parameters can be likened to locating the peak of a mountain range.
Other methodologies, in the form of algorithms, may be used to optimize a process.
To optimize a process like the photocatalytic degradation process, it is essential to study all factors influencing the process.
This work describes the use of factorial design to optimize a process for the preparation of nanostructured lipid carriers (NLC) based on cetyl palmitate and capric/caprylic triglycerides as structural lipids and Pluronic 68 as the colloidal stabilizer, for delivery of the local anesthetics lidocaine and prilocaine (both at 2.5%).
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Generally, these instruments are used for the control of the industrial process or service, but they could be used in an innovative way to control and to optimize a particular process: the technology transfer process.
The vector must be designed to optimize a desired process.
To optimize a formulation process, various experimental design methods can be used [15, 16].
Design of experiment (DOE) has long been recognized as a powerful method to optimize a complex process in industry.
In this work, the response-surface methodology (RS M was applied to optimize a biostimulation process for a hydrocarbon-contaminated Antarctic soil, considering a Carbon:Nitrogen:Phosporus (C N P) ratio of 100 10 1 as a reference.
With the advantage of statistical design (RSM), it provides an alternative methodology to optimize a particular process by considering the mutual interactions among the factors and to give an estimate of the combined effects of these factors on the final results, which could lead to simplification of process optimization and cheaper production costs.
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