Systematic experimental design and analysis for cell culture studies.

Experiments are conducted extensively around the world in the field of science and engineering, usually to discover and elucidate information and performance of processes or systems. A well-designed experiment is the crux to improved process yields, improved consistency and a closer conformance to o...

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Bibliographic Details
Main Author: Tan, Royston Heng Chye.
Other Authors: Lim Mayasari
Format: Theses and Dissertations
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/54341
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Institution: Nanyang Technological University
Language: English
Description
Summary:Experiments are conducted extensively around the world in the field of science and engineering, usually to discover and elucidate information and performance of processes or systems. A well-designed experiment is the crux to improved process yields, improved consistency and a closer conformance to optimal or desired criteria, and reduced in overall development cost and time. Design of Experiments (DOE) is a carefully planned and efficient approach used in the quality control for planning, analyzing and interpreting sets of experiments, targeted at maximizing the amount of information gained, while keeping the resources used at a minimal. Factorial designs have been shown to be superior as compared to the commonly employed One-Factor-at-a-Time designs. Factorial designs increase the efficiency in which experiments can be conducted by reducing the number of runs required, which leads to a reduction in time and resources required, which is highly desired in the world of research and development whereby resources are limited and costly. Furthermore, Factorial designs also consider the possible interactions between factors which are highly desirable as it is very common for factors to have influences on one another. These fundamental principles and application of Factorial designs have been clearly explored in this paper and readers should understand the effectiveness of Factorial designs and apply it in their experiments. This paper may serves as a starting platform for students working on their school experiments as well as experimenters who are new to Factorial designs.