Statistical methods are becoming increasingly vital for pharmaceutical manufacturers. Design of experiments (DOE) is a primary tool for determining the relationship between the factors that have an effect on a process and the response of that process.
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Design of experiments (DOE) is a powerful technique for process optimization that has been widely deployed in almost all types of manufacturing processes and is used extensively in product process design and development. There have not been as many efforts to apply powerful quality improvement techniques such as DOE to improve non-manufacturing processes. Factor levels often involve changing the way people work and so have to be handled carefully. It is even more important to get everyone working as a team. This paper explores the benefits and challenges in the application of DOE in non-manufacturing arena.
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The TRW team used a combination of DOE (response surface methodology RSM) and Monte Carlo analysis to optimize a braking system where one of the objectives was to quickly generate pressure when demanded by the vehicle stability control system.
FLSmidth recently installed two turnkey SuperCell flotation machines the world's largest flotation cells at Rio Tinto's Kennecott Utah Copper concentrator near Salt Lake City, Utah. They used DOE to substantially reduce the amount of testing and fine-tuning required after installation.
DOE was used to determine the optimum setting conditions for three components leading to a high Hg Yield at a lower temperature.
RTP Company, which compounds custom engineered thermoplastics, used Design-Expert software to determine which injection molding process conditions would optimize conductive properties for a particular material. Their DOE made it possible to explore the complete processing space and provided users with a formula to calculate the conditions that would deliver the required resistivity levels.
In this presentation design of experiments (DOE) was applied to a chemical process. DOE together with computer modeling lead to a better understanding of the process and the defining of new conditions.
Statistical methods are becoming increasingly important for the pharmaceutical industry. The FDA and other regulatory and standard-setting organizations are moving swiftly to establish Quality by Design (QbD) guidance relevant to the needs of pharmaceutical manufacturing. The FDA suggests the use of design of experiments (DoE) because it provides a structured, organized method for determining the relationship between factors affecting a process and the response of that process.