Quality By Design
Quality By Design - Related Videos
06:42
From Theory to Design: The Role of Creativity in Designing Experiments
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2023
Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University Research studies come into being when a researcher speculates about human thought, emotions, or behavior, and has a theory that offers a potential explanation. Often the researcher’s theory is firmly situated in everyday common experiences that may not naturally lend themselves to direct empirical study. For example, researchers speculated that perception of a person on Facebook is influenced by...
02:01
Group Design
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2020
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to...
02:01
Factorial Design
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2020
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
07:51
Fabrication of Silica Ultra High Quality Factor Microresonators
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Cited by 22 •
2012
We describe the use of a carbon dioxide laser reflow technique to fabricate silica resonant cavities, including free-standing microspheres and on-chip microtoroids. The reflow method removes surface imperfections, allowing long photon lifetimes within both devices. The resulting devices have ultra high quality factors, enabling applications ranging from telecommunications to biodetection.
01:27
Service Quality
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2024
Service quality is essential for customer satisfaction and loyalty. To effectively meet customer expectations, focus on aspects like tangibles, reliability, responsiveness, assurance, and empathy. Tangibles are the physical aspects of a service that customers interact with. For instance, the design and cleanliness of a hotel lobby or the professionalism of the staff's attire contribute to a customer's overall impression. A well-maintained environment and transparent, visually appealing...
FAQs
Critical quality attributes provide the target characteristics that a chemical product must meet. Quality By Design connects these attributes to critical material attributes, such as relevant properties of starting or formulation materials, and to critical process parameters, meaning process settings that can affect quality. This linkage helps teams identify which inputs and operations require the strongest understanding and control.
Risk assessment helps prioritize the material attributes and process parameters most likely to influence product quality, while process understanding explains how those factors produce their effects. Together, they direct experimental work toward meaningful sources of variability rather than treating every factor equally. The result is a more focused development program and a stronger basis for consistent manufacturing decisions.
A design space summarizes the combinations of material attributes and process parameters understood to support the predefined quality objectives. Operating within this scientifically established range can make the process more robust against expected variability. It also provides a basis for the control strategy, linking development knowledge to practical decisions about how the process should be managed.
End-product testing evaluates quality after production, whereas Quality By Design builds quality knowledge into formulation and process development. By examining causes of variability and their relationships to quality attributes, the approach supports prevention and control of failures rather than depending primarily on detection afterward. This lifecycle perspective also preserves useful process knowledge beyond a single finished-product result.
A typical application begins by defining quality objectives and identifying critical quality attributes. Developers then assess risks, examine critical material attributes and critical process parameters, and use experiments to clarify their relationships. The resulting process understanding supports a design space and control strategy. These elements guide development, manufacturing, and later quality decisions throughout the product lifecycle.
Experiments test how selected material attributes and process parameters influence critical quality attributes. Their purpose is not simply to generate measurements, but to build evidence about process relationships and sources of variability. When combined with risk assessment, experimental findings help refine the design space and identify which factors need tighter control for reliable chemical product quality.
In chemistry, QbD supports formulation and process development by connecting chemical materials, operating conditions, and product quality objectives. It can reduce variability and failures by emphasizing understanding and control during development instead of relying mainly on final testing. The documented scientific rationale also strengthens regulatory knowledge and supports informed quality decisions across the product lifecycle.