A Review of Analysis of Dynamic Response in Design of Experiments

He, Zhen; Panpan, Zhou; Zhang, Min; Goh, T. N.

doi:10.1002/qre.1627

Cited by 9 publications

(2 citation statements)

References 53 publications

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“…However, among the most widely used are the Ishikawa's Fishbone Diagram (Figure 3) and the Failure Mode and Effects Analysis (FMEA), which are thoroughly explained to the students in Drug Analysis courses [48,50,51]. In addition, DoE allows researchers to use their knowledge regarding the product and/or process instead of merely applying the commonly known "trial and error" [52,53]. DoEs are used to organize, conduct and interpret results of experiments in an efficient way, guaranteeing the collection of the greatest possible amount of useful information through the execution of a small number of tests.…”

Section: Quality By Design Approach For Industrial Pharmacy In the Ac...mentioning

confidence: 99%

Quality by Design: A Suitable Methodology in Industrial Pharmacy for Costa Rican Universities

Henríquez¹,

Murillo-Castillo²,

Ramírez-Arguedas³

et al. 2022

Preprint

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The aim of this review is to present the Quality by Design (QbD) model as a suitable methodology to perform research in the academic Costa Rican institutions that teach Pharmacy. Pubmed, Science Direct, and Google Scholar databases were screened for original and review papers, as well as short communications published not more than 10 years ago. Publications were screened by title and abstract. Relevant references were used to develop three important themes: The University’s Research Model in Costa Rica, QbD Model, and QbD as a Research Methodology for Industrial Pharmacy in the Academy. In this sense, the QbD model is a great methodology for carrying out research projects regarding Pharmaceutical Sciences but especially for Drug Development. Academic research based on this model enables training and developing practical, scientific, and leadership skills in pharmacy students. The generated knowledge can be shared in the classrooms, which represents an ideal environment to communicate their research results and to foster collaborative work between researchers, professors, and students. The participation of all these actors allows a high level of commitment to research work, which benefits the scientific advancement of the university and society. It is important to visualize the student body as potential key actors in the research process, encouraging in them the desire to become trained scientific researchers who want to pursue a career in the academy, giving continuity to it.

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Section: Quality By Design Approach For Industrial Pharmacy In the Ac...mentioning

confidence: 99%

Quality by Design: A Suitable Methodology in Industrial Pharmacy for Costa Rican Universities

Henríquez¹,

Murillo-Castillo²,

Ramírez-Arguedas³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Industries have, therefore, all the time more highlighted building up measures competent of concurrently optimizing the multi-response dynamic systems in the light of the increasing complexity of modern product design. To deal with the requirements of the contemporary industries, more than a few studies have (Tong et al, 2002;Tong et al, 2004;Hsieh et al, 2005;Wang and Tong, 2005;Wu and Yeh, 2005;Chang, 2006;Wang, 2007;Wu, 2007;Chang, 2008;Tong et al, 2008;Wu, 2009;Zhong and Liu, 2009;Chang and Chen, 2011;Wang et al, 2011;Sharma et al, 2012;Gauri, 2014;Zhang et al, 2014;Wu, 2015;He et al, 2015;Bashiri et al, 2016) have proposed different procedures for optimizing a multi-response dynamic system. Applying the two-step procedure is not feasible for optimizing a multi-response dynamic system because it is almost impossible to find out any control factor that may be considered as an adjustment factor.…”

Section: Introductionmentioning

confidence: 99%

Optimization of multi-response dynamic systems integrating multiple regression and Taguchi’s dynamic signal-to-noise ratio concept

Pal¹,

Gauri²

2017

Int. J. Eng. Sci. Tech

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The principal difference between a dynamic and a static system is that the former includes a signal factor for expressing the intended output while the later does not. Assuming a linear association exists between the response and signal variables, Taguchi offered a two-stage route for optimizing a dynamic system: maximize the dynamic signal-to noise ratio (DSN) and then, change the gradient to the desired gradient by a suitable modification parameter. Some researchers have indicated limitations to Taguchi's DSN analysis, and advocated alternative approaches for optimization of a dynamic system. However, the Taguchi method as well as these alternative approaches is useful for optimizing a single-response dynamic system only. In realism, the majority of the contemporary manufacturing practices encompass numerous response variables as well as industries demand for developing procedures for optimizing multi-response dynamic system. This paper proposes a novel procedure that integrates multiple regression (MR) technique and Taguchi's DSN concept to optimize the multi-response dynamic system. In this method, appropriate multiple regression equations according to a chosen model for dynamic system are fitted first based on the observed experimental data and then DSN (called MRDSN) for different response variables are computed using the MRbased predicted values. Finally, weighted MRDSN is considered as the objective function for the optimization. The proposed procedure is investigated with respect to three modelling approaches for the dynamic systems. The results of analysis reveal that the proposed procedure with response modelling approach results in the best optimization performance. It also results in better optimization performance than back-propagation neural network-based approach and data mining-based approach reported by the past researchers.

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Robust functional response-based metamodel optimization considering both location and dispersion effects for aeronautical airfoil designs

Han

Ouyang

2021

Struct Multidisc Optim

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A Review of Analysis of Dynamic Response in Design of Experiments

Cited by 9 publications

References 53 publications

Quality by Design: A Suitable Methodology in Industrial Pharmacy for Costa Rican Universities

Quality by Design: A Suitable Methodology in Industrial Pharmacy for Costa Rican Universities

Optimization of multi-response dynamic systems integrating multiple regression and Taguchi’s dynamic signal-to-noise ratio concept

Robust functional response-based metamodel optimization considering both location and dispersion effects for aeronautical airfoil designs

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