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Tuan-Ho Le,신상문 한국품질경영학회 2018 품질경영학회지 Vol.46 No.1
Purpose: For more than 30 years, robust parameter design (RPD), which attempts to minimize the process bias (i.e., deviation between the mean and the target) and its variability simultaneously, has received consistent attention from researchers in academia and industry. Based on Taguchi’s philosophy, a number of RPD methodologies have been developed to improve the quality of products and processes. The primary purpose of this paper is to review and discuss existing RPD methodologies in terms of the three sequential RPD procedures of experimental design, parameter estimation, and optimization. Methods: This literature study composes three review aspects including experimental design, estimation modeling, and optimization methods. Results: To analyze the benefits and weaknesses of conventional RPD methods and investigate the requirements of future research, we first analyze a variety of experimental formats associated with input control and noise factors, output responses and replication, and estimation approaches. Secondly, existing estimation methods are categorized according to their implementation of least-squares, maximum likelihood estimation, generalized linear models, Bayesian techniques, or the response surface methodology. Thirdly, optimization models for single and multiple responses problems are analyzed within their historical and functional framework. Conclusion: This study identifies the current RPD foundations and unresolved problems, including ample discussion of further directions of study.
Ample Discussions on Robust Design Modeling and Optimization
Tuan-Ho Le,Thanh-Tra Hoang,Sangmun Shin(신상문) 한국경영과학회 2013 한국경영과학회 학술대회논문집 Vol.2013 No.5
Robust design (RD) based on Taguchi’s philosophy is to improve the quality of products and processes by reducing noise factors’ effects. For more than two decades, a number of RD methods have been received constant attentions from many researchers and practitioners. In this paper, ample discussions for RD methods are demonstrated by categorizing three RD stages, such as experimental design, estimation, and optimization. In experimental design stage, a number of experiment formats associated with control and noise factors are discussed in order to investigate existing problems and further research directions. Also, many RD estimation methods (i.e., response surface methodology (RSM), maximum likelihood estimation (MLE), and Bayesian approach) reported in literature are introduced. Finally, analyses of historical and functional development of optimization models for single and multiple responses problems are summarized in this paper.
Ample Discussions on Robust Design Modeling and Optimization
Tuan-Ho Le,Thanh-Tra Hoang,Sangmun Shin(신상문) 대한산업공학회 2013 대한산업공학회 춘계학술대회논문집 Vol.2013 No.5
Robust design (RD) based on Taguchi’s philosophy is to improve the quality of products and processes by reducing noise factors’ effects. For more than two decades, a number of RD methods have been received constant attentions from many researchers and practitioners. In this paper, ample discussions for RD methods are demonstrated by categorizing three RD stages, such as experimental design, estimation, and optimization. In experimental design stage, a number of experiment formats associated with control and noise factors are discussed in order to investigate existing problems and further research directions. Also, many RD estimation methods (i.e., response surface methodology (RSM), maximum likelihood estimation (MLE), and Bayesian approach) reported in literature are introduced. Finally, analyses of historical and functional development of optimization models for single and multiple responses problems are summarized in this paper.
LeAnh, Tuan,Tran, Nguyen H.,Saad, Walid,Le, Long Bao,Niyato, Dusit,Ho, Tai Manh,Hong, Choong Seon IEEE 2017 IEEE Transactions on Vehicular Technology VT Vol.66 No.9
<P>In this paper, a novel framework is proposed to jointly optimize user association and resource allocation in the uplink cognitive femtocell network (CFN). In the considered CFN, femtocell base stations (FBSs) are deployed to serve a set of femtocell user equipments (FUEs) by reusing subchannels used in a macrocell base station (MBS). The problem of joint user association, subchannel assignment, and power allocation is formulated as an optimization problem, in which the goal is to maximize the overall uplink throughput while guaranteeing FBSs overloading avoidance, data rate requirements of the served FUEs, and MBS protection. To solve this problem, a distributed framework based on the matching game is proposed to model and analyze the interactions between the FUEs and FBSs. Using this framework, distributed algorithms are developed to enable the CFN to make decisions about user association, subchannel allocation, and transmit power. The algorithms are then shown to converge to a stable matching and exhibit a low computational complexity. Simulation results show that the proposed approach yields a performance improvement in terms of the overall network throughput and outage probability, with a small number of iterations to converge.</P>
김민채,Tuan-Ho Le,Cheng Bao,김진태,전향숙,신상문,이홍진 한국식품과학회 2017 Food Science and Biotechnology Vol.26 No.6
To provide a platform for evaluating significant interactions contributing to the enhanced physiological efficacy and reduced hepatotoxicity, we used a robust design to determine the optimal combination of six major green tea catechins, epigallocatechin gallate (EGCG), epigallocatechin (EGC), epicatechin gallate (ECG), epicatechin (EC), gallocatechin, and catechin. Based on the mixture design, 28 experiments were performed to inhibit nitric oxide (NO) in RAW 264.7 cells and hepatotoxicity in Chang liver cells. Significant candidates, EGCG, EC, gallocatechin and catechin, were selected after optimization. The combination showing simultaneous enhancement of NO inhibition and reduction of hepatotoxicity was EGCG and gallocatechin at a ratio of 0.65 to 0.35 by surface response methodology and desirability function, through which their co-treatment was validated. Here, we describe a platform for simultaneously determining the optimized combination of natural components exerting enhanced efficacy and reduced toxicity.
( Gyuhyo Choi ),( Tuan-ho Le ),( Sangmun Shin ) 한국품질경영학회 2015 한국품질경영학회 학술대회 Vol.2015 No.2
Purpose: Food and Drug Administration (FDA) and European Medicines Agency (EMA) have revised and proposed new tighten regulations based on quality by design (QbD) in order to improve drug quality and safety. This design space generated by design of experiment (DoE) methods is significantly required to successfully perform QbD. Although many examples for the design space have reported in literature, there is room for improvement associated with multidimensional perspectives normal acceptable ranges (i.e., safe operating conditions) of input factors. Therefore, the motivation of this paper is to propose an alternative identification method for generating a multidimensional safe design space on a quality oriented drug development process. Methodology/Approach: First of all, functional relationships between input factors and their associated output responses are exploited and estimated by using response surface methodology (RSM). While customizing statistical confidence and prediction intervals for RSM, the normal acceptable ranges can also be obtained. Next, a multidimensional safe design space is then generated on the overlay contour plot with the importance of input factors. Finally, a case study for a drug development process is performed for verification purposes. Findings: A new multidimensional design space identification method based on normal acceptable ranges is proposed in order to identify the safe operating conditions of input control factors. As results, the proposed safe design space provided significantly small variability of output responses. Also, within this safe design space, the quality of drug product can be consistently controlled. Research Limitation/implication: As the number of input control factors increase dramatically, the safe design space cannot be obtained because of high dimensionality. For further study, a weight assignment method regarded as this dimensionality problem can be investigated. Originality/Value of paper: The proposed multidimensional design space identification method provides significant drug quality improvement results, such as variability reduction, statistical reliability, and reproducibility of quality characteristics. This proposed method includes a new application of statistical inferences associated with RSM and Design of experiment (DoE). This is the first attempt in the QbD literature.