Academic literature on the topic 'Confounded fractional factorials design'

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Journal articles on the topic "Confounded fractional factorials design"

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Kramer, Keith E., and G. Morris Southward. "Fractional Factorials in Psychology: An: Examination of the Basis for the Holistic Approach." Proceedings of the Human Factors Society Annual Meeting 29, no. 10 (October 1985): 924–26. http://dx.doi.org/10.1177/154193128502901005.

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Statistical methods and experimental designs are used by the researcher to collect and analyze data. One of the most commonly used treatment designs is the analysis of variance. Simon (1976) has examined data from fourteen years of experiments published in the Human Factors journal that were analyzed using this approach. One of his conclusions is that interactions of three or more variables are negligible. To take advantage of this Simon (1973, 1977) has proposed using fractional factorials in psychological research. This investigation examined Simon's analysis and conclusions and questions the use of fractional factorials without proper theoretical justification. An empirical investigation of fractional factorials using computer simulation techniques examined the effect of confounding when the assumption that high order interactions are negligible is violated. The results show that in certain cases biases of unconfounded and confounded effects can result.
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Dülmer, Hermann. "The Factorial Survey." Sociological Methods & Research 45, no. 2 (April 27, 2015): 304–47. http://dx.doi.org/10.1177/0049124115582269.

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The factorial survey is an experimental design consisting of varying situations (vignettes) that have to be judged by respondents. For more complex research questions, it quickly becomes impossible for an individual respondent to judge all vignettes. To overcome this problem, random designs are recommended most of the time, whereas quota designs are not discussed at all. First comparisons of random designs with fractional factorial and D-efficient designs are based on fictitious data, first comparisons with fractional factorial and confounded factorial designs are restricted to theoretical considerations. The aim of this contribution is to compare different designs regarding their reliability and their internal validity. The benchmark for the empirical comparison is established by the estimators from a parsimonious full factorial design, each answered by a sample of 132 students (real instead of fictitious data). Multilevel analyses confirm that, if they exist, balanced confounded factorial designs are ideal. A confounded D-efficient design, as proposed for the first time in this article, is also superior to simple random designs.
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Rosenbaum, Paul R. "Dispersion Effects from Fractional Factorials in Taguchi's Method of Quality Design." Journal of the Royal Statistical Society: Series B (Methodological) 56, no. 4 (November 1994): 641–52. http://dx.doi.org/10.1111/j.2517-6161.1994.tb02005.x.

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KUMAR, PRAKASH, KRISHAN LAL, ANIRBAN MUKHERJEE, UPENDRA KUMAR PRADHAN, MRINMOY RAY, and OM PRAKASH. "Advanced row-column designs for animal feed experiments." Indian Journal of Animal Sciences 88, no. 4 (January 5, 2023): 499–503. http://dx.doi.org/10.56093/ijans.v88i4.78895.

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Inappropriate statistical designs may misinterpret results of animal feed experiments. Thus complete statistical designs can make animal feed research more appropriate and cost effective. Usually factorial row-column designs are used when the heterogeneity in the experimental material is in two directions and the experimenter is interested in studying the effect of two or more factors simultaneously. Attempts have been to develop the method of construction of balanced nested row column design under factorial setup. Factorial experiments are used in designs when two or more factors have same levels or different levels. The designs that are balanced symmetric factorials nested in blocks are called block designs with nested row-column balanced symmetric factorial experiments. These designs were constructed by using confounding through equation methods.Construction of confounded asymmetrical factorial experiments in row-column settings and efficiency factor of confounded effects was worked out. The design can be used in animal feed experiment with fewer resources by not compromising the test accuracy.
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RIBEIRO, Paulo César Moraes, Matheus Pena CAMPOS, Leila Aparecida Salles PIO, and Júlio Sílvio de Sousa BUENO FILHO. "FRACTIONAL FACTORIALS IN A CASE STUDY NUTRITION EXPERIMENT WITH BANANA TREES." REVISTA BRASILEIRA DE BIOMETRIA 37, no. 3 (September 26, 2019): 335. http://dx.doi.org/10.28951/rbb.v37i3.402.

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In this paper we study combining designs concatenating levels from a full factorial for some factors with screening alternatives for the others. This was done to deal with a practical situation in plant nutrition experiments. The original problem was a study design for 14 potential factors in banana tree nutrition, and researchers imagined four full factorials were needed to test their hypothesis, being two from the 33 and two of the 34 series. As this would demand at least 216 experimental units and facing limited resources we seek for a different planning strategy. The idea was to combine in the same experiment four instances of DSD (Denitive Screening Designs) for 10 three-level factors, each in a different block, with a fraction of the full factorial of the 34 series. A central point treatment, with average level for all factors, was present in all blocks. Interchange algorithms were used to concatenate the factor levels. Resulting optimized design was compared to the designs sampled following the same principle. Design comparison criterion was the expected average variance of the estimates for factors (Ar optimality). Optimization reduced 4.02% of the average values of the criterion in a reference population of sampled designs. It was possible to show that the variance for linear and quadratic effects in the full factorial were higher than in the optimized plan. As an example, the analysis of an actual eld trial is presented. Authors recommend the use of fractional factorial strategy including DSD designs in agronomic trials, specially in the screening phase.
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Rajarathinam, A., A. Radhika, and C. C. Gujarathi. "CONSTRUCTION OF SOME BALANCED BINARY VARIANCE BALANCED BLOCK DESIGN BASED ON FRACTIONAL FACTORIALS." Far East Journal of Theoretical Statistics 52, no. 1 (March 18, 2016): 17–33. http://dx.doi.org/10.17654/ts052010017.

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Dwornicka, Renata, and Jacek Pietraszek. "The outline of the expert system for the design of experiment." Production Engineering Archives 20, no. 20 (September 1, 2018): 43–48. http://dx.doi.org/10.30657/pea.2018.20.09.

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Abstract The design of experiment (DoE) is a methodology originated from early 1920s when Fisher’s papers created the analysis of variance and first known experimental designs: latin squares. It is focused on a construction of empirical models based on measurements obtained from specifically structured and driven experiments. Its development resulted in the constitution of four distinctive branches recognized by the industry: factorials (full or fractional), Taguchi’s robust design, Shainin’s Red-X®and a response surface methodology (RSM). On one hand, the well-known success stories of this methodology implementations promise great benefits, while on other hand, the mathematical complexity of mathematical and statistical assumptions very often lead to improper use and wrong inferences. The possible solution to avoid such mistakes is the expert system supporting the design of experiments and subsequently the analysis of obtained data. The authors propose the outline of such system and provides the general analysis of the ontology and related inference rules.
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Bisgaard, Soren. "A Comparative Analysis of the Performance of Taguchi's Linear Graphs for the Design of Two-Level Fractional Factorials." Applied Statistics 45, no. 3 (1996): 311. http://dx.doi.org/10.2307/2986090.

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U, Ali H., Lasisi K. E., and Nwaosu S. C. "Comparing The Performance of Bayesian And Frequentist Analysis Methods of Irregular Fractional Factorials Using Design Based optimality And Efficiency Criteria." IOSR Journal of Mathematics 13, no. 03 (July 2017): 68–72. http://dx.doi.org/10.9790/5728-1303056872.

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Zhang, Hui, David Bourell, Yanling Guo, Xiaodong Zhang, Yu Zhuang, Yueqiang Yu, Kaiyi Jiang, and Wasim M. K. Helal. "Study on laser sintering of pine/co-PES composites and the investment casting process." Rapid Prototyping Journal 25, no. 8 (September 9, 2019): 1349–58. http://dx.doi.org/10.1108/rpj-01-2019-0019.

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Purpose A pine/co-PES composite (PCPES composite) was proposed as the feedstock for powder bed fusion (laser sintering, LS). This paper aims to provide some necessary experimental data and the theoretical foundation for LS of pine/co-PES, especially for the application of using the laser-sintered pine/co-PES parts as complex structural patterns in investment casting. Design/methodology/approach The PCPES composites with different pine loadings were mixed mechanically. The composite’s preheating temperature and processing temperature during LS were determined experimentally based on the material’s thermal behavior. The effects of pine powder on the binding mechanism of PCPES composites were discussed through analyzing the microstructure of the laser-sintered parts’. Mechanical properties and dimensional precision of laser-sintered PCPES parts in different pine loadings were tested, and the parts’ mechanical properties were strengthened by wax-infiltration post-processing. The influence extents of process parameters on the mechanical properties of laser-sintered 20 Wt.% pine/co-PES parts were investigated using a 1/2 fractional factorials experiment. Findings 20 Wt.% pine/co-PES is considered to be a promising wood-plastic composite for laser sintering. The relationship between mechanical strength of its laser-sintered parts and process parameters was built up using mathematical formulas. Experimental results show density, tensile strength, flexural strength and surface roughness of laser-sintered 20 Wt.% pine/co-PES parts are improved by 72.7-75.0%, 21.9-111.3%, 26.8-86.2%, 27.0-29.1% after post-process infiltration with a wax. A promising application of the wax-infiltrated laser-sintered parts is for investment casting cores and patterns. Research limitations/implications The proper process parameters and forming properties of laser-sintered parts are limited to the results of laser sintering experiments carried on using AFS 360 rapid prototyping device. Originality/value This investigation not only provides a new feedstock for laser sintering with the advantages of low cost and fabricability but also uses an advanced technique to produce personalized wood-plastic parts efficiently. Mathematical models between mechanical properties of laser-sintered PCPES parts and LS process parameters will guide the further LS experiments using the 20 Wt.% pine/co-PES composite. Besides, the laser-sintered PCPES parts after wax-infiltration post-processing are promising as complex structural patterns for use in investment casting.
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Dissertations / Theses on the topic "Confounded fractional factorials design"

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Rajagopalan, Ravishankar. "Response-Probability Model Analysis Plots With Applications in Engineering and Clinical Research." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1238137483.

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Alberto, Manuel Ana Mário. "Planeamento de experiências e controlo de qualidade na indústria : revisão e aplicação metodológica." Master's thesis, 2013. http://hdl.handle.net/10400.2/2399.

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Dissertação de Mestrado em Estatística, Matemática e Computação apresentada à Universidade Aberta
O presente trabalho apresenta uma breve revisão e aplicação da metodologia de Planeamento de experiências e Controlo da Qualidade no processo na Indústria. Esta pesquisa incidiu no processo de fabrico de sumo e foram definidas duas variáveis resposta: a presença de bolhas de ar no interior das embalagens e defeitos da colagem das embalagens, que são as ocorrências frequentes provocadas por diferentes causas, conhecidas e desconhecidas. O principal objectivo desta pesquisa é a identificação das causas dos defeitos durante o processo de fabrico do produto em estudo e, consequentemente procurar a sua diminuição. Para se atingir o objectivo preconizado, aplicou-se a técnica de planeamento factorial completo 2k para a identificação dos principais factores que influenciam o processo de produção. De entre os diferentes factores que envolvem o processo, destacam-se a velocidade, a pressão, a temperatura, o tempo e a quantidade. Identificados os factores, fez-se a optimização do processo para definição dos melhores níveis. Para a primeira variável usou-se a técnica de Planeamento factorial Composto; ao passo que para segunda variável, para além dessa técnica, usou-se ainda a técnica de Planeamento Composto Central. Para verificação dos resultados, usou-se a metodologia de superfície de resposta.
In this work a brief revision and an application of Experimental Design and Quality Control methodologies in industry is presented. This research is essentially based in the process of manufacturing juice, and has been defined into two ways. In the process of manufacturing, the presence of air balls within the packages and general defects of the package, due to unknown causes were detected. The main objective of this research is to identify the causes of such defects during the manufacturing process of the product and consequently to try to minimize them. In order to achieve this objective, a study has begun with the identification of the main factors that influence the production process. In between the different factors of the production process, speed, pressure and temperature, time and quantity are some of the most prominent factors. The causes were identified, and complete factorial design 2k. To verify the results, the methodology of response surface has been used.
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Book chapters on the topic "Confounded fractional factorials design"

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Evans, Mark. "The 2k-p Experimental Design: Fractional Factorials." In Optimisation of Manufacturing Processes, 39–53. London: CRC Press, 2022. http://dx.doi.org/10.1201/9780138744885-6.

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"Fractional Factorials at 2-Levels." In Quality By Experimental Design, 113–62. Chapman and Hall/CRC, 2005. http://dx.doi.org/10.1201/b16649-15.

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"Fractional Factorials at Two Levels." In Quality by Experimental Design, 107–52. Chapman and Hall/CRC, 2016. http://dx.doi.org/10.1201/b19616-15.

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"Two-level factorial experiments: fractional factorials." In Design of Experiments, 245–64. Chapman and Hall/CRC, 2010. http://dx.doi.org/10.1201/9781439894903-15.

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"9. Fractional Factorials with More Than Two Levels." In Statistical Design and Analysis of Experiments, 177–92. Society for Industrial and Applied Mathematics, 1998. http://dx.doi.org/10.1137/1.9781611971149.ch9.

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Conference papers on the topic "Confounded fractional factorials design"

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Daniels, Mitchell A., Levi J. Suryan, and John P. Parmigiani. "Effects of Finite Element Damage Modeling Parameters in Carbon Fiber Panels Under Mode III Loading." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50297.

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Modeling the progression of damage is required to fully describe the behavior of advanced composite materials in engineering applications. However, damage progression can be complex and is often difficult to determine. Errors in analyses can arise due to uncertainties in the material parameters associated with damage progression models. The commercial software Abaqus uses the Hashin damage criterion that consists of six strength based damage initiation material inputs and four energy based damage propagation inputs for composite lamina. The initiation inputs consist of the tensile and compressive strengths parallel and perpendicular to the fiber direction, longitudinal shear strength, and transverse shear strength. The damage propagation properties consist of the fracture-energies that define the stress-displacement relationship for tension and compression of the fibers and the matrix. To create an accurate finite element model, it is important to understand the effects of the material properties on the outputs of the analysis. The research presented in this study will determine the effect of the ten damage properties under a specific loading case using an Abaqus finite element model, with a focus on determining when the four damage progression properties have a significant effect. Edge-notched panels under mode III loading with 20 and 40 ply layups consisting of 30% zero degree plies were considered in the study. The explicit solver in Abaqus was used for the panel analysis. To evaluate the effects of the properties, fractional factorial sensitivity studies were used. Fractional factorials allow for a broad screening of several factors at relatively small computational cost. The factorial design used the ten Abaqus Hashin properties as factors at levels of ±50% from their nominal values. The maximum load the panel experienced was used as the metric for comparison. The effects were then calculated, weighted to the sum of all effects, and plotted to compare each factor. For both the 20 and 40 ply panels, the tensile strength in the direction of the fibers was shown to have the largest effect. The 20 ply panel showed a very small effect of the fracture energy of the fiber in tension, while the 40 ply panel showed a greater effect of this parameter. This is due to damage propagation mainly occurring after max load for thinner panels. Thicker panels are able to transfer load to more plies as damage occurs and the material softens. This allows the panel to carry an increased load after initial damage and through damage progression. Therefore the damage propagation has more of an effect on max load for the 40 ply panels. This principle is illustrated by differences in the experimental load displacement curve shapes of the 20 and 40 ply panels. In addition, the analysis showed the thicker panels exhibited more damage at the maximum load. These results illustrate where in the mode III loading case the damage progression properties have a major effect. This can be used to inform future analysis and inform further research into measuring the damage progression of composite materials.
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