Experimental Design for Product and Process Design and Development

Montgomery, Douglas C.

doi:10.1111/1467-9884.00179

Cited by 114 publications

(77 citation statements)

References 42 publications

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“…This is similar to what is often done for normal theory regression when the response variance depends on the predictors (Montgomery 1999;Myers and Montgomery 2002, section 11.4.6). There are differences, however.…”

Section: Weibull Regression With Nonconstant Ksupporting

confidence: 74%

The Constant Shape Parameter Assumption in Weibull Regression

Mueller

Rigdon

2015

Quality Engineering

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The usual assumption in Weibull regression is that the scale parameter is a function of the predictor variables, and the shape parameter is constant. We consider the problem of estimating parameters in the presence of a nonconstant shape parameter and the effect of assuming a constant shape parameter when it really is not constant. We consider both classical and Bayesian methods of estimation. The misspecification of a constant shape parameter can lead to a loss of power for tests regarding the slope parameters. We find that prediction intervals can be inaccurate when the shape parameter is incorrectly assumed to be constant.

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Section: Weibull Regression With Nonconstant Ksupporting

confidence: 74%

The Constant Shape Parameter Assumption in Weibull Regression

Mueller

Rigdon

2015

Quality Engineering

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“…Analysis of variance, ANOVA, is a statistical decision-making tool used for detecting any differences in average performances of tested parameters [7]. Analysis of variance (ANOVA) was used to check the adequacy of the model for the responses in the experimentation.…”

Section: Design Of Experimentsmentioning

confidence: 99%

Optimization by Box-Behnken Design of in-Situ Carbon Dioxide Conversion Using Lanthanum Oxide

Rosid

Bakar²,

Ali³

2017

MJAS

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Lanthanum oxide based catalyst was revealed as one of potential catalyst to convert carbon dioxide to wealth product methane in simulated natural gas. To produce higher conversion of carbon dioxide, the Response Surface Methodology utilizing BoxBehnken design (BBD) was used to optimize the lanthanum oxide based catalysts by three critical parameters which were calcination temperature, based ratio and catalyst dosage. The maximum CO 2 conversion was achieved at 1000 o C calcination temperature using 7 g of catalyst for 60% based loading. The optimization result from BBD is in good agreement with experimental data. The optimize parameters gave 99% of CO 2 conversion determined using Fourier Transformation Infrared (FTIR) and yielded about 50% of CH 4 at reaction temperature of 400 °C. X-ray Diffraction (XRD) analysis showed an amorphous structure with RuO 2 as active species and Field Emission Scanning Electron Microscope (FESEM) illustrated the catalyst surface was covered with small and dispersed particles with undefined shape. EDX analysis revealed that when the calcination temperature was increased, the mass ratio of Ru increased.Keywords: Box-Behnken design, optimization, response surface methodology, lanthanum oxide Abstrak Mangkin asas lanthanum oksida adalah salah satu mangkin berpotensi menukarkan karbon dioksida kepada produk metana yang banyak dalam simulasi gas asli. Untuk menghasilkan penukaran karbon dioksida yang tinggi, kaedah gerak balas permukaan menggunakan reka bentuk Box-Behnken (BBD) untuk mengoptimumkan mangkin asas lantanum oksida oleh tiga parameter kritikal yang mana suhu kalsin, nisbah asas, dan dos mangkin. Maksimum penukaran CO 2 dicapai pada suhu kalsin 1000 o C menggunakan 7 g mangkin untuk 60% nisbah asas. Keputusan pengoptimuman dari BBD adalah selari dengan data eksperimen. Parameter yang optimum memberikan 99% penukaran CO 2 apabila ditentukan menggunakan Inframerah transformasi Fourier (FTIR) dan menghasilkan 50% metana pada suhu tindak balas 400 o C. Analisis pembelauan sinar-X (XRD) menunjukkan struktur amorfus dengan RuO 2 sebagai aktif spesis dan Mikroskop Imbasan Elektron Pancaran Medan ( FESEM ) menunjukkan permukaan mangkin diselaputi dengan partikel yang bersaiz kecik dan terserak sekata tanpa bentuk. Analisis EDX menunjukkan apabila suhu kalsin meningkat, nisbah jisim Ru meningkat.

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“…For a small number of noise variables and a small number of control variables, the recommended designs can estimate all the main effects and most two-factor interactions. 68 . Using the combined array design, a single model containing both the control factors and the noise factors can be fitted to the response of interest as presented previously.…”

Section: Split-plot Experiments For Robust Designmentioning

confidence: 99%

Robust Parameter Design: A Review

Robinson

Borror

Myers

2003

Quality & Reliability Eng

188

107

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Parameter design is an engineering methodology intended as a cost-effective approach for improving the quality of products and processes. The assumption is that there are both controllable factors (control variables) and uncontrollable/difficult to control factors (noise variables) that operate on the quality characteristic of a process. The goal of parameter design is to choose the levels of the control variables that optimize a defined quality characteristic while minimizing the variation imposed on the process via the noise variables. Parameter design was popularized in the mid 1980s by Japanese quality consultant Genichi Taguchi. A panel discussion edited by Nair summarized important responses to Taguchi's ideas and methodology. In the last decade, there have been many applications and new developments in this important area. This review paper focuses largely on the work done since 1992, but a historical perspective of parameter design is also given.

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Experimental Design for Product and Process Design and Development

Cited by 114 publications

References 42 publications

The Constant Shape Parameter Assumption in Weibull Regression

The Constant Shape Parameter Assumption in Weibull Regression

Optimization by Box-Behnken Design of in-Situ Carbon Dioxide Conversion Using Lanthanum Oxide

Robust Parameter Design: A Review

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