Economical Second-Order Designs Based on Irregular Fractions of the 3 n Factorial

Hoke, Albert T.

doi:10.2307/1267667

Cited by 46 publications

(25 citation statements)

References 5 publications

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“…Table 4 includes one of the best designs derived and compares it with the corresponding benchmark, the CMR design [11]. For comparison purposes, other designs have been included such as Roquemore's hybrid designs [30], Hoke [31], Box and Behnken [32], Notz [33], and del Castillo [12] designs. The case analysed below considers two controllable and two noise factors, i.e.…”

Section: Results For the Rpd Modelmentioning

confidence: 99%

Design of robust parameter experiments in a continuous space using an evolutionary optimization algorithm

Santiago

2012

Journal of Statistical Computation and Simulation

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Two common experimental designs used in robust parameter design (RPD) are crossed array and mixed resolution designs. However, the prohibited number of runs, constraints in the design space or special model requirements render some of these designs inadequate. This paper presents the application of an evolutionary strategy to produce nearly optimal design matrices for RPD. The designs are derived by solving a nonlinear optimization problem involving both D-and G-efficiency simultaneously. The methodology presented allows the user to obtain new exact designs for a specific number of runs, and a particular experimental region. The combination of D-and G-efficiency results in experimental designs that outperform the corresponding benchmarks.

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Section: Results For the Rpd Modelmentioning

confidence: 99%

Design of robust parameter experiments in a continuous space using an evolutionary optimization algorithm

Santiago

2012

Journal of Statistical Computation and Simulation

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“…[10,12]. Using RSM, it is possible to estimate linear, interaction, and quadratic effects of the factors and to provide a prediction model for the response [13]. The textile industry is one of the largest and oldest industries worldwide and yarn manufacturing is the key process of it.…”

Section: Central Composite Designmentioning

confidence: 99%

Performance Optimization, Prediction, and Adequacy by Response Surfaces Methodology with Allusion to DRF Technique

Shukla¹,

Nishkam

2014

ISRN Textiles

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The RSM introduces statistically designed experiments for the purpose of making inferences from data. The second-order model is the most frequently used approximating polynomial model in RSM. The most common designs for the second-order model are the 3 factorial, Doehlert, Box-Behnken, and CCD. In this Box and Behnken design of three variables is selected as a representative of RSM and 70 : 30 polyester-wool DRF yarn knitted fabrics samples as a process representative. The survey reveals that secondorder model is the most frequently used approximating polynomial model in RSM. The Box-Behnken is the most suited design for optimization and prediction of data in textile manufacturing and this model is well-suited for DRF technique yarn knitted fabric. The trend was as higher wool fiber length shows higher fabric weight, abrasion, and bursting strength, correlation of TM was not visible; however, role of strands spacing is found dominant in comparison to other variables; at 14 mm spacing it shows optimum behaviors. The optimum values were weight (gms/mt 2 ) 206 at length 75 mm, TM 2.5 and 14 mm spacing, abrasion (cycles) 1325 at length 70 mm, TM 2.25 and 14 mm spacing, bursting (kg/cm 2 ) 14.35 at length 70 mm, and TM 2.00 and 18 mm spacing. A selected variables, fiber length, TM, and strand spacing, have substantial influence. The adequacies of response surface equations are very high. The line trends of knitted fabric basic characteristics were almost the same for actual and predicted models. The difference (%) was in range of 1.21 to −1.45, 2.01 to −7.26, and 17.84 to −6.61, the accuracy (%) was in range of 101.45 to 98.79, 107.27 to 97.99, and 106.61 to 82.16, and the Discrepancy Factor ( -Factor) was noted to be 0.016, 0.002, and 0.229 for weight, abrasion, and bursting, respectively, between actual and predicted data. The -estimation factors for actual and predicted data were that (i) the ratio were in range of 1.01 to 0.99, 1.02 to 0.93, and 1.22 to 0.94 for weight, abrasion, and bursting, respectively, (ii) the multiple-ratio was in range of 1.26 to 0.86, (iii) the ratio product was in range of 1.22 to 0.92, and (iv) the toting ratio was in range of 1.02 to 0.94.

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“…These designs use variables in a ratio or interval scale and the encoding of factor levels is performed using a vector model of three levels, equivalent in their spatial distribution and grouped into subsets. The design of this experiment was constructed from factorial 3 q subsets, defined by Hoke (1974) and developed by Gilmour (2006).…”

Section: Appendix Amentioning

confidence: 99%

Designing a hotel website: An empirical analysis for a classic destination using a conjoint experiment

Huertas-García

Gázquez–Abad

Forgas-Coll

et al. 2014

SAJBM

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Internet has become one of the most important channels for the promotion and sale of services related to tourism. As a result, producers and distributors alike are keen to resolve the question as to which factors will determine website choice by internet browsers. In this paper we develop an experiment to determine the factors that need to be taken into consideration when designing a website for a mature, familiar tourist destination. To this end, the basic factors shaping the architecture of a website are theoretically described and, based on the results of a conjoint experiment, the main factors influencing a website for a classic destination are extracted. Our results suggest that a website that includes objective information (e.g., price, activities of interest, number of rooms) and multiple photos has a positive influence on customer perceptions. The paper also makes an important methodological contribution, as it proposes a new design for calculating the weight of the factors, interactions of two factors and the factors squared.

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Economical Second-Order Designs Based on Irregular Fractions of the 3 n Factorial

Cited by 46 publications

References 5 publications

Design of robust parameter experiments in a continuous space using an evolutionary optimization algorithm

Design of robust parameter experiments in a continuous space using an evolutionary optimization algorithm

Performance Optimization, Prediction, and Adequacy by Response Surfaces Methodology with Allusion to DRF Technique

Designing a hotel website: An empirical analysis for a classic destination using a conjoint experiment

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