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Journal articles on the topic 'Central composite designs'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Iwundu, Mary Paschal. "Alternative Second-Order N-Point Spherical Response Surface Methodology Design and Their Efficiencies." International Journal of Statistics and Probability 5, no. 4 (June 11, 2016): 22. http://dx.doi.org/10.5539/ijsp.v5n4p22.

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The equiradial designs are studied as alternative second-order N-point spherical Response Surface Methodology designs in two variables, for design radius ρ = 1.0. These designs are seen comparable with the standard second-order response surface methodology designs, namely the Central Composite Designs. The D-efficiencies of the equiradial designs are evaluated with respect to the spherical Central Composite Designs. Furthermore, D-efficiencies of the equiradial designs are evaluated with respect to the D-optimal exact designs defined on the design regions of the Circumscribed Central Composite Design, the Inscribed Central Composite Design and the Face-centered Central Composite Design. The D-efficiency values reveal that the alternative second-order N-point spherical equiradial designs are better than the Inscribed Central Composite Design though inferior to the Circumscribed Central Composite Design with efficiency values less than 50% in all cases studied. Also, D-efficiency values reveal that the alternative second-order N-point spherical equiradial designs are better than the N-point D-optimal exact designs defined on the design region supported by the design points of the Inscribed Central Composite Design. However, the N-point spherical equiradial designs are inferior to the N-point D-optimal exact designs defined on the design region supported by the design points of the Circumscribed Central Composite Design and those of the Face-centered Central Composite Design, with worse cases with respect to the design region of the Circumscribed Central Composite Design.

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2

Jensen, D. R. "C432. Efficiency comparisons of central composite designs." Journal of Statistical Computation and Simulation 52, no. 2 (April 1995): 177–83. http://dx.doi.org/10.1080/00949659508811664.

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3

O. Ngonadi, Lilian, and Francis C. Eze. "Some Optimality Variations of Central Composite Designs." Academic Journal of Applied Mathematical Sciences, no. 54 (April 15, 2019): 32–42. http://dx.doi.org/10.32861/ajams.54.32.42.

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Some variations of central composite designs (CCD) under complete and partial replications of cube, axial and center points are studied using A, D and G optimality criteria. The results obtained suggest that complete replication of the cube, axial and center points are better than the partial replication of cube, axial and center points under the A and D optimality criteria studied while it varies under G optimality criterion. The partial replication of the cube, axial and center point for all the CCDs studied, the partial replicated cube point is D optimal but varies under A and G optimality criteria.

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4

O. Ngonadi, Lilian, and Francis C. Eze. "Some Optimality Variations of Central Composite Designs." Academic Journal of Applied Mathematical Sciences, no. 54 (April 15, 2019): 32–42. http://dx.doi.org/10.32861/ajams.54.32.42.

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Some variations of central composite designs (CCD) under complete and partial replications of cube, axial and center points are studied using A, D and G optimality criteria. The results obtained suggest that complete replication of the cube, axial and center points are better than the partial replication of cube, axial and center points under the A and D optimality criteria studied while it varies under G optimality criterion. The partial replication of the cube, axial and center point for all the CCDs studied, the partial replicated cube point is D optimal but varies under A and G optimality criteria.

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5

M. P., Iwundu,. "Construction of Modified Central Composite Designs for Non-standard Models." International Journal of Statistics and Probability 7, no. 5 (August 8, 2018): 95. http://dx.doi.org/10.5539/ijsp.v7n5p95.

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The use of loss function in studying the reduction in determinant of information matrix due to missing observations has effectively produced designs that are robust to missing observations. Modified central composite designs are constructed for non-standard models using principles of the loss function or equivalently first compound of (I ) matrix associated with hat matrix . Although central composite designs (CCDs) are reasonably robust to model mis-specifications, efficient designs with fewer design points are more economical. By classifying the losses due to missing design points in the CCD portions, where there are multiple losses associated with specified CCD portions, the design points having less influence may be deleted from the full CCD. This leads to a possible increase in design efficiency and offers alternative designs, similar in the structure of CCDs, for non-standard models.

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6

E.I., Jaja, Etuk E.H., Iwundu M.P., and Amos E. "Robustness of Central Composite Design and Modified Central Composite Design to a Missing Observation for Non-Standard Models." African Journal of Mathematics and Statistics Studies 4, no. 2 (May 11, 2021): 25–40. http://dx.doi.org/10.52589/ajmss-c5nkoi81.

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Missing observations in an experimental design may lead to ambiguity in decision making thereby bringing an experiment to disrepute. Robustness, therefore, enables a process, not to break down in the presence of missing observations. This work constructed a modified central composite design (MCCD) from a four-variable central composite design (CCD) augmented with four center points using the leverage of a hat-matrix. The robustness of the CCD and MCCD were assessed when a design point is missing at the factorial, axial, and center points of the experiment, for a non-standard model, using the loss criterion, D-optimality, D-efficiency, and relative D-efficiency. When the designs are complete the MCCD shows higher D-efficiency and D-optimality for the non-standard model when compared to the CCD. In the absence of an observation from any of the designs, the CCD is found to be a more robust and efficient design compared to the MCCD as it has overall lower loss values at all the factors levels.

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7

Palasota, John A., and Stanley N. Deming. "Central composite experimental designs: Applied to chemical systems." Journal of Chemical Education 69, no. 7 (July 1992): 560. http://dx.doi.org/10.1021/ed069p560.

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8

Mays, Darcy P., and Karen R. Schwartz. "Two-stage central composite designs with dispersion effects." Journal of Statistical Computation and Simulation 61, no. 3 (October 1998): 191–218. http://dx.doi.org/10.1080/00949659808811910.

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9

Sanchez, Susan M., and Paul J. Sanchez. "Very large fractional factorial and central composite designs." ACM Transactions on Modeling and Computer Simulation 15, no. 4 (October 2005): 362–77. http://dx.doi.org/10.1145/1113316.1113320.

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10

Ohaegbulem, Emmanuel, and Polycarp Chigbu. "An approach to measuring rotatability in central composite designs." International Journal of Advanced Statistics and Probability 3, no. 2 (May 31, 2015): 126. http://dx.doi.org/10.14419/ijasp.v3i2.4657.

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<p>An approach to measure design rotatability and a measure, that quantifies the percentage of rotatability (from 0 to 100) in the central composite designs are introduced. This new approach is quite different from the ones provided by previous authors which assessed design rotatability by the viewing of tediously obtained contour diagrams. This new approach has not practical limitations, and the measure is very easy to compute. Some examples were used to express this approach.</p>

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11

Angelopoulos, P., H. Evangelaras, and C. Koukouvinos. "Small, balanced, efficient and near rotatable central composite designs." Journal of Statistical Planning and Inference 139, no. 6 (June 2009): 2010–13. http://dx.doi.org/10.1016/j.jspi.2008.09.001.

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12

Park, Sung H., and Kiho Kim. "Construction of central composite designs for balanced orthogonal blocks." Journal of Applied Statistics 29, no. 6 (August 2002): 885–93. http://dx.doi.org/10.1080/02664760220136195.

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13

Wang, Li, G. Geoffrey Vining, and Scott M. Kowalski. "Two-strata rotatability in split-plot central composite designs." Applied Stochastic Models in Business and Industry 26, no. 4 (June 26, 2009): 431–47. http://dx.doi.org/10.1002/asmb.796.

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14

Marget, Wilmina M., and Max D. Morris. "Central Composite Experimental Designs for Multiple Responses With Different Models." Technometrics 61, no. 4 (March 22, 2019): 524–32. http://dx.doi.org/10.1080/00401706.2018.1549102.

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15

Mays, Darcy P. "Optimal Central Composite Designs in the Presence of Dispersion Effects." Journal of Quality Technology 31, no. 4 (October 1999): 398–407. http://dx.doi.org/10.1080/00224065.1999.11979946.

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16

Ukaegbu, Eugene C., and Polycarp E. Chigbu. "Evaluation of Orthogonally Blocked Central Composite Designs with Partial Replications." Sankhya B 79, no. 1 (June 7, 2016): 112–41. http://dx.doi.org/10.1007/s13571-016-0120-z.

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17

Iwundu, Mary, and Henry Onu. "Equiradial designs under changing axial distances, design sizes and varying center runs with their relationships to the central composite designs." International Journal of Advanced Statistics and Probability 5, no. 2 (July 13, 2017): 77. http://dx.doi.org/10.14419/ijasp.v5i2.7701.

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In assessing the preferences of equiradial designs based on design size, axial distance and number of center points in relation to the central composite designs, D-absolute deviation (D-AD) and G-absolute deviation (G-AD) are proposed as new design measures of closeness of experimental designs. Each absolute deviation is positive or zero. The G-absolute deviation is zero or approximately zero at equals 1 center point. For greater than 1, G-absolute deviation decreases for increasing values of . On the other hand, the D-absolute deviation decreases as the design size increases. Designs having G-AD values of zero or approximately zero are identical or near identical in G-optimality properties. Also, designs having D-AD values of zero or approximately zero are identical or near identical in D-optimality properties. It is conjecturally hoped that at some increased design size, the equiradial designs and the central composite designs, having same axial or radial distance will coincide (be identical) in their properties, with D-AD value of zero or approximately zero.

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18

Borkowski, John J. "Spherical Prediction-Variance Properties of Central Composite and Box-Behnken Designs." Technometrics 37, no. 4 (November 1995): 399. http://dx.doi.org/10.2307/1269732.

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19

Yakubu, Yisa, Angela Unna Chukwu, Bamiduro Timothy Adebayo, and Amahia Godwin Nwanzo. "Effects of Missing Observations on Predictive Capability of Central Composite Designs." International Journal on Computational Science & Applications 4, no. 6 (December 31, 2014): 1–18. http://dx.doi.org/10.5121/ijcsa.2014.4601.

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20

Borkowski, John J. "Spherical Prediction-Variance Properties of Central Composite and Box—Behnken Designs." Technometrics 37, no. 4 (November 1995): 399–410. http://dx.doi.org/10.1080/00401706.1995.10484373.

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21

Kim, Hyuk-Joo, and Yun-Mi Ko. "On Slope Rotatability of Central Composite Designs of the Second Type." Communications for Statistical Applications and Methods 11, no. 1 (April 1, 2004): 121–37. http://dx.doi.org/10.5351/ckss.2004.11.1.121.

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22

Leksakul, Komgrit, and Alonggot Limcharoen. "Central composite designs coupled with simulation techniques for optimizing RIE process." International Journal of Advanced Manufacturing Technology 70, no. 5-8 (October 18, 2013): 1219–25. http://dx.doi.org/10.1007/s00170-013-5374-2.

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23

M. P., Iwundu. "Useful Numerical Statistics of Some Response Surface Methodology Designs." Journal of Mathematics Research 8, no. 4 (July 25, 2016): 40. http://dx.doi.org/10.5539/jmr.v8n4p40.

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<p>Useful numerical evaluations associated with three categories of Response Surface Methodology designs are presented with respect to five commonly encountered alphabetic optimality criteria. The first-order Plackett-Burman designs and the Factorial designs are examined for the main effects models and the complete first-order models respectively. The second-order Central Composite Designs are examined for second-order models. The A-, D-, E-, G- and T-optimality criteria are employed as commonly encountered optimality criteria summarizing how good the experimental designs are. Relationships among the optimality criteria are pointed out with regards to the designs and the models. Generally the designs do not show uniform preferences in terms of the considered optimality criteria. However, one interesting finding is that central composite designs defined on cubes and hypercubes with unit axial distances are uniformly preferred in terms of E-optimality and G-optimality criteria.</p>

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24

Ghosh, Subir, and Chinglin Lai. "Measuring influence of observations in predict1on and estimation for central composite designs." Communications in Statistics - Simulation and Computation 26, no. 1 (January 1997): 233–57. http://dx.doi.org/10.1080/03610919708813376.

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25

Liong, Shie-Yui, Jaya ShreeRam, and Yaacob Ibrahim. "Catchment Calibration Using Fractional-Factorial and Central-Composite-Designs-Based Response Surface." Journal of Hydraulic Engineering 121, no. 6 (June 1995): 507–10. http://dx.doi.org/10.1061/(asce)0733-9429(1995)121:6(507).

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26

Kim, Hyuk-Joo. "Extended Central Composite Designs with the Axial Points Indicated by Two Numbers." Communications for Statistical Applications and Methods 9, no. 3 (December 1, 2002): 595–605. http://dx.doi.org/10.5351/ckss.2002.9.3.595.

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27

Yakubu, Y., and AU Chukwu. "Split-Plot Central Composite Designs Robust to a Pair of Missing Observations." Journal of Applied Sciences and Environmental Management 22, no. 9 (November 27, 2018): 1409. http://dx.doi.org/10.4314/jasem.v22i9.08.

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28

Borkowski, John J. "Finding maximum G-criterion values for central composite designs on the hypercube." Communications in Statistics - Theory and Methods 24, no. 8 (January 1995): 2041–58. http://dx.doi.org/10.1080/03610929508831601.

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29

Ebrahimi-Najafabadi, Heshmatollah, Riccardo Leardi, and Mehdi Jalali-Heravi. "Experimental Design in Analytical Chemistry—Part I: Theory." Journal of AOAC INTERNATIONAL 97, no. 1 (January 1, 2014): 3–11. http://dx.doi.org/10.5740/jaoacint.sgeebrahimi1.

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Abstract This paper reviews the main concepts of experimental design applicable to the optimization of analytical chemistry techniques. The critical steps and tools for screening, including Plackett-Burman, factorial and fractional factorial designs, and response surface methodology such as central composite, Box-Behnken, and Doehlert designs, are discussed. Some useful routines are also presented for performing the procedures.

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30

E.I., Jaja, Iwundu M.P., and Etuk E.H. "The Comparative Study of CCD and MCCD in the Presence of a Missing Design Point." African Journal of Mathematics and Statistics Studies 4, no. 2 (May 11, 2021): 10–24. http://dx.doi.org/10.52589/ajmss-jf1a1dza.

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The work constructed a modified central composite design from a rotatable central composite design augmented with seven center points adapted from the work of Wu and Li (2002). The comparison of the robustness of the CCD and MCCD to missing observation was investigated at various design points of factorial, axial and center points’ when the model is non-standard, using A-efficiency and the Losses associated. The results of the evaluations of the designs to missing observations are presented, and the MCCD is shown to be more A-optimal while the CCD is more robust and relatively A-efficient to a missing observation.

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31

Zlatanovska, Katerina, Ljuben Guguvcevski, Risto Popovski, Cena Dimova, Ana Minovska, and Aneta Mijoska. "Fracture Resistance of Composite Veneers with Different Preparation Designs." Balkan Journal of Dental Medicine 20, no. 2 (July 1, 2016): 99–103. http://dx.doi.org/10.1515/bjdm-2016-0016.

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Summary Background: The aim of this in vitro study was to examine the fracture load of composite veneers using three different preparation designs. Material and methods: Fifteen extracted, intact, human maxillary central incisors were selected. Teeth were divided into three groups with different preparation design: 1) feather preparation, 2) bevel preparation, and 3) incisal overlap- palatal chamfer. Teeth were restored with composite veneers, and the specimens were loaded to failure. The localization of the fracture was recorded as incisal, gingival or combined. Results: Composite veneers with incisal overlap - palatal chamfer showed higher fracture resistance compared to feather preparation and bevel preparation. The mean (SD) fracture loads were: Group 1: 100.6±8.0 N, Group 2: 107.4±6.8 N, and Group 3: 122.0±8.8 N. The most common mode of failure was debonding for veneers with feather preparation and fracture when incisal edge is reduced. The most frequent localization of fracture was incisal. Conclusion: The type of preparation has a significant effect on fracture load for composite veneers. This study indicates that using an incisal overlap- palatal chamfer preparation design significantly increases the fracture resistance compared to feather and bevel preparation designs.

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32

Yakubu, Y., and A. U. Chukwu. "Missing Observations in Split-Plot Central Composite Designs: The Loss in Relative A-, G-, and V- Efficiency." Journal of Applied Sciences and Environmental Management 25, no. 2 (April 15, 2021): 239–47. http://dx.doi.org/10.4314/jasem.v25i2.16.

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The trace (A), maximum average prediction variance (G), and integrated average prediction variance (V) criteria are experimental design evaluation criteria, which are based on precision of estimates of parameters and responses. Central Composite Designs(CCD) conducted within a split-plot structure (split-plot CCDs) consists of factorial (𝑓), whole-plot axial (𝛼), subplot axial (𝛽), and center (𝑐) points, each of which play different role in model estimation. This work studies relative A-, G- and V-efficiency losses due to missing pairs of observations in split-plot CCDs under different ratios (d) of whole-plot and sub-plot error variances. Three candidate designs of different sizes were considered and for each of the criteria, relative efficiency functions were formulated and used to investigate the efficiency of each of the designs when some observations were missing relative to the full one. Maximum A-efficiency losses of 19.1, 10.6, and 15.7% were observed at 𝑑 = 0.5, due to missing pairs 𝑓𝑓, 𝛽𝛽, and 𝑓𝛽, respectively, indicating a negative effect on the precision of estimates of model parameters of these designs. However, missing observations of the pairs- 𝑐𝑐, 𝛼𝛼, 𝛼𝑐, 𝑓𝑐, and 𝑓𝛼 did not exhibit any negative effect on these designs' relative A-efficiency. Maximum G- and Vefficiency losses of 10.1,16.1,0.1% and 0.1, 1.1, 0.2%, were observed, respectively, at 𝑑 = 0.5, when the pairs- 𝑓𝑓, 𝛽𝛽, 𝑐𝑐, were missing, indicating a significant increase in the designs' maximum and average variances of prediction. In all, the efficiency losses become insignificant as d increases. Thus, the study has identified the positive impact of correlated observations on efficiency of experimental designs. Keywords: Missing Observations, Efficiency Loss, Prediction variance

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33

Chigbu, Polycarp E., and Eugene C. Ukaegbu. "Recent Developments on Partial Replications of Response Surface Central Composite Designs: A Review." Journal of Statistics Applications & Probability 6, no. 1 (March 1, 2017): 91–104. http://dx.doi.org/10.18576/jsap/060108.

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34

Coetzer, R. L. J., L. M. Haines, and L. P. Fatti. "Central composite designs for estimating the optimum conditions for a second-order model." Journal of Statistical Planning and Inference 141, no. 5 (May 2011): 1764–73. http://dx.doi.org/10.1016/j.jspi.2010.11.026.

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35

Ukaegbu, Eugene C., and Polycarp E. Chigbu. "Graphical Evaluation of the Prediction Capabilities of Partially Replicated Orthogonal Central Composite Designs." Quality and Reliability Engineering International 31, no. 4 (March 4, 2014): 707–17. http://dx.doi.org/10.1002/qre.1630.

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36

Ukaegbu, Eugene C., and Polycarp E. Chigbu. "Comparison of Prediction Capabilities of Partially Replicated Central Composite Designs in Cuboidal Region." Communications in Statistics - Theory and Methods 44, no. 2 (December 15, 2014): 406–27. http://dx.doi.org/10.1080/03610926.2012.745561.

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37

Xie, Yu Feng, Xiao Lei Ma, Yun Feng Gao, and Xing Da Lu. "Optimization of Fermentation Medium for Pullulan Production by Aureobasidium pullulans A225 Using Plackett-Burman and Response Surface Methodology." Advanced Materials Research 785-786 (September 2013): 279–86. http://dx.doi.org/10.4028/www.scientific.net/amr.785-786.279.

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In this study, response surface methodology (RSM) was used to optimize the medium based on the PlackettBurman and Central-Composite Designs for the production of pullulan using a strain of Auerobasidium pullulans A225. Peptone, K2HPO4, and MgSO4 were found to have significant effects on pullulan production using the PlackettBurman Design. The steepest ascent experiment was adopted to determine the optimal region of the medium composition. The concentrations of the three above mentioned compounds were further optimized using the Central-Composite Design. Results showed that the final concentration of medium optimized using RSM was 6.34 g/L peptone, 7.91 g /L K2HPO4, and 0.46 g/L MgSO4. Production of pullulan reached 72.56 g/L under the optimized medium.

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38

Molpeceres, Jesus, Manuel Guzman, Maria R. Aberturas, Mercedes Chacon, and Laura Berges. "Application of Central Composite Designs to the Preparation of Polycaprolactone Nanoparticles by Solvent Displacement." Journal of Pharmaceutical Sciences 85, no. 2 (February 1996): 206–13. http://dx.doi.org/10.1021/js950164r.

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39

Isaza, Clara E., Cristina Rodriguez, Lyzett Uribe, Hugo A. Perez, Jannet Salinas, and Mauricio Cabrera-Rios. "The use of central composite designs to improve cytotoxicity data generation: a case study." IIE Transactions on Healthcare Systems Engineering 1, no. 4 (October 2011): 226–31. http://dx.doi.org/10.1080/19488300.2011.631096.

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40

Stewardson, Dave, David Porter, and Tony Kelly. "The dangers posed by saddle points, and other problems, when using central composite designs." Journal of Applied Statistics 28, no. 3-4 (March 2001): 485–95. http://dx.doi.org/10.1080/02664760120034199.

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41

Borkowski, John J. "Minimum, maximum, and average spherical prediction variances for central composite and box-behnken designs." Communications in Statistics - Theory and Methods 24, no. 10 (January 1995): 2581–600. http://dx.doi.org/10.1080/03610929508831634.

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42

Ukaegbu, et al., Eugene C. "of Prediction Variance Properties of Rotatable Central Composite Designs for 3 to 10 Factors." International Journal of Computational and Theoretical Statistics 2, no. 2 (November 1, 2015): 87–97. http://dx.doi.org/10.12785/ijcts/020203.

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43

Shen, Pao-sheng. "A simulation study for a class of central composite designs with nested sub-experiment." Computational Statistics 24, no. 3 (December 2, 2008): 481–95. http://dx.doi.org/10.1007/s00180-008-0142-8.

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44

Gustavo González, A., and Domingo González-Arjona. "Computational program for evaluating and optimizing response-surface curves based on central composite designs." Analytica Chimica Acta 298, no. 1 (November 1994): 65–73. http://dx.doi.org/10.1016/0003-2670(94)90043-4.

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45

Umer, R., Z. Barsoum, HZ Jishi, K. Ushijima, and WJ Cantwell. "Analysis of the compression behaviour of different composite lattice designs." Journal of Composite Materials 52, no. 6 (June 13, 2017): 715–29. http://dx.doi.org/10.1177/0021998317714531.

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Four all-composite lattice designs were produced using a lost-mould procedure that involved inserting carbon fibre tows through holes in a core. Following resin infusion and curing, samples were heated to melt the core, leaving well-defined lattice structures based on what are termed BCC, BCCz, FCC and F2BCC designs. Analytical and numerical models for predicting the mechanical properties of the four designs are presented and these results are compared with the experimental data from the quasi-static compression tests. Compression tests on the four lattice structures indicated that the F2BCC lattice offered the highest compression strength, although when normalized by relative density, the BCCz lattice structure out-performed other structures. Similarly, the specific compression strengths were found to be superior to those of more traditional core materials. A number of failure mechanisms were also highlighted, including strut buckling, fracture at the strut-skin joints and debonding of reinforcing members at the central nodes. Finally, it is believed that the properties of these lattices can be further increased using higher fibre volume fractions.

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46

Czyrski, Andrzej, and Hubert Jarzębski. "Response Surface Methodology as a Useful Tool for Evaluation of the Recovery of the Fluoroquinolones from Plasma—The Study on Applicability of Box-Behnken Design, Central Composite Design and Doehlert Design." Processes 8, no. 4 (April 17, 2020): 473. http://dx.doi.org/10.3390/pr8040473.

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The aim of this study was to find the best design that is suitable for optimizing the recovery of the representatives of the 2nd, 3rd and 4th generation of fluoroquinolones. The following designs were applied: Central Composite Design, Box–Behnken Design and Doehlert Design. The recovery, which was a dependent variable, was estimated for liquid–liquid extraction. The time of shaking, pH, and the volume of the extracting agent (dichloromethane) were the independent variables. All results underwent the statistical analysis (ANOVA), which indicated Central Composite Design as the best model for evaluation of the recovery. For each analyte, an equation was generated that enabled to estimate the theoretical value for the applied conditions. The graphs for these equations were provided by the Response Surface Methodology. The statistical analysis also estimated the most significant factors that have an impact on the liquid–liquid extraction, which occurred to be pH for ciprofloxacin and moxifloxacin and the volume of an extracting solvent for levofloxacin.

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47

Ikehata, Keisuke, Michael A. Pickard, Ian D. Buchanan, and Daniel W. Smith. "Optimization of extracellular fungal peroxidase production by 2 Coprinus species." Canadian Journal of Microbiology 50, no. 12 (December 1, 2004): 1033–40. http://dx.doi.org/10.1139/w04-098.

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Optimum culture conditions for the batch production of extracellular peroxidase by Coprinus cinereus UAMH 4103 and Coprinus sp. UAMH 10067 were explored using 2 statistical experimental designs, including 2-level, 7-factor fractional factorial design and 2-factor central composite design. Of the 7 factors examined in the screening study, the concentrations of carbon (glucose) and nitrogen (peptone or casitone) sources showed significant effects on the peroxidase production by Coprinus sp. UAMH 10067. The optimum glucose and peptone concentrations were determined as 2.7% and 0.8% for Coprinus sp. UAMH 10067, and 2.9% and 1.4% for C. cinereus UAMH 4103, respectively. Under the optimized culture condition the maximum peroxidase activity achieved in this study was 34.5 U·mL–1 for Coprinus sp. UAMH 10067 and 68.0 U·mL–1 for C. cinereus UAMH 4103, more than 2-fold higher than the results of previous studies.Key words: Coprinus peroxidase, central composite design, fractional factorial design, production optimization, response surface.

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Habrat, Witold, Marcin Żółkoś, Janusz Świder, and Elżbieta Socha. "Forces modeling in a surface peripheral grinding process with the use of various design of experiment (DoE)." Mechanik 91, no. 10 (October 8, 2018): 929–31. http://dx.doi.org/10.17814/mechanik.2018.10.165.

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The paper presents forces modeling with the use of DoE models, such as (Box-Wilson) central composite design in face centered variant (CCF) and Box-Behnken design in a surface peripheral grinding process of 100Cr6 steel with M3X60K5VE01-35 grinding wheel. Experiment design and result analysis were done with the use of Design-Expert software. Force models, obtained with application of selected designs of experiment, were compared on the basis of the coefficient of determination, and values of residual standard deviation.

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Brachet, A., L. Mateus, S. Cherkaoui, P. Christen, J. Y. Gauvrit, P. Lantéri, and J. L. Veuthey. "Application of central composite designs in the supercritical fluid extraction of tropane alkaloids in plant extracts." Analusis 27, no. 9 (November 1999): 772–78. http://dx.doi.org/10.1051/analusis:1999143.

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López, Roberto, Camino Fernández, Fernando J. Pereira, Ana Díez, Jorge Cara, Olegario Martínez, and Marta E. Sánchez. "A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend." Biomolecules 10, no. 5 (May 19, 2020): 787. http://dx.doi.org/10.3390/biom10050787.

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In this paper, response surface methodology (RSM) designs and an artificial neural network (ANN) are used to obtain the optimal conditions for the oxy-combustion of a corn–rape blend. The ignition temperature (Te) and burnout index (Df) were selected as the responses to be optimised, while the CO2/O2 molar ratio, the total flow, and the proportion of rape in the blend were chosen as the influencing factors. For the RSM designs, complete, Box–Behnken, and central composite designs were performed to assess the experimental results. By applying the RSM, it was found that the principal effects of the three factors were statistically significant to compute both responses. Only the interactions of the factors on Df were successfully described by the Box–Behnken model, while the complete design model was adequate to describe such interactions on both responses. The central composite design was found to be inadequate to describe the factor interactions. Nevertheless, the three methods predicted the optimal conditions properly, due to the cancellation of net positive and negative errors in the mathematical adjustment. The ANN presented the highest regression coefficient of all methods tested and needed only 20 experiments to reach the best predictions, compared with the 32 experiments needed by the best RSM method. Hence, the ANN was found to be the most efficient model, in terms of good prediction ability and a low resource requirement. Finally, the optimum point was found to be a CO2/O2 molar ratio of 3.3, a total flow of 108 mL/min, and 61% of rape in the biomass blend.

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