Mathematical Models Used in Intelligent Assistive Technologies: Response Surface Methodology in Software Tools Optimization for Medical Rehabilitation

Plastics play an essential role in packaging materials because of their durability to different environmental conditions. With its importance in the community lies the problem with waste disposal. Plastic is a non-biodegradable material, making it a big problem, especially when thrown in dumpsites. In solving the plastic problem, one efficient way to reduce its volume is through thermal processing such as pyrolysis. This study used the pyrolysis method to recover energy from plastic waste. Liquid oil from plastic was comparable to regular fuel used in powering engines. Before the pyrolysis process, a 3k factorial Box-Behnken Design was used in determining the number of experiments to be used. The output oil yield in each pyrolysis runs was optimized in different parameters, such as temperature, residence time, and particle size using response surface methodology to determine the optimum oil yield. Between polyethylene (PE), mixed plastic, and polystyrene (PS), PS produced its highest oil yield of 90 %. In comparison, mixed plastic produced only its highest oil yield of 45 % in 500 ºC temperature, 120 min residence time, and 3 cm particle size. The produced quadratic mathematical models in PE, mixed, and PS plastic were significant in which the p-values were less than 0.05. Using mathematical models, the optimum oil yield for PE (467.68 ºC, 120 min residence time, 2 cm particle size), mixed (500 ºC, 120 min residence time, 2.75 cm particle size) and PS plastic (500 ºC, 120 min residence time, 2 cm particle size) were 75.39 %, 46.74 %, and 91.38 %, respectively

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Optimization of Laser Transmission Joint between PET and Titanium Using Response Surface Methodology

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.154-155.1119 ◽

2010 ◽

Vol 154-155 ◽

pp. 1119-1124

Author(s):

Xin Hua Song ◽

Xiao Wang ◽

Pin Li ◽

Zhen Kai Xu ◽

Kai Wang ◽

...

Keyword(s):

Response Surface Methodology ◽

Mathematical Models ◽

Response Surface ◽

Process Parameters ◽

Near Infrared ◽

Dissimilar Materials ◽

Main Effect ◽

Encapsulation Process ◽

Joining Process ◽

Pet Films

Laser transmission joint between biocompatible, dissimilar materials have the potential for application in biomedical and their encapsulation process. This paper is devoted to laser transmission joint between 0.1mm thick PET films and 0.1mm thick Titanium using near-infrared diode lasers. Response surface methodology (RSM) is used to develop mathematical models between the joining process parameters. The developed mathematical models are tested for adequacy using analysis-of-variance (ANOVA) method. In addition, the main effect of each parameter and the interaction effects with other process parameters are analyzed. Finally, the experimental results agree with those predicted indicate that the developed mathematical models can predict the responses adequately.

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Optimized characterization of response surface methodology on lubricant with titanium oxide nanoparticles

Industrial Lubrication and Tribology ◽

10.1108/ilt-09-2016-0214 ◽

2017 ◽

Vol 69 (3) ◽

pp. 387-392 ◽

Cited By ~ 4

Author(s):

Nor Syahirah Mohamad ◽

Salmiah Kasolang

Keyword(s):

Response Surface Methodology ◽

Mathematical Models ◽

Response Surface ◽

Quadratic Model ◽

Coefficient Of Determination ◽

Contour Plot ◽

Content Type ◽

Independent Variables ◽

Non Linear System

Purpose An optimized model is often deployed to reduce trial and error in experimental approach and obtain the multi-variant correlation. In this study, response surface methodology (RSM), namely, Box–Behnken design (BBD) approach, has been used to optimize the characterization of lubricant with additives. BBD is based on multivariate analysis whereby the effects of different parameters are considered simultaneously. It is a non-linear system which is more representative of the actual phenomenon. This study aims to investigate the effect of three independent variables, namely, speed, load and concentration of TiO2, on the coefficient of friction (CoF). Design/methodology/approach RSM was applied to get the multiplicity of the self-determining input variables and construct mathematical models. Mathematical models were established to predict the CoF and to conduct a statistical analysis of the independent variables’ interactions on response surface using Minitab 16.0 statistical software. Three parameters were regulated: speed (X1), load (X2) and concentration of TiO2 (X3). The output measured was the CoF. Findings The result obtained from BBD has shown that the most influential parameter was speed, followed by concentration of TiO2 nanoparticles and then normal load. Analysis of variance indicated that the proposed experiment from the quadratic model has successfully interpreted the experimental data with a coefficient of determination R2 = 0.9931. From the contour plot of BBD, the optimization zone for interacting variables has been obtained. The zone indicates two regions of lower friction values (<0.04): concentration between 0.5 to 1.0 Wt.% for a speed range of 1,000 to 2,000 rpm, and load between 17 to 20 kg for a speed in the range of 1,200 to 1,900 rpm. The optimized condition shows that the minimum value of CoF (0.0191) is at speed of 1,782 rpm, load of 20 kg and TiO2 concentration of 1.0 Wt.%. Originality/value In general, it has been shown that RSM is an effective and powerful tool in experimental optimization of multi-variants.

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Response surface methodology as a tool for modelling galacto-oligosaccharide production

Journal of Dairy Research ◽

10.1017/s0022029917000541 ◽

2017 ◽

Vol 84 (4) ◽

pp. 464-470

Author(s):

Claudia I. Vénica ◽

Carina V. Bergamini ◽

María C. Perotti

Keyword(s):

Response Surface Methodology ◽

Reaction Time ◽

Mathematical Models ◽

Response Surface ◽

Maximum Concentration ◽

Cheese Whey ◽

Value Added ◽

Reaction Conditions ◽

Lack Of Fit ◽

Central Composite

The experiments reported in this research paper describe the effects of β-galactosidase enzyme dose and cheese whey amount, on the maximum concentration and yield of galacto-oligosaccahride (GOS) and reaction time. The experimental plan was based on central composite rotational design (CCRD) and modelled by response surface methodology (RSM). The results indicate that the proposed mathematical models could adequately describe the concentration and yield of GOS and the reaction time within the limits of the factors that are being investigated. The variance analysis shows high values of coefficients of determination (>0·97) while no significant lack of fit was evident. Hence, the models could be employed to select reaction conditions applied in the manufacture of products enriched in bioactive compounds with high value-added.

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