Multiple Response Optimization Research Articles

Optimization of Conditions for Extraction of Pepsin-Soluble Collagen from Indonesian Local “Kacang” Goatskin by Response Surface Methodology

Indonesian local “Kacang” goat is an animal species widely known by consumers over the world which possesses many health effects. Goatskin is one of body parts which has potential as collagen sources. The optimal conditions for collagen extraction were determined by response surface methodology in this study. Multiple response optimization designs were applied to evaluate the effects of two independent variables (curing time of NaOH and hydrolysis time) on the pepsin-soluble collagen yield of Indonesian local “Kacang” goatskin. Correlation analysis of the mathematical regression model indicated that quadratic polynomial model could be employed to optimize the extraction of pepsin-soluble collagen. The optimal conditions to obtain the highest yield of pepsin-soluble collagen was without curing NaOH and 24 h time of hydrolysis.

Optimization of performance and emission characteristics of PPCCI engine fuelled with ethanol and diesel blends using grey-Taguchi method

The performance and emission characteristics of a PPCCI engine fuelled with ethanol and diesel blends were carried out on a single cylinder air cooled CI engine. In order to achieve the optimal process response with a limited number of experimental cycles, multi objective grey relational analysis had been applied for solving a multiple response optimization problem. Using grey relational grade and signal-to-noise ratio as a performance index, a combination of input parameters was prefigured so as to achieve optimum response characteristics. It was observed that 20% premixed ratio of blend was most suitable for use in a PPCCI engine without significantly affecting the engine performance and emissions characteristics.

Enhanced transdermal delivery of ondansetron using nanovesicular systems: Fabrication, characterization, optimization and ex-vivo permeation study-Box-Cox transformation practical example

This study aimed to formulate suitable nanovesicles (NVs) for transdermal delivery of Ondansetron. It also illustrated a practical example for the importance of Box-Cox transformation. A 23 full factorial design was used to enable testing transfersomes, ethosomes, and transethosomes of Ondansetron simultaneously. The independent variables (IVs) studied were sodium taurocholate amount, ethanol volume in hydration medium and sonication time. The studied dependent variables (DVs) were: particle size (PS), zeta potential (ZP) and entrapment efficiency (EE). Polynomial equations were used to study the influence of IVs on each DV. Numerical multiple response optimization was applied to select an optimized formula (OF) with the goals of minimizing PS and maximizing ZP absolute value and EE. Box-Cox transformation was adopted to enable modeling PS raised to the power of 1.2 with an excellent prediction R2 of 1.000. ZP and EE were adequately represented directly with prediction R2 of 0.9549 and 0.9892 respectively. Response surface plots helped in explaining the influence of IVs on each DV. Two-sided 95% prediction interval test and percent deviation of actual values from predicted ones proved the validity of the elucidated models. The OF was a transfersomal formula with desirability of 0.866 and showed promising results in ex-vivo permeation study.

Aplicação de Técnicas de Planejamento de Experimentos para Otimização do Comportamento Tribológico e Térmico de Materiais de Atrito Durante o Processo de Frenagem

RESUMO Sistemas de freio têm a finalidade de reduzir ou manter a velocidade de um veículo, levá-lo à imobilidade ou mantê-lo imóvel. O princípio básico dos sistemas de freios por atrito é a conversão da energia cinética do veículo em energia térmica. Neste estudo, buscou-se analisar os parâmetros de operação de um sistema de freio a disco para motocicletas utilizando-se um banco de ensaios baseado no procedimento Krauss, descrita pela norma ABNT NBR 6143/1995. Optou-se por conduzir um Experimento fatorial completo 2³, em que os três fatores de controle considerados (tipo de disco de freio, tipo de pastilha e o valor da pressão de acionamento da manete de freio) foram alterados deliberadamente em dois níveis cada. Analisou-se as propriedades dos materiais envolvidos novos e após um determinado tempo de uso, denominado materiais assentados. Para avaliar o desempenho do sistema de freio durante o processo de frenagem, analisaram-se duas variáveis de resposta simultaneamente: coeficiente de atrito e temperatura final. A partir dos experimentos, o desempenho tribológico mais satisfatório ocorreu para os materiais constituintes do par de atrito, disco e pastilhas, assentados, e um menor valor de pressão de acionamento da manete de freio. Já para a temperatura, o melhor resultado ocorreu para os materiais do par de atrito novo e um menor valor de pressão. Com o intuito de encontrar a melhor combinação dos níveis de cada fator que otimize o desempenho global destas duas variáveis resposta, foi proposta uma técnica de otimização de múltiplas respostas. Como resultado, obteve-se os níveis assentados do par de atrito e o menor valor de pressão como os capazes de otimizar as duas variáveis resposta simultaneamente. Por fim, o banco de ensaios foi adaptado com um motor de maior potência, o que possibilitou evidenciar e esclarecer mais sobre o efeito brake fade.

Advances in solution methods for optimisation of multiple quality characteristics in manufacturing processes

A typical problem generally encountered in the quality control and improvement operations of manufacturing processes involves simultaneously optimising multiple critical quality characteristics (or 'multiple responses'). These type of problems are so-called 'multiple response optimisation (MRO) problems'. Owing to correlation between multiple responses, trade-off solution(s) are inevitable. The term 'trade-off' is an explicit compromised solution, considering the bias from the targets and variability in the responses. The global best solution for such a problem is usually unknown. Over the years, various solution methods and their theoretical advancement are proposed. However, only a handful of critical reviews are evident in open literature. Available review articles on MRO seem insufficient and address only specific aspects of the solution methods (e.g., response-surface modelling, problem formulation, or optimisation techniques). In this study, five different types of solution methods suggested for MRO problems are categorised and critically reviewed, including response-surface-based contour plot, response surface-free data mining methods, etc. The theoretical relationship between the MRO and the multi-objective-optimisation solution methods is analysed along with identifying potential research direction in this domain.

Multi Performance Optimization in Wire Cut EDM of Inconel 825 Using Desirability Function Coupled With Analytical Hierarchy Process

In this work, optimization of multiple responses (SR, kerf, MRR) is carried out using desirability function analysis (DFA) with weights optimized by analytical hierarchy process (AHP) in WEDM of Inconel 825. Process parameters Ton, Toff, Ip and SV are varied as per Box-Behnken L27 orthogonal array. At the optimum setting Ton: 112µs, Toff: 48µs, Ip: 200A and SV: 25V, SR, kerf and MMR improved by 3.73%, 1.22% and 4.46% respectively. Toff has significant effect on composite desirability (CD) followed by SV, Ton and Ip. CD improved by 1.48% with optimized weights as compared to equal weights.

Modelling and Optimization of Al–SiC MMC through EDM Process Using Copper and Brass Electrodes

Extensive investigation done on machinability of aluminium/10% silicon carbide metal matrix composite (Al/SiC MMC) with copper and brass electrodes in die-sinking electrical discharge machining (EDM) is reported in the present study. Experiments are performed as per the Box-Behnken design of RSM to study the two performance characteristics i.e. electrode wear ratio (EWR) and material removal rate (MRR) with the five input machining parameters like, low voltage current, high voltage current, pulse off time, pulse on time and flushing pressure. Quadratic regression models are developed for the individual responses and multi-objective particle swarm optimisation (MOPSO) algorithm is employed to find the optimal process parameter settings. Finally, a novel MOPSO algorithm has been suggested for simultaneous optimisation of multiple responses which presents valuable information for governing the machining parameters to enhance accuracy of the electrical discharge machined parts and a confirmation test is performed at the optimized parameter setting for copper and brass electrodes respectively to validate the result. The scanning electron microscope (SEM) also used to investigate the surface characteristics of the machined surface.

Optimization of Process Parameters of EDM Process Using Fuzzy Logic and Taguchi Methods for Improving Material Removal Rate and Surface Finish

The main indent of this work is to optimization of multiple responses of Electric discharge machining (EDM) using Fuzzy method coupled with Taguchi is attempted. The work piece material was AISI 304 Stainless Steel and a cylindrical copper electrode with side impulse flushing was used. The effect of machining parameters, i.e., discharge current,pulse on time, discharge voltage and Inter Electrode Gap (IEG) on the Material Removal Rate (MRR), Tool Wear Rate and Surface Roughness (Ra) in EDM are examined. L9 orthogonal array was used to design the experiment and the effect of the factors on the responses were studied. As the responses are conflicting in nature, factors of a single combination will not be treated as best machining performance for all responses. The multiple responses were converted into a single characteristic index by using Fuzzy logic known as Multi Performance Characteristic Index (MPCI). Finally, MPCIs were optimized by using Taguchi.

Machining performance of aluminium matrix composite and use of WPCA based Taguchi technique for multiple response optimization

Machining performance of aluminium matrix composite and use of WPCA based Taguchi technique for multiple response optimization

Effect of chitosan and carrageenan-based edible coatings on post-harvested longan (Dimocarpus longan) fruits

ABSTRACTThe effect of chitosan/carrageenan and glycerol as edible coating materials in preserving the fresh longan fruits stored at ambient temperature was evaluated. The concentration of coating components played an important role in the process of controlling quality changes and quantity losses. Changes in fruits’ weight loss, respiration rate and color were used as a measure of the coating’s effectiveness. Results have shown that increase in the chitosan or carrageenan concentration led to significant (p < 0.05) decreases in water loss, weight loss and respiratory rate in coated fruits. However, in carrageenan-coated fruits, high increase in concentration (> 1.19%) of the carrageenan resulted in slight increases in water and weight losses. From the multiple response optimization analysis, a combination of 1.29% (w/v) chitosan with 0.42% glycerol and 1.49% (w/v) carrageenan with 0.03% glycerol were predicted to give the desired coating because they were able to preserve the longan by showing minimal quality changes and quantity losses.

Multiple-response optimization for surface quality and productivity during turning Al 7075/SiCp composite in spray cooling environment

Effects of machining process parameters on average roughness (Ra) of machined surface and rate of material removal (M) were investigated while turning silicon carbide particulate reinforced Al 7075 (Al 7075/SiCp) metal matrix composite in air-water spray cooling environment. Quadratic models were developed for the responses. Taguchi based grey relational analysis was used to optimize Ra and M simultaneously, which revealed 206 m/min of cutting speed (V), 0.05 mm/rev of feed (f) and 0.3 mm of depth of cut (d) were the optimized parametric levels. Significance of process parameters on the multi-response quality index was verified through Analysis of Variance (ANOVA).

Property Optimization of Impeller Casting Using GRA

Ductile irons are important engineering materials because of its high strength to weight ratio and castability. The ductile iron castings are used widely for automobile applications due to its wide spectrum of property range. Weight reduction is important in automobile to improve its fuel efficiency which can be achieved by thinning down the casting sections without altering its functionality. Generally automobile castings are having varying section thickness. Varying thickness castings offers different cooling rates while solidification of the casting. The solidification cooling rate decides the final microstructure in cast components. Cooling rate was found to be affect directly the amount of pearlite and ultimately as cast properties in varying thickness ductile iron castings. In view of this, the automobile impeller casting is selected as it consists of varying section thickness in which small sections are connected to central hub. The casting solidification simulations were performed and analyzed. The solidification cooling rates were analyzed further to correlate the experimental processing parameters. The samples from poured castings were analyzed for microstructure and hardness at different section thickness. Multiple response optimization of microstructure and hardness is carried out by combined taguchi and Grey Relational Analysis (GRA). Contribution of input variables on the output variables is attained using ANOVA.

SRO_ANN: An integrated MatLab toolbox for multiple surface response optimization using radial basis functions

SRO_ANN, a MatLab® toolbox for implementing multiple surface response optimization by artificial neural networks (SRO_ANN) is presented. Radial basis functions, a type of artificial neural networks, are applied through an easily managed graphical user interface. A detailed description of the interface is provided, including a simulated and two literature examples which allow one to show the potentiality of the software. The discussed experimental examples correspond to: (1) the maximization of the research octane number (RON) of fuels, influenced by three factors (reaction temperature, operating pressure and low liquid hourly space velocity), and (2) the optimization of the calcification process for diced tomatoes, evaluated through three different responses (calcium content, firmness and pH), which are affected by three factors (calcium concentration, solution temperature and treatment time). The results show that the application of a nonparametric tool can enhance the performance of optimization modeling tasks.

Multi-objective performance investigation of orthopaedic bone drilling using Taguchi membership function.

Orthopaedic bone drilling attacks the surrounded bone cells and tissues in terms of thermal and mechanical in such a way that these cells can get damaged permanently. This damage to the surrounding of drill point upsurges the rehabilitation time of injury and in some cases leads to the failure of the bone screw joint. This study is based on the optimization of multiple response characteristics to minimize the damage during the bone drilling. All real-life problems, including bone drilling, require the multiple response optimization for getting a combined optimization result for all countable response characteristics. The Taguchi optimization technique is observed as a highly recommended tool for single response optimization. This article uses the Taguchi technique with little modification of membership function that will help to convert the multiple response characteristics into single response and further optimize it as a single function of performance. Rotational speed, feed rate of tool at three different levels with three different kinds of drilling tools are the drilling parameters selected for the study. The objective of this study is to minimize the surface roughness and thrust force simultaneously. Analysis of variance helps to find the percentage contribution and significance of each parameter on the performance.

β-Carotene nanodispersions synthesis by three-component stabilizer system using mixture design.

In current research, simple centroid mixture design was applied to evaluate the interaction effects between three selected food grade stabilizers, namely, Tween 80, gelatine and pectin as stabilizing system in the formation of carotenoid nanoparticles through solvent displacement process. Both, particle size and β-carotene loss of produced nanodispersions, as selected response factors, special cubic regression models with acceptable determination coefficient (>90%) was obtained. The multiple response optimization analysis showed that the overall optimum concentration for stabilizers will be 35% w/w Tween 80, 46% w/w gelatine and 19% w/w pectin, which led to the production of β-carotene nanoparticles of spherical shape with minimum particle size of 155.8nm and carotenoids loss of 25.3% w/w.

Optimization of single screw extrusion process for producing fish feeds based on vegetable meals and evaluation of nutritional effects using a juvenile Piaractus mesopotamicus model

Optimization of extrusion process for producing extruded feeds based on vegetable meals using a single screw extruder was study. Also growth performance of extruded feed obtained in optimal conditions using a juvenile P mesopotamicus model was evaluated. In order to study the simultaneous effect of blend moisture (M) and extrusion temperature (T) on expansion (E), bulk density (BD), water absorption index (WAI), water solubility index (WSI), and floatability (F) a central composite design (32) was used. The levels of each variable were: T: 160–180–200°C and M: 14–16–18g/100g. A multiple response optimization of physical properties of experimental extruded feed (E, F, BD and WSI) was performed using the Derringer’s desirability function. The global desirability function value was 0.8805, and the obtained optimal conditions were 181.5°C and 15.8g/100g of moisture content. Experimental extruded feed (EF) obtained at such conditions presented the following physical properties: E: 2.23±0.03, F: 99.0±1.0%, BD: 270.9±13.8g/L, and WSI: 12.9±1.5g/100g. Crude protein content of EF was higher than that of control feed (CF). However, no significant difference for crude lipid (∼37.9g/kg) and total starch content was found. Gelatinized starch for EF (430.5±7.0g/kg) was higher than that obtained for CF (378.9±6.7g/kg), corresponding to 97.0±2.1 and 88.1±2.2% of degree of gelatinization, respectively. Chemical score of CF was 93.3%, lysine being the limiting amino acid. However, in the case of EF no limiting amino acid was found. Both diets presented a predominance of unsaturated fatty acids of C18 series (C18:1 and C18:2 (n–6)). EF showed higher content of oleic, linolenic, cis-11-eicosenoic and di-homo-γ-linolenic acid than CF. Nevertheless, only for CF, eicosapentaenoic acid, docosapentaenoic, and docosahexaenoic acid were detected. Significant differences in final fish body weight, weight gain, specific growth rate, and condition factor were not detected between dietary treatments after 120days of feeding trial. Extrusion using a single screw extruder in optimal process conditions could be used to obtain fish feed based in vegetable meals and good physical properties with proper growth performance on juvenile P. mesopotamicus.

Improved extraction methods for simultaneous recovery of umami compounds from six different mushrooms

Given the importance of umami compounds in culinary and food industries, this study sought to develop improved methods for simultaneous extraction of various umami taste components such as free amino acids (FAAs) and 5′-mononucleotides from shiitake mushroom (Lentinula edodes), oyster mushroom (Pleurotus ostreatus), tea tree mushroom (Agrocybe aegerita), and white, brown and portobello champignons (Agaricus bisporus). An optimized HPLC method was developed for efficient analysis of 5′-mononucleotides. Using multiple response optimization approach, optimum conditions required for extraction of total FAAs, total 5′-mononucleotides and total umami compounds were determined. The highest recovery of FAAs was obtained when mushrooms were extracted at room temperature for 180min, while the highest 5′-mononucleotides were recovered by extracting at 70°C for 30min. Based on the desirability function, the optimal parameters of temperature, time and solvent volume for simultaneous recovery of umami components were found to be 70°C, 30min and 50mL, respectively. Using the optimized method, white champignons and tea tree mushrooms were found to be the richest source for umami components. Water was found to be a better solvent than conventionally used 0.1M HCl for extraction of FAAs from mushrooms.

Uncertainty analysis of trade‐offs between multiple responses using hypervolume

AbstractWhen multiple responses are considered in process optimization, the degree to which they can be simultaneously optimized depends on the optimization objectives and the amount of trade‐offs between the responses. The normalized hypervolume of the Pareto front is a useful summary to quantify the amount of trade‐offs required to balance performance across the multiple responses. To quantify the impact of uncertainty of the estimated response surfaces and add realism to what future data to expect, 2 versions of the scaled normalized hypervolume of the Pareto front are presented. To demonstrate the variation of the hypervolume distributions, we explore a case study for a chemical process involving 3 responses, each with a different type of optimization goal. Results show that the global normalized hypervolume characterizes the proximity to the ideal results possible, while the instance‐specific summary considers the richness of the front and the severity of trade‐offs between alternatives. The 2 scaling schemes complement each other and highlight different features of the Pareto front and hence are useful to quantify what solutions are possible for simultaneous optimization of multiple responses.

A multiresponse model for reliability‐based simulation optimization in systems subjected to random external stresses

AbstractSystems with multiple output characteristics are very difficult to optimize, especially where outputs are interrelated and some external factors affect their performance. In many systems, some correlations and/or conflicts exist between performance measures. Multiple response optimization is a mathematical‐statistical technique that helps experts improve all the system's outputs, simultaneously. The present work aims to derive a stress‐strength reliability measure for multiresponse problems, so the strength criteria of a system are optimized against external stresses. To achieve this purpose, multivariate normal‐normal stress‐strength models are developed and applied for optimization of (s, S) inventory systems in which demands and lead times are random. At the end, a numerical example is also studied to illustrate the efficacy of the proposed approach.

Chemical assisted ultrasonic machining of polycarbonate glass and optimization of process parameters by Taguchi and grey relational analysis

Polycarbonate bullet proof (UL-752) glass is highly demanded material in automobile, aerospace and space industries. It is also used in security chambers or buildings, because of its unique properties such as; impact bare capacity, hardness, excellent transparency, higher mechanical strength, good dimensional stability etc. Objective of this research investigation is focused at studying the impact of different input parameters (concentration, abrasive, power rating, grit size, HF acid concentration and tool material) on output responses (material removal rate, tool wear rate and surface roughness) in ultrasonic drilling of polycarbonate bullet proof (UL-752) glass. The experiments have been performed by using Taguchi’s L27 orthogonal array and grey relation analysis has been used for the optimization of multiple responses. To find out the significant factors, analysis of variance is further employed. Through GRA approach, MRR and TWR improved by 113% and 100% respectively. HF acid also reduced the delamination affect.