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Dynamic multiple responses by ideal solution analysis
Abstract
High technology industry must continuously improve product quality and multiple correlated product quality characteristics must be assessed simultaneously due to product complexity. While many Taguchi method applications have addressed a state system problem, dynamic multi-response problems have seldom been examined. This study presents a novel optimization procedure for dynamic multiple responses based on Taguchi’s parameter design. The signal to noise (SN) ratio and system sensitivity are used to assess the performance of each response. Principal component analysis is then performed on the SN values and system sensitivity values to obtain a set of uncorrelated components. The optimization direction for each component is also determined based on the corresponding variation mode chart. Finally, the relative closeness to the ideal solution resulting from the technique for order preference by similarity to ideal solution is determined as an overall performance index for multiple responses. A case study obtained from biological reduction of an ethyl acetoacetate process demonstrates the effectiveness of the proposed procedure.
... Industries have, therefore, all the time more highlighted building up measures competent of concurrently optimizing the multi-response dynamic systems in the light of the increasing complexity of modern product design. To deal with the requirements of the contemporary industries, more than a few studies have (Tong et al., 2002;Tong et al., 2004;Hsieh et al., 2005;Wang and Tong, 2005;Wu and Yeh, 2005;Chang, 2006;Wang, 2007;Wu, 2007;Chang, 2008;Tong et al., 2008;Wu, 2009;Zhong and Liu, 2009;Chang and Chen, 2011;Wang et al., 2011;Sharma et al., 2012;Gauri, 2014;Zhang et al., 2014;Wu, 2015;He et al., 2015;Bashiri et al., 2016) have proposed different procedures for optimizing a multi-response dynamic system. Applying the two-step procedure is not feasible for optimizing a multi-response dynamic system because it is almost impossible to find out any control factor that may be considered as an adjustment factor. ...
... The available approaches for the optimization of dynamic systems can be broadly classified into three categories: (1) mathematical modelling based approaches (Tong et al., 2002;Hsieh et al., 2005;Wu, 2007;Zhang et al., 2014;Bashiri et al., 2016), (2) multiple attribute decision making (MADM) methods based approaches (Tong et al., 2004;Wang and Tong, 2005;Wang, 2007;Zhong and Liu, 2009;Gauri, 2014;Wu, 2015) and (3) meta-heuristic approaches (Chang, 2006;Chang, 2008;Tong et al., 2008;Chang and Chen, 2011). The implementation of the mathematical modelling based approaches requires that the engineers possess a well-built experience in mathematics or statistics, whereas the MADM method based approaches are easy to implement but the optimal solution derived by these approaches may not guarantee that all response means are near to their relevant goal values at different signal levels. ...
... Tong et al. (2002) have used dual-response-surface method (RSM) and composite desirability function (CDF) for optimization of a multi-response dynamic system. Tong et al. (2004) utilizes principal component analysis (PCA) to simplify the dynamic multi-response problems and applied TOPSIS (technique for order preference by similarity to ideal solution) (Hwang and Yoon, 1981;Hwang et al., 1993) to derive the overall performance index for optimization. Hsieh et al. (2005) have made use of regression analysis to examine the noteworthy control factors influencing the deviations as well as responsiveness of a dynamic system and then employed CDF for optimization. ...
The principal difference between a dynamic and a static system is that the former includes a signal factor for expressing the intended output while the later does not. Assuming a linear association exists between the response and signal variables, Taguchi offered a two-stage route for optimizing a dynamic system: maximize the dynamic signal-to noise ratio (DSN) and then, change the gradient to the desired gradient by a suitable modification parameter. Some researchers have indicated limitations to Taguchi’s DSN analysis, and advocated alternative approaches for optimization of a dynamic system. However, the Taguchi method as well as these alternative approaches is useful for optimizing a single-response dynamic system only. In realism, the majority of the contemporary manufacturing practices encompass numerous response variables as well as industries demand for developing procedures for optimizing multi-response dynamic system. This paper proposes a novel procedure that integrates multiple regression (MR) technique and Taguchi’s DSN concept to optimize the multi-response dynamic system. In this method, appropriate multiple regression equations according to a chosen model for dynamic system are fitted first based on the observed experimental data and then DSN (called MRDSN) for different response variables are computed using the MRbased predicted values. Finally, weighted MRDSN is considered as the objective function for the optimization. The proposed procedure is investigated with respect to three modelling approaches for the dynamic systems. The results of analysis reveal that the proposed procedure with response modelling approach results in the best optimization performance. It also results in better optimization performance than back-propagation neural network-based approach and data mining-based approach reported by the past researchers. Keywords: multiple responses, multiple regression, weighted dynamic signal-to-noise ratio, performance measure modelling, response function modelling, response modelling, optimization
... Industry has increasingly emphasized developing procedures capable of simultaneously optimizing the multi-response dynamic systems in light of the increasing complexity of modern product design. To cope with the need of the modern industries, several studies (Tong et al., 2001;Tong et al., 2004;Hsieh et al., 2005;Wu & Yeh, 2005;Chang, 2006;Wang, 2007;Chang, 2008;Tong et al., 2008;Wu, 2009;Chang & Chen, 2011;Gauri, 2014) have proposed different procedures for optimizing a multi-response dynamic system. The goal of optimizing a multi-response dynamic system is to find a setting combination of control factors (controllable variables) that would result in the optimum values of all response variables at all signal levels. ...
... Different researchers have advocated different approaches for modelling the multiple responses but most of them (Tong et al., 2001;Hsieh et al., 2004;Chang, 2006;Chang, 2008;Wu, 2009;Chang and Chen, 2011) have used CDF as the performance metric for optimization of the multi-response dynamic systems. Tong et al. (2004), Wang and Tong (2004), Wu and Yeh (2005), Wang (2007) and Gauri (2014) have used different performance metrics. While overall relative closeness to the ideal solution is considered as the performance metric by Tong et al. (2004), overall grey relational grade is considered as the performance metric by Wang and Tong (2004) and Wang (2007). ...
... Tong et al. (2004), Wang and Tong (2004), Wu and Yeh (2005), Wang (2007) and Gauri (2014) have used different performance metrics. While overall relative closeness to the ideal solution is considered as the performance metric by Tong et al. (2004), overall grey relational grade is considered as the performance metric by Wang and Tong (2004) and Wang (2007). Wu and Yeh (2005) have derived total quality loss and minimized it to determine the optimal settings for a multi-response dynamic system, and Gauri (2014) considered overall utility value as the objective function for optimization of multi-response dynamic systems. ...
A dynamic system differs from a static system in that it contains signal factor and the target value depends on the level of the signal factor set by the system operator. The aim of optimizing a multi-response dynamic system is to find a setting combination of input controllable factors that would result in optimum values of all response variables at all signal levels. The most commonly used performance metric for optimizing a multi-response dynamic system is the composite desirability function (CDF). The advantage of using CDF is that it is a simple unit less measure and it has a good foundation in statistical practice. However, the problem with the CDF is that it does not consider the variability of the individual response variables. Moreover, if the specification limits for the response variables are not provided the CDF cannot be computed. In this paper, a new performance metric for multi-response dynamic system, called multiple regression-based weighted signal-to-noise ratio (MRWSN) is proposed, which overcome the limitations of CDF. Two sets of experimental data on multi-response dynamic systems, taken from literature, are analysed using both CDF-based and the proposed MRWSN-based approaches for optimization. The results show that the MRWSN-based approach also results in substantially better optimization performance than the CDF-based approach.
... The various approaches for solving multi-response optimization problems in dynamic system can broadly be classified into three categories, e.g. (1) Response surface methodology and desirability function (RSM-DF) based approaches (Tong et al., 2002;Hsieh et al., 2005;Wu, 2009) (2) Artificial intelligence (AI) based approaches (Chang, 2006;Chang, 2008;Tong et al., 2008;Chang and Chen, 2011 ) and (3) Principal component analysis (PCA) based approaches (Tong et al., 2004;Wang, 2007). The basic advantage of using desirability function as performance metric is that it is a simple unitless measure and can allow the user to weigh the responses according to their importance. ...
... The main advantage of PCA-based approaches is that it takes into account correlation among the multiple responses. Tong et al. (2004) have proposed a PCA-based technique for order preference by similarity to ideal solution (TOPSIS) method, whereas Wang (2007) has proposed a PCA-based multiple criteria evaluation of the grey relational model (MCE-GRM) for optimization of multiple responses in a dynamic system. The PCA-based approaches are easily understandable and can be implemented using Excel sheet. ...
... Taguchi used SNR (η) and system sensitivity (SS) as the performance measures in a dynamic system to assess the robustness of a process (Tong et al, 2004;Wang, 2007). The SNR and SS values for j th response variable corresponding to i th trial, ij and ij SS , can be obtained using the following equations: ...
Optimization of a multi-response dynamic system aims at finding out a setting combination of input controllable factors that would result in optimum values for all response variables at all signal levels. In real life situation, often the multiple responses are found to be correlated. The main advantage of PCA-based approaches is that it takes into account the correlation among the multiple responses. Two PCA-based approaches that are commonly used for optimization of multiple responses in dynamic system are PCA-based technique for order preference by similarity to ideal solution (TOPSIS) and PCA-based multiple criteria evaluation of the grey relational model (MCE-GRM). This paper presents a new PCA-based approach, called PCA-based utility theory (UT) approach, for optimization of multiple dynamic responses and compares its optimization performance with other existing PCA-based approaches. The results show that the proposed PCA-based UT method is superior to the other PCA-based approaches.
... Training in neural network 88 5. 30 Regression plot for training data 5. 31 Regression plot for testing data 5. 32 Membership function plot 91 5. 33 Surface plot of MPCI vs Ip, Ton 93 5. 34 Surface plot of MPCI vs Ip, τ 93 5. 35 The convergence curve 94 5. 36 Pareto-optimal front for objectives MRR and TWR 98 5. 37 Pareto-optimal front for objectives Ra and Circularity 98 5.38 Pareto-optimal front for objectives MRR and TWR 102 5. 39 Pareto-optimal front for objectives Ra and Circularity 102 5. [40][41][42][43][44][45][46][47] White layer thick ness 104-108 5. [48][49] SEM picture of machined surface 109 6. 1 Two-dimensional axisymmetric model 111 6. 2 Mode of heat transfer in the work piece 111 6. 3 Temperature distribution 114 6.4 Predicted bowl shaped crater using the FEM analysis 114 6.5 ...
... The reason of applying PCA is to obtain uncorrelated principal components when PCA is applied to responses. Finally, closeness coefficient obtained through TOPSIS is treated as single response [45]. Tong and Su proposed a fuzzy TOPSIS method to convert multiresponses (deposition thickness and refractive index) in plasma enhanced chemical vapor deposition (PECVD) process into single response. ...
The present work proposes an intelligent approach to solve multi-response optimization problem in electrical discharge machining of AISI D2 using response surface methodology (RSM) combined with optimization techniques. Four process parameters (factors) such as discharge current (Ip), pulse-on-time (Ton), duty factor (τ) and flushing pressure (Fp) and four important responses like material removal rate (MRR), tool wear rate (TWR), surface roughness (Ra) and circularity (r1/r2) of machined component are considered in this study. A Box-Behnken RSM design is used to collect experimental data and develop empirical models relating input parameters and responses. Genetic algorithm (GA), an efficient search technique, is used to obtain the optimal setting for desired responses. It is to be noted that there is no single optimal setting which will produce best performance satisfying all the responses. In industries, to solve such problems, managers frequently depend on their past experience and judgement. Human intervention causes uncertainties present in the decision making process gleaned into solution methodology resulting in inferior solutions. Fuzzy inference system has been a viable option to address multiple response problems considering uncertainties and impreciseness caused during judgement process and experimental data collection. However, choosing right kind of membership functions and development of fuzzy rule base happen to be cumbersome job for the managers. To address this issue, a methodology based on combined neuro-fuzzy system and particle swarm optimization (PSO) is adopted to optimize multiple responses simultaneously. To avoid the conflicting nature of responses, they are first converted to signal-to-noise (S/N) ratio and then normalized. The proposed neuro-fuzzy approach is used to convert the responses into a single equivalent response known as Multi-response Performance Characteristic Index (MPCI). The effect of parameters on MPCI values has been studied in detail and a process model has been developed. Finally, optimal parameter setting is obtained by particle swarm optimization technique. The optimal setting so generated that satisfy all the responses may not be the best one due to aggregation of responses into a single response during neuro-fuzzy stage. In this direction, a multi-objective optimization based on non-dominated sorting genetic algorithm (NSGA) has been adopted to optimize the responses such that a set of mutually dominant solutions are found over a wide range of machining parameters. The proposed optimal settings are validated using thermal-modeling of finite element analysis.
... TOPSIS is an aggregation operator that was developed by Chen and Hwang (1992) and has been widely applied by other researchers (Cheng et al., 2003;Deng et al., 2000;Montanari, 2004;Singh and Agrawal, 2012;Tong et al., 2004). In the conceptual design phase, TOPSIS has been used in a very limited way (Chang and Chen, 2014;Lin et al., 2008). ...
... which is desirable in decision-making situation being considered. TOPSIS, which is widely used in the literature (Chang and Chen, 2014;Cheng et al., 2003;Deng et al., 2000;Montanari, 2004;Singh and Agrawal, 2012;Tong et al., 2004), has a high degree of compensation since it greatly intensifies the effect of high LPVs. This intensification effect is mainly attributed to the use of a sum of an Euclidean distance to calculate the closeness of initial concepts to the reference concepts. ...
Making decisions on a sound basis in early phases is one of the most difficult challenges in the product development process, especially when dealing with immature concepts. Moreover, life-cycle cost can be influenced up to 70% by decisions taken during the conceptual design phases. The need for reliable multi-criteria decision aiding methods is thus greater in these phases. Various multi-criteria decision aiding methods are proposed and used in the literature. The main criticism of these methods is that they usually produce contradictory results for the same problem. In this work, seven widely used multi-criteria decision aiding methods (weighed sum, weighted product, Kim and Lin, compromise programming, TOPSIS, quadratic mean and ELECTRE I) are analysed. This analysis was based on a real industrial case to develop a solar collector. The proposed multi-criteria decision aiding methods were compared in terms of three criteria deemed relevant in the relevant context: (1) adaptation of the type of results the multi-criteria decision aiding method is expected to bring, (2) correct handling of input information and (3) adaptation of the degree of compensation. Based on these criteria, it was proven that weighted product is the most appropriate multi-criteria decision aiding method in our case. In addition, it has been demonstrated that sensitivity analysis can improve the benefit of using the multi-criteria decision aiding method chosen when dealing with imprecise information due to immaturity of concepts.
... The effect of L-histidine on the corrosion mitigating property of PVA was explored by adopting Taguchi experimental design. This approach of process optimization enables the study of influence of individual factors, establishes the relationship between variables and operational conditions, and predicts the performance at the optimum levels based on the concept of S/N ratio ofthe response values of a few well-defined experiments [21]. ...
... The values reported as errors arise from uncontrollable factors (noises), which should be less than 50%; otherwise the results would not be reliable [21]. The error value reported in Table 5 is 0%. ...
The synergistic influence of L-histidine on the acid corrosion inhibition property of polyvinyl
alcohol was monitored by the Taguchi experimental design. The proposed Taguchi methodology
consisted of four factors viz., L-histidine, PVA, exposure time and temperature, at three different
levels which were connected in sequence wise to achieve a L9 orthogonal array. A L9orthogonal
array of experiments was constructed and the resulted experimental inhibition efficiencies
were adopted for the analyses to find the optimum conditions for the better synergism. The
experiments wereperformed with the selected factors and levels and the results were further
processed with Qualitek-4 software usingthe quality character “bigger is the better” to find
the optimized conditions. A validation experiment was conducted at the specified optimized
conditions and the results were used to calculate the synergism parameter.The synergism
parameter is greater than one proved the synergistic effect of L-histidine on PVA.
... The best factor/level combination is obtained using this method whereas the mean of the response is taken to the target value. It also helps to reduce variability (Tong et al., 2004). ...
In this study removing heavy metals, Cr (III), and Pb (II) from wastewater, Microorganism Trichoderma sp. biosorption was performed using Cr (III), and Pb (II) removal was taken into account. For this study, 3^3 Factorial Experiment Designs were used, and temperature (°C), biosorbent dosage (g/L), and pH were selected as the main factors for Cr (III), and Pb (II) metals and three levels of these factors were determined as low, medium, and high. In this study, which was carried out to increase the metal removal efficiency and biosorption capacity, the main factors and the significance of each interaction of these factors were examined with 3^3 Factorial Design. For this purpose, by conducting Analysis of Variance (ANOVA) via Response Surface Methodology and optimization, more detailed results were obtained regarding the factors affecting the efficiency of metal removal from wastewater.
... Then, it needs to determine the positive (best) ideal solution (PIS) and the negative (worst) ideal solution (NIS). The ideal best and ideal worst solution formulas are defined as follows [37]: ...
The video game market has become increasingly popular among children and adolescents in recent decades. In this research, we investigated the Video Game Addiction Scale (VGAS) for Chinese children and adolescents. We aimed to examine children and adolescents’ prioritization on the VGAS criteria and comparative analysis of the trend of video game addiction among them. A cross-sectional paper questionnaire study was conducted on 1400 Chinese students from grade 3 (9 years old) to grade 12 (18 years old). The respondents had to complete the socio-demographic information and the VGAS test. The VGAS characteristic was prepared in 18 criteria, which was the combination of the Video Game Addiction Test (VAT), Gaming Addiction Scale (GAS), and Revised Chinese Internet Addiction (CIAS-R). Eventually, the VGAS criteria prioritization was ranked methodologically through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for each grade separately. Additionally, the Analytic Hierarchy Process (AHP) weighting technique was utilized to analyze the video game addiction of each grade under the four alternatives, individually. The results indicate that 3rd-grade students with some levels of addiction were the youngest who felt their life would not be fun without video games. Students in 5th grade with some levels of addiction were the youngest students who disclosed that their willingness to play video games is for forgetting their problems or feeling down. Moreover, they played video games more than before, thus, they did not sleep enough. Pupils of grade 6 reported that they played video games more than last semester. In their opinion, it is fair to play video games this much and does not need to reduce playing hours. Not getting enough sleep because of playing video games was seen in 7th graders as their first preference. 10th-grade students were the first to neglect to do their important responsibilities for playing video games. None of the 7th and 12th graders were somehow safe from video game addiction. In conclusion, playing video games can negatively affect studying, sleeplessness, getting far from society, and skipping important responsibilities for school students. Furthermore, the symptoms of video game addiction had seen at younger ages. These data provided insights for decision-makers to target effective measures to prevent children and adolescents’ video game addiction.
... The best factor/level combination is obtained using this method whereas the mean of the response is taken to the target value. It also helps to reduce variability (Tong et al., 2004). ...
This study aims to prepare a low‐cost, environmentally friendly, and alternative, biosorbent to remove chromium Cr (III) and lead Pb (II) from polluted water and to find out the highest removal efficiencies using 2k factorial experiments. The Cr (III) and Pb (II) tolerant fungal strain identified as Penicillium chrysogenum was isolated from ceramic industrial sludge. The impact of process variables on biosorption of Cr (III) and Pb (II) by P. chrysogenum was first evaluated with the Taguchi screening design. Factors and levels were determined to optimize Cr (III) and Pb (II) removal efficiency. According to this, five factors; initial concentration, pH, biosorbent dose, temperature, and inactivation methods were determined for both metals, each factor defined as a fixed factor with two levels. Optimization of the parameters affecting the removal process was determined by the Taguchi method and the signal‐to‐noise (S/N) ratios are calculated. The maximum removal efficiency (99.92%) was observed at pH 7, biosorbent 1 mg L–1, inactivation with autoclaving, and at 20°C with an initial metal concentration of 50 mg L–1 Cr (III). On the other hand, the maximum removal efficiency (98.99%) was observed at pH 4, biosorbent 5 mg L–1, inactivation with autoclaving, and at 20°C with an initial metal concentration of 50 mg L–1 Pb (II). Furthermore, metal ions removal by P. chrysogenum was also confirmed by scanning electron microscopy (SEM) combined with an energy dispersive X‐ray spectrometer (EDS). The presence of functional groups on fungal cells of metal binding was investigated by Fourier transform infrared (FT‐IR).
... To assess robustness of overall process, Taguchi technique employed S/N ratio as a performance evaluation of a dynamic system (Tong et al., 2004). Mean square deviation (MSD), is the numerical expression for S/N ration for 'bigger-is-better' situations for performance statistics that determine deviation from target and is given by ...
In this study, a previously isolated bacterial strain, Micrococcus sp. MAGK3 was employed to explore its malathion biodegradation potential. A considerable degradation (66.79%) was attained with malathion (0.03%) being the sole carbon source after 240h of incubation. To enhance malathion biodegradation, effects of co-substrates, pH, temperature, initial malathion concentration, agitation (rpm), and inoculum size were evaluated using Taguchi methodology. Experiments with various combinations of factors were conducted, and results in respect of malathion biodegradation were evaluated in the Qualitek-4 software to determine the key effect of individual factors, their interaction effects, and optimal levels of process factors. All parameters contributed to malathion biodegradation, and Taguchi DOE's ability to predict optimum response, was established by experimentation via optimized levels of factors (carbon source 0.1%, nitrogen source 0.1%, pH 7, temperature 35 °C, pesticide concentration 0.03%, agitation 150 rpm, and inoculum size 2%(w/v). Results confirmed that pesticide concentration caused the maximum impact (34.09%) on malathion degradation followed by nitrogen source (32.11%), temperature (20.99%), RPM (6.55%), inoculum size (3.26%), carbon source (2.81%) and pH (0.2%). Before optimization, Micrococcus sp. MAGK3 had an average degradation of 57.94% within 168 h, but after optimization, the rate of biodegradation improved to 87% within 38 h. Confirmation of malathion biodegradation was performed by UHPLC, and GC-MS analysis and a possible degradation pathway was proposed for malathion biodegradation by Micrococcus sp. MAGK3. For the time being, this is the first publication to employ the Taguchi design of experiment to optimize the degradation of malathion by Micrococcus sp. MAGK3.
... The analysis showed that the increase in all parameters except for CS concentration caused a decrease in EE%, and the effect was significant for all factors at all levels ( Figure 1). The Taguchi designs help to assess the effect of the main factors on responses in a few experiments (9 instead of 3 4 or 98 experiments) (Chunlai et al., 2019;Joseph & Piganatiells, 1988;Tong et al., 2004). However, this design does not consider the interactions among the factors, which is the main limitation of the design. ...
Crocin, as a nutraceutical component of saffron (Crocus sativus L.), possesses numerous therapeutic effects. In the current study, a crocin‐loaded chitosan/alginate (CS/ALG) nanocarrier was developed for oral delivery. The influence of preparation variables including pH and the concentrations of CS, ALG, and calcium chloride (CaCl2) on encapsulation efficiency (EE%) and loading efficiency (LE%) of CS/ALG nanoparticles (NPs) was evaluated by L9 Taguchi orthogonal array (OA). The results showed that at 0.25% w/v CS, 0.1% w/v ALG, pH 4.5, and absence of CaCl2, crocin was loaded into CS/ALG NPs with EE% and LE% of 91.5% and 27.4%, respectively. Ultrasonication reduced the particle sizes (PSs) up to 100 nm, and freeze‐dried NPs reproduced the particles with average size of 90 nm. Scanning electron microscopy (SEM) was successfully used to characterize the structure and morphology of freeze‐dried NPs, confirming very fine NPs having sizes less than 100 nm. Crocin loaded into NPs showed higher stability in simulated gastric pH 2 compared to free crocin (2.1% and 7.5% degradation at 60 min, respectively). Furthermore, a pH‐dependent sustained crocin release was observed with faster release at pH 2. Overall, the very small PS along with high encapsulation efficiency and stability can enhance crocin oral bioavailability making CS/ALG nanovehicles promising as an effective delivery system.
Practical Application
Crocin as a functional component of Saffron is not sufficiently stable in gastrointestinal tract and its absorption is not complete. Chitosan/Alginate nanoparticles can encapsulate it efficiently, protect it and enhance its absorption orally. The availability and simplicity of the materials and equipments employed in current research provide the possibility to industrial scale up of the Crocin nanoparticles.
... The S/N ratio is used to evaluate quality features and is used to calculate the deviation from the expected value. The loss function L(y) has been used to express the deviation [40], and it is estimated by the equa- The S/N ratio, which is employed in Taguchi methodology to analyse the robustness of a dynamic process, is a performance feature of that process [41]. The 'bigger is better' mathematical expression for the S/N ratio measures departure from the target and is expressed as mean square deviation (MSD). ...
Cellulose nanofibre (CNF) is a sustainable and nanostructured eco-friendly material. The high cost of CNF, on the other hand, limits its use in a variety of applications, which can be overcome by developing a suitable extraction technique and employing low-cost biomass. Therefore, the purpose of present study is to use Taguchi methodology to optimise various process parameters during bleaching process in order to get a higher crystallinity CNF from I. cylindrica. According to ANOVA, sodium chlorite had the greatest effect (48.08%) on CNF extraction, followed by temperature (24.53%), time (20.74%), and glacial acetic acid (6.65%). Between glacial acetic acid and time, the strongest interaction (SI 58.61%) was found. The sodium chlorite and time (SI 47.57%) had the second highest interaction, followed by sodium chlorite and temperature (SI 29.41%), sodium chlorite and glacial acetic acid (SI 21.66%), temperature and time (SI 19.1%), and glacial acetic acid and temperature (SI 16.15%). The S/N ratio of CNF was improved from 30.81 to 36.734. The Taguchi technique predicts the highest optimal yield using the sodium chlorite (10 g/mL), glacial acetic acid (20 mM), temperature (70 °C), and time (2 h) as parameters. The crystallinity index was evidently increased from 46.36 to 50.21 while raw biomass was pretreated. After additional alkali treatment, the crystallinity index was enhanced to 61.42. The crystallinity index of CNF was increased to 67.65 when bleaching conditions were optimised.
... Its calculation process is the same regardless of the number of alternatives (Shih et al., 2007), which enables quicker computation (Jati, 2012). For each alternative, the method concurrently considers the distance from both the best solution and the worst one (Tong, Wang, Chen, & Chen, 2004). The positive ideal solution includes all the best values of every single rank, while the negative ideal solution includes all the worst ones (Bai, Dhavale, & Sarkis, 2014). ...
When manufacturing a product, companies must consider the specifications of its design and choose the manufacturing technology that matches them the best in terms of product quality, production time and costs. Since all these parameters can be represented by several different and conflicting indicators, the problem of technology selection can be defined as a multi-criteria decision-making (MCDM) problem. Although several mathematical models have been developed to solve similar problems, recent literature still presents a lack of specific applications of renowned decision-making techniques to the technology matching problem in the manufacturing sector. This study attempts to fill this gap by proposing a manufacturing-oriented model of the Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS), one of the most solid and robust MCDM methods. The solution we present, which is designed for general manufacturing processes, has been applied to the specific case of a producer of food and beverage plants and equipment that is interested in reengineering one of its products. Due to the complexity of the food and beverage industry, the case study is useful for supporting the definition of the general model and validating its applicability. Further, the results of the specific application prove the effectiveness of our model.
... The extent of difference between the average impacts determines the relative impact of the individual factors on the inconsistency of the results. It is based on the fact that larger is the difference, greater will be the impact (Kumar et al. 2013;Tong et al. 2004). The results revealed that concentration was the most influential on the silica yield among the other two factors, followed by volume and time. ...
This study was attempted towards the retrieval of silica from rice husk ash to annihilate the local problems of disposal from the rice milling industries for enhancement of silica purity. Optimization of process factors using the Taguchi technique involved variation in sodium hydroxide concentration (NaOH), alkali impregnation volume per unit weight of the rice husk ash, and reaction time for designing the experimental matrix utilizing L16 orthogonal array at four different levels. The maximum silica extraction was 98.26% obtained with 4 N of NaOH, 20 ml/g of alkali volume, and treatment time 60 min. The identical experimental data set was also applied to an artificial neural network model (ANN) with the LM algorithm for predicting the feasibility of the extraction process. Both Taguchi and neural networks suggested a high coefficient of determination and a satisfactory correlation between experimental and predicted silica recovery values. The detailed characterization of the synthesized silica powder and residual rice husk ash was executed using field emission scanning electron microscopy (energy-dispersive spectroscopy), Fourier transform infrared spectroscopy, thermogravimetric, Brunauer Emmett Tellet surface area, and particle size analysis. The simultaneous reuse of residual ash and silicate was performed to ensure the best possible reclamation of silica and reusability of rice husk ash. The detailed cost estimation of the synthesized silica powder further suggested the effectiveness of the optimized process. Thus, a comprehensive approach for enhancement of the silica yield and purity by adopting Taguchi and ANN optimization proved to be useful in this study.
... S/N ratio used in Taguchi methodology is a performance characteristics of a dynamic process to assess the robustness of the entire process [27]. The mathematical representation for the S/N ratio of 'bigger is better,' measure the deviance from the target and represented as mean square deviation (MSD) which is written by ...
... have been applying TOPSIS method for construction solutions since 1986 (Zavadskas, 1986;Zavadskas, Fiedler and Peldschus, 1986). Seeing that TOPSIS method is widely applied (Triantaphyllou, 2000;Zavadskas, Kaklauskas and Banaitienë, 2001;Opricovic and Tzeng, 2004;Tsaur, Chang and Yen, 2002;Vilutienë and Zavadskas, 2003;Cheng, Chang and Huang, 2003;Tong et. al., 2004;Montanari, The compromise ranking method (called VIKOR) was newly developed and presented by Opricovic (Opricovic, 1998;Opricovic and Tzeng, 2004). It is used for engineering goals one of the first times by the authors of this paper. ...
The authors analyse the problem of derelict buildings’ redevelopment by means of multi criterion decision‐making techniques. The aim of the research is to rank derelict buildings’ redevelopment alternatives from the multiple sustainability approach. Moreover, handling of MCDM techniques is discussed. The MCDM techniques used are: technique for order preference by similarity to ideal solution (TOPSIS) and compromise ranking method (VIKOR). A Lithuanian case study is presented to illustrate similarities and differences of ranking results using these methods in particular situation. The comparisons of the results after multiple criteria analysis implementation are made in the paper and scientific recommendations for a sustainable redevelopment of derelict buildings in Lithuanian rural areas are suggested on a basis of calculations.
First Published Online: 18 Oct 2010
... Many authors have investigated multi-response surface optimization problems and proposed different solution approaches (interested readers are referred to Khuri (1996)). These approaches have varied widely, from simple weighted sums (e.g., Antony 2001) to more complex regression and mathematical programming approaches (e.g., Reddy et al. 1997), principal components analysis (e.g., Su and Tong 1997), and dynamic multiple responses (e.g., Tong et al. 2004). Derringer and Suich (1980) proposed a desirability function approach to MRSO problems, where utility functions are modeled for each response to incorporate the DM's preference into the problems. ...
This paper discusses utilization of multi-response surface optimization (MRSO) to select the preferred solutions from among various non-dominated solutions (NDS). Since MSRO often involves conflicting responses, the decision-maker’s (DM) preference information should be included in the model in order to choose the preferred solutions. In some approaches this information is added to the model after the problem is solved. However, this paper proposes a three-stage method for solving the problem. In the first stage, a robust approach is used to construct a regression model. In the second phase, non-dominated solutions are generated by the -constraint approach. The robust solutions obtained in the third phase are NDS that are more likely to be Pareto solutions during consecutive iterations. A simulation study is then presented in order to show the effective performance of the proposed approach. Finally, a numerical example from the literature is brought in to demonstrate the efficiency and applicability of the proposed methodology.
... ANOVA is an efficient tool to investigate the statistical significance of aid of probability value (P-value), regression (R 2 ), and adjusted coefficients (R 2 adjusted ) [33]. The optimal levels of the factors exhibiting highest bioflocculating activity will also exert highest bioflocculant yield because of the reason that activity is directly proportional to the product formation. ...
Klebsiella pneumoniae strain NJ7 was isolated and screened for the production of bioflocculant and used for the flocculation of starch processing industrial wastewater (SPIW). The bioflocculant had the ability to reduce 41% chemical oxygen demand and 90% turbidity, from the SPIW. The strain is capable of utilizing the bioflocculated nutrient rich SPIW as a sole source for the bioflocculant production with doubled yield as compared to its conventional production medium. The parameters influencing bioflocculant production were optimized using Taguchi's orthogonal array (OA) experiments which suggested that 85.79% flocculation and 111.67 (mg/100 mL) bioflocculant yield could be achieved when 80% of SPIW inoculated with K. pneumoniae strain NJ7 at 30°C for 24 h at 120 rpm. This is the first report on bioflocculant production by K. pneumoniae using wastewater, without any additives and its statistical optimization (Taguchi's OA). The concept of statistical optimization and the use of wastewater lead to bioflocculant production cost effective. © 2017 American Institute of Chemical Engineers Environ Prog, 2017
... Su & Tong 1997), and dynamic multiple responses (e.g. Tong et al. 2004). ...
As the ordinary least squares (OLS) method is very sensitive to outliers as well as to correlated responses, a robust coefficient estimation method is proposed in this paper for multi-response surfaces in multistage processes based on M-estimators. In this approach, experimental designs are used in which the intermediate response variables may act as covariates in the next stages. The performances of both the ordinary multivariate OLS and the proposed robust multi-response surface approach are analyzed and compared through extensive simulation experiments. Sum of the squared errors in estimating the regression coefficients reveals the efficiency of the proposed robust approach.
... Taguchi deneysel tasarım metodu sinyal gürültü oranı (S/N) kullanarak yanıt değişkenin hem ortalaması hem de varyansı ile ilgili bilgilere yoğunlaşmaktadır. Bu yöntem kullanılarak elde edilen en iyi faktör/seviye kombinasyonu, yanıt ortalamasını hedef değerine taşırken; bir yandan da değişkenliğinin azaltılmasını sağlar [34] . Taguchi, çok değişkenli deneyleri az sayıda deneme ile gerçekleştirme için Ortogonal Dizilerden (OD) yararlanmaktadır. ...
Bu çalışmada, Taguchi deneysel tasarım metodu kullanılarak tekstil atıksuyunun arıtımında alüminyum elektrotların kullanıldığı Elektrokoagülasyon prosesinde optimum deney şartları; başlangıç pH, akım yoğunluğu, elektriksel iletkenlik, elektroliz süresi ve elektrotlar arası mesafe belirlenmiştir. Deneysel çalışmada performans kriteri olarak KOİ parametresi incelenmiştir. Optimizasyon çalışması için belirlenen parametre sayısı 5 ve her bir parametre için 4 farklı seviye incelenmesi düşünülerek L16 (4 5) Taguchi faktöriyel deney tasarımı yapılmıştır. Elde edilen sonuçlar neticesinde, KOİ giderme verimine göre optimum koşullar sırasıyla, başlangıç pH 6, akım yoğunluğu 100 A/m 2 , iletkenlik 7,5 ms/cm, elektroliz süresi 15 dakika ve elektrotlar arası mesafe 2,5 cm olarak bulunmuştur. Bu şartlarda tahmin edilen KOİ giderme verimi %76,8 iken deneysel olarak bulunan değer %75,1'dir. Sonuç olarak tekstil atıksuyunun arıtımında EC prosesi Taguchi deneysel tasarım metodu kullanılarak bu prosese etki eden parametreler optimize edilmiştir.
... Among numerous MCDM methods, TOPSIS, proposed by Hwang and Yoon (1981 ), is well known and has been widely applied. In the past decades, considerable effort s have been made to modify (or extend) TOPSIS, and to compare (or hybridize) it with other MCDM methods ( Ahi, Aryanezhad, Ashtiani, & Makui, 2009;Antucheviciene, Zakarevicius, & Zavadskas, 2011;Antuchevi čiene, Zavadskas, & Zakarevi čius, 2010;Aya g & Özdemir, 2012;Cables, García-Cascales, & Lamata, 2012;Chang, Lin, Lin, & Chiang, 2010;Chen, 2012;Chen, 2015;Chen, Li, & Liu, 2011;Deng, Yeh, & Willis, 20 0 0;Doukas et al., 2014;Doukas, Karakosta, & Psarras, 2010;Goh et al., 2013;Hu, Du, Mo, Wei, & Deng, 2016;Hussein, Ali, Rasid, Sali, & Mansoor, 2016;I ¸s ıklar, Alptekin, & Büyüközkan, 2007;Jahanshahloo, Lotfi, & Izadikhah, 2006;Junior, Osiro, & Carpinetti, 2014;Kannan et al., 2014;Khalili-Damghani et al., 2013;Li, Adeli, Sun, & Han, 2011;Lourenzutti & Krohling, 2016;Mokhtarian, Sadi-Nezhad, & Makui, 2014;Nouri et al., 2015;Ölçer, 2008;Olson, 2004;Opricovic & Tzeng, 2004;Rashid et al., 2014;Sang et al., 2015;Shih, Shyur, & Lee, 2007;Tavana, Zandi, & Katehakis, 2013;Taylan, Bafail, Abdulaal, & Kabli, 2014;Tong, Wang, Chen, & Chen, 2004;Torlak, Sevkli, Sanal, & Zaim, 2011;Tzeng, Lin, & Opricovic, 2005;Tzeng & Huang, 2011;Wang, 2014;Wang & Luo, 2009;Wang, Chan, & Li, 2015;Wang, Zhu, & Wang, 2016;Yue, 2011;Yue, 2014;Zanakis, Solomon, Wishart, & Dublish, 1998;Zavadskas, Turskis, & Tamošaitiene, 2010;Zhang & Yu, 2012 ). The TOPSIS is a ranking method based on the concept of compromised solution. ...
As a tool for decision analysis, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) attempts to choose alternative that should simultaneously have the closest distance from the positive ideal solution (PIS) and the farthest distance from the negative ideal solution (NIS). Although the ranking index of TOPSIS is reasonable, it contains a flaw. That is, this ranking index is irrespective of the weights of separations of an alternative from the PIS and the NIS. In other words, no matter what weights the decision-maker assigns to these two separations, the ranking results would not differ as if he has no preference for these two separations. This flaw will certainly limit the applicability of TOPSIS. By treating the separations of an alternative from the PIS and the NIS as a “cost” criterion and a “benefit” criterion, respectively, we reduced the original MCDM (Multi-Criteria Decision Making) problem to a new MCDM problem with these two criteria only. By proposing w − and w + as the weights of the “cost” criterion and the “benefit” criterion, respectively, we defined a new ranking index. Experimental results showed that if the number of alternatives exceeds two or if the relative importance of the two separations should be considered, the proposed ranking index would be a better choice. Finally, two numerical examples of a real-life case are given for illustration. In summary, the proposed ranking index is intelligible and intrinsically superior to the original ranking index in seeking compromised solutions.
... Taguchi used the S/N ratio as a performance measurement of a dynamic system to evaluate the robustness of the overall process. 32 The mathematical expression for the S/N ratio for the "bigger is better" case for the performance statistics that measure deviation from the target, called as mean square deviation (MSD) was given by Validation of the experimental model (Phase IV) ...
The present investigation is mainly concerned with the rapid development of extracellular xylanase assay conditions by using Taguchi methodology. The extracellular xylanase was produced from Aspergillus niger (KP874102.1), a new strain isolated from a soil sample of the Baramura forest, Tripura West, India. Four physical parameters including temperature, pH, buffer concentration and incubation time were considered as key factors for xylanase activity and were optimized using Taguchi robust design methodology for enhanced xylanase activity. The main effect, interaction effects and optimal levels of the process factors were determined using signal-to-noise (S/N) ratio. The Taguchi method recommends the use of S/N ratio to measure quality characteristics. Based on analysis of the S/N ratio, optimal levels of the process factors were determined. Analysis of variance (ANOVA) was performed to evaluate statistically significant process factors. ANOVA results showed that temperature contributed the maximum impact (62.58%) on xylanase activity, followed by pH (22.69%), buffer concentration (9.55%) and incubation time (5.16%). Predicted results showed that enhanced xylanase activity (81.47%) can be achieved with pH 2, temperature 50°C, buffer concentration 50 Mm and incubation time 10 min.
... For example, Ic 16 adopts the TOPSIS method to evaluate and assess the company ranking. Tong et al. 17 obtain the optimal factor combination according to the overall performance index for multiple responses using TOPSIS method. Ulker and Sezen 18 adopt the TOPSIS method to determine the best printed circuit board design computer-aided design (CAD) tool problem. ...
Product style characteristics have a large impact on product function. Making an objective and precise assessment of style characteristic has become an increasing importance to improve the production efficiency and reduce environmental pollution. This work proposes a framework built by analytic hierarchy process and technique for order preference by similarity to ideal solution methods, that is, analytical hierarchy process and technique for order performance by similarity to ideal solution, to evaluate automotive style design alternatives’ performance, together with automotive style design characteristics. Analytic hierarchy process is applied to obtain weights of the performance, and technique for order preference by similarity to ideal solution is adopted to rank the design alternatives. A case study is illustrated to test and verify the proposed method. Simultaneously, sensitivity analysis is provided to monitor the robustness of this method. The results show that it provides an effective and feasible method for evaluation of automotive style design alternatives’ performance.
... Taguchi recommends analyzing the mean response for each run and also suggests analyzing variation using an appropriately chosen signal-to-noise ratio (S/N). Taguchi used the signal-to-noise (S/N) ratio as a performance measure in a dynamic system to assess the robustness of a process (Tong et al., 2004) and showed the magnitude of the interactions between control factors and noise factors. For the larger the better responses, the following relation is used for the S/N calculation. ...
In this work,the effectiveness of electro-Fenton process degradation of sodium dodecylbenzene sulfonate (SDBS) anionic surfactant in acidic wastewater was investigated. Taguchi method was applied to study the effect of process parameters on oxidation of SDBS pollutant. An orthogonal array L9 experimental designthat allows investigating the simultaneous variation of current density, initial acidity of wastewater, and the initial SDBS concentration was employed to evaluate the effect of these parameters as control factors. Taguchi experimental design in dynamic sense was carried out with electrolysis time chosen as signal factor. Each experiment comprises the addition of peroxide (170 mg l -1 ; 0.005M) as a fixed component of Fenton's reagent and NaCl (1.5 mg l -1 ) as supportive electrolyte. The results revealed that SDBS degradation in acidic aqueous phase, can reached high values by the electro-Fenton process. The estimation of linear model coefficients for S/N (signal to noise) ratios expression has acceptable fitness of 93.5% with the selected control and signal factors. Main effects and analysis of variance (ANOVA) indicates that the current density and the acidity have high impact on electro-Fenton degradation of SDBS process with high sum of squares and low p-values that signifies the 0.05 α-level. Moreover, Taguchi optimalanalysis indicates that high S/N ratio of response can be obtained with 0.3 mA cm-2 current density, pH=2 initial acidity of wastewater, and 10 mg l-1 initial SDBS surfactant concentration.
... Lee-Ing Tong et al. [14] used the signal to noise (SN) ratio and system sensitivity are used to assess the performance of each response. They performed principal component analysis (PCA) on SN values and system sensitivity values to obtain a set of uncorrelated principle components, which are linear combinations of the original responses. ...
In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.
... But Dr. Taguchi's method has a limitation because his method is an additive linear model and incompatible with a multi-objective problem. Several approaches have been presented to apply this method to the multiple-objective problems [17], [18], [19], [20], [21]. However, these works can not prevent trapping in a local minimum without reaching global optimization. ...
This paper presents a useful robust parameter design methodology for a microwave circuit. A set of design values is decided to satisfy the specification and to reduce the effect of variability in manufacture. The multi-objective problem is treated as a single optimization problem. The function which shows the variability from the ideal relationship between signal and response is minimized under the limiting conditions based on the specifications. We have used the iterative technique with the Monte Carlo method to search the controllable values. Taguchi's OA is used to consider the noise factors dealing with the production tolerance. The proposed method is applied to the design of a microwave amplifier, and its effectiveness is studied with the computer simulation and experiments. The first run rate achieved 97 % in the manufactures of a microwave amplifier.
... But Taguchi's method has a limitation because it is an additive linear model and is incompatible with the multi-objective problem. Several approaches have been applied to multiple-objective problems [16], [17], [18], [19], [20]. However, these works cannot prevent trapping in a local minimum without reaching global optimization. ...
Our target is to achieve a liigher first run rate in tlie quantity production of microwave circuits. For tliis purpose, we propose a useful robust parameter design methodology In which the multi-objective problem is treated as a single optimization problem under limiting conditions. A set of controllable factors, which provide an acceptable production, is calculated by considering such noise factors as manufacturing variations. We used the iterative technique with the Monte Carlo method to search for these values. The noise factors are assigned to Taguchi's orthogonal array to reduce the CPU time. Our proposed method is applied to the design of a microwave amplifier. This method's performance is compared with four optimization methods in the microwave circuit simulation, and its effectiveness is experimentally confirmed. The calculated controllable factors are not unique among these optimization methods to minimize the variations of the gain in manufactures. Our method is more efficient to find many candidates than the other optimization methods. The produced amplifiers have achieved a first run rate of 97% in its manufacture.
... The approach extends those of Su & Tong (1997) and Antony (2000), where only one principal component was considered in the optimization. The same type of analysis was already proposed by Tong et al. (2004), although using a technique for order preference by similarity to ideal solution to optimize the multiresponse problem. Khuri & Conlon (1981)'s "generalized distance" approach searches for treatments where the squared distance of the outcomes from their targets is minimized. ...
Dans les plans d'expériences multiréponse (MRE) le même élément expérimental est évalué par rapport à plus d'une réponse simultanément. L'optimisation de MREs implique typiquement la détermination du point dans la surface réponse où les réponses sont optimales par rapport aux critères donnés. Des fonctions utilitaires (utility functions) sont employées pour transformer des résultats de réponses à chaque traitement expérimental en mesures de performance. Nous étudions l'optimisation de MREs où quelques résultats de réponse sont des profils plutôt que de différentes valeurs. Une réponse profil donne un ou plusieurs profils comme résultats observés à chaque traitement, et l'objectif est d'identifier les résultats qui sont les plus proches du profil cible. Nous proposons l'utilisation de la distance de Hausdorff, une métrique de similarité du domaine de traitement d'image, en combinaison avec une fonction de désirabilité pour obtenir une fonction utilitaire qui donne la distance des résultats de réponse profil à sa cible désirée. Un exemple de l'industrie alimentaire illustre nos propositions. Abstract In multiresponse experiments (MRE) the same experimental unit is evaluated with respect to more than one response simultaneously. Optimization of MREs typically involves determining the point in the design region where responses perform best with respect to given criteria. Utility functions are used to transform responses outcomes at each experimental treatment into performance measures. Here we investigate the optimization of MREs where some response outcomes are profiles rather than individual values. A profile response gives one or more profiles as observed outcomes at each treatment, and the objective is to identify the outcome that is closest to a target profile. We propose the use of the Hausdorff Distance, a simmilarity metric from the field of image recognition, in combination with a desirability function to obtain a utility function that gives the distance of a response profile outcome to its desired target. A case example from the food industry illustrates our propositions.
... Taguchi Yöntemi sinyal gürültü oranı (S/N) kullanarak yanıt değişkenin hem ortalaması hem de varyansı ile ilgili bilgilere yoğunlaşmaktadır. Bu yöntem kullanılarak elde edilen en iyi faktör/seviye kombinasyonu, yanıt ortalamasını hedef değerine taşırken; bir yandan da değişkenliğinin azaltılmasını sağlar[6].Problem İçin Uygun Ortogonal Dizinin SeçimiProses hızının artmasıyla lifler fazla sürtünme seviyelerine maruz kalacaktır. Böylece meydana gelen yük miktarı artacaktır[16] . ...
In this article the effect of antistatic material used to avoid static electricity problem specially in synthetic fibers spinning on ring yarn quality parameters was investigated by Taguchi L4 orthogonal array. Two factors with two levels; the level of static electricity generated due to fiber friction and the amount of antistatic material applied to fibers was taken into account. (Static electricity level×amount of antistatic material applied to fibers) interaction was also discussed. Ne24 ring yarn samples have been spun from polyester fibers and their quality parameters were determined. In production of yarn samples, static electricity was measured at carding process according to BS 7506-2 by using Statometer ΙΙ device and its level was adjusted by selecting two different carding speeds. Minitab 14 software program was used to evaluate the results statistically. By using the Taguchi method the static electricity level and the antistatic material amount that enable to obtain optimum yarn quality parameters were determined. Moreover the effect of these two factors interaction on yarn quality parameters could also be determined.
... In this paper synergistic influence of L-Leucine on the corrosion inhibition performance of mild steel in 1M HCl is presented by adopting Taguchi experimental design. This approach of process optimization enables the study of influence of individual factors, establishes the relationship between variables and operational conditions, and predicts the performance at the optimum levels based on the concept of S/N ratio of the response values of a few well-defined experiments 17 . ...
In this paper, Taguchi method is applied to find the optimum conditions for the synergistic influence of L-leucine on polyvinyl alcohol (PVA) in the corrosion inhibition of mild steel. A L9 orthogonal array of experiments is constructed and the resulted experimental inhibition efficiencies are adopted for the signal to noise ratio and variance analysis (ANOVA). The proposed Taguchi methodology consists of four factors viz., concentration of L-Leucine, concentration of PVA, exposure time and temperature, at three different levels which are connected in sequence wise to achieve the overall inhibition optimization. The experimental results performed with the selected factors and levels were further processed with Qualitek-4 software at bigger is better as quality character to find the optimized conditions. The experimental result at the optimized conditions are used to calculate the synergism parameter and is found be greater than one.
... The OA facilitates the identification of influencing factors, establishment of the relationship between the process parameters and responses at the optimum levels with few experimental trials [20]. Taguchi's OA methodology involves the use of SNR, which determines the robustness of the process thereby minimizing the variation in quality [21]. ...
An indigenous mixed bacterial culture was screened and acclimated to decolorize a sulfonated azo dye; Acid Red 88 (AR88) under changing growth conditions. The process parameters influencing the average decolorization rate, ADRAR88 (μg min−1) was optimized using Taguchi's orthogonal array (OA-L25), under design of experiments. The value of ADRAR88 is 888.86 (μg min−1) when the operational parameters like pH, 8.0, temperature, 35°C and AR88 concentration, 500 (mg L−1) were maintained for 6 h. The mixed culture exhibited 87.89 and 90.58% reduction in the level of chemical oxygen demand (COD) and aromatic amines, respectively. It was found that increasing AR88 concentration, were found to be insignificant on the basis of analysis of variance (ANOVA) and signal-to-noise ratio (SNR) variation for the obtained responses from Taguchi's OA experiments. The decolorization by the mixed culture was confirmed by UV–vis spectrophotometry, whereas biotransformation was evidenced by spectroscopic studies like Fourier transform infrared (FTIR), proton nuclear magnetic resonance (1H-NMR), and chromatographic techniques like high performance liquid chromatography (HPLC), thin layer chromatography (TLC), and gas chromatography coupled with mass spectrometry (GC-MS) analyses. The induction and activities of various AR88 degrading oxido-reductive enzymes was elucidated. The phytotoxicity test using plant seeds revealed the extent of detoxification of parent dye compound by the mixed culture. © 2015 American Institute of Chemical Engineers Environ Prog, 2015
The present study is to use Taguchi methodology to develop an optimal ultrasound-mediated phycoerythrin extraction (UMPEE) condition from Anabaena sp. BTA 903. For improved PE extraction, Taguchi methodology (TM) was used to optimize five process parameters such as solid-to-liquid ratio (SLR), duty cycle (DC), electrical acoustic intensity (EAI), pH, and calcium chloride. The optimum condition necessary to achieve a higher PE yield, the average performance of individual parameters, and corresponding interactive effects were computed using the signal-to-noise (S/N) ratio. Analysis of variance (ANOVA) was used to determine the statistically significant parameters and their contribution. Duty cycle had the greatest impact (28.36%) on phycoerythrin (PE) extraction. Electrical acoustic intensity had the second-highest impact (23.65%) on PE extraction, followed by calcium chloride (22.14%), solid–liquid ratio (13.33%), and pH (10.11%) on PE extraction. When PE extraction was carried out, the optimal conditions for SLR, EAI, DC, pH, and calcium chloride were 0.25 g/ml, 16.99 w/cm², 75%, 7, and 0.01 g/ml, respectively. The S/N ratio of PE extraction yield was improved from 30.42 to 33.95. Anabaena sp. BTA 903 might be considered a possible candidate for PE feedstock because the maximum 50.24 mg/g of PE was recovered experimentally utilising optimum conditions predicted by the model. The batch extraction was found to be second-order, and the rate constant was computed as 3.2 × 10⁻⁴ Lmg⁻¹ min⁻¹ for extraction of PE. The aforementioned kinetic data will aid in the development of an extractor for large-scale PE extraction from Anabaena sp. BTA 903.
Prodigiosin is natural red colourant derived from Serratia marcescens. However, the high cost of prodigiosin restricts its use in food and pharmaceutical industries, which can be addressed with the design of a suitable extraction procedure. Therefore, the present study aims to use Taguchi methodology to optimize various process parameters during ultrasound-assisted extraction (UAE) to get a higher prodigiosin extraction yield. The most significant contribution comes from the solid-to-liquid ratio (36.66%), followed by sonication of duty cycle (34.82%), medium pH (15.7%), and acoustic intensity (12.82%). The Taguchi technique predicts the highest optimal yield using the solid–liquid ratio (0.3 g/mL), duty cycle sonication (75%), acoustic intensity (12.5 w/cm²), and medium pH (3) as parameters. When the extraction conditions were optimized, the yield of prodigiosin increased by 4166.89 mg/L. In the future, the above extraction conditions determined using Taguchi approach will be applied for large-scale extraction of prodigiosin. Finally, a second-order kinetic model is used to suit the batch extraction investigation and the second-order rate constant (k) has a value of 4 × 10⁻⁵ L/mg/min. In the future, the rate constant, which is reported for the first time, will be used to create a batch extractor for commercial extraction of prodigiosin. Prodigiosin has also been shown to have substantial antioxidant and scavenging properties, which increase in a dose-dependent way with prodigiosin concentration. Because of its antioxidant and scavenging properties, prodigiosin can be used as food additives or pharmaceutical ingredients in industries.
In this study, the treatment of metal plating industrial wastewater containing Nickel (Ni) by electrocoagulation (EC) process under various operating conditions was investigated. The EC process was optimized using the Taguchi experimental design method. In order to examine the effects of operating parameters on EC in the EC process where iron (Fe) electrodes are used; initial pH value, current density and electrolysis time were selected as independent variables and optimum experimental conditions were determined in the EC process. Ni removal efficiency (%) was used as performance evaluation parameter. In the optimization study, L9 (33) Taguchi factorial experimental design was made by choosing 3 different levels of parameter factor and examining 3 different levels for each parameter. As a result of the experimental plan, the optimum experimental operating conditions determined by the taguchi method according to the Ni removal efficiency were found to be initial pH 9, current density 150 A/m2 and electrolysis time 60 minutes, respectively. The estimated Ni removal efficiency under these conditions is 99.97%, while the experimentally found value is 99.57%. It was seen that the estimated Ni removal efficiency obtained in the experimental design and the Ni removal efficiencies obtained in real experimental conditions were close. As a result, it shows that the Taguchi method can be applied as an optimization method in the treatment of such wastewaters
by EC process. In addition, it has been determined that the operating parameters affecting this process can be optimized by using the EC process and the Taguchi experimental design method in the treatment of various industrial wastewaters containing Ni.
The purpose of this study is to investigate the removal of hexavalent chromium (Cr (VI)) from metal plating industrial wastewater by electrocoagulation (EC) process using iron electrodes. Therefore, the operating parameters of the EC process were optimized using the Taguchi experimental design method. To examine the effects of operating conditions on EC; Optimum experimental conditions were determined in the EC process by choosing the initial pH value, current density and electrolysis time as controllable variables. In addition, the operating cost of the EC process and the sludge generation amount of the process were also calculated. In the Taguchi optimization study, L9 (33) Taguchi factorial experimental design was made by choosing 3 different parameters and 3 different levels for each parameter. In this context, the initial pH of the wastewater (3, 7, 9), current density (75, 100, 150 A/m2) and electrolysis time (15, 30, 60 minutes) were investigated as operating parameters. As a result of the experimental plan, the optimum experimental operating conditions determined by the Taguchi method according to the Cr (VI) removal efficiency (%) were found to be initial pH 7, current density 100 A/m2 and electrolysis time 30 minutes, respectively. 99.14% Cr (VI) removal was obtained under optimum conditions. It was observed that the estimated Cr (VI) removal efficiency (100.00%) obtained in the experimental design and the Cr (VI) removal efficiencies obtained in real experimental conditions were close. This shows that the Taguchi method can be applied as an optimization method in the treatment of such wastewaters with the EC process. As a result of the experimental study, the energy consumption for real wastewater was calculated as 5.88 kWh/m3, the electrode consumption as 0.6961 kg/m3 and the operating cost as 1.006885 $/m3 under optimum conditions. The amount of sludge formed under these conditions was determined as 2.628 kg/m3 .
Özet: Gıda sektörünün ana hammaddesini tarımsal ürünler oluşturmaktadır. Bu bağlamda sektörde doğru tedarikçinin seçilmesi sağlıklı, güvenli ve yüksek kaliteli gıda ürünlerinin üretilmesi için gereklidir. Bu çalışmanın amacı, gıda ürünleri imalatı sektöründe faaliyet gösteren bir firmada en uygun hammadde tedarikçi seçimi probleminin, AHP ve TOPSIS yöntemlerinin birlikte kullanılarak çözümünün sağlanmasıdır. Çalışmada, karar verici olarak firmanın satın alma yöneticisinin uzman görüşüne başvurulmuştur. Ana kriterler; kalite, maliyet, teslimat ve tedarikçi profili olarak belirlenmiştir. Alt kriterler ise; hammadde kalitesi, kullanılabilir hammadde miktarı, hammadde fiyat uygunluğu, fiyat iskontosu, taşıma maliyeti, hızlı teslimat, güvenilir teslimat, coğrafi yakınlık, geçmiş performans, güvenilirlik ve ilişkidir. Çalışma sonuçlarına göre "kalite" en önemli kriter olarak tespit edilmiştir. Diğer kriterlerin önem sıralaması ise maliyet, teslimat ve tedarikçi profili şeklindedir. Ayrıca D1 tedarikçisi, en yüksek puana sahip tedarikçi olarak firmanın mevcut tedarikçileri arasında seçilmiştir. Çalışmada gıda sektöründe hammadde tedarikçi seçiminde AHP-TOPSIS yöntemlerinin kullanılmasıyla ilgili değerlendirme yapılarak önerilerde bulunulmuştur.
Abstract: The main raw materials of the food industry are agricultural products. It is necessary to select the right suppliers in the industry to produce healthy, safe and high quality food products. The aim of this study was to use AHP and TOPSIS methods together in order to solve the problem of selecting the ideal raw material supplier for a company operating in the food products manufacturing sector. The purchasing manager of the company was consulted as the decision maker. The main criteria were quality, cost, delivery and supplier profile. The subcriteria were raw material quality, amount of available raw materials, affordable raw materials, discount, transportation cost, fast delivery, safe delivery, geographic proximity, past performance, reliability and relationship. The results showed that "quality" was the most important criterion, followed by cost, delivery, and supplier profile. The supplier D1 had the highest score and therefore was selected as a current supplier for the company. The use of AHP-TOPSIS methods in raw material supplier selection in the food industry was evaluated, and suggestions were made based on the results.
A statistical optimization was performed to achieve a higher yield of cell growth and 4-chlorophenol (4-CP) biodegradation, where isolated Bacillus subtilis MF447840.1 was used as biocatalyst. Taguchi methodology was used to evaluate the optimum condition for eleven process parameters. Six media components such as ammonium nitrate, magnesium sulfate, dipotassium phosphate, monopotassium phosphate, calcium chloride, and trace element, and five physicochemical factors such as pH, temperature, agitation, inoculum size, and incubation time, were considered for optimization owing to their significant effect on cell growth and 4-CP biodegradation. Orthogonal Arrays (OA) layout of L27 was used for designing of various experimental trials. Signal to noise (S/N) ratio was used to evaluate the individual effects of process parameters and their optimal level during evaluation of cell growth and 4-CP biodegradation. Optimization studies revealed that 911.45 mg/L of biomass yield and 1000 mg/L of 4-CP biodegradation were found with ammonium nitrate (0.75 g/L), magnesium sulfate (0.25 g/L), dipotassium phosphate (0.75 g/L), monopotassium phosphate (0.25 g/L), calcium chloride (0.02 g/L), trace element (1%), pH (7.5), temperature (37 °C), agitation (150 rpm), inoculum size (10%), and incubation time (40 h).
Due to energy expansion and sustainable development of resources and systems, there has been an increasing demand for environmentally friendly alternative energy systems.
Microbial fuel cells (MFCs) are considered one of the most promising alternative energy generation systems. The microorganism is one of the key limiting factors to enhance the performance efficiency of MFC. Therefore, proper evaluation of screening protocol is imperative benchmarks for selection of biocatalyst in MFC. In the present study, an attempt was taken for rapid evaluation of iron-reduction capacity and growth of Shewanella algae through optimization of process parameters using Taguchi methodology. Here, five process parameters, including lactose, trace element, inoculum percentage, pH, and temperature, were taken into consideration as imperative factors and were optimized for evaluation of iron-reduction analysis along with growth of bacteria. The main effect of each parameter, along with their interaction influence and optimal value, was determined using a signal-to-noise (S/N) ratio. The evaluation of quality characteristics of each parameter was also determined in Taguchi robust methodology using S/N ratio. Analysis of variance was performed to assess statistically important process parameters. Predicted results exhibited that enhanced bacterial growth (120%) and iron-reduction capacity (114%) can be achieved with 8 g/L of lactose, 2 mL of trace element solution, 7 of initial pH, 30 °C of temperature, and 4% (v/v) of inoculum percentage. It is evident from the results that Shewanella algae can be used as a promising catalyst for MFC.
Çok ölçütlü karar verme yöntemlerinden birisi olan TOPSIS (Technique
for Order Preference by Similarity to Ideal Solution) yöntemi işletmelerin finansal performansının ölçümünde yaygın kullanılan yöntemlerden birisidir. TOPSIS yönteminin temelinde en düşük maliyetli, en yüksek fayda sağlayan seçenek optimum seçenektir.
TOPSIS yönteminde kullanılacak finansal oranların, performansı
ölçülecek işletmelere göre isabetli seçilmesi yapılacak analizin
başarısını olumlu etkilemektedir. Üretim işletmelerinde, TOPSIS
yöntemi ile yapılan finansal performans analizinde mali tablolardan elde
edilen maliyet ve karlılık oranlarının kullanılması, yöntemin özüne
oldukça uygun düşmektedir. Bu çalışmanın amacı, üretim işletmelerinde
TOPSIS yöntemi ile yapılacak finansal performans analizinde maliyet
ve karlılık oranlarının başarısını test etmektir. Bu doğrultuda, Borsa
İstanbul Ana Metal Sanayi Endeksine kote olan bir şirketin başarısı
yıllara göre hesaplanmış ve elde edilen sonuçların doğruluğu ve
altındaki ekonomik nedenler incelenmiştir. 2008 ile 2017 yılları
arasındaki maliyet ve karlılık oranlarına göre 2008 yılı en başarılı yıl
iken 2015 yılı en az başarılı yıl olarak tespit edilmiştir. Analiz
sonucunda elde edilen bulgular temel analiz sonuçları ile doğrulanmakla
birlikte sektörde yaşanan ulusal ve uluslararası gelişmeler analizin
sonuçlarını desteklemektedir. Sonuç olarak yapılan çalışmada kullanılan
maliyet ve karlılık oranları TOPSIS yöntemi ile isabetli sonuçlar ortaya
koymuştur.
The purpose of the study is to introduce Fuzzy TOPSIS method which utilizes group decision-making in fuzzy environments and clarify the method’s process with an application including assessment of candidates in human resource selection. The application took about eight months. For this purpose, juries composed of firm managers in a shopping mall had evaluated the decision criteria and also salespeople candidates subject to them through interviews by using linguistic variables. Data gained from these evaluations transformed to triangular fuzzy numbers and used in Fuzzy TOPSIS method’s algorithm. Salespeople candidates were ranked from the best to the worst with respect to the calculated closeness coefficients. The interviews were applied to different candidates by different juries at different times.
In conclusion, it can be possible a more accurate and effective group decision-making by using Fuzzy TOPSIS method that assesses linguistic variables. The study also shows that Fuzzy TOPSIS method can be rather useful method for human resource selection.
Polysaccharides as natural hydrogels provide a promising strategy to prepare stimuli responsive drug carriers in pharmaceutical industries. In this work, Fe3O4 magnetic nanoparticles (MNPs) functionalized with (3-amino propyl) triethoxy silane (APTES) and coated by Chitosan (CS) and Tragacanth Gum (TG) to encapsulate curcumin. The synthesized nanocomposite was characterized using FT-IR, FE-SEM, EDX and XRD analysis. Taguchi Method (L9) with 3 levels and 4 variables was used to optimize the effect of concentration of Fe3O4@APTES, TG: CS ratio, nanocomposite weight, and curcumin weight on the drug loading. The release behaviour of curcumin was further studied in two different pH 7.4 and 3.4 and at temperatures 37 °C and 40 °C. The nanocomposite showed a higher swelling ratio at pH 3.4 and temperature 40 °C with good pH and thermosensitive in vitro drug release profiles. The results indicate that the nanocomposite has a good potential for delivery of chemotherapeutic drugs.
Temel bileşenler analizi büyük değişken kümesi içeren verinin boyutunu orijinal veride bilgi kaybına yol açmadan küçük kümeye indirger. Deneysel çalışmalarda çoklu korelasyona sahip yanıt değişkenler sıklıkla bulunmaktadır. Temel bileşenler analizi yanıt değişkenler kümesindeki bilginin çoğunu içeren bir genel yanıt değişken elde etmek için kullanılabilir. Genel yanıt değişken elde edildikten sonra, birkaç bağımsız değişkenden etkilenen yanıt değişkeni optimize etmek için yanıt yüzey yöntemi kullanılabilir. Bu çalışmada fitik asit, fitat fosforu, toplam fosfor gibi korelasyonlu yanıt değişkenler içeren ekmek üretim işlemi verisine temel bileşenler analizi uygulanmıştır. Temel bileşenler analizi ile oluşturulan yeni yanıt değişkeni optimize etmek için yanıt yüzey yöntemi uygulanmış ve en uygun koşullar elde edilmiştir.
Priority Sequencing Rules provide the guidance for the order in which the jobs are to be processed at a workstation. The application of different priority rules in job shop scheduling gives different order of scheduling. More experimentation needs to be conducted before a final choice is made to know the best priority sequencing rule. Hence, a comprehensive method of selecting the right choice is essential in managerial decision making perspective. This paper considers seven different priority sequencing rules in job shop scheduling. For evaluation and selection of the best priority sequencing rule, a set of eight criteria are considered. The aim of this work is to demonstrate the methodology of evaluating and selecting the best priority sequencing rule by using hybrid multi criteria decision making technique (MCDM), i.e., analytical hierarchy process (AHP) with technique for order preference by similarity to ideal solution (TOPSIS). The criteria weights are calculated by using AHP whereas the relative closeness values of all priority sequencing rules are computed based on TOPSIS with the help of data acquired from the shop floor of a manufacturing firm. Finally, from the findings of this work, the priority sequencing rules are ranked from most important to least important. The comprehensive methodology presented in this paper is very much essential for the management of a workstation to choose the best priority sequencing rule among the available alternatives for processing the jobs with maximum benefit.
Due to the increase in complexity and expectations of more reliable solutions for a problem, the importance of multi-objective problem solutions is increasing day by day. It can play a significant role in making a decision. In the present approach, many combinations of the optimization techniques are proposed by the researchers. These hybrid evolutionary methods integrate positive characteristics of different methods and show the advantage to reach global optimization. In this chapter, Taguchi method and the GRA (Grey Relation Analysis) technique are pronounced and used to optimize a multi-objective metal cutting process to yield maximum performance of tungsten carbide-cobalt cutting tool inserts in turning. L18 orthogonal array is selected to analyze the effect of cutting speed, feed rate, and depth of cut using cryogenically treated and untreated inserts. The performance is evaluated in terms of main cutting force, power consumption, tool wear, and material removal rate using main effect plots of S/N (Signal to Noise) ratios. This chapter indicates that the grey-based Taguchi technique is not only a novel, efficient, and reliable method of optimization, but also contributes to satisfactory solution for multi-machining objectives in the turning process. It is concluded that cryogenically treated cutting tool inserts perform better. However, the feed rate affects the process performance most significantly.
This study aims at constructing an algorithm, while the product/process is with multiple quality characteristics, which is to select critical factors and decide the optimal parameter allocations. The algorithm intends to figure out the key control factors of the product/process with multiple quality characteristics through Decision Making Trial and Evaluation Laboratory, and then to decide the optimal parameter allocations by Technique for Order Preference by Similarity to Ideal Solution, Fuzzy Inference, Taguchi Method, etc. Reasonably and subjectively, the algorithm presented by the current study selects the critical factors. In addition, through Technique for Order Preference by Similarity to Ideal Solution and applying Fuzzy Inference to Taguchi methods, the algorithm not only advances the completeness of the optimized Taguchi methods but certifies the accuracy of the selected optimized parameters. Finally, taking the manufacturing process of the precise investment casting of produce YJ1097 as an example, this study demonstrates the algorithm provided to be feasible and valid.
Taguchi's method is a popular methodology utilized within many different industries in order to improve product quality and process performance. Digital dynamic systems denote the problems where both the input and output are digital values in Taguchi's method. When the signal factor levels are classified into two classes and the output is classified into two or more classes, two or more errors will occur in experiments. The digital dynamic systems are generally applied in the fields of telecommunication, computer operations, chemistry and tests of detection of medicine or environmental pollution. TheSN ratio recommended by Taguchi is based on the errors with the same loss coefficient to optimize the problems. However, the losses due to the errors are not equal in practice. This paper proposes a general model for optimizing parameter design and selecting threshold value for the digital dynamic systems where the output is classified into four classes. The implementation and the effectiveness of the proposed approach are illustrated through two case studies.
MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and approaches have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the multiple criteria decision-making (MCDM) techniques and approaches. This study reviewed a total of 393 papers published from 2000 to 2014 in more than 120 peer reviewed journals (extracted from Web of Science). According to experts’ opinions, these papers were grouped into 15 fields. Furthermore, these papers were categorized based on authors, publication date, name of journals, methods, tools, and type of research (MCDM utilizing research, MCDM developing research, and MCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, AHP method in the individual tools and hybrid MCDM in the integrated methods were ranked as the first and second methods in use. Additionally, European Journal of Operational Research as the first journal with 70 publications was the significant journal in this study; finally, energy, environmental and sustainability were ranked as the first area that have applied DM techniques and approaches.
In this paper, Taguchi method was applied to determine the optimum operating conditions for textile wastewater treatment by electrocoagulation (EC) with iron electrodes. The removal efficiency of chemical oxygen demand (COD) and turbidity was considered as the performance parameters. L9 orthogonal array (OA, three factors in three levels) was selected as the experimental design for three controllable parameters mentioned above. These parameters that mainly affect the EC process were specified as initial pH, current density and electrolysis time. Each parameter was examined at three levels using Taguchi method. Performance analysis was followed by a variance analysis in order to determine the optimum levels and relative magnitude of the effect of parameters. Taguchi’s “the larger the better” performance formula was used. The optimum operating conditions in terms of COD and turbidity were found to be initial pH of 7 and 8, current density of 150 A/m2 and electrolysis time of 20 and 30 min. At the optimum conditions, COD and turbidity removal efficiencies were obtained as 42.2 and 99.1%, respectively. Operating costs of EC process for COD and turbidity removals were calculated as 1.52 and 1.73 €/m3. Besides, the UV-Vis spectrum was used to detect the changes in textile wastewater quality. In EC process, COD concentration of treated effluent was above the permitted direct discharge limits. So, active carbon was used to increase COD removal efficiency of EC process under the optimum operational conditions. COD and turbidity removal efficiencies in the EC/activated carbon (AC) process by adding 2,000 mg/l AC were 67.9 and 99.3%, respectively. Operation cost of EC/AC process is calculated as 1.64 €/m3. Besides, the operation costs at different operating conditions were also determined.
In this investigation, the combined process efficiency with respect to biogas generation was evaluated by Taguchi robust design using raw vegetable wastes (RVW) and waste plastics (WP) as the key components. The signal-to-noise (S/N) ratio was used to estimate the main effects, interaction effects, and optimal levels of the process factors. Among the various experimental combinations, statistical analysis of the optimized result showed that enhanced biogas production could be achieved with the plastic content (15%), height to diameter (h/D) ratio (30), water content (125 ml), and digestion period (18 week). The Taguchi methodology predicted a maximum biogas (24.83 m3/ton of RVW) could be generated with those selected process parameters under optimized condition. The experimental data showed that enhanced biogas production (24.16 m3/ton of RVW) was found with the optimized conditions.
Most manufactured products must conform to multiple "fitness for use" criteria. The manufacturing design must balance these different needs and find settings of design parameters that maximize product quality. This paper proposes the use of quadratic quality loss functions applied to response surface models to solve this multiple criterion problem. The discussion concentrates on the premanufacturing phase, when off-target losses predominate over losses due to random variability, but the methodology is equally applicable to situations in which both sources contribute appreciably to quality losses. It is shown that operating a process at the minimum of the loss function has the additional benefit of minimizing sensitivity of the product to noise variation in the design parameter settings, leading to robust designs automatically.
The purpose of off-line quality control is to design robust products using robust manufacturing processes before the actual manufacturing of the product. Most of the research work has focused on determining the optimal level settings of process parameters for products with a single quality characteristic. In this paper, we employ the loss function approach to determine the optimal level settings of the process parameters of the production processes for products with multiple characteristics.
Abstract Most previous Taguchi method applications have only addressed a single-response problem. However, more than one correlated response normally occurs in a manufactured product. The multi-response problem has received only limited attention. In this work, we propose an effective procedure on the basis of principal component analysis (PCA) to optimize the multi-response problems in the Taguchi method. With the PCA, a set of original responses can be transformed into a set of uncorrelated components. Therefore, the conflict for determining the optimal settings of the design parameters for the multi-response problems can be reduced. Two case studies are evaluated, indicating that the proposed procedure yields a satisfactory result.
To achieve high enantiomeric excess in Bakers' yeast reduction of ethyl 3-oxobutanoate (2) to ethyl (S)-(+)-3-hydroxybutanoate(1), selective inhibition of unnecessary R-enzymes by organic acids, their derivatives and sulfhydryl reagents have been widely investigated. Acetic acid and crotonic acid were identified as good ee controllers, both giving alcohol (1) in up to ≥99% ee. Some other alkenoic and alkanoic acids with short side chains were found to be effective but to lesser degrees. Sulfhydryl reagents were ineffective or in some cases had the opposite effect to what was intended. The pH alone of the reaction mixture had no relation to the resulting high values of enantiomeric excess. The result that the effect of acetic acid on yeast reduction was not dependent on the preincubation time strongly suggested that the inhibition was a noncovalent one.
The importance of using energy-related characteristics in robust experimentation is demonstrated. Much of the controversy and debate over the effectiveness of Taguchi methods is based on a misunderstanding of the guidelines provided by Taguchi for choos..
A statistical procedure that involves experimental design and simultaneous optimization is proposed to search for appropriate machine settings such that both casting quality and die life are considered. Specifically, experimental design is used to colle..
Dimensional quality is a measure of conformance of the actual geometry of products with the designed geometry. In the automotive body assembly process, maintaining good dimensional quality is very difficult and critical to the product. In this paper, a dimensional quality analysis and diagnostic tool is developed based on principal component analysis (PCA). In quality analysis, the quality loss due to dimensional variation can be partitioned into a mean deviation and piece-to-piece variation. By using PCA, the piece-to-piece variation can be further decomposed into a set of independent geometrical variation modes. The features of these major variation modes help in identifying the underlying causes of dimensional variation in order to reduce the variation. The variation mode chart developed in this paper provides the explicit and exact geometrical interpretation of variation modes, making PCA easily understood. A case study using an automotive body assembly dimensional quality analysis will illustrate the value and power of this methodology in solving actual engineering problems in a practical manner.
The data from a case study involving the optimization of the sealing function of an automobile door weatherstrip is modelled using multiple regression models. It is demonstrated that the experimental statistics which are needed to calculate signal-to-noise performance statistics may be readily obtained with the use of a linear statistical model.
One of the conventional approaches used in off-line quality control is the Taguchi method. However, most previous Taguchi method applications have only dealt with a single-response problem and the multi-response problem has received only limited attention. The theoretical analysis in this study reveals that Taguchi's quadratic loss function and the indifference curve in the TOPSIS (Technique for order preference by similarity to ideal solution) method have similar features. The Taguchi method deals with a one-dimensional problem and TOPSIS handles multi-dimensional problems. As a result, the relative closeness computed in TOPSIS can be used as a performance measurement index for optimizing multi-response problems in the Taguchi method. Next, an effective procedure is proposed by applying fuzzy set theory to multiple attribute decision making (MADM). The procedure can reduce the uncertainty for determining a weight of each response and it is a universal approach which can simultaneously deal with continuous and discrete data. Finally, the effectiveness of the proposed procedure is verified with an example of analysing a plasma enhanced chemical vapour deposition (PECVD) process experiment. © 1997 by John Wiley & Sons, Ltd.
In this paper we demonstrate the ability of the Taguchi technique accurately to characterize and successfully to optimize complicated multi‐response processes with the minimum of experiments, provided one uses simple statistical techniques which can ensure valid, and definitive results. We point out the usefulness of suitable data‐transformations, and we suggest a systematic procedure for establishing the optimal operating conditions and for carrying out confirmatory experiments.
For the particular case detailed in this paper (which is typical of multi‐response processes) the Taguchi technique achieved an improvement in uniformity of a factor of 2, together with optimized process control.
Robust product and process design is an important technique for achieving high quality at low cost. It involves making the product's function much less sensitive to various sources of noise such as manufacturing variation, environmental variation and deterioration. This is a problem in optimization involving minimization of the mean square loss resulting from the deviation of the product's function from its target. Here we show that the optimization can be carried out in two steps: first maximize a quantity called signal-to-noise ratio (S/N) and then bring the performance on target by special adjustment parameters. The two-step procedure works for a wide variety of product functions and makes the optimization process more efficient and practical compared to the direct minimization of the quadratic loss function.
A key chiral intermediate S(−)-4-chloro-3-hydroxybutanoic acid, methyl ester 2 was made in high optical purity by the stereoselective reduction of 4-chloro-3-oxobutanoic acid methyl ester 1 by cell suspensions of Geotrichum candidum SC 5469. A reaction yield of 95% and optical purity of 96% was obtained for 2 by glucose-, acetate-, or glycerol-grown cells (10% w/v) of G. candidum SC 5469. Substrate was used at 10 mg ml−1 concentration. The optical purity of 2 was increased to 99% by heat treatment of cell suspensions (55°C for 30 min) prior to conducting bioreduction of 1 at 28°C.Glucose-grown cells of G. candidum SC 5469 have also catalyzed the stereoselective reduction of ethyl-, isopropyl-, and tertiary-butyl esters of 4-chloro-3-oxobutanoic acid and methyl- and ethyl esters of 4-bromo-3-oxobutanoic acid. A reaction yield of > 85% and optical purity of > 94% were obtained. NADP-dependent oxidoreductase responsible for the stereoselective reduction of β-keto esters of 4-chloro- and 4-bromo-3-oxobutanoic acid was purified 100-fold. The molecular weight of the purified enzyme is 950,000. The purified oxidoreductase was immobilized on Eupergit C and used to catalyze the reduction of 1 to 2. The cofactor NADP required for the reduction reaction was regenerated by glucose dehydrogenase.
Optimizing multi-response prob-lems in the Taguchi method by fuzzy multiple attribute decision making. Quality and Reliability Engineering Inter-national 13
- L.-I Tong
- C.-T Su
Tong, L.-I., Su, C.-T., 1997. Optimizing multi-response prob-lems in the Taguchi method by fuzzy multiple attribute decision making. Quality and Reliability Engineering Inter-national 13, 25–34.
Multi-response optimization in industrial experiments using Taguchi’s quality loss function and principal component analysis
- Antony