Multi-response Signal-to-noise Research Articles

Optimisation of the process of dyeing cotton fabric with natural dyes from jackfruit wood by immersion without heating

PurposeThis paper aims to examine the recipe for and standard methods of dyeing cotton fabric with natural dyes from jackfruit wood extract. The dyeing of the fabric was performed by immersion it without heating for a short time to obtain the best results.Design/methodology/approachThe dyeing experiment using cotton fabric with jackfruit wood extract was conducted by immersion at room temperature. The independent variables studied were the mordant method, type of mordant, mordant concentration, salt concentration and dyeing pH. The dependent variables were colour strength and colour fastness to washing and rubbing. The orthogonal array L16 (45) was used in the study to obtain the optimal values for each parameter of the response variables. The multi-response signal-to-noise (MRSN) method was used to optimise the five response variables with different quality characteristics so that the best parameters could be obtained based on the highest MRSN ratio value.FindingsThe best parameters were obtained at an MRSN value of 4.5254 under A3B3C1D2E4 conditions, namely, the dyeing process with post mordant, aluminium nitrate type mordant, mordant concentration of 10 g/L, salt concentration of 15 g/L and dyeing a pH: of 10. Under these conditions, the value of K/S was obtained at 1.893, colour fastness to washing (GS: 4) and (SS: 4–5), dry rubbing (SS: 5) and wet rubbing (SS: 4–5).Research limitations/implicationsObtaining a standard recipe and method for dyeing cotton cloth with jackfruit wood extract by immersion without heating is expected to lead to the development of natural dyes, and especially their application on an industrial scale. This standard and method can be used as technical guidelines by industry. The use of aluminum nitrate as a mordant will help achieve optimal dyeing results. The use of polyaluminium chloride (PAC) mordant, which has the potential to produce high colour strength, and papaya fruit sap, which has the capacity to increase colour fastness, still need to be developed to improve the results of natural dyes.Practical implicationsThe standard recipe and dyeing method will be able to improve the results of the dyeing of cotton fabrics with natural dyes. Short immersion dyeing without heating and the optimal results obtained are the main attractions for their use by the textile/batik industry, as the process is easier and a lower cost. The results of dyeing with dark colours and good colour fastness mean the textile products are of the higher quality demanded by consumers, thereby increasing sales. This will encourage the use of and increase the need for natural dyes by industry, consequently reducing the use of synthetic dyes.Social implicationsThe use of natural dyes, chemical mordant from aluminum salts, and natural mordant from papaya fruit sap in the dyeing process in the textile/batik industry in Indonesia will produce eco-textile and eco-batik products that are environmentally friendly and of high quality. This in turn will increase consumer interest and sales, meaning that the income and economy of workers in the textile industry/crafts sector will also increase. In addition, the use of natural dyes with the selection of a safe mordant (not containing heavy metals) will reduce the use of synthetic dyes, which pollute and damage the aquatic environment.Originality/valueThis study found a standard recipe and method of dyeing cotton fabric with natural dyes from jackfruit wood extracted by immersion without heating for a short time to obtain the best results. In addition, the discovery was of PAC, a new mordant which is effective in the use of natural dyes can give high colour strength to cotton fabric. In addition to the discovery of a new mordant, PAC, which has the potential to produce high colour strength, papaya fruit sap also has the capacity to increase colour fastness with the use of natural dyes from the flavonoid group.

Taguchi‐based optimization of design and fuel parameters of partially premixed charge CI engine fuelled with biodiesel and butanol blends

AbstractSimultaneous control of NOx and smoke emission of compression ignition engine was the major challenge for the researchers as their formation mechanisms are inversely proportional to each other. In the present study, combustion process was modified as partially premixed charge combustion (PPCC) which supplies a premixed charge of fuel and air through inlet valve in addition to the fuel injected into the cylinder. This resulted in reduction of combustion temperature with lean air fuel ratio. To investigate the influence of various factors on these emissions, six design factors and two fuel factors of the engine were selected as factors and NOx, smoke, and brake thermal efficiency were selected as responses for the investigation. Experimental test matrix was designed based on Taguchi L18 orthogonal array. Multi response Signal to Noise (MRSN) ratio was calculated for the response variables and the optimum combination level of factors was obtained simultaneously using Taguchi's parametric design and the same was tested experimentally. Influence of each factor and most influencing factor on the chosen objective was determined by analyzing the variance of the MRSN ratio. This investigation reveals that among the factors tested, main injection fuel is the most influencing factor with a maximum percentage contribution of 44.5. It has been observed that normal combustion mode parameters have more influence with a percentage of contribution of 80 when compared with the parameters of PPCC mode. It has also been observed that fuel factors have higher percentage contribution of 53 compared with the design factors contribution of 43.6.

Optimization of injection timing and anti-oxidants for multiple responses of CI engine fuelled with algae biodiesel blend

Effect of addition of anti-oxidants into the algae biodiesel blend with modification of its fuel injection timing was investigated for the emission control of a compression ignition (CI) engine. It was planned to control the NOx emission of the engine fuelled with algae biodiesel blend by equally concentrating on the smoke control and brake thermal efficiency (BTE). Hence NOx, smoke and BTE were the responses for the present investigation. Experiment test matrix were designed with two different anti-oxidants (Pyrogallol (PY) and Butylated hydroxytoluene (BHT)) and fuel injection timing as the factors by choosing three levels in each factor. A single cylinder stationary engine was tested with the designed test matrix as per the Taguchi Orthogonal array. Experiments results were analysed by calculating multi response signal to noise (MRSN) ratio for the loss functions of the selected responses and also by analysing the variance of obtained MRSN ratio. From the results it was observed that when fuelled with algae biodiesel blend, BHT plays a most significant role followed by injection timing for the reduction of engine NOx emission with equal importance to the smoke control and BTE. It was also observed that the influence of pyrogallol was less when compared with other factors for the NOx control of the CI engine fuelled with algae biodiesel blend.

Multi-objective optimization of underfloor air distribution (UFAD) systems performance in a densely occupied environment: A combination of numerical simulation and Taguchi algorithm

Underfloor air distribution (UFAD) systems are on the way of development owing to their substantial energy saving potential as well as their capability for establishing thermally comfortable environments. Comprehensive evaluating these systems necessitates considering multiple effective factors ranging in several levels, which significantly augments the number of test cases and can even make the conducting of research impossible. Proposing a methodology for combining CFD results and the Taguchi optimization algorithm using the multi-response signal to noise (MRSN) analysis, the present study addresses this issue. In order to investigate the performance of UFAD systems applied in a densely occupied classroom from three fundamental viewpoints of thermal comfort, indoor air quality (IAQ), and energy saving, this research employs a multi-objective optimization approach. The utilized algorithm concludes that setting the following conditions provides the optimal state: (i) The underfloor diffusers beside the seats of occupants, (ii) The return vent at the height of 1.5 m from the floor, (iii) ACH equal to 14, (iv) Supply air temperature equal to 18 °C, and (v) Vertical air distribution from the underfloor diffusers. The ultimate simulation outcomes demonstrate that, according to the PMV and mean age of air values equal to 0.24 and 147 s in occupied and breathing zones, respectively, the thermal comfort conditions and desirable IAQ are established. Furthermore, energy saving compared to conventional mixing ventilation systems is a significant amount of 13.2%. In addition, local thermal comfort in terms of the vertical temperature difference and local convective cooling (draft) is achieved.

다구찌 기법에 의한 Cr2O3 플라즈마 코팅의 공정최적화

In the present study, process optimization for plasma-sprayed chromium oxide coating was performed using Taguchi method and analysis of variance (ANOVA). Chromium oxide coating specimens were fabricated by plasma-spray process according to L9 orthogonal array table. Hardness and porosity for each specimen was measured. The approach of Taguchi design for multi-response optimization problem is based on loss function of the quality characteristics. Multi-response signal-to-noise (MRSN) ratio was calculated for the response variables and the optimum combination level of variables, that is, the spray distance, the argon flow rate, the powder feed rate, and the surface velocity were obtained.

Modelling and Optimisation of Coconut Shell Drying and Carbonisation Using Multi-response Taguchi Method with Multi-response Signal-to-noise Procedure

The main purpose of this work is to optimize the biomass drying and carbonization process in terms of both proximate analysis and biomass calorific value, simultaneously. The biomass material used in the study is coconut shells. The independent variables are the drying temperature, the drying time, the carbonization temperature and the carbonization holding time. The dependent variables are proximate analysis and calorific value. The primary methods used to gain the expected result are Taguchi and multi-response signal-to-noise (MRSN) procedure. Simultaneous optimization by using MRSN generate a value of 2.48 and the result corresponds to a drying temperature of 100 °C, a drying time of 24 h, carbonization temperature of 650 °C, and carbonization time of 120 mins. These results are best achieved by using configuration A1B3C3D3. The optimal expected values obtained in this study are maximum calorific values and fixed carbon of 7744 cal/g and 92.934%, respectively, and minimum moisture, volatile matter, and ash content of 0.354%, 2.318%, and 1.437%, respectively. All indicators are satisfied since the resulting model is deemed to be valid and feasible. The novelty of this work is the simultaneous parameter optimization of the five response variables, which have different quality characteristics into a single best parameter. هدف اصلی از این کار این است برای بهینه سازی خشک کردن زیست توده و فرایند کربن از نظر هر دو آنالیز تقریبی و ارزش زیست توده گرمایی، به طور همزمان. مواد زیست توده مورد استفاده در مطالعه پوسته نارگیل است. متغیرهای مستقل هستند که درجه حرارت خشک کردن، زمان خشک شدن، درجه حرارت کربن و کربنی برگزاری زمانی. متغیرهای وابسته هستند آنالیز تقریبی و ارزش گرمایی. روش اصلی استفاده می شود برای به دست آوردن نتیجه مورد انتظار هستند تاگوچی و چند پاسخ سیگنال به نویز (MRSN) روش. بهینه سازی به طور همزمان با استفاده از MRSN تولید یک ارزش 2.48 و نتیجه مربوط به درجه حرارت خشک کردن از 100 درجه سانتیگراد، زمان خشک کردن 24 ساعت، درجه حرارت کربناتی در 650 درجه سانتیگراد و زمان کربناتی در 120 دقیقه. این نتایج با استفاده از بهترین A1B3C3D3 پیکربندی به دست آورد. ارزش مطلوب به دست آمده در این مطالعه مقادیر حداکثر گرمایی و کربن ثابت 7744 کال / g و 92.934٪، به ترتیب، و حداقل رطوبت، مواد فرار، و خاکستر 0.354٪، 2.318٪ و 1.437 درصد، به ترتیب می باشد. تمام شاخص راضی از نتیجه مدل معتبر و عملی محسوب می شود. به تازگی از این کار بهینه سازی پارامتر همزمان از پنج متغیر پاسخ، که دارای ویژگی های با کیفیت مختلف را به یک بهترین پارامتر است.

Weighting analysis of pellet quality attributes using Multi Response Signal to Noise (MRSN) method

Quality of pellets, one form of animal feed, is not only measured by the nutritional content but also by its physical form. The physical strength of the pellet is determined from crushing and not easily moldy. Both quality characteristics are measured by reliability (pellet durability index) and resistance (water content percentage). In order to improve the quality of pellet, this study applied Multi Response Signal to Noise (MRSN) method. The weight of product quality attributes used will influence the method in determining the selected alternatives. To accommodate the weighting of dynamic product quality attributes, this study also ran weighting sensitivity analysis of product quality attributes. The results showed that the combination of factor level that produced the optimal pellet is A2, B1, C1, D1, E1, F1, G2 or combination of production process run with vapor pressure 1.9 bar, temperature conditioner 80 ° C, 3.5mm pellet diameter mold, cooler temperature 30 ° C, time in cooler 2 minutes, roller distance 1.5 cm, mixing time 175 seconds. This optimum combination can increase PDI percentage by 2.132% and decrease difference to target of water content by 0.234%. The optimum factor level combination will change if the weight for % PDI rises to be more than 0.77228 or decreases to be less than 0.00561, or in other words, the optimum combination will not change if the weight for % PDI is in the range 0.00561 - 0.77228.

Modelling and Optimization the Best Parameters of Rice Husk Drying and Carbonization Using Taguchi Method with Multi Response Signal to Noise Procedure

The goal of this study is to optimize parameters the rice husk drying and carbonization process in terms a calorific value and proximate analysis simultaneously. The independent variables are the drying temperature (A) at 100; 105, or 110 °C; the drying time (B) at 12, 18, or 24 h; the carbonization temperature (C) at 450; 550, or 650 °C; and the carbonization holding time (D) at 60; 90, or 120 mins. The methods of the research are Taguchi and multi-response signal-to-noise(MRSN) procedure. The results show that simultaneous optimization of the drying and carbonization of rice husk in terms of the proximate analysis and calorific value, is determined by using the MRSN procedure, and it yields a result of 2.042. The best parameters are a drying temperature of 100 °C; a drying time of 24 h; a carbonization temperature of 650 °C; and a carbonization holding time of 120 mins. The optimal estimated calorific value, fixed carbon, moisture, volatile matter, and ash content are 5665 cal/g, 83.2, 0.06, 3.1 and 6.86 %, respectively. The resulting models are valid and feasible. The advantages of this work compared to previous studies are models and the simultaneous parameter optimization of multi-response variables, which have different quality characteristics into a single best parameter.

Optimizing Multiple Quality Responses in the Taguchi Method Using Fuzzy Goal Programming: Modeling and Applications

The Taguchi method is only an effective approach for optimizing process performance with a single quality response. However, customers are concerned about multiple quality responses on a product. Furthermore, process engineers have preferences on process settings. Consequently, collaboration between product and process engineers is required to satisfy customers as well as process requirements. This research proposes a collaborative approach for optimizing process performance with multiple quality responses on manufactured products in the applications of the Taguchi method using the Min–Max fuzzy goal programming model. Requirements on quality responses and process factors are described by proper membership functions. Then, an optimization model is developed and then solved to minimize the maximal deviation from each goal. Four case studies are provided for illustration, where it is noted that the proposed approach (a) considers preferences on quality responses and factor settings, which are ignored by grey relational analysis, multi-response signal-to-noise (MRSN) technique, and grey–fuzzy logic approach, (b) develops mathematical relationships between each quality response and process factors, contrary to MRSN and grey analysis that combine all responses into one index, and (c) involves process knowledge about preferred process settings, which is ignored by grey relational analysis. In conclusion, the proposed collaborative optimization model may provide great support to process/product engineers in robust design.

심해 잡음인자를 고려한 망간단괴 시험집광기의 채집운용시 주행장치 다구치 강건설계

A deep-sea manganese nodule miner consists of 4 parts: the pickup device, crusher, disposal device, and tracked vehicle. The tracked vehicle is an essential component to keep the self-propelled miner moving across deep-sea soil. The performances of the tracked vehicle are influenced by noise factors: the shear strength of the seafloor, bottom current, seafloor slope, track speed, reaction forces of flexible hose, etc. It is necessary to adopt a robust design method that improves the performances and minimizes the variation caused by noise factors. Taguchi's method, the most widely known robust design method, searches for the robust optimum using an orthogonal array composed of the product of the inner array and outer array. In this paper, we propose a new screening technique to reduce the number of input factors and apply the MRSN (Multi-Response Signal to Noise) ratio to convert multiple performances into single one in order to overcome the difficulties and limitations of using Taguchi's method in a case with many input factors and multiple performances. A test miner was already designed and tested. It has about 1/10 the capacity of a commercial one and was successfully operated at an in-shore area. Taguchi's robust design was applied to the tracked vehicle of the test miner, and design improvements were implemented for the vehicle.

Multi response optimisation in emission control of CI engine fuelled with crude rice bran oil blend

In the present work, high free fatty acid (FFA) crude rice bran oil (CRBO) blend was tested in a stationary CI engine and investigation was focused to reduce NOx emission than diesel with lesser smoke density. Combustion process was modified by varying the factors namely fuel injection timing, percentage EGR and fuel injection pressure in a combination suggested by Taguchi’s L9 orthogonal array. Three levels were chosen in each factor and NOx emission, smoke density and brake thermal efficiency were taken as the response variables. Multi response signal-to-noise (MRSN) ratio was calculated for the response variables and the optimum combination level of factors was obtained simultaneously using Taguchi’s parametric design. Obtained optimum combination level was confirmed experimentally and significant improvement was observed in the response variables.

Experimental studies to validate simulated results for nozzle effectiveness using multi-response optimisation during cylindrical grinding process

The computational fluid simulation (using ANSYS CFX module) approach was used to study six different nozzle shapes and cross section to study the grinding fluid flow behaviour through them. On the basis of the simulation study, two best shapes of nozzles namely spline followed by convergent-divergent were identified for obtaining the peak velocity of the fluid. The results were experimentally validated using all the six nozzles used in the simulation study along with other grinding process parameters to identify the parameters which significantly affect the quality of the grinding output. The results showed different level settings for the three factors for optimising the three response parameters. Multi-response signal-to-noise (MRSN) was used to optimise the three responses together. Spline shaped nozzle gave the best results for the three responses followed by convergent divergent which also validated the simulation study results. The workpiece speed and nozzle tip distance were key factors that affect...

Multi-Objective Optimization of Die-Sinking Electric Discharge Machining

— Parametric optimization of electric discharge machining (EDM) is a challenging task. Many researchers have employed different multi-objective optimization techniques for the same. This work employs multi-response signal-to-noise (MRSN) technique to find the optimum factor/level combination of input parameters. Experiments have been conducted on die-sinking EDM by taking heat treated D2 steel as work piece and copper as tool electrode. Experiments have been designed as per Taguchi’s L36 orthogonal array. Two cases v.i.z. high cutting efficiency and high surface finish have been taken. Analysis of variance (ANOVA) is employed to indicate the level of significance of machining parameters in both the cases. Finally, results have been verified experimentally and a significant improvement in material removal rate and surface roughness is observed.

Optimization of a Stationary Diesel Engine Fuelled With Crude Rice Bran Oil Methyl Ester Using the Taguchi Method

In the present work an attempt was made to reduce the NOx emission of crude rice bran oil methyl ester (CRBOME) with a marginal increase in smoke density and decrease in brake thermal efficiency in a stationary CI engine. Three factors namely fuel injection timing, quantity of exhaust gases recycled and fuel injection pressure were chosen. Experiments were designed by employing design of experiments method and tests were conducted with combination of factors as per Taguchi’s L9 orthogonal array. Percentage contribution of each factor and the most influencing factor in controlling the response variables (NOx emission, smoke density and brake thermal efficiency) were obtained through ANOVA. Multi-response signal-to-noise (MRSN) ratio was calculated and the optimum combination level of factors was obtained simultaneously using Taguchi’s parametric design. Among the three, the most influencing factor for the chosen objective was found out by analyzing the MRSN ratio through ANOVA. The optimum combination obtained shows a lower NOx emission with less influence on smoke density and brake thermal efficiency.

Multi-response optimization and empirical modeling of cardiopulmonary responses during manual lifting tasks

An experimental study involving five independent lifting variables (namely weight, lift frequency, horizontal distance from the object, operator, and vertical distance) and their interactions was conducted using the Taguchi L27 design. Two responses—heart rate and oxygen uptake—were measured during each trial. To optimize both responses simultaneously, the signal‐to‐noise ratio was normalized to obtain a multi‐response signal‐to‐noise (MRSN) ratio for each trial. The MRSN ratio was analyzed using analysis of variance to identify the optimal condition in which both responses were optimized at the same time. Lift frequency was found to be the most significant factor, and operator and horizontal distance were found to be least significant. The empirical modeling equation was developed and can be used to predict the response values during experimental trials involving similar work conditions. © 2010 Wiley Periodicals, Inc. © 2011 Wiley Periodicals, Inc.

Performance studies of Wire Electro Discharge Machining (WEDM) of Inconel 718

This paper describes the development of mathematical models and multi response optimisation to predict and select the best cutting parameters for Wire Electro Discharge Machining (WEDM) process. Inconel 718 was selected as work material for experimentation. A brass wire of 0.25 mm diameter was applied as a tool electrode to cut the specimen. The responses were optimised concurrently using Multi Response Signal to Noise (MRSN) ratio. ANOVA was employed to identify the level of importance of the machining parameters. Finally, experimental confirmations were carried out to identify the effectiveness of this proposed method.

Modeling and multi-response optimization of Inconel 718 on machining of CNC WEDM process

This paper describes the development of artificial neural network (ANN) models and multi-response optimization technique to predict and select the best cutting parameters of wire electro-discharge machining (WEDM) process. To predict the performance characteristics namely material removal rate and surface roughness, artificial neural network models were developed using back-propagation algorithms. Inconel 718 was selected as work material to conduct experiments. A brass wire of 0.25 mm diameter was applied as tool electrode to cut the specimen. Experiments were planned as per Taguchi's L9 orthogonal array. Experiments were performed under different cutting conditions of pulse on time, delay time, wire feed speed, and ignition current. The responses were optimized concurrently using multi-response signal-to-noise (MRSN) ratio in addition to Taguchi's parametric design approach. Analysis of variance (ANOVA) was employed to identify the level of importance of the machining parameters on the multiple performance characteristics. Finally, experimental confirmations were carried out to identify the effectiveness of this proposed method. A good improvement was obtained.

Multi-response optimisation of WEDM process using principal component analysis

Like many other processes, the wire electrical discharge machining (WEDM) process has several performance characteristics. Determination of the optimal process settings with respect to all these performance measures (responses) is an important issue. Taguchi’s robust design method can only be applied to optimise a single-response problem. Some researchers have attempted to optimise WEDM operations using a multi-response signal-to-noise (MRSN) ratio and constraint optimisation methods. Both these methods suffer from some weaknesses. The principal component analysis (PCA)-based approach for multi-response optimisation can effectively overcome those weaknesses. In this paper, some modifications in the PCA-based approach are suggested and two sets of experimental data published by the past researchers are analysed using this modified procedure. It is observed that the PCA-based optimisation can give better results than the constrained optimisation and MRSN ratio-based methods, which can be attributed to the fact that the possible correlation among the multiple responses is taken care in the PCA-based approach.