PEER-REVIEW ARTICLE PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4543 Process Maximization of Salt Free Reactive Dyeing on Cotton using Taguchi Approach Shekh Md. Mamun Kabir a,* This study optimized the salt free reactive dyeing process using the Taguchi approach. Dyeing of cotton fabric with reactive dyes is popular because of its bright and brilliant color in various shade ranges. Cationization with ALBAFIX-WFF and the dyeing process on cotton fabric was carried out using the exhaust method. To determine the optimum process conditions, two types of multiple characteristic parameters, including the single characteristic value conversion method and the process maximization method, were used on the basis of color strength (K/S) and wash fastness. The single characteristic value conversion method confirmed that the optimum process condition was a cationization temperature of 40 °C and a dyeing pH of 11. Most importantly, the optimal conditions were confirmed by the process maximization method as a concentration of ALBAFIX-WFF 30 g/L, cationization temperature at 80 C, dyeing pH 12, and material-to-liquor ratio (M:L) of 1:5. More suitable dyeing properties are also achieved by the process maximization method. DOI: 10.15376/biores.18.3.4543-4557 Keywords: Reactive dyes; Salt free dyeing; Taguchi method; Color strength; Wash fastness Contact information: Department of Wet Process Engineering, Bangladesh University of Textiles, Tejgaon, Dhaka-1208, Bangladesh; mamunkabir.butex@gmail.com INTRODUCTION Reactive dyes are the most popular dyestuffs used for cotton dyeing. A large amount of salt is required to achieve higher exhaustion of the reactive dye from the dye bath onto the fiber (Broadbent 2001). To overcome the repulsion forces occurring between the negative charged fibers and the dye molecules, electrolytes are needed for the dyeing process. However, the resulting discharge of salt has a harmful effect on the environment (Shore 2002). Recently, there has been improvement of the dye-ability on cotton fabric without salt. Pre-treatment with a cationic agent on cotton fabric has been studied as an alternative approach instead of using an electrolyte (salt) (Buschle-Diller and Zeronian 1992; Montazer 2007). Primary and secondary hydroxyl groups of cotton can actively participate in the chemical modification (Chattopadhyay et al. 2007; Montazer 2007; Choudhury 2014). Cotton fabric was cationized using CIBAFIX-WFF (a polyamino chlorohydrin quaternary ammonium compound) (Kannan 2006; Sanjit 2014). Salt-free reactive dyeing was carried out by cationization of cotton (Hauser and Tabba 2001; EI-Shishtawy and Nassar 2002; Montazer 2007) and Ramie fiber with 3-chloro-2- hydroxypropyltrimethylammonium chloride (CHPTAC) (Liu et al. 2007). In addition, cationization of jute fabrics by ALBAFIX-WFF (poly-diallyl dimethyl ammonium chloride) and sodium hydroxide was found to improve the dye-ability of reactive dye (Arju et al. 2014). The cationization of cotton fabric using chitosan (Bhuiyan et al. 2014), Kemifix REA, Optifix F, and Optifix RSL (Mustafa Tutak et al. 2010), Solfix-E (polyaminochlorohydrin quaternary ammonium salt with epoxide functionality), and PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4544 polyacryloxyethyltrimethylammonium chloride (PAOTAC) was used as a cationic agent for salt-free reactive dyeing (Lewis and McIlroy 1997; Teng et al. 2011). The cationized cotton substrate would be a suitable starting material of eco-friendly dyeing process for reducing the pollution load in terms of salinity and color discharge from the textile dyeing industries (Khatri et al. 2015; Arivithamani and Giri Dev 2017). However, the addition of NaOH for cationization caused the pH to rise to a very high level; subsequent neutralizing of the pH in wastewater treatments results in in-situ production of salt (Novak et al. 1998). The Taguchi method was used to find out the optimum condition for Digital Textile Printing Process (Jung et al. 2016). The Taguchi method was used to find sewing conditions that minimize the seam pucker (Park and Young 2005) and maximize the delamination strength of fusible interlinings (Yoon et al. 2010). Dyeing process optimization and color strength prediction for viscose/Lycra blended knitted fabrics was measured by the Taguchi Method (Hossain et al. 2016). Optimization of the dyeing process of cotton knit fabric and reduction of the re-dyeing process was analyzed by the Taguchi method and ANOVA (Analysis of variance) (Wahyudin et al. 2017). Optimization of chemical coagulation of real textile wastewater was investigated by the Taguchi method (Gokkus et al. 2012; Swapnil et al. 2015). Kuo and Lin (2019) used the Taguchi method and fuzzy theory to find optimum processing parameters for sueding fabric comfort. Investigating the effect of temperature, heating time, concentration, and particle size on the improved gel spinning process of ultra-high molecular weight polyethylene (UHMWPE) was measured using the Taguchi method (Rajput et al. 2018). Analysis for optimization of coating process conditions for denim fabrics (Üstüntağ et al. 2020), the bursting strength of knitted fabrics (Mavruz and Ogulata 2010), and optimization of concrete strengthened with polymer after high temperature (Mavruz and Ogulata 2010) were also studied by the Taguchi method. The Taguchi method was used for design optimization of cutting parameters (Yang et al. 1998) and optimization of end milling parameters (Ghani et al. 2004). The present studies were related to cotton fabric treated with cationizing agent in order to enhance the use of salt-free for reactive dyeing. The resulting performance was evaluated by color strength, exhaustion, fixation, and fastness properties. In the present optimized system, it might be assumed that NaOH is playing the role in increasing the ionic strength of the aqueous system as a means of suppressing electrostatic repulsions. However, there has been no research conduct to analyze the optimum condition by the help of Taguchi approach based on two characteristics, such as color strength and wash fastness. The multiple characteristic values are converted by statistical analysis into a single characteristic value and process maximization method. In addition, the most suitable statistical value was analyzed by the performance of dyeing properties. EXPERIMENTAL Materials Cotton (1 × 1 single jersey, GSM 150, scoured and bleached) fabric was used for the experiment. AlBAFIX-WFF (supplied by HUNTSMAN) was applied as a cationizing agent for cationization of cotton fabric. Novacron Ruby S-3B (supplied by HUNTSMAN) reactive dye (2% shade) was used for dyeing the fabric. PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4545 Cationization Cotton fabric was treated with ALBAFIX-WFF (20/30/40 g/L) along with NaOH (20 g/L) at a temperature of 40 C/60 C/80 C for 20 min. The material-to-liquor ratio (M:L) (w:v) ratio was taken as 1:10, and the treatment was carried out in exhaust method. After cationization, fabric was washed and dried in open air for 24 h. Dyeing Cotton fabric was dyed with 2% (owf) Reactive dye (Novacron Ruby S-3B), 2 g/L wetting agent, 1 g/L leveling agent, and the required amount of soda wash (Na2CO3) to maintain the specified pH. Dyeing was carried out in the exhaust method at 60 C for 60 min. The pH was set to either10, 11, or 12, and the M:L ratio (w:v) was 1:5, 1:10, and 1:15, respectively. After dyeing, the fabric was washed with cold water (room temperature) then hot water (70 C) and again cold water. Finally, the sample was dried in an oven dryer. Measurement of Color The color strength (k/s) values of the dyed cotton fabrics were analyzed using a spectrophotometer (Datacolor 650, USA, standard light D65; 10o standard observer, specular component included). The color strength (k/s) value was calculated from the sample reflectivity (R), as follows, 𝑘 𝑠 = (1−𝑅)2 2𝑅 (1) where k is the absorption coefficient, s is the scattering coefficient, and R is the reflectivity (McDonald et al 1997). Measurement of Color Fastness Color fastness to wash was evaluated according to ISO 105-C06 (A2S). In addition, color staining was assessed with the help of Grey Scale and Light Box (D65 light source). Experimental Design Several factors are known to affect the color strength (K/S) value and wash fastness. Four important controllable factors were chosen in this study: ALBAFIX-WFF (A), cationization temperature (B), dyeing pH (C), and material and liquor ratio (M:L) (w:v) of dyeing (D). Their levels are as shown in Table 1. The orthogonal array selection rules are given in Table 2. The L9 (34) orthogonal array is shown in Table 3. Each experiment was repeated three times. Table 1. Different Factors and Levels Factor Concentration of ALBAFIX-WFF(g/L) A Cationizing Temperature (C) B Dyeing pH C Dyeing M:L Ratio D Level 1 20 40℃ 10 1:5 2 30 60℃ 11 1:10 3 40 80℃ 12 1:15 PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4546 Table 2. Selection Process of Orthogonal Array Factors 2 3 4 5 6 7 8 9 10 Levels 2 L4 L4 L8 L8 L8 L8 L12 L12 L12 3 L9 L9 L9 L18 L18 L18 L18 L27 L27 4 L16 L16 L16 L16 L32 L32 L32 L32 L32 5 L25 L25 L25 L25 L25 L50 L50 L50 L50 Table 3. L9 (34) Table of Orthogonal Array Exp. No Factors and Levels (Treatment Conditions) Characteristics Value (Color strength/ Wash fastness) A B C D y1 y2 y3 1 1 1 1 1 y11 y12 y13 2 1 2 2 2 y21 y22 y23 3 1 3 3 3 y31 y32 y33 4 2 1 2 3 y41 y42 y43 5 2 2 3 1 y51 y52 y53 6 2 3 1 2 y61 y62 y63 7 3 1 3 2 y71 y72 y73 8 3 2 1 3 y81 y82 y83 9 3 3 2 1 y91 y92 y93 Both color strength (k/s) and wash fastness values were determined. The signal to noise (S/N) ratio of each experiment was calculated using Eq. 2 (Jung et al. 2016). Signal to Noise Ratio = −𝟏𝟎 𝐥𝐨𝐠 𝟏 𝒏 (∑ 𝟏 𝒚𝒊 𝟐 𝒏 𝒊=𝟎 ) (2) The number of repetitions for an experimental combination is n, the index number is i, and yi is the characteristic value. In the Taguchi method, the S/N ratio is equivalent to the inverse of expected loss. Therefore, the expected loss is proportional to the S/N ratio. In this study, color strength (k/s) and wash fastness were chosen for characteristic value y and 9 S/N ratios were calculated using three characteristic values and measured three times per interval. Process Evaluation by Dye Exhaustion, Fixation (%) and Levelness Parameter The maximum process method was evaluated by dye exhaustion and fixation (%), which was determined by UV-Vis spectrophotometry (Cintra 2020, GBC, Australia). The percentage dye exhaustion (E%) and fixation (F%) were calculated according to the following equations E% = [1 - (A1/Ao)] × 100 (3) F% = [(Ao - A1- A2 ) /Ao)] × 100 (4) Here, Ao and A1 are the absorbance of the dye solution at λmax before and after dyeing. A2 is the absorbance of the dye-soaped solution with a non-ionic surfactant. The levelness of the dyed fabric was assessed using an instrumental method that was developed by Yang and Li (1993). PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4547 𝑆𝑟(𝜆) = √ ∑ [( 𝑘 𝑠 )𝑖,𝜆−( 𝑘 𝑠 ̅ )𝜆]2𝑛 𝑖=1 (𝑛−1) (5) ( 𝒌 𝐬 ̅ )𝝀 = 𝟏 𝐧 ∑( 𝒌 𝒔 )𝒊,𝝀 (6) Here, λ is the wavelength for the measurement, n is the total number of measurements, and (k/s)i,λ is the k/s value of the ith measurement at λ. The levelness parameter was modified by Koh et al. (2001). Here, Sr(λ) is the relative sample standard deviation of (k/s)λ and V(λ) is the spectral luminous function. Thus, the unlevelness value is described as: 𝑈 = ∑ 𝑆𝑟(𝜆)𝑉(𝜆)700 400 (7) The levelness parameter LLev is varied to give different values, which are very similar to the gray-scale rating for color change if (U≥0.3114) 𝐿𝐿𝑒𝑣 = 1.20 × [ 2.00 − ∑ 𝑆𝑟(𝜆) 𝑉(𝜆)] 700 400 ] (8) And if U< 0.3114, then: 𝐿𝐿𝑒𝑣 = 5.0 − 1.2 × exp( 7 6 ) × 𝑈 (9) RESULTS AND DISCUSSION Optimum Condition by Taguchi Method Color strength (k/s) and wash fastness were taken as characteristics values. Four factors and three levels were considered to find optimum conditions based on the two characteristic values of color strength (k/s) and wash fastness. In this study, optimum conditions were calculated by two methods, i.e. by means of single characteristics and when using the process maximization selection method. Single Characteristics data Conversion Method The average characteristic values and S/N ratios are shown in Tables 4, 5, and 6. Table 4. Normalized Characteristics Value for Color Strength (k/s) Exp. No Characteristics Value (k/s) Average of Characteristics value Normalized Characteristics Value (k/s) y1 y2 y3 y1 y2 y3 1 16.96 16.782 17.012 16.9180 1.0024 0.9919 1.0055 2 13.866 14.063 13.88 13.9363 0.9949 1.0090 0.9959 3 17.248 16.285 17.301 16.9446 1.0179 0.9610 1.0210 4 12.713 12.992 13.385 13.0300 0.9756 0.9970 1.0272 5 17.621 15.776 18.566 17.3210 1.0173 0.9108 1.0718 6 13.946 13.43 13.888 13.7546 1.0139 0.9763 1.0096 7 17.322 17.416 16.935 17.2243 1.0056 1.0111 0.9832 8 15.737 14.626 15.046 15.1363 1.0396 0.9662 0.9940 9 16.613 16.682 16.448 16.5810 1.0019 1.0060 0.9919 PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4548 Normalized characteristics value was calculated using Eq. 10 (Jung et al. 2016). Normalized yi = 𝑦𝑖 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑦𝑖 (10) Likewise, the signal to noise ratio was calculated as follows: S/N = −𝟏𝟎 𝐥𝐨𝐠 𝟏 𝒏 (∑ 𝟏 𝒚𝐢 𝟐 𝒏 𝒊=𝟎 ) (11) Here, the number of repetitions for a multiple experiment is n, the index number is i, and yi is the characteristic value of the ith experiment. Table 5. Normalized Characteristics Value for Wash Fastness (Staining on Cotton) Exp. No Characteristics Value (Wash Fastness) Average of Characteristics value Normalized Characteristics Value (Wash Fastness) y1 y2 y3 y1 y2 y3 1 3 3 3 3.00 1.00 1.00 1.00 2 3.5 3 3 3.1666 1.1052 0.9473 0.9473 3 3.5 3 3.5 3.3333 1.05 0.90 1.05 4 3.5 3.5 3.5 3.50 1.00 1.00 1.00 5 3.5 3 3.5 3.3333 1.05 0.90 1.05 6 3.5 3.5 3.5 3.50 1.00 1.00 1.00 7 3 3 3 3.00 1.00 1.00 1.00 8 3.5 3.5 3 3.3333 1.05 1.05 0.90 9 3.5 3.5 3.5 3.50 1.00 1.00 1.00 Table 6. S/N Ratio of Average Characteristics Value Exp. No Factors and Levels (Treatment Conditions) Characteristics Value (K/S +Wash fastness) S/N Ratio A B C D y1 y2 y3 1 1 1 1 1 1.0012 0.9959 1.0027 -0.0006902 2 1 2 2 2 1.0501 0.9782 0.9716 -0.01624 3 1 3 3 3 1.0339 0.9305 1.0355 -0.03326 4 2 1 2 3 0.9878 0.9985 1.0136 -0.001745 5 2 2 3 1 1.0336 0.9054 1.0609 -0.06382 6 2 3 1 2 1.0069 0.9881 1.0048 -0.0012 7 3 1 3 2 1.0028 1.0055 0.9916 -0.00076 8 3 2 1 3 1.0448 1.0081 0.9470 -0.02186 9 3 3 2 1 1.0009 1.0030 0.9959 -0.000694 The sum of squares was calculated using Eq. 11. Sum of Square = ∑ (Sum of characteristics value at level i)2 Number of characteristics value at level 𝑖 𝑛 𝑖=1 - (∑ 𝑦i 𝑝 𝑖=1 ) 2 𝑁 (11) where yi is the characteristic value at level i, p is the number of levels, and N is the total number of characteristic values. The S/N Ratio was calculated using Eq. 12. Each level= Average S/N Ratio at each level-Total average S/N Ratio (12) The total average S/N Ratio was calculated using Eq. 13. PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4549 Total average S/N Ratio = Total S N Ratio 9 (13) The results of the analysis of the S/N ratio are shown in Table 7. Table 7. Analysis of S/N Ratio for Single Characteristic Value Factor Level Sum Sum of Square Average of S/N Ratio Contribution Pooling A 1 -0.0501902 0.000331 -0.16730066 0.00005 Yes 2 -0.066765 -0.022255 -0.00547 3 -0.02263 -0.00075433 0.01602 B 1 -0.0031952 0.001692 -0.00106506 0.0157 No 2 -0.10192 -0.0339733 -0.01719 3 -0.035154 -0.011718 -0.00506 C 1 -0.0237502 0.001309 -0.00791673 0.00886 No 2 -0.018679 -0.00622633 0.01055 3 -0.09784 -0.032613 -0.01583 D 1 -0.0652042 0.00042 -0.0217347 -0.00499 Yes 2 -0.0182 -0.006067 0.01071 3 -0.056865 -0.018955 -0.00217 Fig. 1. Cause and effect diagram of single characteristic value for color strength and wash fastness Factors B and C had the largest values of 0.001692 and 0.001309 by sum of squares. Factors A and D, with relatively small sum of square error, were pooled for error. The results of the F-Test are shown in Table 8. The degrees of freedom were calculated using Eq. 14. Degrees of freedom = (Level - 1) (14) Table 8. ANOVA Results Factor Sum of Square (S) Degrees of Freedom (ɸ) Mean Square (V=S/ɸ) F0=V/Ve F(2,4,0.95) B 0.0016917 2 0.0008458 4.50852 6.94 C 0.001309 2 0.0006545 3.4888 6.94 Total 0.0007506 4 0.0001876 (Ve) Cationization temperature and dyeing pH were considered to be the factors -0.04 -0.035 -0.03 -0.025 -0.02 -0.015 -0.01 -0.005 0 A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 S N R a ti o Factors and Levels PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4550 affecting color strength (k/s) and wash fastness. The optimum condition was B1 C2 where the S/N Ratio of each factors became the highest, with a cationization temperature of 40 ℃ and dyeing at pH 11. Average and Confidence Interval under Optimum Condition: The optimal S/N Ratio (SNo) can be predicted as follows, SNo = û + b1 + c2 (15) = -0.01678 + 0.0157 + 0.01055 = 0.00947 where û is the average S/N ratio, b1 is the contribution of B1, and c2 is the contribution of C2. Difference of Expected Loss The current condition was experiment 2 in Table 8 and its S/N ratio (SNc) was - 0.01624. The predicted S/N ratio at maximum condition (SNo) was 0.00947. The difference of expected losses can be done using equation (16). SN= −10 log 𝐿 SNo–SNc= d = 0.02571 −10log 𝐿0 - −10log 𝐿𝑐= d = 0.02571 𝐿𝑐 𝐿0 = 10 𝑑 10 (16) =10 0.02571 10 = 1.0059 where L is the expected loss of characteristics value and it means the variance of characteristics value. In this case, the expected loss is 1.0059 times larger than that of optimum condition, which means that color strength (K/S) and fastness have been improved. Process Maximization Method Single parameter design for each characteristic value The optimum two characteristic values have been chosen according to the single parameter design method. Color Strength Results S/N Ratio of Color Strength (k/s) are as represented in Table 9. Table 9. S/N Ratio (k/s value) for Process Maximization Method Exp. No Factors and Levels (Treatment Conditions) Characteristics Value (K/S Value) S/N Ratio A B C D y1 y2 y3 1 1 1 1 1 16.960 16.782 17.012 24.5665 2 1 2 2 2 13.866 14.063 13.880 22.8824 3 1 3 3 3 17.248 16.285 17.301 24.5705 4 2 1 2 3 12.713 12.992 13.385 22.2930 PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4551 5 2 2 3 1 17.621 15.776 18.566 24.7109 6 2 3 1 2 13.946 13.430 13.888 22.7652 7 3 1 3 2 17.322 17.416 16.935 24.7209 8 3 2 1 3 15.737 14.626 15.046 23.5886 9 3 3 2 1 16.613 16.682 16.448 24.3917 Table 10. Evaluation of S/N Ratio (K/S Value) for Process Maximization Method Factor Level Sum Sum of Square Average of S/N Ratio Contribution Pooling A 1 72.0194 1.5695 24.0064 0.1743 No 2 69.7691 23.2563 -0.5758 3 72.7012 24.2337 0.4016 B 1 71.5804 0.0531 23.8601 0.028 Yes 2 71.1819 23.7273 -0.1048 3 71.7274 23.9091 0.077 C 1 70.9203 3.4445 23.6401 -0.192 No 2 69.5671 23.1890 -0.6431 3 74.0023 24.6674 0.8353 D 1 73.6691 2.3611 24.5563 0.7242 No 2 70.3685 23.4561 -0.376 3 70.4521 23.4840 -0.3481 Fig. 2. Cause and effect diagram of process maximization value for color strength and wash fastness The sum of square of factors A, C, and D had the largest value of 1.5695, 3.4445, and 2.3611, respectively. F-tests are shown in Table 11. Table 11. ANOVA Results (K/S value) Factor Sum of Square (S) Degree of Freedom (ɸ) Mean Square (V=S/ɸ) F0=V/Ve F(2,2,0.95) A 1.5695 2 0.78475 29.5524 19 C 3.4445 2 1.72225 64.8571 19 D 2.3611 2 1.18055 44.4576 19 Error 0.0531 2 0.02655 (Ve) Total 7.4282 8 Table 11 factors A, C and D could be considered to be meaningful. Concentration 22 22.5 23 23.5 24 24.5 25 A1 A2 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 S /N R a ti o Factors and Levels PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4552 of ALBAFIX-WFF, dyeing pH and M: L Ratio considered to be the factors affecting highest color strength (K/S) and wash fastness. The optimum condition was A3 C3 D1 where S/N ratio of each factors becomes largest, such as Concentration of ALBAFIX-WFF 40 g/l, Dyeing pH of 12 and M: L Ratio of 1:5. Wash Fastness Results S/N Ratio for Wash Fastness are illustrated in Table 12. Table 12. S/N Ratio (Wash Fastness) S.L No Factors and Levels (Treatment Conditions) Characteristics Value (Wash Fastness) S/N Ratio A B C D y1 y2 y3 1 1 1 1 1 3 3 3 9.5424 2 1 2 2 2 3.5 3 3 9.9445 3 1 3 3 3 3.5 3 3.5 10.38 4 2 1 2 3 3.5 3.5 3.5 10.8813 5 2 2 3 1 3.5 3 3.5 10.38 6 2 3 1 2 3.5 3.5 3.5 10.8813 7 3 1 3 2 3 3 3 9.5424 8 3 2 1 3 3.5 3.5 3 10.38 9 3 3 2 1 3.5 3.5 3.5 10.8813 Table 13. Results of S/N Ratio (Wash Fastness) Factor Level Sum Sum of Square Average of S/N Ratio Contribution Pooling A 1 29.86 0.875 9.9533 -0.3592 No 2 32.14 10.7133 0.4008 3 30.80 10.2666 -0.0459 B 1 29.96 0.797 9.9866 -0.3259 No 2 31.20 10.400 0.0875 3 32.14 10.7133 0.4008 C 1 30.80 0.33 10.2666 -0.0459 Yes 2 31.70 10.5666 0.2541 3 30.30 10.100 -0.2125 D 1 30.80 0.28 10.2666 -0.0459 Yes 2 30.36 10.120 -0.1925 3 31.64 10.5466 0.2341 Fig. 3. Cause and effect diagram for wash fastness 9.4 9.6 9.8 10 10.2 10.4 10.6 10.8 A1 A1 A3 B1 B2 B3 C1 C2 C3 D1 D2 D3 S /N R a ti o Factors and Levels PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4553 The sum of square of factors A, and B had the largest value of 0.875 and 0.797. The results of the F-test are shown in Table 14. Table 14. ANOVA Results (Wash Fastness) Factor Sum of Square (S) Degree of Freedom (ɸ) Mean Square (V=S/ɸ) F0=V/Ve F(2,4,0.95) A 0.875 2 0.4375 2.8688 6.94 B 0.797 2 0.3985 2.6131 6.94 Error 0.61 4 0.1525(Ve) Total 2.282 8 Table 14 factors A, and B could be considered to be meaningful. The optimum condition was A2 B3 where S/N Ratio of each factors becomes largest, in other words, Concentration of ALBAFIX-WFF 30 g/l, Cationization temperature at 80. Process maximization levels of characteristics values are shown in Table 15. Table 15. Optimum Levels of Characteristics Values Characteristics Value Optimum Levels Color Strength (K/S) A3C3D1 Wash Fastness A2B3 As can be seen in Table 15, A is the only conflicting factor in this experiment, which had different optimum level between color strength (k/s) and wash fastness. Factors B, C, D were low conflicting factors and the optimum levels of each factor were B3, C3 and D1. S/N ratios of conflicting factor A are shown in Table 16. Table 16. Average and Normalized S/N Ratio of Conflicting Factor Factors SN Ratio (K/S Value) Average (K/S value) S/N Ratio Wash fastness value Average (Wash fastness) Normalized SN Ratio k/s value Wash fastness A1 24.0064 23.8321 9.9533 10.3110 1.0073 0.9653 A2 23.2563 10.7133 0.9758 1.0390 A3 24.2337 10.2666 1.0168 0.9956 In this case, level 2 with the maximum value of 1.0390 was selected. So, the selected optimum condition after compromise was A2 B3 C3 D1. Comparison of Progress Effect The progress effect of the determination of the process maximization is as shown in Table 17. The single characteristics value conversion method showed more progressive than the process maximization method. PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4554 Table 17. Comparison of Progress Effect Method Optimum Level Progress Effect Single characteristics value Conversion method B1 C2 1.005937 Process maximization method A2 B3 C3 D1. 0.9949 Evaluation of Dyeing quality and Dyeing Properties The dye exhaustion, fixation, and levelness of the cationized cotton fabric dyed with Reactive Red are shown in Table 18. The process maximization method revealed higher exhaustion (80.25%) and fixation (97.98%) than the single characteristic value conversion method exhaustion (77.65%) and fixation (81.29%). This difference arises because the concentration of ALBAFIX-WFF of 30 g/l, cationization temperature at 80 ℃, dyeing pH of 12, and M: L ratio of 1:5 enhanced the swelling of the fiber, which could be introduced dyestuff into the interior of the cellulosic material. However, the single characteristic value method levelness value was quite a bit higher than for the process maximization method. This can be explained based on the fact that the levelness value ensures that low dye uptake reduces dye desorption from the fabric surfaces (Kabir et al. 2020). Table 18. Dyeing Properties of Different Methods Method Optimum Level Exhaustion (%) Fixation (%) Levelness (L) Single characteristics value Conversion method A2B1 C2D1 77.65 81.29 4.93 Process maximization method A2 B3 C3 D1. 80.25 97.98 4.92 Dyeing Mechanism of Cationized Cotton Fabric The dyeing mechanism of reactive dye in a cationized cotton is illustrated in Fig. 4. It was clearly found that most of the reactive dyes were easily absorbed and diffused into the cationized cotton due to the presence of nucleophilic cationic sites, which attract the oppositely charged anionic reactive dyes by electrostatic attractions in the exhaust dyeing process. The cationic sites of the cationized cotton fabric could also restrict the movement of dye anions, resulting in decreased hydrolysis of reactive dyes (Arivithamani and Giri Dev 2017). The longitudinal morphology of cotton fibers was examined under bright field illumination using an optical microscope (Leitz Dialux, UK). It is clearly apparent that raw cotton has natural convolutions. However, after alkali treatment at pH 11 and pH 12 conditions, fibers became more rod-like cylinders, and the convolutions were completely removed. Most importantly, alkaline pH 12 conditions gave rise to a rounder shape can be formed which influenced more dye exhaustion and fixation (Remadevi et al. 2016, Wicker and Hallam 1970). PEER-REVIEWED ARTICLE bioresources.com Kabir (2023). “Salt-free reactive dyeing of cotton,” BioResources 18(3), 4543-4557. 4555 O H O H HO H H HO O H OH N OH N OH Cl- Cl- OHHN SS N NN HN S N N Cl O O O O O O O O O S O O O S OO O S O O O SO3Dye Exhaustion of dye on fibre without addition of salt NaOH O H O H HO H H HO O H OH N OH N OH CH3 SO2 O2S CH3 Dye Dye Cationized cotton Novacron Ruby S-3B Cationized cotton dyed fabric Fig. 4. Dyeing mechanism of cationized cotton fabric and optical images of cotton fibers cross- sections CONCLUSIONS The Taguchi approach was used in this study to optimize the process for salt-free reactive dyeing of cotton. Color strength (k/s) and wash fastness were selected as characteristics values and two kinds of multiple characteristics value analyses were performed. 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