Optimum Levels Of Parameters Research Articles

Development and validation of a stability-indicating ultra-high-performance liquid chromatography method for the estimation of ibrutinib and trace-level quantification of related substances using quality-by-design approach.

A new ultra-high-performance liquid chromatography method was developed using quality-by-design principles for quantifying trace-level impurities of ibrutinib. The method utilized an ACQUITY UPLC BEH C18 column with a mobile phase consisting of equal parts of 0.02 M formic acid in water and 0.02 M formic acid in acetonitrile. The critical method parameters, including mobile phase pH, column temperature, and flow rate, were optimized using the design of experiments. Statistical analysis revealed the impact of these parameters on critical quality attributes. Perturbation and response surface plots illustrated the individual and interactive effects of the parameters. The optimal parameter levels were determined to be pH,2.5; column temperature, 28°C; and flow rate, 0.55 mL/min. Confirmation experiments demonstrated the method's robustness, with the separation of impurities and unknown degradation products within a 5-min runtime. The optimized ultra-performance liquid chromatography method was validated according to ICH guidelines. The method exhibited linear response within the range of 0.025-100 μg/mL for ibrutinib and 0.0187-0.225 μg/mL for impurities (r2 > 0.9995), with limits of detection/limits of quantification of 0.01/0.025 and 0.015/0.0187 for ibrutinib and four impurities, respectively. Recoveries for the drug and impurities ranged from 92.69 to 102.7%, and precision was below 2% and 8% relative standard deviation for ibrutinib and impurities, respectively.

Numerical investigation of specific performance parameters of the S-ROTOR; a Savonius type turbine design

After the energy crisis in the 1970s, studies on alternative electrical energy production processes gained more importance especially considering the possibility of a new energy crisis that may come up nowadays. Despite their low power generation, s-rotor designs used in vertical axis wind turbines are open to development due to their features, such as producing high torque and having many configurations. In this study, the optimum s-rotor design is created using the aspect ratio, overlap ratio, quarter blade gap ratio, and fin as parameters. The effective levels of each parameter were found by performing Computational Fluid Dynamic analysis. Then, using the Responds Surface Optimization method, optimum parameter levels were determined, and the optimum s-rotor design was created. The findings showed that the newly designed s-rotor provided a remarkable performance increase in high tip-speed ratios. In addition, the maximum power coefficient of the s-rotor increased from about 0.06 to 0.10, and it was determined that the aspect ratio was more effective on the power coefficient than the other parameters.

Optimizing conditions for the recovery of lignans from sesame cake using three green extraction methods: Microwave-, ultrasound- and accelerated-assisted solvent extraction

Lignans, a group of polyphenolic low molecular weight bioactive compounds with health benefits, are major constituents of sesame cake (SC), a by-product derived from sesame oil processing. The utilization of this by-product in the food or nutraceutical industries could explore its valorization route in compliance with sustainability and circular economy principles. This study aimed to investigate the impact of different environmental-friendly processing approaches such as ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE) and accelerated solvent extraction (ASE) for lignans extraction from SC using central composite design (CCD) with response surface methodology (RSM). Sesaminol triglucoside (SETRI) and sesaminol diglucoside (SEDI) were identified and quantified as the major lignan glucosides in SC. Ethanol/water mixture was selected as ‘green’ solvent for all extraction methods. The influence of ethanol concentration (X1), extraction time (X2), temperature (X3) and solid-to-solvent (SS) ratio or solid weight (X4) on extraction yield (EY), SETRI and SEDI contents for each technique was examined. The developed models exhibited a high degree of desirability (> 0.72) with determined optimal levels of extraction parameters as follows: X1 = 71%, X2 = 10 min, X3 = 50 °C, X4 = 1.50 g/20 mL for UAE; X1 = 80%, X2 = 5 min, X3 = 50 °C, X4 = 0.85 g/20 mL for MAE; X1 = 80%, X2 = 20 min, X3 = 65 °C, X4 = 2 g for ASE. Under these optimal conditions, the experimental values for EY, SETRI and SEDI contents in SC extracts were: 8.28%, 105.98 mg/g and 16.93 mg/g, respectively for UAE; 8.75%, 105.41 mg/g and 18.76 mg/g, respectively for MAE; 9.34%, 108.00 mg/g and 18.34 mg/g, respectively for ASE. The ANOVA analysis from the RSM were fitted with quadratic models yielding acceptable R2 (> 0.87), adjusted R2 (> 0.77), predicted R2 (> 0.74), and nonsignificant lack-of-fit (p > 0.05) values. Ethanol concentration and solid-to-solvent ratio were the most influencing factors affecting lignans extraction. Although ASE was found as the most suitable method for extracting lignans from SC, from an industrial viewpoint, UAE could be a more affordable technique due to advances in ultrasonic processing devices for large scale applications.

Optimization of TIG welding process parameters on 304 austenitic stainless steel sheet metal using fuzzy logic based Taguchi method

TIG welding can be used to produce excellent weld quality and precise welding operation for sheet metals. The aim of this study was to get the best welding parameters for enhancing ultimate tensile strength, bending strength and Rockwell hardness of the butt-weld joint. The experimental work was used, and the experiment was carried out on 2 mm thickness of 304 austenitic-stainless steel sheet metal using the L9 orthogonal array of the Taguchi design. Automated TIG welding fixture was developed to control the welding speed accurately. The selected welding parameters were welding speed, current, voltage and gas flow rate with their three levels. Based on the fuzzy logic based Taguchi method, the best optimal levels of parameters were found at the values of 110 A of current, 13.86 cm/min of speed, 17.5 V of voltage and 7.5 L/min of gas flow rate. The analysis results of ANOVA showed that gas flow rate and current were found as the significant factors, and the contributions of the gas flow rate, current, speed and error were 47.63%, 34.34%, 16.49% and 1.54%, respectively. According to the confirmation tests, the multi response performance index mean value of the confirmatory test of 0.6068 was found between the 95% confidence interval of 0.5028 and 0.7314, and the maximum ultimate tensile strength, bending strength and Rockwell hardness were obtained 614.8 MPa, 765.32 MPa and 95.3 HRB, respectively.

Optimization of process parameters effects on mechanical properties of selective laser melted iron samples

AbstractSelective laser melting is an additive manufacturing technology whereby parts are built through selective melt of a powder bed by a laser beam. This technology is used to produce net shape parts in 3D printers. In this study, the effect of selective laser melting parameters on the mechanical properties (ultimate tensile strength and hardness) of iron has been experimentally extracted, and the optimum levels of the parameters have been determined for optimum mechanical properties using signal‐to‐noise analysis. The selected parameters include the laser power, the laser scanning speed, and the laser hatch distance, and the design of experiments was done by the Taguchi method. The main effects of factors and interactions were considered in this paper. The results show that the optimum parameter levels for the ultimate tensile strength include the laser power of 200 W, the laser scanning speed of 600 mm/s, and the hatch distance of 70 μm. The optimal parameters for hardness are similar to the maximum tensile strength, except that the optimum hatch distance is 60 μm.

Investigation of Physical and Chemical Properties of Bitumen Modified with Waste Vegetable Oil and Waste Agricultural Ash for Use in Flexible Pavements

The rapid growth of the world population and the rapid diversification of consumption habits due to technological advancements have increased waste production. An investigation of the effects of biomass products, such as waste vegetable oil and waste agricultural ash, on bitumen’s physical and chemical properties was conducted in this study. By recycling biomass products, this study aimed to improve the performance and stability of bituminous hot mixtures, optimize the number of additives, and create more economical designs. Using the Taguchi method, 0%, 2%, 4% by weight of waste vegetable oil and 0%, 3%, and 6% by weight of waste agricultural ash were added to 70/100 penetration pure bitumen with an orthogonal array of L9. For 10, 20, and 30 min, modified bitumen samples were prepared at 170 °C, 180 °C, and 190 °C with a constant mixing speed of 3000 RPM. The samples were tested for penetration, softening point, flash point, rolling thin film oven (RTFOT), FTIR, and Marshall Design stability and flow. Based on the obtained performance statistics, 95% confidence levels were assigned to the predictions. The stability and softening point values decreased as the oil content increased, while flash and penetration values increased. With increasing ash content, stability, flash, and softening point values increased, and penetration values decreased. Compared to oil and ash additives, mixing temperature and time had relatively little effect on the modification process. Overall, the optimum parameter levels were 4% for oil, 0% for ash, 170 °C for temperature, and 10 min for time.

Tensile Test Optimization Using the Design of Experiment and Soft Computing

The tensile testing of various materials to evaluate the influence of different machining parameters is a fundamental requirement in every industry. The objective of this study is to investigate the effects of temperature, the area of the contact point, and the operator on the tensile test of brass samples. This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). By combining these techniques, the study aims to leverage their individual strengths and achieve superior results. The results reveal that the area of the contact point exerts the most significant influence on the tensile test, followed by the operator and temperature. The optimal levels of these parameters are determined to be a level of two for the operator, a level of three for the area of the contact point, and a level of one for the temperature. The study demonstrated that the hybrid soft computing method outperformed the traditional DOE method, achieving a substantial improvement in elongation of 32.9%. The optimized combination of machining parameters led to a notable enhancement in the brass samples’ tensile properties, highlighting the effectiveness of the applied methodology. The marginal error of only 0.72% in the hybrid approach showcases its high precision and reliability in determining the optimal levels of machining parameters. These findings underscore the potential of the Taguchi optimization method, ANFIS, and GA in achieving superior results in the tensile testing of materials, particularly in cases where multiple parameters are involved. The research results provide valuable insights for industries relying on precise material characterization, offering a robust methodology for optimizing tensile testing procedures. The study’s success in leveraging a hybrid soft computing approach serves as a promising avenue for future research in the field of material testing and optimization techniques.

Some Observations on Phytoplankton Bloom, Water pH and Dissolved Oxygen in Aerated Shrimp Ponds

The purpose of water quality management is to create a good and stable aquatic environment for the growing shrimp so as to obtain the optimum possible yield in the shortest possible time, and to attain a healthy and dynamic symbiotic environment. Maintaining optimum levels of physico-chemical parameters and their balance induce growth of shrimp, while fluctuation impairs the ecology and its balance, causes stress, deterioration and negative effects on shrimp. When, among all the hydrological parameters, pH and DO are considered as most critical for shrimp growth and survival. Phytoplankton plays a significant role in stabilizing the whole pond ecosystem, in minimizing the fluctuation of water quality and lowers the levels of NH,, HS, etc., which are toxic to shrimp. Since growth, survival and yield of Penaeus monodon depend largely upon the water quality, it is essential to maintain a stable water colour and to understand the role of these variables in shrimp pond ecosystem, where aquatic environment is artificially controlled by periodic liming, water exchange and aeration.

Optimization of heat pipe charged with CuO nanofluid using Taguchi technique

Aim of this study is to investigate the influence of various working parameters on the performance of thermosyphon heat pipe, charged with aqueous copper oxide nanofluid. This heat pipe was used as an absorber in twin glass evacuated tube solar collector for heating edible oil stored in an insulated tank. Design of experiments was formulated using minitab™ 19 considering prominent heat pipe working parameters like CuO nanoparticle concentration, CuO nanoparticle size, copper heat pipe diameter, filling ratio, stirring speed and surfactant concentration and their levels through research gaps. Experiments were performed on clear sunny days and impact of parameters on heat pipe solar collector performance was examined using Main effect plot, signal to noise (S/N) ratio and ANOVA. From response table of signal to noise ratio and the ANOVA results, it is concluded that the nanoparticle concentration, nanoparticle size, filling ratio and stirring speed plays important role in heat pipe performance improvement while other parameters like heat pipe diameter and surfactant concentration are less significant. Thus Optimum levels of parameters for best heat pipe solar collector performance were obtained as, nanofluid concentration of 0.3 (% weight), nanoparticle size of 30–50 nm, 8 mm of heat pipe diameter, 45 % of filling ratio, stirring speed of 1200 rotations per minute while preparing nanofluid and surfactant mixing in nanofluid as 0.3 (% volume).

Electron beam welding of dissimilar Titanium to aluminium: Interface microstructure and mechanical properties

Welding of dissimilar metals, titanium–aluminium having wide differences in mechanical and thermal properties was highly challenging. In the present investigation, the electron beam welding method was used to join titanium alloy with pure aluminium. The results show that at the optimum parameter levels such as beam current of 6 mA, welding speed of 8 mm/s, and beam offset of 70:30 (Ti:Al) toward titanium, a defect-free joint with the higher mechanical strength of 120 MPa was achieved compared to the other combination of parameters. The percentage contribution of significant parameters was welding speed of 62%, and beam current of 25%. The scanning electron microscope was used to study the Ti–Al interface microstructure in detail. A significant increase in the micro-hardness in the weld zone was due to a change in titanium microstructure from equiaxed α-phase to acicular α and the formation of Ti-Al intermetallics in the fusion zone. X-ray diffraction analysis was used to analyze the phases present in the fusion zone. It was confirmed that there were mainly Al-Ti compounds like Al2Ti, Al3Ti, AlTi, AlTi2, Al11Ti5. These phases are harmful and contributed to higher hardness and brittleness in the fusion zone. At optimum conditions, a defect-free joint without intermetallics was obtained without an increase in hardness in the fusion zone.

Multi-Response Optimization Analysis of the Milling Process of Asphalt Layer Based on the Numerical Evaluation of Cutting Regime Parameters

The present study aimed to optimize the process parameters (milling depth and advanced speed) for an asphalt milling operation using a multi-response approach based on Taguchi design of experiments (DOE) and Grey Relational Analysis (GRA). Nine simulations tests were conducted using Discrete Element Method (DEM) in order to determine the forces acting on the cutting tooth support and tip. The considered performance characteristics were cutting forces (smaller is better category) and chip section area (larger is better category). A Grey Relational Grade (GRG) was determined from GRA, allowing to identify the optimal parameter levels for the asphalt milling process with multiple performance characteristics. It was found that that the optimal milling parameters for multi-response analysis are a milling depth of 200 mm and an advanced speed of 30 mm/min. Furthermore, analysis of variance (ANOVA) was used to determine the most significant factor influencing the performance characteristics. The analysis results revealed that the dominant factor affecting the resultant cutting force was milling depth, while the main factor affecting chip section area was the advanced speed. Optimizing milling efficiency is essential in machining operations. A key factor in this direction is comprehending the interplay between chip removal and cutting forces. This understanding is fundamental for achieving increased productivity, cost-effectiveness, and extended tool lifespan during the milling process.

Investigation and optimization of wire EDM process parameters for Al 5454 alloy machining

In the current research, the use of a wire electric discharge machine (WEDM) to machine aluminium 5454 alloy work material is studied. A zinc-coated brass wire with a diameter of 0.25 mm is used as the tool material, and deionized water is used as the dielectric fluid. In this work, different parameters like pulse on time (Ton), current, power, wire feed rate, wire tension, and flushing pressure are varied for analysis of the performance of material removal rate (MRR) and surface roughness (SR). Taguchi L16 is used to design the experiments. Multi-response optimization is done by the multi-response signal-to-noise ratio (MRSN) method to obtain the best combination of parameters. To find the significance of parameters, the Analysis of Variance (ANOVA) technique has been used. From the experimental investigation, it was found that current is the most influential parameter and flushing pressure is the least influential parameter for MRR and SR. The optimal level of input parameters obtained using the optimization method for material removal rate and surface roughness are Peak current = 15A, Pulse on time = 32 s, Wire tension = 15 N, Wire feed = 165 mm/min, Power = 25w, flush pressure = 7 bar. The confirmation experiments are conducted to verify the results obtained by the MSRN method. Optimal WEDM settings for machining Al 5454 alloy samples enhanced improvements in material removal rate and surface finish.

Investigations of performance characteristics on direct metal laser sintered MONEL K-500 superalloy

MONEL K-500 superalloy is difficult to manufacture precisely in traditional manufacturing processes like casting, forming and machining. The direct metal laser sintering (DMLS) process is one of the best metal additive manufacturing processes used in this work. In this work, Laser Power (LP), Scan Speed (SS), Hatch Distance (HD) and Layer Thickness (LT) are used as DMLS process parameters. L09 Orthogonal array is used for printing the MONEL K-500 metal parts. The performance characteristics like ultimate tensile strength (UTS) and surface toughness (Ra ) are improved by 2% and 17% for the Taguchi optimum parameter levels. Contour plots explained the interaction effects of DMLS process parameters on performance characteristics. The better microstructural characteristics obtained the higher optimum parameter level.

Integration of Multivariate Statistical Control Chart and Machine Learning to Identify the Abnormal Process Parameters for Polylactide with Glass Fiber Composites in Injection Molding; Part I: The Processing Parameter Optimization for Multiple Qualities of Polylactide/Glass Fiber Composites in Injection Molding.

This paper discusses the mixing of polylactide (PLA) and glass fiber which use injection molding to produce a functional composite material with glass fiber properties. The injection molding process explores the influence of glass fiber ratio, melt temperature, injection speed, packing pressure, packing time and cooling time on the mechanical properties of composite. Using the orthogonal table planning experiment of the Taguchi method, the optimal parameter level combination of a single quality process is obtained through main effect analysis (MEA) and Analysis of variance (ANOVA). Then, the optimal parameter level combination of multiple qualities is obtained through principal component analysis (PCA) and data envelopment analysis (DEA), respectively. It is observed that if all the quality characteristics of tensile strength, hardness, impact strength and bending strength are considered at the same time, the optimal process conditions are glass fiber addition 20 wt %, melt temperature 185 °C, injection speed 80 mm/s, holding pressure 60 MPa, holding time 1 s and cooling time 15 s, and the corresponding mechanical properties are tensile strength 95.04 MPa, hardness 86.52 Shore D, impact strength 4.4408 J/cm2, bending strength 119.89 MPa. This study effectively enhances multiple qualities of PLA/GF composite.

Investigation of electrical resistance on coir fiber reinforced P-polyvinyl chloride composites

Current power electronics instruments like switches, cables, transformers and good electrical insulating materials are gaining consideration for their compact and environmental design. A plasticized polyvinyl chloride/coir fiber-based polymer composite, displaying good electrical resistance, is suggested to meet these objectives. Coir fiber is chosen as it gives powered strength and has fewer lumens than other fillers. Plasticized polyvinyl chloride is strengthened using coir fiber to create a insulating polymer composites. The design of experiments (DOE) method is used to create various samples with 2/4/6 wt.% of fiber content, 75/150/225 μm of fiber size and triethoxy (ethyl) silane (1)/sodium hydroxide (2)/potassium hydroxide (3) of chemical treatments using the response surface methodology through Box–Behnken design. Further, analysis of variance (ANOVA) is carried out using MINITAB statistical software to achieve optimum parameter levels through the regression equation. Additionally, the comparison of experimental and optimized findings leads to error analysis. A combination of 2 wt.% of coir fiber, 208.33 μm of coir fiber size and Triethoxy(ethyl) silane Treatment produces a composite with high resistance of 274.47 Giga-ohms, which is significant for good insulating purpose.

Multi-Geometry Parameters Optimization of Large-Area Roll-to-Roll Nanoimprint Module Using Grey Relational Analysis and Artificial Neural Network.

Micro- and nanofabrication on polymer substrate is integral to the development of flexible electronic devices, including touch screens, transparent conductive electrodes, organic photovoltaics, batteries, and wearable devices. The demand for flexible and wearable devices has spurred interest in large-area, high-throughput production methods. Roll-to-roll (R2R) nanoimprint lithography (NIL) is a promising technique for producing nano-scale patterns rapidly and continuously. However, bending in a large-scale R2R system can result in non-uniform force distribution during the imprinting process, which reduces pattern quality. This study investigates the effects of R2R imprinting module geometry parameters on force distribution via simulation, using grey relational analysis to identify optimal parameter levels and ANOVA to determine the percentage of each parameter contribution. The study also investigates the length and force ratio on a backup roller used for bending compensation. The simulation results and the artificial neural network (ANN) model enable the prediction of nip pressure and force distribution non-uniformity along the roller, allowing the selection of the optimal roller geometry and force ratio for minimal non-uniformity on a specific R2R system. An experiment was conducted to validate the simulation results and ANN model.

Ultrasonic welding of printed/molded sustainable polymer specimens with energy directors

Fused deposition modeling is preferred to fabricate the biodegradable poly lactic acid (PLA) parts, owing to its impeccable characteristics, such as, customization, waste minimization and scalability. However, limited printing volume constraint restricts the ubiquitous applications of this technique. The current experimental investigation is focused on the employment of ultrasonic welding technique to address the printing volume challenge. The effect of infill density, type of energy directors (triangular (TED), semicircular (SCED) and cross energy directors (CED)) and different levels of welding parameters have been investigated on the mechanical and thermal behavior of welded joints. Presence of rasters and gap between them plays a pivotal role in overall heat generation at weld interface. The joint performance of 3D printed parts has also been compared with injection molded specimens of same material. All printed/molded welded specimens with CED recorded higher tensile strength than equivalent specimens with TED and SCED. Moreover, These specimens also performed better than specimens without energy directors and recorded higher tensile strength, that is, 317, 73.5, 59.7 and 42% higher for injection molded (IM), 80%, 90% and 100% infill density (IF) specimens without energy directors at lower level of welding parameters (LLWP). These specimens also exhibited higher tensile strength at optimal levels of welding parameters. Although, at medium and higher levels of welding parameters, both printed/molded specimens with CED observed comparatively more degradation of joints due to higher concentration of energy at weld interface. The dynamic mechanical analysis (DMA), thermogravimetric analysis (TGA), derivative thermogravimetry (DTG) and field emission scanning electron microscopy (FESEM) analysis have been performed to substantiate the experimental results.

Ultrasonic welding of banana fiber based HDPE composites with energy directors

Joints are an integral element of any product and a source of failure under different loading environments. The current experimental investigation explores in detail the ultrasonic welding behavior of banana fiber/HDPE composites. The effect of fiber loading, type of energy directors and process parameters has been investigated on the mechanical and thermal behavior of the welded joints. The comparative assessment has been supported by the results of the dynamic mechanical analysis and the thermal conductivity of the fibers and HDPE. The mechanism of heat generation during welding process has been discussed. The TGA, DTG, DSC and FESEM analysis has been performed to substantiate the results. Composite adherends welded at optimum level of welding parameters with cross energy director profile depicted better load bearing characteristics. The short fibers also participated in the diffusion mechanism during welding. TGA and DTG results showed no significant effect on thermal stability of composites post welding.

Energy extraction from waste plastics and its optimization study for effective combustion and cleaner exhaust engaging with water and cetane improver: A response surface methodology approach

This study describes the extraction of energy from waste plastics via the pyrolysis process and its optimization for efficient combustion with cleaner exhaust using water and a cetane enhancer. Water emulsion with cetane improver in waste plastic oil (WPO) was first proposed in this study, and a response surface methodology (RSM) tool was used to optimise the individual parameters. Fourier Transform Infrared (FTIR) spectra were used to characterise the WPO, and ASTM standards were used to evaluate its properties. To enhance the fuel qualities, performance, and emission characteristics, water and Diethyl ether (DEE) were added to WPO. Since the WPO, water, and DEE had their pros and cons on overall engine performance and emissions as a whole, the optimal level of individual parameters was crucial in this field. The process parameters combinations were selected based on the Box-Behnken design, and the experiments were conducted in a stationary diesel engine. The experimental results indicate that the WPO yield rate during the pyrolysis process is 43.93%, and the C–H bonds have the maximum contribution to the WPO yield rate. The result of the optimization indicates that the proposed RSM model is highly robust, and the coefficient of determination is closer to one. The optimal concentrations of WPO, water, and DEE in conventional diesel fuel for efficient and environmentally friendly production are 15.001%, 12.166%, and 2.037%, respectively. The confirmation test indicates that the predicted and experimental values under optimal conditions are in good agreement, and the aggregate demand for fossil fuel has decreased by 28.2%.

Optimization Of process parameters for microbial cellulose production from rice-washing wastewater (NATA-DE-LERI) By Acetobacter Xylinum

Nata is a bacterial cellulose obtained from the fermentation of Acetobacter xylinum. It is often found in desserts as a health supplement because of its high fiber content. It is not only produced from coconut water, known as nata-de-coco but can also be produced from other sources, such as wastewater from rice washing, called nata-de-leri. This study aimed to optimize the parameters of bacterial cellulose (nata-de-leri) fermentation by statistical methods to improve production. First, the Placket-Burman Screening Design was applied to address the essential parameter components affecting nata-de-leri production. Eight factors are continuously checked, and unimportant elements are removed to obtain a smaller, more manageable set of characteristics. Second, a feedback surface method using Central Composite Design (CCD) was used to determine the optimal level of fermentation parameters using yield response. The results of this study show that sucrose concentration, CO(NH2)2 concentration, inoculum concentration and fermentation time are believed to be the main factors for nata production. The estimated optimal values nata-de-leri production when using 500 ml of rince washing wastewater are as follows: sucrose is 17.5 g; CO(NH2)2 is 12 g; volume of starter is 60 ml; fermentation time for 12 days. This results in a yield of 97.20%. From this study, the optimum yield in nata-de-leri is 20% larger than the baseline parameters