A Study of Design Optimization Using Response Surface Analysis and Fabricaiton MEMS Probe Tip

In semiconductor manufacturing process, probe station that is testing equipment is important. Inspection step is for detecting defects on semiconductor before the packaging. Probe card is a part of probe station and contains probe tip that contacts to semiconductor. Through probe tip, it can inspect defects of semiconductor. In this paper, optimization method is used with response surface analysis to design MEMS type probe tip. And fabricating probe tip uses maskless lithography, electro-plating and lapping process.

Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

Optimization and Characterization of Cellulose Extraction from Grevillea robusta (Silky Oak) Leaves by Soda-Anthraquinone Pulping Using Response Surface Methodology

Response surface methodology (RSM) using the central composite design (CCD) was applied to examine the impact of soda-anthraquinone pulping conditions on Grevillea robusta fall leaves. The pulping factors studied were: NaOH charge 5% to 20% w/v, pulping time 30 to 180 minutes, and the anthraquinone charge 0.1 to 0.5% w/w based on the oven-dried leaves. The responses evaluated were the pulp yield, cellulose content, and the degree of delignification. Various regression models were used to evaluate the effects of varying the pulping conditions. The optimum conditions attained were;NaOH charge of 14.63%, 0.1% anthraquinone, and a pulping period of 154 minutes, corresponding to 20.68% pulp yield, 80.56% cellulose content, and 70.34% lignin removal. Analysis of variance (ANOVA), was used to determine the most important variables that improve the extraction process of cellulose. The experiment outcomes matched those predicted by the model (Predicted R2 = 0.9980, Adjusted R2 = 0.9994), demonstrating the adequacy of the model used. FTIR analysis confirmed the elimination of the non-cellulosic fiber constituents. The lignin and hemicellulose-related bands (around 1514 cm−1, 1604 cm−1, 1239 cm−1, and 1734 cm−1) decreased with chemical treatment, indicating effective cellulose extraction by the soda-anthraquinone method. Similar results were obtained by XRD, SEM and thermogravimetric analysis of the extracted cellulose. Therefore, Grevillea robusta fall leaves are suitable renewable, cost-effective, and environmentally friendly non-wood biomass for cellulose extraction.

Long-term deformation analysis of Shuibuya concrete face rockfill dam based on response surface method and improved genetic algorithm

Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained from laboratory triaxial tests often underestimate the deformation of high rockfill dams.Therefore, constitutive model parameters obtained by back analysis were used to calculate and predict the long-term deformation of rockfill dams.Instead of using artificial neural networks (ANNs), the response surface method (RSM) was employed to replace the finite element simulation used in the optimization iteration.Only 27 training samples were required for RSM, improving computational efficiency compared with ANN, which required 300 training samples.RSM can be used to describe the relationship between the constitutive model parameters and dam settlements.The inversion results of the Shuibuya concrete face rockfill dam (CFRD) show that the calculated settlements agree with the measured data, indicating the accuracy and efficiency of RSM.

Optimal design of butterfly-shaped linear ultrasonic motor using finite element method and response surface methodology

A new method for optimizing a butterfly-shaped linear ultrasonic motor was proposed to maximize its mechanical output. The finite element analysis technology and response surface methodology were combined together to realize the optimal design of the butterfly-shaped linear ultrasonic motor. First, the operation principle of the motor was introduced. Second, the finite element parameterized model of the stator of the motor was built using ANSYS parametric design language and some structure parameters of the stator were selected as design variables. Third, the sample points were selected in design variable space using latin hypercube Design. Through modal analysis and harmonic response analysis of the stator based on these sample points, the target responses were obtained. These sample points and response values were combined together to build a response surface model. Finally, the simplex method was used to find the optimal solution. The experimental results showed that many aspects of the design requirements of the butterfly-shaped linear ultrasonic motor have been fulfilled. The prototype motor fabricated based on the optimal design result exhibited considerably high dynamic performance, such as no-load speed of 873 ram/s, maximal thrust of 27.5 N, maximal efficiency of 43%, and thrust-weight ratio of 45.8.

Optimization on the Conversion of Bamboo Shoot Shell to Levulinic Acid with Environmentally Benign Acidic Ionic Liquid and Response Surface Analysis

Levulinic acid（LA） has been identified as a promising green,biomass derived platform chemical.Response surface analysis（RSA） with a four-factor-five-level central composite design（CCD） was applied to optimize the hydrolysis conditions for the conversion of bamboo（Phyllostachys Praecox f.preveynalis） shoot shell（BSS） to LA catalyzed with ionic liquid [C4mim]HSO4.The effects of four main reaction parameters including temperature,time,C[C4mim]HSO4（initial [C4mim]HSO4 concentration） and XBSS（initial BSS intake） on the hydrolysis reaction for yield of LA were analyzed.A quadratic equation model for yield of LA was established and fitted to the data with an R2 of 0.9868,and effects of main factors and their corresponding relationships were obtained with RSA.Model validation and results of CCD showed good correspondence between actual and predicted values.The analysis of variance（ANOVA） of the results indicated that the yield of LA in the range studied was significantly（P＆lt;0.05） affected by the four factors.The optimized reaction conditions were as follows：temperature of 145 ℃,time of 103.8 min,C[C4mim]HSO4 of 0.9 mol.L-1 and XBSS of 2.04%（by mass）,respectively.A high yield [（71±0.41）%（by mol）,triplicate experiment] was obtained at the optimum conditions of temperature of 145 ℃,time of 104 min,C[C4mim]HSO4 of 0.9 mol.L-1 and XBSS of 2%（by mass）,which obtained from the real experiments,concurred with the model prediction [73.8%（by mol） based on available C6 sugars in BSS or 17.9%（by mass） based on the mass of BSS],indicating that the model was adequate for the hydrolysis process.

Deformation prediction and analysis of underground mining during stacking of dry gangue in open-pit based on response surface methodology

Deformation prediction and the analysis of underground goaf are important to the safe and efficient recovery of residual ore when shifting from open-pit mining to underground mining.To address the comprehensive problem of stability in the double mined-out area of the Tong-Lv-Shan(TLS)mine,which employed the dry stacked gangue technology,this paper applies the function fitting theory and a regression analysis method to screen the sensitive interval of four influencing factors based on single-factor experiments and the numerical simulation software FLAC3D.The influencing factors of the TLS mine consist of the column thickness(d),gob area span(D),boundary pillar thickness(h)and height of tailing gangue(H).The fitting degree between the four factors and the displacement of the gob roof(W)is reasonable because the correlation coefficient(R2)is greater than0.9701.After establishing29groups that satisfy the principles of Box-Behnken design(BBD),the dry gangue tailings process was re-simulated for the selected sensitive interval.Using a combination of an analysis of variance(ANOVA),regression equations and a significance analysis,the prediction results of the response surface methodology(RSM)show that the significant degree for the stability of the mined-out area for the factors satisfies the relationship of h>D>d>H.The importance of the four factors cannot be disregarded in a comparison of the prediction results of the engineering test stope in the TLS mine.By comparing the data of monitoring points and function prediction,the proposed method has shown promising results,and the prediction accuracy of RSM model is acceptable.The relative errors of the two test stopes are1.67%and3.85%,respectively,which yield satisfactory reliability and reference values for the mines.

Application of response surface methodology and central composite rotatable design for modeling the influence of some operating variables of the lab scale thickener performance

This study discussed the application of response surface methodology(RSM)and central composite rotatable design(CCRD)for modeling and optimization of the influence of some operating variables on the performance of a lab scale thickener for dewatering of tailing in the flotation circuit.Four thickener operating variables,namely feed flowrate,solid percent,flocculant dosage and feedwell height were changed during the tests based on CCRD.The ranges of values of the thickener variables used in the design were a feed flowrate of 9–21 L/min,solid percent of 8%–20%,flocculant dosage of 1.25–4.25 g/t and feedwell height of 16–26 cm.A total of 30 thickening tests were conducted using lab scale thickener on flotation tailing obtained from the Sarcheshmeh copper mine,Iran.The underflow solid percent and bed height were expressed as functions of four operating parameters of thickener.Predicted values were found to be in good agreement with experimental values(R2values of 0.992 and 0.997 for underflow solid percent and bed height,respectively).This study has shown that the RSM and CCRD could effciently be applied for the modeling of thickener for dewatering of flotation tailing.

Optimization of Fermentation Medium for Producing α-Hydroxyphenylacetic Acid by Using Plackett-Burman Design and Response Surface Methodology

Plackett-Burman design and response surface methodology were applied in order to optimize the fermentation medium of (R)-α-hydroxyphenylacetic acid ((R)-HPA) producing Bacillus sp. HZG-19. The factors playing important roles in the production of (R)-HPA were selected based on Plackett-Burman design. The path of steepest ascent was undertaken to optimize said fermentation medium. Finally, the optimal levels of the factors with the greatest change in regard to product yield were further optimized using Box-Behnken and response surface analysis. The optimal conditions were found to be as follows: casein peptone 30.49 (g × L-1), glycerol 14.09 (g × L-1), KH2PO4 0.1345 (g × L-1), K2HPO4 0.01 (g × L-1), CaCl2 0.1 (g × L-1), MnSO4 0.01 (g × L-1). Under the optimal conditions described above, the yield of (R)-HPA reached 63.30%, which indicated an increase of 14.9%, as compared to the yield obtained before optimization.

Optimization for Microbial Degumming of Ramie with Bacillus subtilis DZ_(5) in Submerged Fermentation by Orthogonal Array Design and Response Surface Methodology

As a kind of natural fiber,ramie fiber has distinctive advantages in textile application,but the application is limited due to the traditional degumming mode.Compared with the traditional degumming process,the microbial degumming process has many advantages.To obtain the optimal conditions for degumming ramie with Bacillus subtilis DZ_(5)(BS DZ_(5)),a combined statistical approach of orthogonal array design(OAD)and response surface methodology(RSM)was used.The influences of initial pH of the bacteria medium,culture temperature,shaking speed,degumming time and inoculum size on submerged fermentation degumming were evaluated by using fractional factorial design.The main factors in the analysis were culture temperature,shaking speed and initial pH.The residual gum mass fraction was used as the optimization index,and the optimal conditions for degumming were determined by central composite design and RSM.Thus with only a limited number of experiments,an optimal ramie microbial degumming condition was found as the culture temperature of 40℃,the initial pH in the culture medium of 8.5,the shaking speed of 205 r/min,the degumming time of 96 h and the inoculum size of 5%.After microbial degumming of ramie under the optimal conditions,there was only 10.6%residual gum by mass in the fiber.In addition,the effective degumming of BS DZ_(5)was also confirmed by a scanning electron microscope(SEM).

EFFECTS OF REACTION AND PROCESSING PARAMETERS ON ETHYLENE POLYMERIZATION USING DIFFERENT ZIEGLER-NATTA CATALYSTS:EMPLOYMENT OF TAGUCHI EXPERIMENTAL DESIGN AND RESPONSE SURFACE METHOD

Different Ziegler-Natta catalysts were employed to polymerize ethylene. To investigate the influences of reaction parameters, namely Al/Ti molar ratio, hydrogen and processing parameters, i.e. ethylene pressure and temperature, a Taguchi experimental design was worked out. An L27 orthogonal array was chosen to take the above-mentioned parameters and relevant interactions into account. Response surface method was the tool used to analyze the experimental design results. Al/Ti, ethylene pressure and temperature were selected as experimental design factors, and catalyst activity and polymerization yield were the response parameters. Increasing pressure, due to an increment in monomer accessibility, and rising Al/Ti, because of higher reduction in the catalysts, cause an increase in both polymerization yield and catalyst activity. Nonetheless, a higher temperature, thanks to reducing ethylene solubility in the slurry medium and partially catalyst destruction, lead to a reduction in both response parameters. A synergistic effect was also observed between temperature and pressure. All catalyst activities will reduce in the presence of hydrogen. Molecular weight also shows a decline in the presence of hydrogen as a transfer agent. However, the polydispersity index remains approximately intact. Using SEM, various morphologies, owing to different catalyst morphologies, were seen for the polyethylene.

Development of six sigma concurrent parameter and tolerance design method based on response surface methodology

Using Response Surface Methodology (RSM), an optimizing model of concurrent parameter and tolerance design is proposed where response mean equals its target in the target being best. The optimizing function of the model is the sum of quality loss and tolerance cost subjecting to the variance confidence region of which six sigma capability can be assured. An example is illustrated in order to compare the differences between the developed model and the parameter design with minimum variance. The results show that the proposed method not only achieves robustness, but also greatly reduces cost. The objectives of high quality and low cost of product and process can be achieved simultaneously by the application of six sigma concurrent parameter and tolerance design.

Design optimization of transonic compressor stage using CFD and response surface model

In order to shorten the design period, the paper describes a new optimization strategy for computationally expensive design optimization of turbomachinery, combined with design of experiment (DOE), response surface models (RSM), genetic algorithm (GA) and a 3-D Navier-Stokes solver(Numeca Fine). Data points for response evaluations were selected by improved distributed hypercube sampling (IHS) and the 3-D Navier-Stokes analysis was carried out at these sample points. The quadratic response surface model was used to approximate the relationships between the design variables and flow parameters. To maximize the adiabatic efficiency, the genetic algorithm was applied to the response surface model to perform global optimization to achieve the optimum design of NASA Stage 35. An optimum leading edge line was found, which produced a new 3-D rotor blade combined with sweep and lean, and a new stator one with skew. It is concluded that the proposed strategy can provide a reliable method for design optimization of turbomachinery blades at reasonable computing cost.

Prediction and optimization of process parameter of friction stir welded AA5083-H111 aluminum alloy using response surface methodology

A systematic approach was presented to develop the empirical model for predicting the ultimate tensile strength of AA5083-H111 aluminum alloy which is widely used in ship building industry by incorporating friction stir welding(FSW) process parameters such as tool rotational speed,welding speed,and axial force.FSW was carried out considering three-factor five-level central composite rotatable design with full replications technique.Response surface methodology(RSM) was applied to developing linear regression model for establishing the relationship between the FSW process parameters and ultimate tensile strength.Analysis of variance(ANOVA) technique was used to check the adequacy of the developed model.The FSW process parameters were also optimized using response surface methodology(RSM) to maximize the ultimate tensile strength.The joint welded at a tool rotational speed of 1 000 r/min,a welding speed of 69 mm/min and an axial force of 1.33 t exhibits higher tensile strength compared with other joints.

Formulation optimization of scutellarin-loaded HP-β-CD/chitosan nanoparticles using response surface methodology with Box–Behnken design

The aim of this paper is to investigate and optimize the preparation of scutellarin(SCU)-loaded HP-β-CD/chitosan(CS) nanoparticles(CD/CS-SCU-NPs). CD/CS-SCU-NPs were prepared by ionic cross-linking method and the process and formulation variables were optimized using response surface methodology(RSM) with a three-level, three factor Box–Behnken design(BBD).The independent variables were the added amounts of CS, sodium tripolyphosphate(TPP)and Pluronic F-68 during the preparation. Dependent variables(responses) were particle size and entrapment efficiency. Mathematical equations and respond surface plots were used to correlate independent and dependent variables.The preparation process and formulation variables were optimized to achieve minimum particle size and maximum entrapment efficiency by calculating the overall desirability value(OD). The optimized NP formulation was characterized for particle size, PDI, zeta potential, entrapment efficiency and in vitro drug release.According to the results, an optimized CD/CS-SCU-NP formulation was prepared. Results for particle size, PDI, zeta potential and entrapment efficiency were found to be around 200 nm,0.5, 25 mV, and 70% respectively. For in vitro study, the release of SCU from the NPs exhibited a biphasic release and was in accordance with Higuchi equation. The optimized preparation was simple with the probability for industrialization. The combination use of RSM, BBD and overall desirability values could provide a promising application for incorporating CD into CS nanoparticles as drug delivery carrier and help develop lab-scale procedures.

General Response Surface Reliability Analysis for Fuzzy-Random Uncertainty both in Basic Variables and in State Variables

A general response surface（RS） method is presented for reliability analysis of complex structure/mechanism with fuzzy-random uncertainty both in basic variables and in failure state variables. On the basis of equivalent transformation from fuzzy basic variable to random basic variable, the fuzziness and randomness in the basic variables are considered simultaneously in the presented general RS method. Once the fuzzy basic variables are transformed into the random basic variables, the conventional RS method is employed to establish the general RS for the complex structure/mechanism with implicit limit state equation by finite element numerical simulation. Furthermore, the general failure probability is defined according to the probability formula for fuzzy-random event by taking the fuzziness and randomness in the failure-safety state into consideration, and an appropriate fuzzy operator is adopted to calculate the general failure probability for the complex structure/mechanism with multiple implicit failure modes. Finally, a general reliability analysis of an elastic linkage mechanism is introduced to illustrate the present method.

Comparative Study on Response Surfaces for Reliability Analysis of Spatially Variable Soil Slope

This paper focuses on the performance of the second-order polynomial-based response surfaces on the reliability of spatially variable soil slope. A single response surface constructed to approximate the slope system failure performance function G（X） （called single RS） and multiple response surfaces constructed on finite number of slip surfaces （called multiple RS） are developed, respectively. Single RS and multiple RS are applied to evaluate the system failure probability pf for a cohesive soil slope together with Monte Carlo simulation （MCS）. It is found thatpe calculated by single RS deviates significantly from that obtained by searching a large number of potential slip surfaces, and this deviation becomes insignificant with the decrease of the number of random variables or the increase of the scale of fluctuation. In other words, single RS cannot approximate G（X） with reasonable accuracy. The value of pc from multiple response surfaces fits well with that obtained by searching a large number of potential slip surfaces. That is, multiple RS can estimate G（X） with reasonable accuracy.

Comparison of Response Surface Methodology and Artificial Neural Network in Predicting the Microwave-Assisted Extraction Procedure to Determine Zinc in Fish Muscles

In this paper, the estimation capacities of the response surface methodology (RSM) and artificial neural network (ANN), in a microwave-assisted extraction method to determine the amount of zinc in fish samples were investigated. The experiments were carried out based on a 3-level, 4-variable Box–Behnken design. The amount of zinc was considered as a function of four independent variables, namely irradiation power, irradiation time, nitric acid concentration, and temperature. The RSM results showed the quadratic polynomial model can be used to describe the relationship between the various factors and the response. Using the ANN analysis, the optimal configuration of the ANN model was found to be 4-10-1. After predicting the model using RSM and ANN, two methodologies were then compared for their predictive capabilities. The results showed that the ANN model is much more accurate in prediction as compared to the RSM.

Optimization of medium components using response surface methodology (RSM) for mycelium biomass and exopolysaccharide production by <i>Lentinus squarrosulus</i>

The interaction between sucrose, yeast extract and initial pH was investigated to optimize critical medium components for mycelium biomass and production of exopolysaccharide (EPS) of Lentinus squarrosulus using Response Surface Methodology (RSM). A central composite design (CCD) was applied and a polynomial regression model with quadratic term was used to analyse the experimental data using analysis of variance (ANOVA). ANOVA analysis showed that the model was very significant (p Lentinus squarrosulus are as follows: sucrose concentration 114.61 g/L, yeast extract 1.62 g/L and initial pH of 5.81;sucrose concentration 115.8 g/L, yeast extract of 3.39 g/L and initial pH of 6.44 respectively.

Reliability analysis for aeroengine turbine disc fatigue life with multiple random variables based on distributed collaborative response surface method

The fatigue life of aeroengine turbine disc presents great dispersion due to the randomness of the basic variables,such as applied load,working temperature,geometrical dimensions and material properties.In order to ameliorate reliability analysis efficiency without loss of reliability,the distributed collaborative response surface method(DCRSM) was proposed,and its basic theories were established in this work.Considering the failure dependency among the failure modes,the distributed response surface was constructed to establish the relationship between the failure mode and the relevant random variables.Then,the failure modes were considered as the random variables of system response to obtain the distributed collaborative response surface model based on structure failure criterion.Finally,the given turbine disc structure was employed to illustrate the feasibility and validity of the presented method.Through the comparison of DCRSM,Monte Carlo method(MCM) and the traditional response surface method(RSM),the results show that the computational precision for DCRSM is more consistent with MCM than RSM,while DCRSM needs far less computing time than MCM and RSM under the same simulation conditions.Thus,DCRSM is demonstrated to be a feasible and valid approach for improving the computational efficiency of reliability analysis for aeroengine turbine disc fatigue life with multiple random variables,and has great potential value for the complicated mechanical structure with multi-component and multi-failure mode.