Papers by Keyword: Response Surface Method (RSM)

Abstract: The airborne vehicle would suffer from impact at landing, the impact load is one of the most important indexes for the security of vehicle. There was a little statistical test data of landing impact load, but it was not enough for researching on the relationship between landing condition and impact load. This paper describes the application of new technology for the prediction of landing impact under stochastic conditions. Based on the Finite Element method, Response Surface Model and Monte Carlo method, the statistical method for landing impact load under stochastic landing conditions was proposed. The results would provide the boundary conditions for the design of vehicle and provide the evaluative terms for landing security.

Abstract: Technology of Friction Stir Welding (FSW) is a relatively new technique for joining metal. In some cases on Aluminum joining, FSW gives better results compared with the arc welding processes, including the quality of welds and less distortion. The purpose of this study is to analyze the parameters effect of high speed tool rotation on micro Friction Stir Spot Welding (μFSSW) to the shear strength of welds. In this case, Aluminum material A1100, with thickness of 0.4 mm was used. Tool material of HSS material was shaped with micro grinding process. The spindle speed was fixed at 30000 rpm. Tool shoulder diameter was 3 mm, and a length of pin was 0.7 mm. The parameter variations used in this study were the variable of pin diameter (1.5 mm, 2.0 mm, and 2.5 mm), a variable of plunge speed (2 mm/min, 4 mm/min, 6 mm/min), and the variable of dwell time (2 seconds, 4 seconds, 6 seconds). Where the variation of these parameters will affect to the mechanical properties of welds (as response) was the shear strength. Response Surface Methods (RSM) was used to analyze μFSSW parameters with the shear strength of welds. From the result of experiment and analysis, it is shown that the important welding parameters in high speed μFSSW process are pin diameter and plunge speed.

Abstract: Aiming to the problems of low precision using traditional response surface method for structural reliability analysis with high nonlinear implicit performance function, Gaussian process regression (GPR) model reconstructing response surface was hybridized into the checking design point method for solving the reliability. Then, an iterative algorithm is presented to reduce the errors of GPR response surface self-adaptively. Thus, a new method namely Gaussian process based response surface for reliability analysis of suspension bridge was proposed. The research results show that the proposed method is feasible. The proposed method has advantages of high efficiency and excellent adaptability for reliability analysis of the complex structural such as suspension bridge.

Abstract: In order to improve the production process of corn starch and accelerate the separation of corn starch, flocculating activity of lactobacillus paracasei subsp.paracasei L1 isolated from natural fermentation of sweet potato acid liquor in corn liquid was optimized. The main influencing factors were determined by Plackett-Burman experimental design and the flocculating activity was optimized by response surface analysis method. The optimum culture conditions was: inoculum concentration 18%, lactose addition 0.2%, corn steeping time 0h, culture temperature 30°C, initial pH of the culture medium pH 6.5, culture time 36h, yeast extract addition 1%,concentration of corn thick liquid 1:3(w/v).The theoretical value of the flocculating activity was 0.1906 mg/ml and the verified value was 0.1854 mg/ml.

Abstract: Anisotropic Conductive Film (ACF) is essential material in LCM (Liquid Crystal Module) process. It is used in bonding process to make the driving circuit conductive. Because the price of TFT-LCD is much lower than before in recent years, the ACF cost has relatively higher ratio in manufacture cost. The conventional long bar ACF cutting unit is changed to short bar ACF cutting unit in new bonding technology. However, the new type machine was not optimized in process and mechanical design. Therefore, the failure rate of new ACF cutting process is much higher than the one of the conventional process. This wastes the material and rework cost is considerably large. How to make the manufacturing cost down effectively and promote the product quality is the concern issue to maintain competition capability for the product. Therefore, the Orthogonal Particle Swarm Optimization is used to analyze the optimal design problem. The ACF cutting yield rate is selected to be objective function for optimization. The quality characteristic function is used in Orthogonal Particle Swarm Optimization. The plasma clean speed, ACF peeling speed and ACF cutter spring setting are selected to study the effect of the yield rate. Results show that the proposed method can provide good solution to improve the ACF cutting process for TFTLCD.

Abstract: The overall heat dissipation coefficients of the sandwich panels with bio-inspired lightweight composite cores were analyzed by using the effective medium model, Then the effective heat dissipation objective function of the panel was constructed. The author took advantage of the Latin hypercube sampling method to sample the experimental data and then to calculate it. On this basis, the static and dynamic mechanical objective functions of the panel were obtained by using the response surface method. Finally, the overall objective function was constructed and solved to achieve the target of multi-functional optimization.

Abstract: This research applies Six Sigma approach in order to reduce defect by increasing the assembly process capability index (Cpk) of Integrated Circuit (IC) production process. This study applies five phases (DMAIC) of Six Sigma approach beginning with define (D), measure (M), analyze (A), improve (I) and control (C) phases, respectively. The response of the research identified in the define phase is the chipped width with Cpk of 0.66 determined from the measure phase. The half-factorial experiments are implemented in the analyze phase to find the significant factors which are water temperature, water pressure and feed rate. In improve phase, the additioanl expriments are performed according to the Box-Behnken design in order to determine the non-linear relation between the chipped width and all mentioned factors. The optimal setting of each factors are determined by applied the response surface optimizer. Under the optimal setting, the control charts are used in the control phase to monitor the chipped width. The resulted Cpk of the response is increased to 1.39 which is greater than the one-sided accpetable process capability of 1.25.

Abstract: The ANN-based optimization design for considering fatigue reliability requirements on structure was proposed in this paper. The ANN-based response surface method was used to analysis fatigue reliability of the structure. The fatigue reliability requirements were taken as constraints while the structural weight as the objective function, the ANN model was performed to simulate the relationship between the fatigue reliability and geometry dimension of the structure, the optimization result of the structure with a minimum weight was obtained, thus can make economic benefit meanwhile ensure the safety of the structure.

Abstract: An end mills wear experiment was designed to model and predict the end mills wear in micro turn-milling process. Based on the on-line visual measurement system, the tool wear was measured, then micro turn-milling tool wear regression models were established according to Response surface Method (RSM). The relationship between cutting parameters and tool wear was discussed in detail. The results indicate that the regression model can predict the value and regularity of end mills wear accurately, which can provide guidance on improving machining precision and quality in micro turn-milling process.

Abstract: Data-mining methods using hierarchical and non-hierarchical clustering are proposed that will help engineers determine appropriate end-milling conditions. We have constructed a system that uses clustering techniques and tool catalog data to support the determination of end-milling conditions for different types of difficult-to-cut materials such as austenitic stainless steel, Ni-base superalloy, and titanium alloy. Variable cluster analysis and the K-means method were used together to identify tool shape parameters that have a linear relationship with the end-milling conditions listed in the catalogs. The response surface method and significant tool shape parameters obtained by clustering were used to derive end-milling condition decision equations, which were used to determine the indicative end-milling conditions for each material. Comparison with the conditions recommended by toolmakers demonstrated that our proposed system can be used to determine the cutting speeds for various difficult-to-cut materials.