• Journal of Korean Society for Quality Management
• /
• v.7 no.2
• /
• pp.22-28
• /
• 1979

The problem considered in this paper is to select the vital factor effect to the product quality through the experimental design and analysis of response surface, so as to control the quality improvement of industrial product. In this time, even through the mathematical model is unknown it could be applicable to control the quality of industrial products and to determine optimum operating condition for many technical fields, particulary, for industrial manufacturing process. When a set of data is available from an experimental design, it is often of interest 1:0 fit polynominal repression model in independent variables (eg, time, temperature, pressure, etc) the optimize the response variable (eg. yield, strength etc). This paper proposes a method known to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model. A criterion can be applied determining to optimum operating conditions in manufacturing industry and improving the fit of response surface which may be used for prediction of responses and quality control of industrial products.

• Journal of the Korean Chemical Society
• /
• v.58 no.1
• /
• pp.80-84
• /
• 2014

The process of petroleum involves in a large amount of oily wastewater that contains high levels of chemical oxygen demand (COD) and toxic compounds. So they must be treated before their discharge into the receptor medium. In this paper, wet peroxide oxidation (WPO) was adopted to treat the oily wastewater. Central composite design, an experimental design for response surface methodology (RSM), was used to create a set of 31 experimental runs needed for optimizing of the operating conditions. Quadratic regression models with estimated coefficients were developed to describe the COD removals. The experimental results show that WPO could effectively reduce COD by 96.8% at the optimum conditions of temperature $290^{\circ}C$, $H_2O_2$ excess (HE) 0.8, the initial concentration of oily wastewater 3855 mg/L and reaction time 9 min. RSM could be effectively adopted to optimize the operating multifactors in complex WPO process.

• Proceedings of the KSME Conference
• /
• 2008.11b
• /
• pp.3044-3048
• /
• 2008

It is well known that Premixed Charge Compression Ignition (PCCI) diesel engines according to many technologies such a change in injection timing, multiple injection strategy, cooled EGR, intake charging and SCV have the potential to achieve homogeneous mixture in the cylinder which result in lower NOx and PM as well as performance improvements. This may generate merely the infinite number of experimental conditions. The use of Response Surface Methodology (RSM) technique can considerably pull down the number of experimental set and time demand. This paper presents the effects of both fuel injection and engine operation conditions on the combustion and emissions in the PCCI diesel engine system. The experimental results have revealed that a change in fuel injection timing and multiple injection strategy along with various operating conditions affect the combustion, emissions and BSFC characteristics in the PCCI engine.

• Journal of Environmental Health Sciences
• /
• v.35 no.6
• /
• pp.491-499
• /
• 2009

The removal of turbidity from $TiO_2$ wastewater by an electrocoagulation/flotation process was studied in a batch reactor. The response surface methodology (RSM) was applied to evaluate the simple and combined effects of the three main independent parameters, current, NaCl dosage and initial pH of the $TiO_2$ solution on the turbidity removal efficiency, and to optimize the operating conditions of the treatment process. The reaction of electrocoagulation/flotation was modeled by use of the Box-Behnken method, which was used for the fitting of a 2nd order response surface model. The application of RSM yielded the following regression equation, which is an empirical relationship between the turbidity removal efficiency of $TiO_2$ wastewater and test variables in uncoded unit: Turbidity removal (%)=69.76+59.76Current+11.98NaCl+4.67pH+5.00Current${\times}$pH-160.11$Current^2-0.34pH^2$. The optimum current, NaCl dosage and pH of the $TiO_2$ solution to reach maximum removal rates were found to be 0.186 A, 0.161 g/l and 7.599, respectively. This study clearly showed that response surface methodology was one of the most suitable method to optimize the operating conditions for maximizing the turbidity removal. Graphical response surface and contour plots were used to locate the optimum point.

• Journal of Korean Institute of Industrial Engineers
• /
• v.7 no.2
• /
• pp.55-59
• /
• 1981

An Application of Experimental Designs to Improve the quality of Industrial product : optimization Methodology of statistical model. The primary object of this paper is to aid scientists and Engineers, in applying response surface procedures to obtain operating conditions for many technical fields, particularly for industrial manufacturing processes. The problem considered in this paper is to select technically and scientifically some important factors affecting the quality of products through the experimental design and analysis of response surface. Even though the mathematical model is unknown these statistical analysis can be applicable to control the quality of industrial products and to determine optimum operating conditions for many technical fields, particularly, for industrial manufacturing processes. This paper proposes a method to obtain the optimum operating condition, and how to find the condition by using table of orthogonal array experiments, and optimization methodology of statistical model.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.25 no.6
• /
• pp.426-433
• /
• 2016

This paper investigates the effects of operating conditions of an air classifier mill (ACM) on the particle sizes of PVC and rice hull. Based on the Box-Behnken matrix, the pulverization experiments were performed considering three operating factors: the air flow rate, the classifier speed and the mill speed. The response surface methodology was applied to identify the effects of the operating factors on the particle size. Results show that the particle sizes are governed by the linear variations of the operating factors. As less air is supplied and the mill rotates more slowly, the powder of both PVC and rice hull becomes finer. Furthermore, the classifier speed has a significant effect on the PVC powder but almost no effect on the rice hull powder. Thus, it is found that strong interactions exist between the material characteristics of a particle and the operating conditions of the ACM.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.04a
• /
• pp.202-205
• /
• 2008

This paper presents an optimization of permanent magnet (PM) in a brushless dc (BLDC) motor using the response surface methodology (RSM). Size and angle of the PM are optimized to minimize the cogging torque, while reducing the magnitude of harmonic at a dominant frequency and maintaining the operating torque. A fitted RS model is constructed by verifying the high reliability of the total variation and the variation of estimated error. The optimized design is validated by carrying out the reanalysis and comparing to the initial model using the nonlinear transient finite element analysis.

• Journal of Korean Society for Quality Management
• /
• v.38 no.3
• /
• pp.413-424
• /
• 2010

Mixture experiments involve combining ingredients or components of a mixture and the response is a function of the proportions of ingredients which is independent of the total amount of a mixture. The purpose of the mixture experiments is to find the optimum blending at which responses such as the flavor and acceptability are maximized. We assume the quadratic or special cubic canonical polynomial model over the experimental region for a mixture since the current mixture is assumed to be located in the neighborhood of the optimal mixture. The cost of the mixture is proportional to the cost of the ingredients of the mixture and is the linear function of the proportions of the ingredients. In this paper, we propose mixture response surface methods to develop a mixture such that the cost is down more than ten percent as well as mean responses are as good as those from the current mixture. The proposed methods are illustrated with the well known the flare experimental data described by McLean and Anderson(1966).

• Journal of the Korean Solar Energy Society
• /
• v.23 no.3
• /
• pp.7-14
• /
• 2003

Absorption potential of desiccant solution significantly decreases after absorbing moisture from humid air, and a regeneration process requires a great amount of energy to recover absorption potential of desiccant solution. In an effort to develop an energy efficient regenerator, this study examines a regeneration process using hot air heated by solar radiation to recover absorption potential by evaporating moisture in liquid desiccant. More specifically, this study is aimed at finding the optimum operating condition of the regenerator by utilizing a well-established statistical tool, so-called response surface methodology(RSM), which may provide a functional relationship between independent and dependent variables. It is demonstrated that an optimization model to find the optimum operating condition can be obtained using the functional relationship between regeneration rate and affecting factors which is approximated on the basis experimental results.

• Journal of the Semiconductor & Display Technology
• /
• v.18 no.3
• /
• pp.115-121
• /
• 2019

Response surface methodology (RSM) is used to investigate the complex coupling effects of different operating parameters on silicon growth rate in planetary CVD reactor. Based on the computational fluid dynamics (CFD) model, an accurate RSM model is obtained to predict the growth rate with different parameters, including temperature, pressure, rotation speed of the wafer, and the mole fraction of dichlorosilane (DCS). Analysis of variance is used to estimate the contributions of process parameters and their interactions. Among the four operating parameters that have been studied, the influences of susceptor temperature and the operating pressure were the most significant factors that affect silicon growth rate, followed by the mole fraction of DCS. The influence of wafer rotation is the least. The validation tests show that the results of silicon deposition rate obtained from the regression model are in good agreement with those from CFD model and the maximum deviations is 2.15%.