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The purpose of this research paper is to optimize the process parameters of selective laser sintering process, and the sintered parts of PA2200 prototypes are built with…
The purpose of this research paper is to optimize the process parameters of selective laser sintering process, and the sintered parts of PA2200 prototypes are built with minimum surface roughness within the range of 10-12 microns using the Taguchi design of experiments approach.
In this research paper, a 3D model is created using catia V5 and exported to rapid prototype machine, and the 3D model file was repaired by using Magics software to remove the facets and saved with file extension .stl (standard triangulation language).Taguchi design of experiments approach L9 orthogonal array was selected with three factors at three levels each and total nine experiments were conducted with the quality index lower-the-better signal-to-noise ratio to produced better quality prototypes by optimizing the process parameters like laser power, layer thickness and temperature and tested on surface tester for surface roughness. The experimental results of surface roughness were compared with Regression Analysis, S/N Ratio, Analysis of Mean and predicted model on sintered prototypes.
The experimental results obtained after testing on the surface tester compared with mathematical model for the quality index lower-the-better signal-noise ratio with optimal process parameters operating at Temperature at level 3, Layer thickness at level 3, and Laser power at level 3, regression analysis, and predictive model the output response variable surface roughness, is with in the range of 9-10.5 microns are all most same and from ANOM (Analysis of Mean), temperature at leve1, layer thickness at level 2, laser power at level 2 is 9 -9.6 microns.
The process parameters such as beam diameter and table speed were not considered on output response variable surface roughness in this research paper.
All the experiments were conducted and the parts are produced by using the material PA2200 in the powder from and sintered by Co2 laser by varying the process parameters with optimal settings to produce minimum surface roughness the out put from this paper is the influence of process parameters on surface roughness can be predicted at optimal settings with in less time and cost.
Diesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this…
Diesel engine can produce power more efficiently with lower exhaust emissions when operated at optimum input parameter settings. To achieve this goal, the purpose of this paper is to optimize the input parameters of diesel engine which will lead to optimum performance and exhaust emissions.
To achieve the goal of improving diesel engine performance and exhaust emissions, four input parameters were considered in the study. Five different levels of each input parameter were taken. Four response variables under no load, half load and full load conditions were recorded. Experiments were performed in random manner according to selected Taguchi L25 orthogonal array. The data were analyzed using grey relational analysis coupled with principal component analysis. Analysis of S/N ratio was performed to obtain the optimum combination of input parameters. The grey relational grade at optimum setting of the input parameters was obtained by regression analysis.
Results of the current research work give the optimum input parameter settings for no load, half load and full load conditions of diesel engine. Engine produces power more efficiently with low exhaust emissions when operated at these optimum settings.
In view of the compliance to the stringent air pollution norms of the nations and fast depleting fossil fuels, it is of the utmost importance to design and operate the engine in the optimum range of its input parameters so that it produces more power with low exhaust emissions. This paper aims at optimizing input parameters of diesel engine to improve performance and exhaust emissions. Results of the study presented in this paper are significantly useful for diesel engine-related researchers and professionals.
From the literature review, it appears that only few researchers have conducted studies pertaining to the optimization of the input parameters of diesel engine to improve performance or exhaust emissions. Although few studies related to the optimization of compression ratio, fuel injection timing, fuel injection pressure and air pressure have been reported, no work related to optimization of temperature and pressure of turbocharged air has been reported. Therefore, the main focus of the current research work is on optimizing the charge air temperature and pressure with respect to performance and exhaust emissions.
The aim of this paper is to circumvent the multi‐distribution effects and small sample constraints that may arise in unreplicated‐saturated fractional factorial designs…
The aim of this paper is to circumvent the multi‐distribution effects and small sample constraints that may arise in unreplicated‐saturated fractional factorial designs during construction blueprint screening.
A simple additive ranking scheme is devised based on converting the responses of interest to rank variables regardless of the nature of each response and the optimization direction that may be issued for each of them. Collapsing all ranked responses to a single rank response, appropriately referred to as “Super‐Ranking”, allows simultaneous optimization for all factor settings considered.
The Super‐Rank response is treated by Wilcoxon's rank sum test or Mann‐Whitney's test, aiming to establish possible factor‐setting differences by exploring their statistical significance. An optimal value for each response is predicted.
It is stressed, by example, that the model may handle simultaneously any number of quality characteristics. A case study based on a real geotechnical engineering project is used to illustrate how this method may be applied for optimizing simultaneously three quality characteristics that belong to each of the three possible cases, i.e. “nominal‐is‐best”, “larger‐is‐better”, and “smaller‐is‐better” respectively. For this reason, a screening set of experiments is performed on a professional CAD/CAE software package making use of an L8(27) orthogonal array where all seven factor columns are saturated by group excavation controls.
The statistical nature of this method is discussed in comparison with results produced by the desirability method for the case of exhausted degrees of freedom for the error. The case study itself is a unique paradigm from the area of construction operations management.