scholarly journals Optimization and Sensitivity Analysis of the Cutting Conditions in Rough, Semi-Finish and Finish Honing

Materials ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 75
Author(s):  
Irene Buj-Corral ◽  
Lourdes Rodero-de-Lamo ◽  
Lluís Marco-Almagro
Keyword(s):  
Sensitivity Analysis ◽  
Removal Rate ◽  
Desirability Function ◽  
Optimization Process ◽  
Process Variables ◽  
Importance Value ◽  
Internal Surfaces ◽  
Oil Flow ◽  
Hydraulic Cylinders ◽  
Proper Values

Honing processes are currently employed to obtain a cross-hatched pattern on the internal surfaces of cylinders that favors oil flow in combustion engines or hydraulic cylinders. The main aim of the present paper is to optimize the machining conditions in honing processes with respect to surface roughness, material removal rate and tool wear by means of the desirability function. Five process variables are considered: grain size, density, pressure, linear speed and tangential speed. Later, a sensitivity analysis is performed to determine the effect of the variation of the importance given to each response on the results of the optimization process. In the rough and semi-finish honing steps, variations of less than 5% of the importance value do not cause substantial changes in the optimization process. On the contrary, in the finish honing step, small changes in the importance values lead to modifications in the optimization process, mainly regarding pressure. Thus, the finish honing phase is more sensitive to changes in the optimization process than the rough and the semi-finish honing phases. The present paper will help users of honing machines to select proper values for the process variables.

Bioremediation Condition Optimization of Hydrocarbon in Soil Using Response Surface Methodology by Microbial Consortium KL9-1

2012 ◽  
Vol 518-523 ◽  
pp. 2073-2078 ◽  
Author(s):  
Qi You Liu ◽  
Yun Bo Zhang ◽  
Dong Feng Zhao ◽  
Chao Cheng Zhao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Microbial Consortium ◽  
Ph Value ◽  
Removal Rate ◽  
Desirability Function ◽  
Nitrogen And Phosphorus ◽  
Predictive Values ◽  
Independent Variables ◽  
Condition Optimization

A response surface methodology was applied to optimize the bioremediation condition of hydrocarbon in soil by microbial consortium KL9-1. A four-level Box-Behnken factorial design was employed to study the relationship of independent variables and dependent variable by applying pH value, inoculation amount of microbial consortium KL9-1, ratio of nitrogen and phosphorus (N/P ) and surfactant (SDBS) concentration as independent variables (factors) and crude oil removal rate as dependent variable (response). Then the statistically significant model was obtained and numerical optimization based on desirability function was carried out for pH 7.0, inoculation amount 50.0 mL, N/P 2: 1 and SDBS concentration 4.0 g, and the hydrocarbon removal rate reached as high as 52.58%. The predictive values showed good agreement with the experimental values under the optimization conditions, by standard variance <1.3%. It showed that the optimal result was reliable.

An Experimental Study of the Abrasive Water Jet Micro-Machining Process for Quartz Crystals

2012 ◽  
Vol 565 ◽  
pp. 339-344 ◽  
Author(s):  
H. Qi ◽  
J.M. Fan ◽  
Jun Wang
Keyword(s):  
Experimental Study ◽  
Removal Rate ◽  
Water Jet ◽  
Machining Process ◽  
Bottom Surface ◽  
Micro Machining ◽  
Abrasive Water Jet ◽  
Process Variables ◽  
Jet Impact ◽  
Micro Channels

An experimental study of the machining process for micro-channels on a brittle quartz crystal material by an abrasive slurry jet (ASJ) is presented. A statistical experiment design considering the major process variables is conducted, and the machined surface morphology and channelling performance are analysed to understand the micro-machining process. It is found that a good channel top edge appearance and bottom surface quality without wavy patterns can be achieved by employing relatively small particles at shallow jet impact angles. The major channel performance measures, i.e. material removal rate (MRR) and channel depth, are then discussed with respect to the process parameters. It shows that with a proper control of the process variables, the abrasive water jet (AWJ) technology can be used for the micro-machining of brittle materials with high quality and productivity.

scholarly journals Waste load allocation under uncertainty using game theory approach and simulation-optimization process

2020 ◽  
Vol 22 (4) ◽  
pp. 815-841 ◽  
Author(s):  
Behnam Andik ◽  
Mohammad Hossein Niksokhan
Keyword(s):  
Game Theory ◽  
Sensitivity Analysis ◽  
Simulation Optimization ◽  
Graph Model ◽  
Decision Makers ◽  
Optimization Process ◽  
Theory Approach ◽  
Waste Load Allocation ◽  
Waste Load ◽  
The Status

Abstract This article aims to present a new methodology for waste load allocation (WLA) in a riverine system considering the uncertainty and achieve the lowest amount of inequity index, cost, and fuzzy risk of standard violation. To find a surface of undominated solutions, a new modified PAWN method, initially designed for sensitivity analysis, was developed and coupled with a simulation-optimization process using multi-objective particle swarm optimization (MOPSO) algorithm, to consider the uncertainty of all affecting variables and parameters by using their probability distribution. The proposed methodology applied to Sefidrood River in the northern part of Iran. Graph model for conflict resolution (GMCR) as a subset of game theory was implemented to attain a compromise on WLA among the stakeholders of a river system's quality in Iran: Department of Environment, Municipal Waste Water, and Private Sector. Some undominated solutions were used in GMCR model and modeling the conflict among decision makers reveals that their preferences and the status quo do not lead to a solely stable equilibrium; thus the intervention of a ruler as arbitrator leads them to reach a compromise on a scenario that has a median FRVS and cost. Sensitivity analysis was done using the PAWN method to assess the sensitivity of three intended objectives to all variables and parameters.

Response Surface Analysis of EDMED Surfaces of AISI D2 Steel

2011 ◽  
Vol 264-265 ◽  
pp. 1960-1965
Author(s):  
Mohan Kumar Pradhan ◽  
Chandan Kumar Biswas
Keyword(s):  
Material Removal ◽  
Pulse Current ◽  
Removal Rate ◽  
Machining Parameters ◽  
Response Functions ◽  
Process Variables ◽  
Aisi D2 ◽  
Pulse On Time ◽  
D2 Steel ◽  
Machining Characteristics

In this study, the effects of the machining parameters in electrical-discharge machining (EDM) on the machining characteristics of AISI D2 steel using copper electrodes were investigated. The response functions considered material removal rate (MRR) and Surface Roughness (Ra),while machining variables are pulse current, pulse on time, pause time and gap voltage. A Response surface methodology was used to reduce the total number of experiments. Empirical models correlating process variables and their interactions with the said response functions have been established. The significant parameters that critically influenced the machining characteristics were examined, and the optimal combination levels of machining parameters for material removal rate, and surface roughness were determined. The models developed reveal that pulse current is the most significant machining parameter on the response functions followed by voltage and pulse off time for MRR. However for, for Ra also pulse current is most significant followed by pulse on time and discharge voltage the respectively. The model sufficiency is very satisfactory as the coefficientR2of is determination (R2) is found to these be greater than 98 %. These models can be used for selecting the values of process variables to get the desired

Through-process sensitivity analysis on the effect of process variables on strength in extruded Al–Mg–Si alloys

2012 ◽  
Vol 212 (1) ◽  
pp. 171-180 ◽  
Author(s):  
Snorre Kjørstad Fjeldbo ◽  
Yanjun Li ◽  
Knut Marthinsen ◽  
Trond Furu
Keyword(s):  
Sensitivity Analysis ◽  
Process Variables

Dimensional Instability Studies in Machining of Inconel 718 Nickel Based Superalloy as Applied to Aerogas Turbine Components

1999 ◽  
Vol 122 (1) ◽  
pp. 55-61 ◽  
Author(s):  
B. K. Subhas ◽  
R. Bhat ◽  
K. Ramachandra ◽  
H. K. Balakrishna
Keyword(s):  
Inconel 718 ◽  
Structural Integrity ◽  
Removal Rate ◽  
Research Work ◽  
Cutting Speed ◽  
Simultaneous Optimization ◽  
Depth Of Cut ◽  
Systematic Research ◽  
Process Variables ◽  
Dimensional Instability

Inconel 718 alloy is used extensively in aerogas turbines and this alloy is most difficult to machine and highly prone to dimensional instability after machining. Such detrimental phenomenon poses an enormous problem in engine assembly and affects structural integrity. This paper highlights the systematic research work undertaken to study the plastic deformation characteristics of Inconel 718, and the effect of process variables on machined surface, subsurface, and dimensional instability. Also illustrated is the technique developed for simultaneous optimization of several process variables such as cutting speed, feed, depth of cut, rake angle, and tool nose radius to control the residual stresses and dimensional instability within the acceptable tolerance band of the component. Prediction equations were developed for residual stress, dimensional instability, tool life, surface finish, and material removal rate. Predicted data were validated experimentally. This paper also presents the qualitative and quantitative data on dimensional instability with specific case studies of jet engine components, and it clearly illustrates the approach followed to develop a technique to control such detrimental effect. [S0742-4795(00)00901-7]

Film Flow Characteristics of Droplet Cooling in a Simplified Bearing Chamber

2013 ◽  
Author(s):  
E. D. Kay ◽  
H. Power ◽  
S. Hibberd
Keyword(s):  
Gas Turbines ◽  
Flow Characteristics ◽  
Temperature History ◽  
Design Parameters ◽  
Flow Conditions ◽  
Internal Surfaces ◽  
Aero Engine ◽  
Oil Flow ◽  
Oil Films ◽  
Engine Bearing

Droplet-cooled oil films develop on the internal surfaces of an aero-engine bearing chamber and are a primary mechanism in removing heat from the chamber as oil is continuously collected and externally cooled and recycled. Predicting the internal oil temperature and oil temperature history is an important thermal problem which becomes more apparent with potential increases in operating temperatures of gas turbines. Studying interacting oil flow and thermal processes within a simplified bearing chamber geometry provides useful information on the trends and characteristics which can arise under different applied flow conditions (e.g. mass flow rate of oil through the system) and insight to the effect chamber design parameters may have on oil degradation and cooling of chamber walls. Thin oil films develop on the walls of a bearing chamber as oil is injected or shed from bearings and impinges on the walls under a strong airflow set in motion by rotating components. Typically the film is also subject to a heat flux from the hot chamber walls and the droplets provide an important cooling effect through “heat-to-oil” mechanisms. We present a mathematical model for the depth-averaged flow and associated heat transfer by thin oil films on the walls of a simplified aero-engine bearing chamber. Cases corresponding to generic flow conditions relevant to an aero-engine bearing chamber are presented. Characteristics of the film and the efficacy of the flow regime to transfer heat from the chamber is explored through calculating residence times and time histories of oil particles as they make a transit of the internal system.

scholarly journals Reliability-Based Robust Design Optimization of Structures Considering Uncertainty in Design Variables

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shujuan Wang ◽  
Qiuyang Li ◽  
Gordon J. Savage
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Robust Design ◽  
Structural Reliability ◽  
Computational Cost ◽  
Optimization Process ◽  
Robust Design Optimization ◽  
Global Approximation ◽  
Design Variables ◽  
Uncertainty In Design

This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO) method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method.

Sensitivity analysis and optimization of EDM process parameters

2019 ◽  
Vol 43 (1) ◽  
pp. 13-25 ◽  
Author(s):  
Uvaraja Ragavendran ◽  
Ranjan Kumar Ghadai ◽  
Akash Kumar Bhoi ◽  
Manickam Ramachandran ◽  
Kanak Kalita
Keyword(s):  
Sensitivity Analysis ◽  
Process Parameters ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Statistical Significance ◽  
Empirical Models ◽  
Optimization Techniques ◽  
Pulse On Time ◽  
Pulse Off Time

Electrical discharge machining (EDM) is a broadly used nonconventional material removal process for the machining of conductive work material irrespective of their hardness. In this article, empirical models for material removal rate (MRR) and surface roughness (Ra) of the workpiece are developed based on the extensive experiments performed on a special steel (WP7V) workpiece using a copper electrode. To account for the various parameters, an experimental design based on response surface methodology (RSM) is conducted considering three different factors namely — current, pulse-on-time, and pulse-off-time, each having three different levels. Analysis of variance (ANOVA) is conducted to test the statistical significance of the proposed empirical models. It is essential to determine the relationship and significance of input–output variation. Thus a sensitivity analysis is conducted. The interaction effect of input variables is also studied. Two different state-of-art optimization techniques, namely genetic algorithm (GA) and particle swarm optimization (PSO), are applied to predict the optimal combination of process parameters. Finally, multi-objective optimization is also carried out to simultaneously maximize MRR while minimizing Ra.

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