Statistical Monitoring and Optimization of Electrochemical Machining using Shewhart Charts and Response Surface Methodology

The response surface methodology (RSM) and Shewhart control charts have been widely used in manufacturing to reduce variation, improve quality and optimize the output. This article proposes an application of individuals & moving range chart (I&MR) and RSM in electrochemical machining. The Shewhart-type I&MR control chart and RSM are combined together in an effective way to successfully guarantee the statistical control of the surface roughness (Ra) of the items produced by wire electrochemical turning, and meanwhile optimize Ra by exploring the optimal values of the machining parameters including applied voltage, wire feed rate, wire diameter, rotational speed and overlap distance. The conducted experiments reveal that the optimal values of the aforementioned factors are 23.67, 0.5, 0.2, 900 and 0.02, respectively. A second-order regression model is also developed to predict the output (Ra) at different combinations of the input parameters. The developed regression model can predict the output values with a determination coefficient (R2) of 96.9%. The proposed combined scheme of Shewhart charts and RSM can be employed in other manufacturing processes and even in different service sectors to efficiently enhance the performance and reduce the cost.

Download Full-text

Modeling of Radial Over Cut in Electrochemical Machining of Al-B4C MMC Using Response Surface Methodology

Journal for Manufacturing Science and Production ◽

10.1515/jmsp-2012-0026 ◽

2013 ◽

Vol 13 (1-2) ◽

pp. 31-36

Author(s):

Sadineni Rama Rao ◽

G. Padmanabhan

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Process Parameters ◽

Feed Rate ◽

Electrolyte Concentration ◽

Electrochemical Machining ◽

Machining Parameters ◽

Matrix Composites ◽

The Matrix ◽

Contour Plots

AbstractElectrochemical machining (ECM) is increasing its importance in machining of metal matrix composites (MMC) due to some specific advantages which can be exploited during machining operation. In ECM the quality of the surface produced is also depends on the workpiece physical and electrical properties along with the process parameters like voltage, feed rate, electrolyte concentration, type of electrolyte, current, gap between electrodes etc. Therefore, in the present work the percentage of reinforcement of the particulates in the matrix is considered one of the process parameters along with the applied voltage, electrode feed rate and electrolyte concentration. A mathematical prediction model of the radial over cut (ROC) was developed using response surface methodology (RSM). The effects of electrochemical machining parameters on the Radial over cut were evaluated. The contour plots were drawn to study the effect of various process parameters and their interaction. In this work the predicted values and measured values are quite close to each other. Therefore, the developed model can be effectively used to predict the radial over cut on electrochemical machining of Al-B4C composites.

Download Full-text

Optimum Selection of Machining Parameters in Electrochemical Machining using Response Surface Methodology

Journal for Manufacturing Science and Production ◽

10.1515/ijmsp.2008.9.1-2.12 ◽

2008 ◽

Vol 9 (1-2) ◽

pp. 12-18

Author(s):

T. Sekar, ◽

R. Marappan,

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Electrochemical Machining ◽

Machining Parameters ◽

Optimum Selection ◽

Selection Of

Download Full-text

Demulsification of a Water-in-crude Oil Emulsion with a Corn Oil BasedDemulsifier using the Response Surface Methodology: Modelling and Optimization

Recent Innovations in Chemical Engineering (Formerly Recent Patents on Chemical Engineering) ◽

10.2174/2405520414999210104154915 ◽

2021 ◽

Vol 14 ◽

Author(s):

Abed Saad ◽

Nour Abdurahman ◽

Rosli Mohd Yunus

Keyword(s):

Response Surface Methodology ◽

Crude Oil ◽

Water Content ◽

Response Surface ◽

Separation Efficiency ◽

Corn Oil ◽

Oil Emulsion ◽

Optimal Values ◽

Input Variables ◽

Oil Emulsions

: In this study, the Sany-glass test was used to evaluate the performance of a new surfactant prepared from corn oil as a demulsifier for crude oil emulsions. Central composite design (CCD), based on the response surface methodology (RSM), was used to investigate the effect of four variables, including demulsifier dosage, water content, temperature, and pH, on the efficiency of water removal from the emulsion. As well, analysis of variance was applied to examine the precision of the CCD mathematical model. The results indicate that demulsifier dose and emulsion pH are two significant parameters determining demulsification. The maximum separation efficiency of 96% was attained at an alkaline pH and with 3500 ppm demulsifier. According to the RSM analysis, the optimal values for the input variables are 40% water content, 3500 ppm demulsifier, 60 °C, and pH 8.

Download Full-text

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

Noise & Vibration Worldwide ◽

10.1177/0957456518763159 ◽

2018 ◽

Vol 49 (2) ◽

pp. 62-81 ◽

Cited By ~ 2

Author(s):

Shailendra Kumar ◽

Bhagat Singh

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Metal Removal ◽

Removal Rate ◽

Statistical Significance ◽

Depth Of Cut ◽

Machining Parameters ◽

Metal Removal Rate ◽

Chatter Index ◽

Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

Download Full-text

Modeling of the machining parameters in turning of Al-5052/TiC/SiC composites: a statistical modeling approach using grey relational analysis (GRA) and response surface methodology (RSM)

Multidiscipline Modeling in Materials and Structures ◽

10.1108/mmms-01-2021-0017 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Venkateshwar Reddy Pathapalli ◽

Meenakshi Reddy Reddigari ◽

Eswara Kumar Anna ◽

P. Srinivasa Rao ◽

D V. Ramana Reddy

Keyword(s):

Response Surface Methodology ◽

Response Surface ◽

Metal Matrix ◽

Machining Parameters ◽

Matrix Composites ◽

Content Type ◽

Relational Analysis ◽

Desirability Approach ◽

Grey Relational ◽

Grey Taguchi

PurposeMetal matrix composites (MMC) has been a section which gives an overview of composite materials and owing to those exceptional physical and mechanical properties, particulate-reinforced aluminum MMCs have gained increasing interest in particular engineering applications. Owing to the toughness and abrasive quality of reinforcement components such as silicon carbide (SiC) and titanium carbide (TiC), such materials are categorized as difficult materials for machining. The work aims to develop the model for evaluating the machinability of the materials via the response surface technique by machining three distinct types of hybrid MMCs.Design/methodology/approachThe combined effects of three machining parameters, namely “cutting speed” (s), “feed rate” (f) and “depth of cut” (d), together with three separate composite materials, were evaluated with the help of three performance characteristics, i.e. material removal rate (MRR), cutting force (CF) and surface roughness (SR). Response surface methodology and analysis of variance (ANOVA) both were initially used for analyzing the machining parameters results.FindingsThe contours were developed to observe the combined process parameters along with their correlations. The process variables were concurrently configured using grey relational analysis (GRA) and the composite desirability methodology. Both the GRA and composite desirability approach obtained similar results.Practical implicationsThe results obtained in the present paper will be helpful for decision-makers in manufacturing industries, who work on metal cutting area especially composites, to select the suitable solution by implementing the Grey Taguchi and modeling techniques.Originality/valueThe originality of this research is to identify the suitability of process parameters combination based on the obtained research results. The optimization of machining parameters in turning of hybrid metal matrix composites is carried out with two different methods such as Grey Taguchi and composite desirability approach.

Download Full-text