PCA based hybrid Taguchi philosophy for optimization of multiple responses in EDM

Mohanty, Sthitapragyan; Mahapatra, Siba Sankar; Mohanty, Ramesh Chandra

doi:10.1007/s12046-018-0982-z

Cited by 7 publications

(3 citation statements)

References 21 publications

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“…Based on the analysis of the S/N ratio calculation, a larger S/N ratio results in accordance with the ideal performance characteristics regardless of the category of performance characteristics. This means that the largest value indicates the best combination to achieve optimal results (Mohanty et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Rachman¹,

Purnomo²,

Fajardini³

et al. 2021

JTAM

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This research aims to obtain optimal value for the surface roughness of the material AISI P20 on the Electrical Discharge Machining (EDM) Sinking process. In the present research, the Taguchi method is used to investigate the signiﬁcant influence of process variables on the machining performance and determine the combination of process variables on the EDM process. Orthogonal array L18 (21 × 33) based on the Taguchi method is chosen for the design of experiment. The experiment is replicated twice to finding out the influence of four process variables such as type of electrode, voltage gap, on-time, and off-time on the response performance. Machining performance is evaluated by surface roughness as a response variable that had quality characteristics, smaller is better. These experimental data were analyzed using the Signal-to-noise ratio and Analysis of Variance. The analysis results show that the surface roughness is influenced by the type of electrode and on time. Combination of process variables to obtain optimal surface roughness are using graphite electrodes, and setting values of gap voltage 40 volt, on-time 250 μs, and off-time 20 μs. This combination of process variables can be applied to the manufacturing process using EDM sinking in order to produce a good quality product that determined based on the surface roughness value.

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Section: Discussionmentioning

confidence: 99%

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Rachman¹,

Purnomo²,

Fajardini³

et al. 2021

JTAM

View full text Add to dashboard Cite

show abstract

“…Later, the Multi-Performance Index (MPI) was calculated using Eq. ( 10) and tabulated in Table 7 [41]. MPI = 0.342Z 1 + 0.262Z 2 + 0.253Z 3 + 0.1Z 4 + 0.043Z 5 .…”

Section: Calculation Of Mpi and Cqlmentioning

confidence: 99%

Archive of Mechanical Engineering

Jogendra

Verma

Mondal

2020

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This paper explores the parametric appraisal and machining performance optimization during drilling of polymer nanocomposites reinforced by graphene oxide/carbon fiber. The consequences of drilling parameters like cutting velocity, feed, and weight % of graphene oxide on machining responses, namely surface roughness, thrust force, torque, delamination (In/Out) has been investigated. An integrated approach of a Combined Quality Loss concept, Weighted Principal Component Analysis (WPCA), and Taguchi theory is proposed for the evaluation of drilling efficiency. Response surface methodology was employed for drilling of samples using the titanium aluminum nitride tool. WPCA is used for aggregation of multi-response into a single objective function. Analysis of variance reveals that cutting velocity is the most influential factor trailed by feed and weight % of graphene oxide. The proposed approach predicts the outcomes of the developed model for an optimal set of parameters. It has been validated by a confirmatory test, which shows a satisfactory agreement with the actual data. The lower feed plays a vital role in surface finishing. At lower feed, the development of the defect and cracks are found less with an improved surface finish. The proposed module demonstrates the feasibility of controlling quality and productivity factors.

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“…One can easily get the overall idea about the system model, reason for changes in the outputs and establish the cause and effect relationship. In recent years, different statistical methods such as factorial design, different regression techniques, analysis of variance (ANOVA), response surface methodology (RSM) and Taguchi methodology are widely used for analysis and optimization of process parameters [35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Experimentation modelling and optimization of electrohydrodynamic inkjet microfabrication approach: a Taguchi regression analysis

et al. 2019

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Electrohydrodynamic (EHD) inkjet is a modern non-contact printing approach, which uses a direct writing technology of functional materials to achieve micro/nanoscale of printing resolution. As an alternative to conventional inkjet technology, the goal of the EHD inkjet printing is to generate uniformly minimized droplets on a substrate. In this study, the effects of applied voltage, standoff height and ink flow rate on droplet diameter formation in EHD inkjet printing process were analysed using Taguchi methodology and regression analysis. Several experiments were carried out using an L 27 (3 13) orthogonal array. Based on signal to noise (S/N) ratio and mean response, optimal droplet diameter was achieved. The analysis of variance (ANOVA) was used to find the significance and percentage of contribution of each input parameter along with their interaction on the output droplet diameter. Analysis of the results revealed that the ink flow rate was the dominant factor that affected the droplet diameter mostly. The effect of the applied voltage is significant until regular ejection starts. It helps reduce droplet diameter more than five times compared with its initial droplet diameter in the absence of the electric field. A confirmation test was carried out with a 90% confidence level to illustrate the effectiveness of the Taguchi optimization method. Both linear and quadratic regression analysis were applied to predict the output droplet diameter. The predicted result from the model and actual test results are very close to each other, justifying the significance of the models. Keywords. Electrohydrodynamic (EHD) inkjet printing; design of experiments (DOE); Taguchi method; analysis of variance (ANOVA).

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PCA based hybrid Taguchi philosophy for optimization of multiple responses in EDM

Cited by 7 publications

References 21 publications

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Archive of Mechanical Engineering

Experimentation modelling and optimization of electrohydrodynamic inkjet microfabrication approach: a Taguchi regression analysis

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