The Use of Taguchi-Grey-Fuzzy to Optimize Performance Characteristics in Turning of AISI D2

Bobby Oedy Pramoedyo Soepangkat; A. Soesanti; Bambang Pramujati

doi:10.4028/www.scientific.net/AMM.315.211

Paper Titles

Life Cycle Assessment of Membrane System for Wastewater Treatment: A Review and Further Research
p.186

Dynamics Control of Pendulums Driven Spherical Robot
p.192

Selecting a CNC Machine Tool Using the Intuitionistic Fuzzy TOPSIS Approach for FMC
p.196

An Integrated Approach for Sustainable Supplier Selection Using Fuzzy Logic and Fuzzy AHP
p.206

The Use of Taguchi-Grey-Fuzzy to Optimize Performance Characteristics in Turning of AISI D2
p.211

Effect of Mesh Topologies on Wall Heat Transfer and Pressure Loss Prediction of a Blade Coolant Passage
p.216

Power Consumption Modeling for Indoor Environment Using Artificial Neural Network
p.221

Effect of Different Filler Materials in the Development of Bipolar Plate Composite for Polymer Electrolyte Membrane Fuel Cell (PEMFC)
p.226

Integrated Steering System Design for Bus Driver Drowsy Behavior Change
p.231

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 315The Use of Taguchi-Grey-Fuzzy to Optimize...

The Use of Taguchi-Grey-Fuzzy to Optimize Performance Characteristics in Turning of AISI D2

Abstract:

In this paper, the optimization of surface roughness, cutting force, feed force and tool life in a turning operation was investigated by using Taguchi method and fuzzy logic. The experiment were conducted under varying cutting speeds, feed rates, depths of cut and noses radius. An orthogonal array, the signal-to-noise (S/N) ratio, grey relational analysis, grey-fuzzy reasoning grade and analysis of variance were employed to the study the performance characteristics in the turning AISI D2. Experimental results have shown that machining performance characteristics in turning process can be improved effectively through the combination of Taguchi method and fuzzy logic.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 315)

Pages:

211-215

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.315.211

Citation:

Cite this paper

Online since:

April 2013

Authors:

Bobby Oedy Pramoedyo Soepangkat, A. Soesanti, Bambang Pramujati

Keywords:

AISI D2, Fuzzy Logic, Taguchi, Turning

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] E.A. Elsayed, A. Chen, Optimal levels of process parameters for products with multiple characteristics, Int. J. Prod. Res. 31 (1993) 1117–1132.

Google Scholar

[2] J.L. Lin, K.S. Wang, B.H. Yan, Y.S. Tarng, Optimization of the electrical discharge machining process based on the Taguchi method with fuzzy logics, J. Mater. Process. Technol. 102 (2000) 48–55.

DOI: 10.1016/s0924-0136(00)00438-6

Google Scholar

[3] J. Antony, Simultaneous optimisation of the multiple quality characteristics in manufacturing processes using Taguchi's quality loss function, Int. J. Adv. Manuf. Technol. 17 (2001) 134–138.

DOI: 10.1007/s001700170201

Google Scholar

[4] J. Deng, Introduction to grey system, J. Grey Syst. 1 (1989) 1–24.

Google Scholar

[5] J.L. Lin, C.L. Lin, The use of grey-fuzzy logic for the optimization of the manufacturing process, J. Mater. Process. Technol 160 (2005) 9 -14.

Google Scholar

[6] L. Zadeh, Fuzzy sets, Inform. Control 8 (1965) 338–353.

Google Scholar

[7] K.H. Hsia, H. Wu, A study on the data preprocessing in grey relation analysis, J. Chin. Grey Syst. Assoc. 1 (1) (1998) 47–53.

Google Scholar

[8] S.H. Hsiang Y.W. Lin, Optimization of the extrusion process for magnesium alloy sheets using the fuzzy-based Taguchi method, The Arabian J. for Sci. and Eng. 34 (2009) 175-184.

Google Scholar