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Multidimensional optimization of electrical discharge machining for high speed steel (AISI M2) using Taguchi-fuzzy approach

Author

Listed:
  • Alaa M. Ubaid

    (University of Sharjah)

  • Shukry H. Aghdeab

    (University of Technology)

  • Ahmed Ghazi Abdulameer

    (University of Technology)

  • Laith Abdullah Al-Juboori

    (Higher Colleges of Technology)

  • Fikri T. Dweiri

    (University of Sharjah)

Abstract

Electrical discharge machining (EDM) is one of the non-traditional machining processes characterized by its ability to machine parts that electrically conductive but difficult to be machined in the traditional machining processes due to its high hardness, complex geometry, and low tolerances. To minimize EDM process cost, ensure the highest process efficiency and achieve the highest product quality, the EDM process needs to be optimized. The aim of this research is optimizing EDM process parameters for machining HSS (AISI M2) material by use of copper electrode and brass electrode considering conflicting performance measures in one and multidimensional levels. The performance measures used in the current research are material removal rate (MRR) and electrode wear rate (EWR), while machining parameters that will subject to optimization process are current (A), pulse on (TON), and pulse off (TOFF). During optimization stages, the Taguchi method, signal to noise ratio (S/N ratio), and analysis of variances (ANOVA) will be used in the first stage to find the optimal machining parameters for each performance measure and for each electrode material. In the second stage, multidimensional optimization approach encompasses using the calculated S/N ratio as input from the first stage, fuzzy logic and ANOVA to calculate multi response performance index which will be used to select optimal machining parameters for each electrode and then select the best electrode and optimal machining parameters for machining AISI M2 steel. In one-dimensional optimization, for brass electrode, to maximize MRR value, the optimal machining parameters combination is A3TON1TOFF3 and to minimize EWR value, the optimal machining parameters combination is A1TON1TOFF2. For copper electrode, to maximize MRR value, the optimal machining parameters combination is A1TON1TOFF3 and to minimize EWR value, the optimal machining parameters combination is A1TON3TOFF1. In multidimensional optimization, for the copper electrode, the optimal machining parameters combination was A1TON1TOFF3 and for the brass electrode, the optimal machining parameters combination is A3TON1TOFF3. It could be concluded that EDM machining of HSS (AISI M2) by using the copper electrode will give the best results and the optimal machining parameters combination is A1TON1TOFF3. Yet, further research needs to be conducted to study these results and analyze machining process effectiveness in terms of cost and process sustainability, i.e. environmental impact. This research has both theoretical and practical implications.

Suggested Citation

  • Alaa M. Ubaid & Shukry H. Aghdeab & Ahmed Ghazi Abdulameer & Laith Abdullah Al-Juboori & Fikri T. Dweiri, 2020. "Multidimensional optimization of electrical discharge machining for high speed steel (AISI M2) using Taguchi-fuzzy approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1021-1045, December.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:6:d:10.1007_s13198-020-00951-6
    DOI: 10.1007/s13198-020-00951-6
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    References listed on IDEAS

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    1. Mary M. Crossan & Marina Apaydin, 2010. "A Multi‐Dimensional Framework of Organizational Innovation: A Systematic Review of the Literature," Journal of Management Studies, Wiley Blackwell, vol. 47(6), pages 1154-1191, September.
    2. Mohan Kumar Pradhan, 2018. "Optimisation of EDM process for MRR, TWR and radial overcut of D2 steel: a hybrid RSM-GRA and entropy weight-based TOPSIS approach," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 29(3), pages 273-302.
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    More about this item

    Keywords

    EDM; Optimization; Fuzzy logic; Taguchi; ANOVA; AISI M2;
    All these keywords.

    JEL classification:

    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics

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