Taguchi-Based Optimization of Machining Parameter in Drilling Spheroidal Graphite Using Combined TOPSIS and AHP Method

  • Pruthviraj ChavanEmail author
  • Ajinkya Patil
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 949)


This paper envisages on enhancing the cutting environments for exterior irregularity (Ra), tool wear (Tw), and material removal rate (MRR) obtained in machining of Spheroidal graphite SG 500/7. Machining trials are accomplished at the VMC using Titanium Nitride (TiN), Titanium Aluminum Nitride (TiAlN), Titanium Carbo-Nitride (TiCN), and Zirconium Nitride (ZrN) covered carbide-cutting tools on SG 500/7 material. Cutting speed, tool material, and feed rate are preferred as the cutting factors. Taguchi L16 orthogonal array is used to design of a tryout. The weight of each criterion is required for calculating the weighted normalized matrix is determined by the analytic hierarchy process (AHP) method. The best cutting environments and their preferences depend on relative nearness value determined using technique for order preference by similarity to ideal solution (TOPSIS). This combined practice is a multi-objective optimization method which has been implemented to simultaneously minimize tool wear, exterior irregularity, and maximize material removal rate (MRR). The statistical outcome shows that significant improvement in the MRR and lowers the exterior irregularity and tool wear using the optimal combination of drilling process parameter obtained by this collective technique.


AHP Spheroidal graphite SG 500/7 Optimization TOPSIS Drilling 


  1. 1.
    Ramesh, V., Mohammed, H., Gopinath, T.: Taguchi method based optimization of drilling parameters of EN31 steel with PVD coated and uncoated drills. J. Manuf. Eng. 10, 112–116 (2015)Google Scholar
  2. 2.
    Pradeep Kumar, J., Packiaraj, P.: Effect of drilling parameters on surface roughness, tool wear, material removal rate and hole diameter error in the drilling of OHNS. Int. J. Adv. Eng. Res. Stud. 150–154 (2012). E-ISSN2249–8974Google Scholar
  3. 3.
    Balasubramaniyan, S., Thangiah, S.: Optimization of machining parameters in turning operation using combined TOPSIS and AHP method. Tech. Gaz. 22, 1475–1480 (2015). Scholar
  4. 4.
    Sreenivasulu, R., Srinivasa Rao, C.: Optimization of surface roughness, circularity deviation and selection of different aluminium alloys during drilling for automotive and aerospace industry. Independent J. Manag. Prod. 7, 413–430 (2015). Scholar
  5. 5.
    Bhanu Prakash, D., Krishnaiah, G.: Optimization of process parameters using AHP and VIKOR when turning AISI 1040 steel with coated tools. Int. J. Mech. Eng. Technol. 8, 241–248 (2017). ISSN Online: 0976-6359Google Scholar
  6. 6.
    Anand Babu, K., Venkataramaiah, P., Dileep, P.: AHP-DENG’S similarity based optimization of WEDM process parameters of Al/SiCp composite. Am. J. Mater. Sci. Technol. 6, 1–14 (2017). Scholar
  7. 7.
    Venkata Rao, R.: Decision Making in the Manufacturing Environment: Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods. Springer London Ltd, England, UK (2007)zbMATHGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.RITIslampurIndia

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