A Fuzzy Analytic Hierarchical Method to Reduce Imprecision and Uncertainty in Drilling Operation’s Factor Selection Process for Unidirectional Carbon Fibre Reinforced Plastic Composite Plates
DOI:
https://doi.org/10.24002/ijieem.v3i1.4447Keywords:
fuzzy analytic hierarchy process, geometric mean , multi-criteria decision making , drilling, machiningAbstract
Parametric selection in machining processes is recently understood as a route to reducing waste generation in drilling activities and achieving a robust resource distribution in drilling activities. However, the selection methods dominant in the literature lack competence in reducing uncertainties and imprecision associated with the drilling process. The purpose of this research is to reduce the uncertainty and imprecision in previously analyzed data that used the analytic hierarchy process (AHP) method. This paper adjusts the uncertainty and imprecision by introducing a geometric mean-based fuzzy analytic hierarchy process. The selection method influences the drilling expert's preferences by imposing the fuzzy theory in a triangular member function that converts the crisp numerical values into fuzzy members and adequately suppresses the imprecision and uncertainty in the elements. The thrust force was positioned first in ranking with a FAHP method's weight of 0.415, which matched the literature value of 0.413 for the AHP method. It was found that the use of the FAHP method has corrected the imprecision and uncertainty introduced by the AHP method. It was found that the thrust force and torque were overestimated by or 0.48% and 3.95%, respectively and was accordingly corrected. Besides, no errors were found with the measurement of eccentricity response. Furthermore, the entry delamination, exit delamination and surface roughness were underestimated by -8.11%, -3.33% and -6.96%, respectively, and therefore corrected by the FAHP method. The usefulness of this effort is to enhance cost-effective decisions and the effectiveness in the distribution of scarce drilling resources.
References
Abdul Nasir, A.A., Azmi, A.I., & Khalil, A.N.M. (2015). Measurement and optimization of residual tensile strength and delamination damage of drilled flax fibre reinforced composites. Measurement, 75, 298-307.
Abhishek, K., Datta, S., & Mahapatra, S.S. (2016). Multi-objective optimization in drilling of CFRP (polyester) composites: Application of a fuzzy embedded harmony search (HS) algorithm. Measurement, 77, 222-239.
Agwa, M.A., & Megahed, A.A. (2019). New nonlinear regression modeling and multi-objective optimization of cutting parameters in drilling GFRE composites to minimize delamination. Polymer Testing, 75, 192-204.
Amini, S., Alinaghian, I., Lotfi, M., Teimouri, R., & Alinaghian, M. (2017). Modified drilling process of AISI 1045 steel: A hybrid optimization. Engineering Science and Technology an International Journal, 20(6), 1653-1661.
Ayağ, Z. (2007). A hybrid approach to machine-tool selection through AHP and simulation. International Journal of Production Research, 45(9), 2029-2050.
Balaji, M., Rao, K.V., Rao, N.M., & Murthy, B.S.N. (2018). Optimization of drilling parameters for drilling of TI-6Al-4V based on surface roughness, flank wear and drill vibration. Measurement, 114, 332-339.
Baraheni, M., & Amini, S. (2019). Comprehensive optimization of process parameters in rotary ultrasonic drilling of CFRP aimed at minimizing delamination. International Journal of Lightweight Materials and Manufacture, 2(4), 379-387.
Bhat, R., Mohan, N., Rohit, S.S., Agarwal, A., Kamal, A.R., & Subudhi, A. (2019). Multi-response optimization of the thrust force, torque and surface roughness in drilling of glass fiber reinforced polyester composite using GRA-RSM. Materials Today: Proceedings, 19(2), 333-338.
Chen, Q., Chatzigeorgiou, G., & Meraghni, F. (2021). Hybrid hierarchical homogenization theory for unidirectional CNTS-coated fuzzy fiber composites undergoing inelastic deformations. Composites Science and Technology, 215, Article 109012.
Gunay, M., Yasar, N., & Korkmaz, M.E. (2016, May). Optimization of drilling parameters for thrust force in drilling of AA7075 alloy [Paper presentation]. International Conference on Engineering and National Sciences, Sarajevo.
Krishnamoorthy, A. (2011). Some studies on modelling and optimization in drilling carbon fibre reinforced plastic composites [Doctoral dissertation, Faculty of Mechanical Engineering, Anna University].
Krishnamoorthy, A., Boopathy, S.R., Palanikumar ,K., & Davim, J.P. (2012). Application of grey fuzzy logic for the optimization of drilling parameters for CFRP composites with multiple performance characteristics. Measurement, 45(5), 1286-1296.
Kaminski, M., & Pawlak, A. (2015). Various approaches in probabilistic homogenization of the CFRP composites. Composite Structures, 133, 425-437.
Kulkarni, S., & Ramachandran, M. (2018). Multicriteria selection of optimal CFRP composites drilling process parameters. REST Journal on Emerging Trends in Modelling and Manufacturing, 4(4), 102-106.
Lurie, S.A., Volkov-Bogorodskiy, D.B., Menshykov O., Solyaev, Y.O., & Aifantis, E.C. (2018). Modelling the effective mechanical properties of “fuzzy fiber” composites across scales length. Composites Part B: Engineering, 142, 24-35.
Meral, G., Sarıkaya, M., Mia, M., Dilipak, H., Şeker, U., & Gupta, M.K. (2019). Multi-objective optimization of surface roughness, thrust force, and torque produced by novel drill geometries using Taguchi-based GRA. The International Journal of Advanced Manufacturing Technology, 101, 1595–1610.
Odusoro, S.I., & Oke, S.A. (2021). Factor selection in drilling unidirectional carbon fibre reinforced plastic composite plates with the HSS drill bit using analytic hierarchy process. International Journal of Industrial Engineering and Engineering Management, 3(1), 1-16.
Okponyia, K.O., & Oke, S.A. (2020). Exploring aluminium alloy metal matrix composites in EDM using coupled factor-level-present worth analysis and fuzzy analytic hierarchy process. International Journal of Industrial Engineering and Engineering Management, 2(1), 25-44.
Putra, M.S.D., Andryana, S., Fauziah, & Gunaryat,i A. (2018). Fuzzy analytical hierarchy process method to determine the quality of gemstones. Advances in Fuzzy Systems, 2018, Article ID 9094380.
Singh, P.K., Kumar, K., & Saini, P. (2020). Optimization of surface roughness and hole diameter accuracy in drilling of EN-31 alloy steel – A TGRA based analysis. Materials Today: Proceedings, 26(2), 2961-2971.
Shirvanimoghaddam, K., Hamim, S.U., Akbari, M.K., Fakhrhoseini, S.M., Khayyam, H., Pakseresht, A.H., Ghasali, E., Zabeth, M, Shadza, K., Munir, Jiag, S., Davim, J.P., & Naebe, M. (2017). Carbon fiber reinforced metal matrix composites: Fabrication processes and properties. Composites part A: Applied Science and Manufacturing, 92, 70-96.
Shokrani, A., Leafe, H., & Newman, S.T. (2019). Cryogenic drilling of carbon fibre reinforced plastic with tool consideration. Procedia CIRP, 85, 55-60.
Soepangkat, B.O.P., Norcahyo, R., Effendi, M.K., & Pramujati, B. (2020). Multi-response optimization of carbon fiber reinforced polymer (CFRP) drilling using back propagation neural network-particle swarm optimization (BPNN-PSO). Engineering Science and Technology, an International Journal, 23(3), 700-713.
Tran, Q.P, Diem, M.T., & Huang, S.C. (2020, October 23-25). Optimization of CFRP drilling process with multi-criteria using TGRA [Paper presentation]. 2020 IEEE Eurasia Conference on IoT, Communication and Engineering, Taiwan.
Wang, Q., & Jia, X. (2020). Multi-objective optimization of CFRP drilling parameters with a hybrid method integrating the ANN, NSGA-II and fuzzy C-means. Composite Structures, 235, Article 111803.
Wu, C., Gao, Y., Fang, J., Lund, E., & Li, Q. (2017). Discrete topology optimization of ply orientation for a carbon fiber reinforced plastic (CFRP) laminate vehicle door. Materials and Design, 128, 9-19.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 International Journal of Industrial Engineering and Engineering Management
This work is licensed under a Creative Commons Attribution 4.0 International License.
The copyright of the received article shall be assigned to the journal as the publisher of the journal. The intended copyright includes the right to publish the article in various forms (including reprints). The journal maintains the publishing rights to the published articles.
This work is licensed under a Creative Commons Attribution 4.0 International License
