Multiple-Objective Optimization Techniques in Laser Joining of Dissimilar Materials Classes: A Comparison between Grey and Ratio Analyses

• Main Authors: Tamrin, K. F., Sheikh, N. A., Rizduan, M. S. M, Nadirah, A. N.
• Format: E-Article
• Language: English
• Published: Universiti Teknikal Malaysia Melaka 2018
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://ir.unimas.my/id/eprint/20213/1/2018%20Tamrin%20%28abstrak%29.pdf; http://ir.unimas.my/id/eprint/20213/; http://journal.utem.edu.my/index.php/jtec/about

Multiple-objective optimization using grey relational analysis (GRA) has found widespread applications especially in manufacturing and machining processes that involve complex processing parameters and output attributes. On the other hand, multiple-objective optimization on the basis of ratio analysis (MOORA) is often applied in the fields of construction and economy. One distinctive feature of MOORA is the assessment of relative importance of all responses (i.e. weighting ratio) which are taken into account mathematically while GRA emphasis the need of a priori information for accurate assignment of weighting ratio. This paper compares these two seemingly different methods by considering their applications in laser joining of dissimilar materials classes in a number of case studies: (a) laser joining of polymer and ceramic, (b) laser joining of polymer and stainless steel, and (c) laser joining of polymer and aluminium alloy. The outcomes of the two methods are compared and discussed. In majority of the cases, the predicted top-ranked alternatives were comparably matched. It is concluded that MOORA is more favourable compared to GRA since it eliminates prior assumption concerning the relative importance of the measured responses, which can lead to unnecessary bias.