2020
DOI: 10.1108/ssmt-05-2020-0016
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Application of multi-quality parameter design in the optimization of underfilling process – a case study of a vehicle electronic module

Abstract: Purpose This paper aims to discuss the key factors affecting the quality characteristics, such as the number of solder balls, the spread distance of residual underfill and the completion time of the underfilling. Design/methodology/approach The Taguchi method is applied to configure the orthogonal table and schedule and execute the experiment. In addition, principal components analysis is used to obtain the points. Then, based on gray relational analysis and the technique for order preference by similarity t… Show more

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Cited by 8 publications
(4 citation statements)
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“…The experimental data of two quality characteristics, such as the standard deviation of solder paste volume and 01005 assembly yield, are obtained in this study, as shown in Table 1, respectively. The SN ratio is calculated, and the influence of various factors on quality characteristics is displayed by a response table and a response graph, and the optimum parameter combination is proposed using the TOPSIS multi-quality analysis method (Huang et al , 2020).…”
Section: Discussionmentioning
confidence: 99%
“…The experimental data of two quality characteristics, such as the standard deviation of solder paste volume and 01005 assembly yield, are obtained in this study, as shown in Table 1, respectively. The SN ratio is calculated, and the influence of various factors on quality characteristics is displayed by a response table and a response graph, and the optimum parameter combination is proposed using the TOPSIS multi-quality analysis method (Huang et al , 2020).…”
Section: Discussionmentioning
confidence: 99%
“…Obtain a single measurement index by using GRA to calculate gray relational coefficients of the various principal component. Determine the optimal process parameter set objectively and effectively (Vimal et al, 2017;Chiang et al, 2006;Lu et al, 2009;Huang et al, 2020). The analysis process is described as follows:…”
Section: Principal Component Gray Relational Analysismentioning
confidence: 99%
“…Conventional underfill materials used in capillary-driven flow are composed of thermoset epoxy polymers with silica filler particles [ 7 , 8 ], generally demonstrating a slow flow rate owing to their high viscosity. Hence, a complete filling of the chip-to-substrate standoff and shortening of the filling time have been regarded as technical challenges [ 9 , 10 ] in capillary-driven flow. Various studies have claimed that capillary-driven flow can be enhanced by modifying the surface wettability [ [11] , [12] , [13] , [14] ], driving pressure gradient [ 15 ], thermal stresses [ [16] , [17] , [18] ], and electric field effects [ [19] , [20] , [21] , [22] ].…”
Section: Introductionmentioning
confidence: 99%