Technology Evaluation and Selection of 3DIC Integration Using a Three-Stage Fuzzy MCDM

Abstract

Abstract:For the purpose of the sustainable development in the global semiconductor industry, emerging three-dimensional integrated circuit (3DIC) integration technologies have demonstrated their importance as potential candidates for extending the lifespan of Moore's Law. This study aimed to explore a technology selection process involving a three-stage fuzzy multicriteria decision-making (MCDM) approach to facilitate the effective assessment of emerging 3DIC integration technologies. The fuzzy Delphi method was first used to determine the important criteria. The fuzzy analytic hierarchy process (fuzzy AHP) was then adopted to derive the weights of the criteria. The fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS) was finally deployed to rate the alternatives. Empirical results indicate that market potential, time-to-market, and heterogeneous integration are the top three decision criteria for the selection of 3DIC integration technologies. Furthermore, 2.5D through-silicon interposer (TSI) is of primary interest to the Taiwanese semiconductor industry, followed by 3DIC through-silicon via (TSV), 3D packaging, and 3D silicon TSV (Si TSV). The proposed three-stage fuzzy decision model may potentially assist industry practitioners and government policy-makers in directing research and development investments and allocating resources more strategically.

A Hybrid Fuzzy Decision Model for Evaluating MEMS and IC Integration Technologies

“…Bairagi, Dey, Sarkar, and Sanyal [ 11 ] proposed a technique for TOPSIS-based (technique for order preference by similarity to ideal solution) fuzzy MCDM approach for selecting the best robotic system. Lee and Chou [ 12 ] explored a technology selection process for evaluating 3DIC (three-dimensional integrated circuit) integration technologies. In addition, Taylan, Alamoudi, Kabli, AlJifri, Ramzi, and Herrera-Viedma [ 13 ] integrated fuzzy AHP, fuzzy VIKOR and TOPSIS methods to determine the most eligible energy systems for investment.…”

Untitled

“…Таble 4. TOPSIS Method in Technology Selection Authors (year) Type of Technology [Habbal et al, 2019] radio access technologies [Gladysz et al, 2017;Wan et al, 2016] radio frequency identification (RFID) [Zhang et al, 2019] energy storage technology [Restrepo-Garcés et al, 2017;Hirushie et al, 2017] renewable energy sources [Karatas et al, 2018] energy technology [Streimikiene, 2013a,b;Streimikiene et al, 2013;Streimikiene, Balezentiene, 2012] electric vehicles [Zheng et al, 2012] green buildings [Peng et al, 2019] restoration technology in engine remanufacturing practice [Aloini et al, 2018] advanced underwater system [Büyüközkan, Güler, 2017] smart glass (SG) [Ansari et al, 2016;Puthanpura et al, 2015] automotive technology [Elahi et al, 2011] ABS sensor technology [Govind et al, 2018] treatment and disposal technology [Ren, 2018] ballast water treatment [Vivekh et al, 2017] desalination technology [Kalbar et al, 2012;Fu et al, 2012] wastewater treatment technology [Jiří, 2018;Mobinizadeh et al, 2016;Gajdoš et al, 2015;Lu et al, 2016] health technology [Lee, James Chou, 2016] emerging three-dimensional integrated circuit (3DIC) [Tavana et al, 2013] advanced-technology projects at NASA [Oztaysi, 2014] information technology [Towhidi et al, 2009] iron-making technology [Parkan, Wu, 1999] robots to perform repetitious, difficult, and hazardous tasks with precision…”

Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System

“…One of the more frequently used modelling tools has been fuzzy-logic-based methods due to their appropriateness to address uncertainty and subjectivity in decision-making processes [24]. FIS and/or fuzzy-AHP analysis have been used to rank water quality indicators [24], aid in environmental management decision-making [25,26], assess the quality and sustainability of supply chains [27][28][29][30], evaluate manufacturing processes [31], manage investment portfolios [32], provide the appropriate healthcare services for senior citizens [33], optimize the liquefied natural gas importation in Korea [34], optimize robot path selections of mobile robots [35], optimize joint distribution alliance partnerships [36], assess emerging three-dimensional integrated circuit technologies [37], assess potassium saturation of calcareous soils [38], evaluate the land suitability for a multitude of purposes [39], evaluate barriers of corporate social responsibility [40], and aid a multitude of other decision-making processes. Concerning the risks of technology transfer, fuzzy analysis was used to aid technology-based decisions for information technology organizations competing in global markets [41] and in transferring biotechnology [42].…”