A selectively calibrated derivation technique and generalized fuzzy TOPSIS for semiconductor supply chain localization assessment

There is a localization wave in the semiconductor industry for pushing wafer foundries to transfer their production capacity to where chip designers are located. The main reasons for the localization of semiconductor supply chains include the US-China trade war, geopolitics, COVID-19, the Ukraine-Russia war, and rising environmental awareness. However, this is a challenging task since some of the issues considered in traditional facility location selection problems are no longer decisive factors. To overcome this challenge, this study proposes the selectively calibrated derivation technique (SCDT)-generalized fuzzy technique for order preference by similarity to ideal solution (GFTOPSIS) approach to help wafer foundries select suitable facility locations for customer-required capacity localization. The proposed SCDT-GFTOPSIS approach has been applied to a real case to validate its effectiveness. According to the experimental results, SCDT effectively improved the accuracy of approximating the fuzzy priorities of criteria by reducing the mean absolute deviation (MAD) by 81%. In addition, the most suitable location for the facility was in Singapore, where the support of the local government was higher, while requiring less total investment and subject to less political and war risk. However, the final selection was subject to further negotiations.