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International Journal of Environment Science and Technology
Center for Environment and Energy Research and Studies (CEERS)
ISSN: 1735-1472 EISSN: 1735-1472
Vol. 13, No. 1, 2016, pp. 275-284
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Bioline Code: st16026
Full paper language: English
Document type: Research Article
Document available free of charge
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International Journal of Environment Science and Technology, Vol. 13, No. 1, 2016, pp. 275-284
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Developing a parametric carbon footprinting tool for the semiconductor industry
Huang, C.-Y.; Hu, A. H.; Yin, J. & Wang, H.-C.
Abstract
The advent of global awareness of sustainable
development resulted in consumer demand for low-carbon
electronic products. Thus, semiconductor industry has to
develop additional core competencies in that direction to
remain competitive. The present study aims to establish a
parametric-based tool that can identify key parameters of
the complicated manufacturing processes in the semiconductor
industry to simplify the calculation of the carbon
footprint of products (CFP). Six regression models for CFP
were developed by applying process and statistical analyses
on 7114 wafer products. Results indicate that these
regression models with the three key parameters (mask
layer, metal layer, and technology node) can effectively
predict the CFP of wafer with six different function types
because the adjusted R2 of all regression models was >0.5.
Moreover, the mask layer could be the most important
parameter for predicting CFP of wafer because of its higher
standardized coefficients (β) in each regression model. This
methodology reduces the time, cost, and information
requirements of the product in traditional life cycle
assessment. The proposed method introduces criteria for
low-carbon decision making in the semiconductor sector.
Keywords
Low-carbon design; Parametric carbon footprinting; Regression analysis; Semiconductor manufacturing; Green competitiveness
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