Simulation for an Energy-Efficient Semiconductor Manufacturing Network

The semiconductor industry plays an important role in reducing carbon emissions and facilitating CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> savings through energy-saving applications, while also generating a significant CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> footprint during the manufacturing process of chips. Despite this, microchips in end-applications have the potential to save CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> several times greater than the emissions generated. Chip manufacturers are required to be transparent in reporting the CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> emissions and customers are demanding to reduce the footprint and to increase the handprint. In this paper, we present a simulation study which analyzes the energy consumption of two exemplary semiconductor products to assess the ratio of fixed and variable energy consumption. In addition, the paper analyzes the most energy consuming processes and the linkage between the capacity utilization and the energy consumption in a typical semiconductor facility. The paper suggests for future work to analyze the handprint as well and to investigate the relation between the footprint and handprint.

Authors

Institutions

Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/wsc63780.2024.10838903
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulation for an Energy-Efficient Semiconductor Manufacturing Network

Abdelgafar Ismail, R. Nayak, Hans Ehm, Saskia Serr et al.
Scheduling and Optimization Algorithms
article

Simulation for an Energy-Efficient Semiconductor Manufacturing Network

Abdelgafar Ismail, R. Nayak, Hans Ehm, Saskia Serr, Tristan Scheuermann
article en

Abstract

The semiconductor industry plays an important role in reducing carbon emissions and facilitating CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> savings through energy-saving applications, while also generating a significant CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> footprint during the manufacturing process of chips. Despite this, microchips in end-applications have the potential to save CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> several times greater than the emissions generated. Chip manufacturers are required to be transparent in reporting the CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> emissions and customers are demanding to reduce the footprint and to increase the handprint. In this paper, we present a simulation study which analyzes the energy consumption of two exemplary semiconductor products to assess the ratio of fixed and variable energy consumption. In addition, the paper analyzes the most energy consuming processes and the linkage between the capacity utilization and the energy consumption in a typical semiconductor facility. The paper suggests for future work to analyze the handprint as well and to investigate the relation between the footprint and handprint.

Infineon Technologies (Germany) (DE)
Affordable and clean energy
Openalex Percentile: Top 62%
Scheduling and Optimization Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.