Author ORCID Identifier
Semester
Summer
Date of Graduation
2025
Document Type
Problem/Project Report (Campus Access)
Degree Type
MS
College
Statler College of Engineering and Mineral Resources
Department
Industrial and Managements Systems Engineering
Committee Chair
Bhaskaran Gopalakrishnan
Committee Co-Chair
Hailin Li
Committee Member
Zhichao Liu
Abstract
Global mandates such as the Paris Agreement to limit global warming to 1.5°C have placed industries under significant pressure to reduce greenhouse gas emissions. Given the high energy intensity of electronics manufacturing, where semiconductor facilities alone consume over 1 billion kWh annually, and projections showing electronics-related emissions could double by 2030, with the industry using 14% of global electricity by 2050, carbon management is now more critical than ever.
This study focuses on a U.S.-based printed circuit board (PCB) facility as a representative case of the electronics manufacturing sector. Equipment-level energy consumption was measured for 21 major energy-consuming machines, selected based on predefined research criteria, to assess load patterns and operational behavior. The first phase of results presents key findings from a week-long real-time monitoring campaign, followed by data extraction, feature engineering, and visualization using Python and Energy Star Portfolio Manager. Power usage correlation analyses, intra- and inter-department comparisons, and unsupervised K-means clustering are used to classify machines into three operational load bands.
In the second part of the study, monitored current values are translated into power consumption and emissions calculations. Scope 1, Scope 2, and selected Scope 3 emission sources are identified, and the U.S. EPA emissions calculator is employed to determine total carbon output. The study further quantifies emissions intensity in terms of kgCO₂e per PCB, offering a replicable and data-driven framework to support sustainability efforts in electronics manufacturing. This study locates critical emission hotspots, offers an actionable and scalable methodology to bridge the gap between theoretical carbon estimation and real-world industrial uses.
Recommended Citation
Adhikari, Nishan, "A Data-Driven Framework for Energy and Emissions Quantification in Electronics Manufacturing: A Case Study of a U.S.-Based PCB Facility" (2025). Graduate Theses, Dissertations, and Problem Reports. 13004.
https://researchrepository.wvu.edu/etd/13004