Oh / Hildreth Analytics for Smart Energy Management

Tools and Applications for Sustainable Manufacturing
1. Auflage 2016
ISBN: 978-3-319-32729-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 295 Seiten, eBook

Reihe: Springer Series in Advanced Manufacturing

This book introduces the issues and problems that arise when implementing smart energy management for sustainable manufacturing in the automotive manufacturing industry and the analytical tools and applications to deal with them. It uses a number of illustrative examples to explain energy management in automotive manufacturing, which involves most types of manufacturing technology and various levels of energy consumption. It demonstrates how analytical tools can help improve energy management processes, including forecasting, consumption, and performance analysis, emerging new technology identification as well as investment decisions for establishing smart energy consumption practices. It also details practical energy management systems, making it a valuable resource for professionals involved in real energy management processes, and allowing readers to implement the procedures and applications presented.

Zielgruppe

Research

Autoren/Hrsg.

Oh, Seog-Chan

Hildreth, Alfred J.

Inhaltsverzeichnis

Introduction.- Energy Performance Analysis: Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DES) for Energy Performance Analysis.- Energy Decision-Making 1: Strategic Planning of Sustainable Manufacturing Projects based on Stochastic Programming.- Energy Decision-Making 2: Demand Response Option Contract Decision based on Stochastic Programming.- Pattern-based Energy Consumption Analysis by Chaining Principle Component Analysis and Logistic Regression.- Ontology-enabled Knowledge Management in Environmental Regulations and Incentive Policies.- Energy Simulation Using EnergyPlusTM for Building and Process Energy Balance.- Energy Management Process for businesses.- Energy Efficiency Accounting to Demonstrate Performance.

Über Autor(innen)

Seog-Chan Oh, PhD is a senior researcher at the General Motors Research and Development Center, Warren, MI since 2007 where he has been developing analytical models for improvement in sustainable manufacturing. He has strong functional expertise in Operations Research and Advanced Statistics. He received the PhD degree in Industrial Engineering from Pennsylvania State University in 2006. Before he began his PhD studies, he was an IT consultant for seven years at Daewoo Information Systems in Korea. He won a Boss Kettering Award, GM’s highest award for recognizing technical inventions and innovations. He also won a Korean Prime Minister Award, TeamGM Award, GM Patent Usage Award, IEEE Appreciation Award, Best Paper Award (KIIE), First Runner-Up Award (IEEE Web Service Challenge) and etc. He holds 4 Patents filed and 45 scholary articles including 3 Books. He has served on AIAG energy working group, IEEE Cloud and SCC program committees and IJWR editorial board. Al Hildreth, PE, CEM is the Company Energy Manager for General Motors – focusing on energy and utility budgets, metrics, benchmarking, efficiency projects, water and carbon reporting. He has worked for GM for over 30 years, including 5 years in Europe and Asia, 10 years with Saturn Corporation in Spring Hill, TN, and previously worked for a manufacturer of air pollution control equipment in R&D. He is a registered Professional Engineer, Certified Energy Manager, and a Certified Hazardous Materials Manager.  He received his Bachelor of Science degree in Engineering from Oakland University and a Master’s of Science degree in Engineering from Rensselaer Polytechnic Institute.