(749d) Energy Efficiency and GHG Emission of Manufacturing Zones: A Data-Driven Modeling and Analysis

Continuously improved industrial practice over the past decades has led to very significant improvement of energy sustainability. This is evidenced by tremendous energy savings, waste reduction, and productivity gains. However, according to the recent data reported to the DOE Industrial Technologies Program, energy loss in manufacturing sectors is still very high (~50% of the total consumption), and the total combustion emissions have reached ~1,200 MMT CO2e. It is shown that small and medium sized industrial and manufacturing facilities have a lower energy use efficiency than large ones; the lack of resources and expertise to address these inefficiencies has made their business less sustainable, especially in global economic competition. Hence, how to improve energy efficiency has been continuously a main focus in industries. Numerous energy consumption/GHG emission analysis methods have been developed for in-depth analysis for industrial systems. However, a further methodological study is needed for systematic analysis of process and non-process energy consumption and loss.

In this work, we will introduce a general, systematic data-driven modeling and analysis method to study energy consumption and loss in a manufacturing zone that usually consists of various types of manufacturing sectors. Huge amounts of energy consumption data in different regions are available from the U.S. Census Bureau and U.S. Energy Information Administration, many of which have been reported by various DOE supported industrial assessment centers. In the presentation, we will present a model-based analysis of the data to characterize the effectiveness of known strategies for energy efficiency improvement. A case study on the energy efficiency of the automotive-centered manufacturing sector, where various chemical and material supply companies exist, will be presented to demonstrate methodological attractiveness.