Industrial energy use is heavily reliant on electricity and fuel from non-renewable sources. Most analyses expect global oil and natural gas production to decline within the next 30 years, while an expanding world population and economy will demand ever-increasing amounts of energy. This discrepancy will invariably increase energy prices and threaten economic development. As such, increasingly dramatic industrial energy efficiency improvements will be needed to maintain the economic viability of manufacturing companies and entire economies. Governmental organizations such as the US Department of Energy (DOE) and the United Nations Development Programme (UNDP) have bracketed energy efficiency potential by calculating the theoretical minimum energy use of some energy-intensive industrial processes.

Unfortunately, incorporating calculations of theoretical minimum energy use into plant-level energy assessments is costly, complex, and seldom done. As a result, most energy assessment reports do not quantify the maximum energy efficiency potential at the facility.

This paper presents a methodology, called Lean Energy Analysis (LEA), which provides a practical way of thinking about and statistically analyzing plant energy use as guide to the theoretical minimum energy use. The process of identifying energy saving opportunities by considering that “any energy use that does not add value to the product or plant environment is waste” is demonstrated with case study examples. The LEA statistical methodology uses as few as 48 data points, which are readily obtainable through on-site data collection and interviews with facility management. Multivariable change-point models of electricity and natural gas usage as functions of outdoor air temperature and the quantity of production are developed. The statistical models are used to subdivide plant energy use into facility, space-conditioning, and production-related components. The results of this analysis provide a quick and economical method of bracketing energy efficiency potential in a facility and measuring control and direct energy conversion efficiencies.