Quantifying Adoption Rates and Energy Savings Over Time for Advanced Manufacturing Technologies

Energy-efficient manufacturing technologies can reduce energy consumption and lower operating costs for an individual manufacturing facility, but increased process complexity and the resulting risk of disruption means that manufacturers may be reluctant to adopt such technologies. In order to quantify potential energy savings at scales larger than a single facility, it is necessary to account for how quickly and how widely the technology will be adopted by manufacturers. This work develops a methodology for estimating energy-efficient manufacturing technology adoption rates using quantitative, objectively measurable technology characteristics, including energetic, economic and technical criteria. Twelve technology characteristics are considered, and each characteristic is assigned an importance weight that reflects its impact on the overall technology adoption rate. Technology characteristic data and importance weights are used to calculate the adoption score, a number between 0 and 1 that represents how quickly the technology is likely to be adopted. The adoption score is then used to estimate parameters for the Bass diffusion curve, which quantifies the change in the number of new technology adopters in a population over time. Finally, energy savings at the sector level are calculated over time by multiplying the number of new technology adopters at each time step with the technology's facility-level energy savings. The proposed methodology will be applied to five state-of-the-art energy-efficient technologies in the carbon fiber composites sector, with technology data obtained from the Department of Energy's 2016 bandwidth study. Because the importance weights used in estimating the Bass curve parameters are subjective, a sensitivity analysis will be performed on the weights to obtain a range of parameters for each technology. The potential energy savings for each technology and the rate at which each technology is adopted in the sector are quantified and used to identify the technologies which offer the greatest cumulative sector-level energy savings over a period of 20 years. Preliminary analysis indicates that relatively simple technologies, such as efficient furnaces, will be adopted more quickly and result in greater cumulative energy savings compared to more complex technologies that require process retrofitting, such as advanced control systems.