Characterizing Energy Consumption in Injection Molding: Model Versus Logger

Abstract

Recent changes in legislation along with environmental initiatives to drive sustainability and reduce carbon emissions have sprouted the development of energy models to characterize manufacturing processes. In the case of injection molding, much work has been performed in coupling sensors with control statistical systems to promptly identify process' instabilities, such as pressure drops or fluctuations in the filling point. Latest energy models for injection molding make use of injection pressure and temperature parameters that are a function of the machine, mold geometry, and process characteristics. The latest state-of-the-art way to measure energy consumption is through the use of energy loggers, which provide power data at the end of the production cycles. Although seemingly correlated, little has been published on the extrapolation of cavity signals for their use in energy calculations. In this study, the advantages and disadvantages of using cavity sensors in injection molding are explored; a novel approach to the use of cavity sensors' pressure and temperature data is proposed by exploring their input in an energy model for the estimation of specific energy consumption (SEC). The model was validated against power data obtained via an energy logger; the averaged energy reported by the model indicated a range of 60–67% accuracy.