Machine-Specific Estimation of Milling Energy Consumption in Detailed Design

Abstract

Manufacturing is a significant contributor to global greenhouse gas emissions and there is an urgent need to reduce the energy consumption of production processes. An important step towards this goal is proactively estimating process energy consumption at the detailed design stage. This is a challenging task as variabilities in factors such as process specifications, machine tool architecture, and workpiece geometry can significantly reduce the accuracy of the estimated energy consumption. This paper discusses a methodology for machine-specific energy estimation in milling processes at the detailed design stage based on the unit process life cycle inventory (UPLCI) model. We develop an adjusted UPLCI model that includes adjustment factors for uncertainties in machine tool specifications and the specific cutting energy of a workpiece material. These adjustment factors are calculated through experimental measurement of energy consumption for a reference test part on a specific machine tool. To validate the adjusted UPLCI model, we conducted a case study that measured the energy consumption for machining three parts made of Aluminum 6082 on two separate three-axis vertical milling machines, a Chevalier QP2040-L and a Leadwell MCV-OP. Results show that the UPLCI model consistently overestimated the total energy consumption for machining the three validation parts across both machine tools. We also found that the adjusted UPLCI model significantly reduced the estimation errors for the same tests for both machine tools.