G-Code Based Toolpath Simulation for Predicting CNC Energy Consumption
Name
anziani-anzianij-bs-meche-2025-thesis.pdf
Description
Thesis PDF
Size
1.78 MB
Format
Adobe PDF
Checksum (MD5)
453460733afc304056afaa902665632a
Author(s)
Anziani, Jonathan
Advisor(s)
Hart, A. John
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
Machining is an energy intensive process, and being able to model the energy consumption of machining would allow manufacturers to consider how to reduce their energy footprint. While many models have been developed for estimating energy consumption, they are not easily applicable or accessible to CNC machining, where the material removal rate is variable. This thesis develops a G-code based simulation that uses a voxel mesh to virtually recreate material removal, approximating the material removal rate at discretized points in the machining process. Using an energy consumption model and machine power data, material removal rates are related to the power consumption of machining the part. The simulation pipeline was validated using power data collected from literature, and for a constant material removal rate the model has shown average absolute error of 3.17% predicting power and 2.89% predicting specific energy consumption for simulated test geometries.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
In Copyright - Educational Use Permitted
Copyright retained by author(s)
Persistent DSpace Link