{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/162446"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/162446","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"G-Code Based Toolpath Simulation for Predicting CNC Energy Consumption","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Anziani, Jonathan"],"institution":"Massachusetts Institute of Technology","degree_name":"Bachelor","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Mechanical Engineering","school":null,"contributors":[],"advisors":["Hart, A. John"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-05","date_published":"2025-05","updated_at":"2026-07-22T22:22:30Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"rights_urls":["https://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/162446","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hart, A. John"]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.B."]},{"key":"dc:title","label":"Title","values":["G-Code Based Toolpath Simulation for Predicting CNC Energy Consumption"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hart, A. John"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Mechanical Engineering"],"dc:creator":["Anziani, Jonathan"],"dc:date.accessioned":["2025-08-21T17:02:16Z"],"dc:date.available":["2025-08-21T17:02:16Z"],"dc:date.issued":["2025-05"],"dc:description.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."],"dc:description.degree":["S.B."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/162446"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["G-Code Based Toolpath Simulation for Predicting CNC Energy Consumption"],"dc:type":["Thesis"],"thesis:degree_name":["Bachelor","Bachelor of Science in Engineering"]},"updated_at":"2026-07-22T22:22:30Z"}