A mechanistic model for the prediction of cutting forces in the face-milling of ductile spheroidal cast iron components for wind industry application

Alessandro Checchi*, Giuliano Bissacco, Hans Nørgaard Hansen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Among renewable energy sources, wind energy has received considerable impulse in the last decade. Not only the number of manufactured wind turbines is raising, but also the overall size of the components is increasing, for improved energy harvesting. The increase of hub dimensions implies the need for larger, tailor built, milling machines, with impact on production costs and the possibility of local production. Within this scope, accurate prediction of process loads during the machining operations plays a central role with respect to the exploration of design solutions and processing strategies while maintaining the necessary product quality. For this purpose a mechanistic model, based on the unified cutting mechanics theory, was developed for the prediction of cutting forces in face milling using inserted cutters, for the machining of ductile spheroidal cast iron. Ductile cast iron alloys are particularly prone to generate segmented chips. The applicability range of the fundamental model, the shear plane model underlying the unified mechanics of cutting, was studied for this phenomenon. A method was proposed to analyse chip segmentation and extract relevant data for the model implementation. Through experimental validation, it was proved that mechanistic models are a reliable option for modelling machining operation even under chip segmentation conditions.

Original languageEnglish
JournalProcedia CIRP
Volume77
Pages (from-to)231-234
ISSN2212-8271
DOIs
Publication statusPublished - 2018
Event8th CIRP Conference on High Performance Cutting (HPC 2018) - Budapest, Hungary
Duration: 25 Jun 201827 Jun 2018

Conference

Conference8th CIRP Conference on High Performance Cutting (HPC 2018)
CountryHungary
CityBudapest
Period25/06/201827/06/2018

Keywords

  • Chip Segmentation
  • Cutting Force Prediction

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