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Title:
A Hybrid Predictive Model for Cyclic Curled Chip Formation with Serrations in Machining Using Topological Properties
PI: I.S. Jawahir
Co-PI’s: O.W. Dillon, C. Eberhart
Graduate Student: R. Kandibanda
Sponsor: National Science Foundation
Abstract:
This project is aimed at developing a hybrid predictive model for cyclic chip formation in dry machining using topological tools and techniques. The inherent stochastic characteristics of the machining operations are considered through a topology-based classification/identification of the entire chip formation process with corresponding uncertainty levels. The proposed approach includes various aspects of changes in the material microstructure during dry machining with tools of different cutting edge radii. The current project also applies topological transformations to multi-scale (micro, meso, and macro) chip formation. This Project will establish the likely influencing parameters of product life, thus, contributing to product sustainability and extended life time of involved products – cutting tool and machined product. The application of topology-based modeling in machining, once proven, can open up new opportunities for modeling of other complex manufacturing processes by virtue of an improved capability to use topological techniques in order to generalize results.
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Fig.1. Modeling of chip formation using Maple |
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