Development of hybrid predictive models and optimization techniques for machining operations

I. S. Jawahir; X. Wang

doi:10.1016/j.jmatprotec.2006.03.133

Development of hybrid predictive models and optimization techniques for machining operations

I. S. Jawahir
, X. Wang

Producción científica: Article › revisión exhaustiva

52 Citas (Scopus)

Resumen

This paper presents a summary of recent developments in modeling and optimization of machining processes, focusing on turning and milling operations. With a brief analysis of past research on predictive modeling, the paper presents the analytical, numerical and empirical modeling efforts for 2D and 3D chip formation covering the development of a universal slip-line model, a comprehensive finite element model, and integrated hybrid models. This includes a newly developed equivalent toolface (ET) model and new tool-life relationships developed for machining with complex grooved tools. At the end, a performance-based machining optimization method developed for predicting optimum cutting conditions and cutting tool selection is presented. The paper also highlights the need for considering a machining systems approach to include the integrated effects of workpiece, cutting tool and machine tool.

Idioma original	English
Páginas (desde-hasta)	46-59
Número de páginas	14
Publicación	Journal of Materials Processing Technology
Volumen	185
N.º	1-3
DOI	https://doi.org/10.1016/j.jmatprotec.2006.03.133
Estado	Published - abr 30 2007

Nota bibliográfica

Funding Information:
The authors of this paper gratefully acknowledge the financial support of the National Science Foundation (NSF) and Kentucky Science and Engineering Foundation (KSEF) for research on predictive model development for machining. Administrative and laboratory support provided by the Center for Manufacturing at the University of Kentucky is also acknowledged.

Financiación

The authors of this paper gratefully acknowledge the financial support of the National Science Foundation (NSF) and Kentucky Science and Engineering Foundation (KSEF) for research on predictive model development for machining. Administrative and laboratory support provided by the Center for Manufacturing at the University of Kentucky is also acknowledged.

Financiadores
National Science Foundation (NSF)
Kentucky Science and Engineering Foundation

ASJC Scopus subject areas

Ceramics and Composites
Computer Science Applications
Metals and Alloys
Industrial and Manufacturing Engineering

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title = "Development of hybrid predictive models and optimization techniques for machining operations",

abstract = "This paper presents a summary of recent developments in modeling and optimization of machining processes, focusing on turning and milling operations. With a brief analysis of past research on predictive modeling, the paper presents the analytical, numerical and empirical modeling efforts for 2D and 3D chip formation covering the development of a universal slip-line model, a comprehensive finite element model, and integrated hybrid models. This includes a newly developed equivalent toolface (ET) model and new tool-life relationships developed for machining with complex grooved tools. At the end, a performance-based machining optimization method developed for predicting optimum cutting conditions and cutting tool selection is presented. The paper also highlights the need for considering a machining systems approach to include the integrated effects of workpiece, cutting tool and machine tool.",

keywords = "Cutting tools, Finite element model, Machining performance, Modeling, Optimization, Slip-line model",

author = "Jawahir, \{I. S.\} and X. Wang",

note = "Funding Information: The authors of this paper gratefully acknowledge the financial support of the National Science Foundation (NSF) and Kentucky Science and Engineering Foundation (KSEF) for research on predictive model development for machining. Administrative and laboratory support provided by the Center for Manufacturing at the University of Kentucky is also acknowledged.",

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AU - Jawahir, I. S.

AU - Wang, X.

N1 - Funding Information: The authors of this paper gratefully acknowledge the financial support of the National Science Foundation (NSF) and Kentucky Science and Engineering Foundation (KSEF) for research on predictive model development for machining. Administrative and laboratory support provided by the Center for Manufacturing at the University of Kentucky is also acknowledged.

PY - 2007/4/30

Y1 - 2007/4/30

N2 - This paper presents a summary of recent developments in modeling and optimization of machining processes, focusing on turning and milling operations. With a brief analysis of past research on predictive modeling, the paper presents the analytical, numerical and empirical modeling efforts for 2D and 3D chip formation covering the development of a universal slip-line model, a comprehensive finite element model, and integrated hybrid models. This includes a newly developed equivalent toolface (ET) model and new tool-life relationships developed for machining with complex grooved tools. At the end, a performance-based machining optimization method developed for predicting optimum cutting conditions and cutting tool selection is presented. The paper also highlights the need for considering a machining systems approach to include the integrated effects of workpiece, cutting tool and machine tool.

AB - This paper presents a summary of recent developments in modeling and optimization of machining processes, focusing on turning and milling operations. With a brief analysis of past research on predictive modeling, the paper presents the analytical, numerical and empirical modeling efforts for 2D and 3D chip formation covering the development of a universal slip-line model, a comprehensive finite element model, and integrated hybrid models. This includes a newly developed equivalent toolface (ET) model and new tool-life relationships developed for machining with complex grooved tools. At the end, a performance-based machining optimization method developed for predicting optimum cutting conditions and cutting tool selection is presented. The paper also highlights the need for considering a machining systems approach to include the integrated effects of workpiece, cutting tool and machine tool.

KW - Cutting tools

KW - Finite element model

KW - Machining performance

KW - Modeling

KW - Optimization

KW - Slip-line model

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DO - 10.1016/j.jmatprotec.2006.03.133

M3 - Article

AN - SCOPUS:33847150015

SN - 0924-0136

VL - 185

SP - 46

EP - 59

JO - Journal of Materials Processing Technology

JF - Journal of Materials Processing Technology

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ER -

Development of hybrid predictive models and optimization techniques for machining operations

Resumen

Nota bibliográfica

Financiación

ASJC Scopus subject areas

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