Optimization of process parameters of mechanical type advanced machining processes using genetic algorithms

被引:93
作者
Jain, Neelesh K.
Jain, V. K. [1 ]
Deb, Kalyanmoy
机构
[1] Indian Inst Technol, Dept Mech Engn, Kanpur 208016, Uttar Pradesh, India
[2] Indian Inst Technol, Mech & Ind Engn Dept, Roorkee 247667, Uttar Pradesh, India
关键词
AJM; AWJW; AMPs; genetic algorithms (GA); optimization; USM; WJM;
D O I
10.1016/j.ijmachtools.2006.08.001
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Generally, unconventional or advanced machining processes (AMPs) are used only when no other traditional machining process can meet the necessary requirements efficiently and economically because use of most of AMPs incurs relatively higher initial investment, maintenance, operating, and tooling costs. Therefore, optimum choice of the process parameters is essential for the economic, efficient, and effective utilization of these processes. Process parameters of AMPs are generally selected either based on the experience, and expertise of the operator or from the propriety machining handbooks. In most of the cases, selected parameters are conservative and far from the optimum. This hinders optimum utilization of the process capabilities. Selecting optimum values of process parameters without optimization requires elaborate experimentation which is costly, time consuming, and tedious. Process parameters optimization of AMPs is essential for exploiting their potentials and capabilities to the fullest extent economically. This paper describes optimization of process parameters of four mechanical type AMPs namely ultrasonic machining (USM), abrasive jet machining (AJM), water jet machining (WJM), and abrasive-water jet machining (AWJM) processes using genetic algorithms giving the details of formulation of optimization models, solution methodology used, and optimization results. (C) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:900 / 919
页数:20
相关论文
共 50 条
[1]  
[Anonymous], MANUFACTURING ENG PR
[2]  
[Anonymous], MULTIOBJECTIVE OPTIM
[3]  
Bagchi Tapan P., 1999, Multiobjective Scheduling by Genetic Algorithms
[4]  
Benedict G.F., 1987, NONTRADITIONAL MANUF
[5]  
BHATTACHARYA A, 1973, NEW TECHNOLOGY
[6]  
Bitter J.G.A., 1963, WEAR, V6, P5, DOI [10.1016/, DOI 10.1016/0043-1648(63)90003-6]
[7]   A new approach for selection of optimal process parameters in abrasive water jet cutting [J].
Chakravarthy, PS ;
Babu, NR .
MATERIALS AND MANUFACTURING PROCESSES, 1999, 14 (04) :581-600
[8]  
Choi GS, 1997, INT J MACH TOOL MANU, V37, P295
[9]  
CHRYSSOLOURIS G, 1990, T ASME, V112, P122
[10]  
Cook N, 1966, MANUFACTURING ANAL