Unit Machining Operations: An Automated Process Planning and Selection Program

1980 ◽  
Vol 102 (4) ◽  
pp. 297-302 ◽  
Author(s):  
R. A. Wysk ◽  
M. M. Barash ◽  
C. M. Moodie
Keyword(s):  
Process Planning ◽  
Manufacturing Systems ◽  
Metal Cutting ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Machining Parameters ◽  
Automated Manufacturing Systems ◽  
Specific Product ◽  
Automated Process Planning ◽  
Automated Process

In most metal cutting or removing facilities, the task of planning piece part operations and sequences is the responsibility of the process planner. Although this individual holds the key to the profitability of a specific product, little has been done to aid the process planner in the performance of his job. With the cost of machinery skyrocketing as the degree of automation is increasing, much emphasis has been placed on process planning or engineering. This paper outlines the responsibilities and functions carried out by the process planner. The paper is primarily concerned with automated manufacturing systems and, in particular, the planning of parts on machining centers. It demonstrates the decisions required of process planner and the lack of quantifiable data available to make logical decisions at the present time. A review of the two approaches to automated process planning, called variant and generative planning, is presented. The paper also describes some of the shortcomings of classification codes that have been used for automated process planning. The framework for a computer generative process planning scheme is demonstrated. The selection of machining parameters (feed, speed and depth of cut) are also discussed.

Investigation of Machining Parameters for Burr Minimization in CNC Turning of Brass Using RSM and GA

2014 ◽  
Vol 627 ◽  
pp. 54-59 ◽  
Author(s):  
R. Ravikumar ◽  
M. Mohamed Abdul Hafeez
Keyword(s):  
Metal Cutting ◽  
Cutting Parameters ◽  
Optimization Techniques ◽  
Cutting Process ◽  
Depth Of Cut ◽  
Work Piece ◽  
Feed Speed ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Control Factors

CNC turning is one among the metal cutting process in which quality of the finished product depends mainly upon the machining parameters such as feed, speed, depth of cut, type of coolant used, types of inserts used etc. Similarly the work piece material plays an important role in metal cutting process. This study involves in indentifying the optimized parameters in CNC turning of Brass. To identify and measure the formation of burrs in the turned samples, are examined under scanning electron microscope (SEM). The optimization techniques used in this study are Response surface methodology, and Genetic algorithm. Several comparisons were made between cutting parameters with surface roughness. These optimization techniques are very helpful in indentifying the optimized control factors with high level of accuracy.

Manufacture of Microcantilever Sensors

2005 ◽  
Author(s):  
Andrew W. McFarland ◽  
Jonathan S. Colton ◽  
Daniel Cox ◽  
Steven Y. Liang
Keyword(s):  
Machine Tool ◽  
Mechanical Response ◽  
Surface Force ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Machining Parameters ◽  
Form Accuracy ◽  
Microcantilever Sensors ◽  
Micro Scale ◽  
Sensing Applications

Mechanical micro machining is an emerging technology with many potential benefits and equally great challenges. The push to develop processes and tools capable of micro scale fabrication is a result of the widespread drive to reduce part and feature size. One important factor that contributes to the ability to machine at the microscale level is the overall size of the machine tool due to the effects of thermal, static, and dynamic stabilities. This paper explores the technical feasibility of miniaturized machine tools capable of fabricating features and parts on the micro scale in terms of depth of cut and part form accuracy. It develops a machine tool and examines its capabilities through benchmarking tests and the making of precision dies for the injection molding of microcantilever parts. The design and configuration of a miniaturized vertical machining center of overall dimension less than 300 mm on a side is presented and the component specifications discussed. The six axis machine has linear positioning resolution of 4 nm by 10 nm by 10 nm, with accuracy on the order of 0.3 μm, in the height, feed, and cross feed directions. The work volume as defined by the ranges of axes travel are 4 mm by 25 mm by 25 mm in the height, feed, and cross feed and 20 degrees in the rotational space. To quantify the performance capability of the miniaturized machine tool as a system, a series of evaluation tests were implemented based on linear and arch trajectories over a range of feed speed and depth of cut conditions. Test results suggest that micro level form accuracy and sub-micron level finish are generally achievable for parts with moderate curvature and gradient in the geometry under selected machining parameters and conditions. An injection mold was made of steel with this machine and plastic microcantilevers fabricated. Plastic microcantilevers are appropriate for sensing applications such as surface probe microscopy. The microcantilevers, made from polystyrene, were 464 to 755 μm long, 130 μm wide and only 6–9 μm thick. They showed very good uniformity, reproducibility, and appropriate mechanical response for use as sensors in surface force microscopy.

Research on Prediction Model of Surface Roughness in Ultrasonic Polishing Nano-ZrO2 Ceramics

2009 ◽  
Vol 69-70 ◽  
pp. 128-132
Author(s):  
Ming Li Zhao ◽  
Bo Zhao ◽  
Yu Qing Wang ◽  
Guo Fu Gao
Keyword(s):  
Surface Roughness ◽  
Orthogonal Test ◽  
Depth Of Cut ◽  
Feed Speed ◽  
Machining Parameters ◽  
Test Results ◽  
Work Situation ◽  
Table Speed ◽  
Abrasive Size ◽  
Regressive Analysis

The orthogonal test of surface roughness in ultrasonic polishing nano-ZrO2 ceramics was carried out in the present paper. Through the test, the influence of machining parameters on the surface roughness was investigated. The test results showed that the influence of abrasive size on surface roughness is the most remarkable, and the other important factors are the depth of cut, on/off work situation of ultrasonic generator, axial feed speed, and working table speed in turns. Furthermore, through the regressive analysis of test data, an empirical formula of surface roughness was established to select reasonable polishing parameters.

scholarly journals Investigation of AlCrN-Coated Inserts on Cryogenic Turning of Ti-6Al-4V Alloy

Metals ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 1338
Author(s):  
Lakshmanan Selvam ◽  
Pradeep Kumar Murugesan ◽  
Dhananchezian Mani ◽  
Yuvaraj Natarajan
Keyword(s):  
Tool Wear ◽  
Cutting Force ◽  
Physical Vapor Deposition ◽  
Metal Cutting ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machined Surface ◽  
Coated Carbide ◽  
Cryogenic Conditions

Over the past decade, the focus of the metal cutting industry has been on the improvement of tool life for achieving higher productivity and better finish. Researchers are attempting to reduce tool failure in several ways such as modified coating characteristics of a cutting tool, conventional coolant, cryogenic coolant, and cryogenic treated insert. In this study, a single layer coating was made on cutting carbide inserts with newly determined thickness. Coating thickness, presence of coating materials, and coated insert hardness were observed. This investigation also dealt with the effect of machining parameters on the cutting force, surface finish, and tool wear when turning Ti-6Al-4V alloy without coating and Physical Vapor Deposition (PVD)-AlCrN coated carbide cutting inserts under cryogenic conditions. The experimental results showed that AlCrN-based coated tools with cryogenic conditions developed reduced tool wear and surface roughness on the machined surface, and cutting force reductions were observed when a comparison was made with the uncoated carbide insert. The best optimal parameters of a cutting speed (Vc) of 215 m/min, feed rate (f) of 0.102 mm/rev, and depth of cut (doc) of 0.5 mm are recommended for turning titanium alloy using the multi-response TOPSIS technique.

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