The Effect of Coolant Concentration on the Machinability of Nickel-Base, Nimonic C-263, Alloy

This paper investigates the effect of coolant concentration on tool performance when machining nickel-base, C-263, alloy with triple coated (TiN/TiCN/TiN) carbide insert at various (3–9%) coolant concentrations and under different cutting speed conditions. Tool life, tool-failure modes, wear rates, component forces and surface finish generated during machining were recorded, analyzed and used to formulate mechanisms responsible for tool wear at the cutting conditions investigated. Analysis of the recorded data shows that tool performance during machining is dependent on coolant concentration. 6% coolant concentration gave the best overall performance as effective combination of cooling and lubrication functions were achieved during machining. Increasing coolant concentration to 9% reduced tool performance due to a reduction of the tool-chip contact length area and the consequent increase in compressive stresses at the tool-chip and tool-workpiece interfaces. This action often leads to pronounced chipping of the tool cutting edge during machining. Friction coefficient between the workpiece material and substrate increases once the coating layer(s) is broken as a result of the direct contact between the tool substrate and the work material. This action increases mechanical wear of the tool, which in turn leads to a significant increase in the cutting force with negligible effect on the feed forces during machining.     

An element-free Galerkin method approach for estimating sensitivity of machined surface parameters

The main objective of this study is to implement a parameter sensitivity analysis method to be used in the search of optimal machining conditions with respect to surface quality. Presently, the element-free Galerkin (EFGM) approximating functions are used to evaluate the properties of machined surfaces with cutting parameters when turning AISI 4140 steel using arbitrary sets of experimental values and the EFGM approximation functions, based on the moving least-squares method, in order to obtain the sensitivities through proper local derivations. This method shows the sensitivity of each surface parameter for each input variable. The variables investigated were cutting speed (v_c), depth of cut (a_p), feed rate (f) and the surface roughness (R_a). The sensitivity results showed that the feed rate has the highest influence on surface roughness when turning AISI 4140 steel followed by cutting speed and depth of cut.     

Vibration and spinal lengthening in simulated vehicle driving

There is active interest in the relationship between back pain and driving. The availability of a precision stadiometer enabled experiments to be done to explore the effects of simulated driving on the change in spinal length, the hypothesis being that the spinal load would cause a shrinking in the length of the spine. The experiments demonstrated that, when exposed to a combination of vertical and horizontal vibration at 4 Hz the spinal length increased for all eight subjects, whilst under no vibration conditions there was a decrease in the average length. At 6 and 8 Hz there was no statistically significant change in length. The results suggest that there is an unloading of the spine when subjects under simulated driving conditions are exposed to vibrations in two directions at a frequency close to the spine's natural frequency.     

Visual discrimination learning and strategy behavior in the fat-tailed dunnarts ( Sminthopsis crassicaudata ).

Fat-tailed dunnarts (Sminthopsis crassicaudata) were trained on visual discrimination learning-set, reversal-set, and spatial delayed-alternation tasks. The learning set involved 36 2-way black-and-white pattern discriminations and 5 probe reversals. Ten reversals of a black-and-white pattern discrimination were followed by 5 novel tasks. Spatial alternation was tested at delays up to 20 s. Learning-set and reversal-set formation, including 1-trial learning and spontaneous transfer from learning set to reversals and vice versa, was found. Learning-set-experienced dunnarts showed no retention of previously learned tasks 1 week after testing but demonstrated consistently high Trial 2 performance, indicating the retention of a response strategy. Delayed-alternation tasks were learned up to 10-s delays. These results provide the first evidence of a visually guided "win-stay, lose-shift" strategy in a marsupial. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Thermal analysis of self-propagating high-temperature reactions in titanium, boron, and aluminum powder compacts

This article focuses on the characterization of self-propagating high-temperature synthesis (SHS) reactions that occur in powder compacts containing titanium, boron, and aluminum. Interest in this powder system is based on the critical need to develop new joining techniques for bonding ceramics to metals. The exothermic reactions of particular interest in this study include those that generate TiB₂, TiB, Ti₃Al, and TiAl from their elemental powders. Data from differential thermal analysis (DTA), thermogravimetric analysis (TGA), and X-ray diffractometry are presented. These results demonstrate that the gas phase surrounding the SHS powders plays an important role in initiating the SHS reaction and in determining which reaction products will form in the final bond.     

The Effect of Argon-Enriched Environment in High-Speed Machining of Titanium Alloy

A major factor hindering the machinability of titanium alloys is their tendency to react with most cutting tool materials, thereby encouraging solution wear during machining. Machining in an inert environment is envisaged to minimize chemical reaction at the tool-chip and tool-workpiece interfaces when machining commercially available titanium alloys at higher cutting conditions. This article presents the results of machining trials carried out with uncoated carbide (ISO K10 grade) tools in an argon-enriched environment at cutting conditions typical of finish turning operations. Comparative trials were carried out at the same cutting conditions under conventional coolant supply. Results of the machining trials show that machining in an argon-enriched environment gave lower tool life relative to conventional coolant supply. Nose wear was the dominant tool-failure mode in all the cutting conditions investigated. Argon is a poor conductor of heat; thus, heat generated during machining tends to concentrate in the cutting region and accelerate tool wear. Argon also has poor lubrication characteristics, leading to increasing friction at the cutting interfaces during machining and an increase in cutting forces required for efficient shearing of the workpiece.     

Finish Machining of Nickel-Base Inconel 718 Alloy with Coated Carbide Tool under Conventional and High-Pressure Coolant Supplies

Single-point turning of Inconel 718 alloy with commercially available Physical Vapour Deposition (PVD)-coated carbide tools under conventional and high-pressure coolant supplies up to 20.3 MPa was carried out. Tool life, surface roughness (Ra), tool wear, and component forces were recorded and analyzed. The test results show that acceptable surface finish and improved tool life can be achieved when machining Inconel 718 with high coolant pressures. The highest improvement in tool life (349%) was achieved when machining with 11 MPa coolant supply pressure at higher speed conditions of 60 m · min^?1. Machining with coolant pressures in excess of 11 MPa at cutting speeds up to 40 m · min^?1 lowered tool life more than when machining under conventional coolant flow at a feed rate of 0.1 mm · rev^?1. This suggests that there is a critical coolant pressure under which the cutting tools performed better under high-pressure coolant supplies.

Cutting forces increased with increasing cutting speed due probably to reactive forces introduced by the high-pressure coolant jet. Tool wear/wear rate increased gradually with prolonged machining with high coolant pressures due to improved coolant access to the cutting interface, hence lowering cutting temperature. Nose wear was the dominant tool failure mode when machining with coated carbide tools due probably to a reduction in the chip-tool and tool-workpiece contact length/area.     

Design of mirror systems for commercial vehicles

This paper describes a computer aided design project for the evaluation of alternative mirror systems for a range of commercial vehicles. Computer modelling of mirror systems introduces the ergonomics parameters into the design programme at an early stage. The flexibility of computer modelling allows a far greater range of designs to be evaluated. The problems can be studied and resolved before producing a series of mirror designs to be evaluated by more conventional techniques on prototype vehicles. Mirrors designed in this way are less likely to require major redesign. Compliance with the legislative requirements of mirror design was a major consideration. Attempts were also made to optimise mirror systems for a range of cabs basing the evaluations on ergonomic as well as legislative criteria.

Additionally, consideration was given to the use of mirrors for viewing trailer swing, passenger exit surveillance (for public service vehicles) and the viewing of objects close to high cabs. SAMMIE (System for Aiding Man-Machine Interaction Evaluation), a computer-aided workplace and work task design system, was used to model the vehicles and to produce the required mirror views on a computer graphics terminal.     

Evaluation of the performance of CBN tools when turning Ti–6Al–4V alloy with high pressure coolant supplies

Cubic Nitride Boron (CBN) tools are generally used for machining harder alloys such as hardened high Cr steels, titanium and nickel alloys. The tools are expected to withstand the heat and pressure developed when machining at higher cutting conditions because of their high hardness and melting point. This paper evaluates the performance of different CBN tool grades in finish turning Ti–6Al–4V (IMI 318) alloy at high cutting conditions, up to 250 m min⁻¹, with various coolant supplies. Tool wear, failure modes, cutting and feed forces and surface roughness of machined surfaces were monitored and used to access the performance of the cutting tools. Comparative trials were carried out with uncoated carbide tools when machining at a speed of 150 m min⁻¹. Test results show that the performance of CBN tools, in terms of tool life, at the cutting conditions investigated is poor relative to uncoated carbide tools, as expected and often, reported due probably to rapid notching and excessive chipping of the cutting edge associated with a relatively high diffusion wear rate that tends to weaken the bond strength of the tool substrate. An increase in the CBN content of the cutting tool also led to a reduction in tool life when machining at the cutting conditions investigated.     

Modelling the correlation between cutting and process parameters in high-speed machining of Inconel 718 alloy using an artificial neural network

An artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between cutting and process parameters during high-speed turning of nickel-based, Inconel 718, alloy. The input parameters of the ANN model are the cutting parameters: speed, feed rate, depth of cut, cutting time, and coolant pressure. The output parameters of the model are seven process parameters measured during the machining trials, namely tangential force (cutting force, F_z), axial force (feed force, F_x), spindle motor power consumption, machined surface roughness, average flank wear (VB), maximum flank wear (VB_max) and nose wear (VC). The model consists of a three-layered feedforward backpropagation neural network. The network is trained with pairs of inputs/outputs datasets generated when machining Inconel 718 alloy with triple (TiCN/Al₂O₃/TiN) PVD-coated carbide (K 10) inserts with ISO designation CNMG 120412. A very good performance of the neural network, in terms of agreement with experimental data, was achieved. The model can be used for the analysis and prediction of the complex relationship between cutting conditions and the process parameters in metal-cutting operations and for the optimisation of the cutting process for efficient and economic production.