Investigation into minimal-cutting-fluid application in high-speed milling of hardened steel using carbide mills

Applying cutting fluid in a metal-cutting process can reduce the rate of tool wear and improve surface quality. However, cutting fluid has negative effects on the working environment and the use of cutting fluid also increases the total production cost. Therefore, there is a need to reduce the use of cutting fluid during machining. To serve that purpose, a minimal-cutting-fluid technique was studied. In the present work the cutting fluid was applied in a form of a high-velocity, narrow, pulsed jet at a rate of 2 ml/min. The performance of machining with pulsed-jet application was studied in high-speed milling of hardened steel, compared to dry machining and machining with flood application. The results clearly show that compared to dry machining and machining with flood application, machining with pulsed-jet application lowers cutting forces, reduces tool wear, increases tool life, and improves surface roughness, especially when machining with high cutting velocity. Moreover. the amount of cutting fluid consumed at the rate of 2 ml/min is a drastic reduction compared to flood application. Also, no harmful oil mist is generated during the pulsed-jet application. In conclusion, the pulsed-jet application can be applied to milling process of hardened steel using ball end mills; it reduces the negative effects to the environment, improves machining performances, and consequently reduces total production cost. (C) 2008 Elsevier Ltd. All rights reserved

Machining applications

There has been an increasing demand for biomedical devices including various instruments, apparatuses, implants, in vitro reagents, and similar articles to diagnose, prevent, or treat diseases, improve human health, prolong human life, and recover from serious injuries. Biomedical devices that we utilize are not only continuously getting smaller and more effective but are also designed with more customized functionalities. In response to that demand, new design innovations, new materials, and prototypes of novel medical devices have been introduced on a regular basis. Design, prototyping, and manufacturing techniques for these materials and designs have also been continuously developing in parallel to the needs in biomedical device demands. There have been a large number of books written about design and manufacturing of various products but biomedical device manufacturing remains less covered than other well-known microelectronics and consumer products. This book brings authors from institutions around the world, perhaps one of the few wide-ranging books on manufacturing processes for medical devices with coverage of various materials including metals and polymers. The book aims to reach audiences such as practicing engineers who are working in medical device industry, students in the biomedical device manufacturing courses, and faculty/researcherswho are conducting research in medical device design, prototyping, and manufacturing

Modelling and Prediction of Surface Roughness and Power Consumption Using Parallel Extreme Learning Machine Based Particle Swarm Optimization

Prediction model allows the machinist to determine the values of the cutting performance before machining. Modelling using improved extreme learning machine based particle swarm optimization, IPSO-ELM has less parameters to adjust and also takes real number as particles while decreasing the norm of output weights and constraining the input weight and hidden biases within a reasonable range to improve the ELM performance. In order to solve the multi objectives modelling problem, we have proposed a parallel IPSO-ELM. In this research work, the best input weights and hidden biases for different performance were identified. The proposed method was able to model the training and the testing set with minimal error. The predicted result from the designed model was able to match the experimental data very closely