Abstract
Intelligent manufacturing technologies and systems are entering a new era with the rapid advances in all important fields of engineering and technology. The goal of this special issue is to provide a multidisciplinary platform for researchers in the field to publish the results of their scientific progress and technologic advancements, with the topics focusing on intelligent manufacturing technologies and systems in the areas of machining, grinding and measurement. This special issue is based on some of the presentations at the 11th Asia-Pacific Conference on Materials Processing (APCMP 2014) held in Auckland, New Zealand, 6–11 July 2014. The conference has a much broader scope, but this special issue only gathered papers in the areas of intelligent manufacturing technologies and systems.
In the field of engineering in medicine, intelligent manufacturing technologies have been applied to create non-invasive super precision brain surgical systems and procedures. In the area of minimally invasive neurosurgery, the paper of Li et al. entitled “Ultrasonic vibration-assisted micro-hole forming on skull” presented an intelligent technology (an ultrasonic vibration assisted micro burr hole forming technique) which bridges the gap between the need for a micro burr hole to be opened on the skull to expose the enclosed brain for further operation and the proper technology available. With the assistance of ultrasonic vibration (29.7 kHz), a micro hole has been successfully formed on skulls with a 300 μm diameter conically-tipped tool, free of cutting and chips. Furthermore, since the ultrasonic vibration tool can fragment the hard bone tissue without causing damage to the soft tissue beneath the skull, brain fluid leakage can be avoided. The next generation of non-invasive or minimally invasive neurosurgery can be established based on these findings.
Chan and Xu in their paper entitled “Evaluation and comparison of lubrication methods in finish machining of hardened steel mould inserts” discussed the effects of Near-Dry, Flood and minimum quantity lubrication (MQL) machining on surface roughness, tool wear, dimensional accuracy and machining time. The results revealed that there were no significant differences between these three lubrication methods. Nevertheless, MQL machining produced more accurate results than Near-Dry machining in dimensional deviation. The regression models show that feed-rate has a larger effect on surface roughness and machining time than step-over, while depth of cut has no significant effect on surface roughness. When combining the MQL technique with the right cutting conditions in modern die and mould manufacturing, machining time and polishing time can be saved, which leads to an overall saving in production cost. Using the Near-Dry and MQL techniques for different finish machining situations can therefore be a good economical solution.
Wavelet theory can be applied to several subject areas. For example, wavelet transform has found its application in predicting surface toughness and monitoring chip breakage. Tangjitsitcharoen et al. have two papers reporting on their work utilising wavelet transforms in machining processes. The paper entitled “A wavelet approach to predict surface roughness in ball-end milling” reports how the Daubechies wavelet transform is employed to analyse the in-process surface roughness. They proved that the in-process surface roughness can be predicted effectively under various cutting conditions using the proposed monitoring system. In the paper entitled “Monitoring of chip breaking and surface roughness in computer numerical control turning by utilizing wavelet transform of dynamic cutting forces”, the researchers proved that the chip-breakage formation can be monitored clearly while the surface roughness can be accurately predicted based on the proposed wavelet transform technique and the decomposition method.
Burr formation during a precise end-face grinding process directly affects the quality of the product. In their paper entitled “Finite element analysis of burr formation and an automatic online micro-deburring method in precise end-face grinding process”, Dong et al. carried out an in-depth study of burr formation and developed burr-removal equipment that can effectively remove the micro-burr caused by the end-face grinding. This is an automated process compared to the often-used manual offline burr removal method that is hard to control the accuracy and easy to destroy the integrity of the working edges of the workpiece.
The final paper entitled “A study of ultra-precision ball rotating displacement measurement using laser focus deviation probes” by Lu et al. presented an ultra-precision ball rotating displacement measurement setup based on laser focus deviation. A dual probe setup is also studied to evaluate diameter variation of a ball with errors introduced by misalignment and spindle radial vibration being automatically eliminated. The study concludes that optical probe-based ball displacement and diameter variation measurement are suitable for in-situ application with a high throughput and accuracy.
As manufacturing moves into an era of Smart Factories in the context of “Factories of the Future”, some fundamental issues in the areas of machining still pose challenges for practical solutions. The papers in this special issue have highlighted some of these issues and the efforts underway to meet these challenges.
The guest editors are thankful to Professor Paul Maropoulos, Editor-in-Chief of Journal of Engineering Manufacture who kindly agreed to bring out this Special Issue based on the expanded and re-reviewed papers presented in APCMP 2014. We are also grateful to the assistance provided by Martin McDonald, Assistant Editor – Peer Review Management STM, Engineering and Materials Science at SAGE Publications Ltd.