This study is concerned with the effects of process parameters such as speed, feed, tilt angle, and tool profile on mechanical and microstructural properties of stir processed, solution treated, and artificially aged AA 2014-T6. The process was carried out with an input condition at rotational and traverse feeds of 600–1400 RPM and 30–90 mm/min, respectively. Five distinct shapes of the tool pin such as triangular, hexagonal, threaded, conical, and cylindrical have been selected to carry out the process with varied tilt angle of 1°–3°. In order to exemplify the status of processed materials, optical, scanning electron microscopy and Vickers hardness measurement along with grain analysis were performed on various regions of processed cross sections. According to the results, combination of processing speed and rotational speed affects the microstructure and associated grain size and average hardness of the processed region.

In recent years use of image processing techniques for texture analysis of machined surface is gaining importance in the field of manufacturing. This manuscript addresses texture identification methodology using Wavelet transform and artificial intelligence techniques. Captured images of machined surface using Electric discharge machining, milling, sand blasting and shaping is decomposed in to sub images and then discrete wavelet transform is applied on the sub images. To select the base wavelet minimum permutation entropy criterion is applied and statistical features were calculated from the base wavelet. Training and testing of feature vector is performed using two artificial intelligence techniques support vector machine and artificial neural network for identifying textured surface images.100 % training identification of textured images is obtained using support vector machine and artificial neural network and 87.5 % and 100 % testing identification of textured images is obtained using support vector machine and artificial neural network respectively. Results revealed that the present methodology identifies machined surface images with high accuracy.

The Internet of Things (IoT) is formed by a set of physical objects with embedded sensors, connected using a network so that they can collect and exchange data. Though the concept looks simple, its deployment in industry has enormous potential to bring major business benefits and radical change. This chapter examines IoT technology and how it is being used in the corporate environment. Based on a review of existing literature and case examples, the various definitions and elements of IoT are discussed, followed by an assessment of how IoT is being used and what benefits are being delivered. Some key emergent themes are then examined – security aspects, the significance of 5G networks, and the need for an IoT strategy and project implementation guidelines. The chapter concludes by outlining possible areas for future research and suggests a step-change in the mega-infrastructure connecting IoT devices is imminent.