PSG College of Technology

About: PSG College of Technology is a based out in . It is known for research contribution in the topics: Machining & Thin film. The organization has 3174 authors who have published 3575 publications receiving 40690 citations.

3Rs and circular economy

Abstract: The circular economy is considered as the legs of sustainability since it influences the entire textile supply chain process. The circular economy is governed by 3Rs, namely Reduce, Reuse, and Recycle, which are the major strategies for eco-friendly processing of textile/apparel products. Both circular economy and 3Rs concept are interchangeable in waste management process. In 3Rs concept, the word Reduction has much wider scope and emphasis in waste reduction at various sequences of production process and different stages of consumption. The quantity of waste generated in the textile/apparel industry could be minimized through planning and strategic policies. As our textile and apparel industries are consumer based, eco-friendly material is the need of the hour everywhere, and it ensures that the products could be utilized for reengineering or to produce components of refashionable material in every production cycle. The new thinking of “take-make-dispose” creates mentality of a linear economy. Recycling/upcycling also plays a major role in the circular economy interconnecting environmental and social dimensions. Hence, this chapter addresses the major key attributes and research opportunities with respect to 3Rs and circular economy and their implications focusing toward textile/fashion industry with the possibility of diverting textiles from landfill and developing the clothing industry for the reuse and recycling of textiles.

Tribological investigations on MoS2-based nanolubricant for machine tool slideways

Abstract: The present study evaluates the tribological characteristics of molybdenum disulphide (MoS2)-based nanolubricant for its use in machine tool slideways. MoS2 nanoparticles were synthesized and physi...

EMG controlled bionic arm

Abstract: The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements are quite small. On the contrary, prosthetic hands are just a pale replication of the natural hand, with significantly reduced grasping capabilities and no sensory information delivered back to the user. Several attempts have been carried out to develop multifunctional Prosthetic devices controlled by electromyography (EMG) signals (myoelectric hands), harness (kinematic hands), dimensional changes in residual muscles, and so forth, but none of these methods permits the “natural” control of more than two DoFs. This paper presents a review of the traditional methods used to control artificial hands by means of EMG signal, in both the clinical and research contexts, and introduces what could be the future developments in the control strategy of these devices. This paper describes a novel approach to the control of a multifunctional prosthesis based on the classification of myoelectric patterns. It is shown that the myoelectric signal exhibits a deterministic structure during the initial phase of a muscle contraction. Features are extracted from several time segments of the myoelectric signal to preserve pattern structure. These features are then classified using an artificial neural network. The control signals are derived from natural contraction patterns which can be produced reliably with little subject training. The new control scheme increases the number of functions which can be controlled by a single channel of myoelectric signal but does so in a way which does not increase the effort required by the amputee. Results are presented to support this approach.