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Abstract:The fundamental machining techniques were established long back. However, machining operations consume a large amount of money annually worldwide. Advanced engineering materials, such as ceramics, MMC, Titanium (Ti), Inconel and its alloys offer properties like high strength at elevated temperature, chemical and wear resistance. Therefore, these materials are being used in making components for aerospace, defence, nuclear, orthopaedic, and marine applications. However, these alloys are classified as a 'difficult-to-cut' due to their poor thermal conductivity, reactivity with tool material, high strength and low modulus of elasticity. Besides various measures to improve machinability of these alloys, the key areas of research focuses on selection of cutting tool material and its geometry, use of various machining environments and selection optimum processing conditions to improve tool life, metal removal rate and decrease cutting forces and surface roughness of the machined component. This paper focuses on machinability of titanium alloys under various machining environments such as -dry, flooded and mist jet cooling. The main objective of the paper is to understand the effect of change in machining environment on various aspects of machining of titanium alloys viz. tool wear, cutting forces, surface roughness and chip morphology. It is evident that the flooded and mist jet environments effectively cool the cutting zone and reduce the cutting forces and tool wear 30 and 40% respectively. On the other hand, flooded lubrication and mist jet cooling improves surface quality 20-30% as compared to dry condition machining. Based on this study, optimum conditions to improve machinability of Ti6Al4V alloys are presented.

The paper consists of optimizing the total distance traveled by the Plasma Cutting Tool Head. It is cross-functional implementation traveling salesman problem to the core manufacturing process of plasma cutting. This study contributes to reduce the total rapid traverse length (Total Through-Air Travelled Distance) by the cutting tool (Plasma Beam), which is totally a non-productive as well as non-value adding process contributing to the machine running costs and cycle time of the product directly and indirectly. For deriving this optimal sequence for the plasma cutting head, a heuristic algorithm is used. This algorithm calculates an optimal solution for a problem creating the best possible sequence. The greedy algorithm follows the problem-solving heuristics of making a locally optimal choice at every stage, finally integrating a globally optimal solution. Hence after deducing this optimal sequence and when accompanied by the Plasma Cutting tool, it resulted in the least distance traveled, contributing to minimizing cost and energy savings of the machine and simultaneously reducing the total traveled distance and similarly the cycle time.