NUST Institutional Repository

Laser-based Ultrasonic Assisted Low Speed Micro Milling of Super Alloys

Show simple item record

dc.contributor.author Haidary, Yadullah
dc.date.accessioned 2023-08-29T04:30:36Z
dc.date.available 2023-08-29T04:30:36Z
dc.date.issued 2023
dc.identifier.other 318519
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/37745
dc.description Supervisor : Dr. Syed Hussain Imran Jaffery en_US
dc.description.abstract Inconel-718 is a nickel-based super alloy with exceptional mechanical properties; including high yield, creep-rupture, and high tensile strength at temperatures up to 977 K. Along with its frequent uses in high temperature fasteners and bolts, and high-speed aircrafts’ parts such as spacers, wheels, buckets, and engines, Inconel-718 have also its applications in automotive, submarine and biomedical industries. Although this nickel-based alloy is an ideal material for high temperature and high corrosive environment, it is difficult to handle while machining it. To improve the machinability of the alloy as compared to the conventional micro milling, an experimental setup has been designed using laser-based ultrasonic assisted low speed micro milling (LLUMM). This study focuses on low-speed ultrasonic milling of laser-cut constantdepth slots which are created on a workpiece of Inconel-718 using Laser Marking Machine. Effects of cutting parameters including cutting speed, feed rate, depth of cut, amplitude of tool vibration and tool coating surface roughness, tool wear and burr formation are investigated, using each factor at four different levels. Cutting tool’s diameter is kept fixed at 0.5mm with uncoated and coated materials, including TiAlN, TiSiN, and nACo. A Design of Experiment technique, namely Taguchi L16 array, is used to create experiments. Experimental data is statistically analysed to identify the best and worst set of parameters for achieving the desired results. Optimization of individual response variables is carried out using signal to noise ratios, with the help of Minitab-21, while multi-objective optimization uses Weighted Grey Relational Grades (W-GRG) in which Grey Relational Analysis is coupled with Principal Component Analysis (GRA-PCA). It has been revealed by validation experiments that LLUMM produces better results as compared to traditional micro milling. en_US
dc.language.iso en en_US
dc.publisher School of Mechanical & Manufacturing Engineering (SMME), NUST en_US
dc.relation.ispartofseries SMME-TH-911;
dc.subject Inconel-718, LLUMM, Laser-Cut, Burr Formation, Weighted Grey Relational Grades, GRA-PCA. en_US
dc.title Laser-based Ultrasonic Assisted Low Speed Micro Milling of Super Alloys en_US
dc.type Thesis en_US


Files in this item

This item appears in the following Collection(s)

  • MS [221]

Show simple item record

Search DSpace


Advanced Search

Browse

My Account