Predicting Tool Wear in Turning Nickel Iron Chromium Superalloy Using Deep Learning from Machined Surface Images
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Predicting Tool Wear in Turning Nickel Iron Chromium Superalloy Using Deep Learning from Machined Surface Images

Predicting Tool Wear in Turning Nickel Iron Chromium Superalloy Using Deep Learning from Machined Surface Images


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About the Book

The need for more robust materials for military jet engines during World War TT, marked the genesis of superalloys. These alloys can retain their high strength even at high temperatures and are prominently used in aerospace and power generation sectors where corrosion resistance and maintaining parent material properties at high temperatures are necessary. Superalloys are composed of a combination of metals primarily from the VTTTB group in the periodic table, such as Ni, Co, Cr, and Fe. These alloys also contain smaller proportions of other essential elements like Al, Ta, Mo, Nb, and Ti. These are topologically closed packed with face-centered cubic (FCC) structures. These superalloys possess higher mechanical strength, viz., higher yield and tensile strength and also provide excellent stability at high temperature. In addition, these alloys show excellent resistance properties for creep, erosion, corrosion and oxidation under critical operating conditions. Because of the excellent properties, superalloys have found applications in aircraft, aerospace, marine, power generation, chemical as well as oil and petrochemical industries. Superalloys are also called 'heat resistance alloys' as they can withstand high temperatures (up to 816 OC) without undergoing any original property change. Hence, they are also used in small household electrical appliances to oversized industrial furnaces. Some of the electrical applications of superalloys are loading coils, transducers, audio transformers, magnetic amplifiers, shielding, relays, etc.

Machining is one of the prime stages in the manufacturing process, which removes the extra material from the object and gives the necessary shape to it. The machining-based manufacturing science is striving continuously to reduce the cost of machining, increase productivity, diminish the environmental impact, and improve the operator's safety. However, superalloys possess poor thermal characteristics (low thermal conductivity and diffusivity), greater work-tool affinity and a tendency to work harden and thus fall into the hard-to-cut materials group. During the machining process, the cutting insert experiences elevated thermal and mechanical loads, leading to distinct wear patterns, namely, flank wear (FW), crater wear, and nose wear.


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Product Details
  • ISBN-13: 9798224388271
  • Publisher: Draft2digital
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Weight: 377 gr
  • ISBN-10: 8224388271
  • Publisher Date: 05 Apr 2024
  • Height: 279 mm
  • No of Pages: 156
  • Spine Width: 8 mm
  • Width: 216 mm


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Predicting Tool Wear in Turning Nickel Iron Chromium Superalloy Using Deep Learning from Machined Surface Images
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