Study and optimization of process parameters for deformation machining stretching mode
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.2.31Keywords:
Deformation machining, Surface roughness, Hardness, Grey Relation Analysis, Analysis of Variance (ANOVA)Dimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Monolithic thin-structure parts with intricate geometric designs are employed in a variety of aeronautical, medical, marine, and automotive applications, which include the moldlines of the fuselage, turbine blades, impellers, avionic shelves, irregular fins, prostheses, bone and joint support, and skull plates. The deformation machining process is the solution to this challenging and difficult-to-manufacture high-quality components with intricate narrow geometries at competitive prices. The aim of the present study is to assess the effect of process parameters of the deformation machining process wherein a thin, floor-like structure is created by milling and is then formed using a single-point incremental forming tool. Investigation involves the design and development of tooling required for the process followed by feasibility checking of the process. To examine the impact of different process parameters on the process response, the experiments were carried out using the design of experiments. The findings of this study indicate that different process parameters, including spindle speed, tool diameter, incremental step depth, and feed rate, have a substantial impact on the process response, like thickness, surface finish, and hardness. Uneven and non-uniform surface patterns during SEM indicate that it is needed to examine the impact of process parameters. This research involves the feasibility study of a new hybrid technique of deformation machining. Conventionally, a metallic structure is produced by joining various components through welding or by fastening. These methods require additional expenditure on equipment, storage, floor space, human resources, etc., with higher lead time. Joining increases weight and reduces fatigue strength. The creation of monolithic structures can eliminate all these disadvantages.Abstract
How to Cite
Downloads
Similar Articles
- Rajni Mathur, Bharti Singh, Anjali Kalse, Veena R. Kolte, Saloni Desai, Sameer Sonawane, Examining the impact of economic cycles on India’s information technology sector , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Senthil Murugan C, Vijayabalan Dhanabal, Sukumaran D, Suresh G, Senthilkumar P, Analysis of distributions using stochastic models with fuzzy random variables , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Aarthi Monalisa M, Anli Suresh, Adoptive bancassurance models transforming patronization among the insured , The Scientific Temper: Vol. 16 No. Spl-2 (2025): The Scientific Temper
- Deepesh Bhardwaj, Niyati Chaudhary, Green Premium: Assessing the Influence of Sustainability Features on Real Estate Market Value in Delhi NCR , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- K. P. SINGH, NIDHI TRIPATHI, ANTIPSYCHOTIC MEDICATION DURING PREGNANCY AND POSSIBLE BIRTH DEFECTS , The Scientific Temper: Vol. 2 No. 1&2 (2011): The Scientific Temper
- Maysam A. Khabisi, Azar B. Masoudzade, Neda F. Rad, On the effectiveness of receiving teacher and peer feedback as a mediator on Iranian English as a Foreign Language learners’ writing skill: Mobile-mediated vs. direct instruction , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- R.R. Jenifer, V.S.J. Prakash, Detecting denial of sleep attacks by analysis of wireless sensor networks and the Internet of Things , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Sangeeta ., Jitander S. Sikka, Meenal Malik, Static deformation of a two-phase medium consisting of a rigid boundary elastic layer and an isotropic elastic half-space induced by a very long tensile fault , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Archana G, Vijayalakshmi V, Improving classification precision for medical decision systems through big data analytics application , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Shane Desai, Bhaskar K. Pandya, Analyzing the Novels of T. S. Pillai and Perumal Murugan from Indian socio-political perspective , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
<< < 16 17 18 19 20 21 22 23 24 25 > >>
You may also start an advanced similarity search for this article.

