Optimization of Turning Parameters for Zirconia-Toughened Alumina-Based Self-Lubricating Composite Cutting Tool Materials Using Grey Relational Approach
Dry machining processes frequently encounter challenges, including increased cutting forces, high friction, and poor surface finishes, primarily due to the absence of lubrication. To address these issues, this study introduces the development of solid-lubricating cutting tools (SLTs) by incorporating elements such as Nichrome, silver, molybdenum, strontium sulfate, and calcium fluoride into a Zirconia Toughened Alumina matrix. The objective was to enhance the tribological performance of cutting tools for turning AISI 4340 steel under dry conditions. An experimental design based on the L8 mixed orthogonal array was employed, and the Grey-Taguchi analysis method was used to optimize multiple performance measures, including cutting forces, coefficient of friction, and surface roughness. Among the fabricated tools, SLT 4 exhibited superior performance. The results demonstrated a 73% reduction in cutting forces, a 45% decrease in the coefficient of friction, and a 66% improvement in surface finish compared to the unmodified base tool. These enhancements were attributed to the formation of a stable self-lubricating layer on the tool surface during machining. A confirmation experiment validated the optimization outcomes, confirming the effectiveness of the proposed tool composition.
Authors
- Siva Prasad Dora (ORCID: https://orcid.org/0000-0001-5012-3840)
- Mathala Prithvi Raj (ORCID: https://orcid.org/0000-0001-8395-3883)
- Pujari Srinivasa Rao (ORCID: https://orcid.org/0000-0002-5183-5687)
- Bagadi Pradeep Kumar (ORCID: https://orcid.org/0000-0003-2642-7259)
- M. Sreenivasa Rao (ORCID: https://orcid.org/0000-0002-9808-7655)
Institutions
- Indian Institute of Management Visakhapatnam (IN)
- GITAM University (IN)
Publication Details
- Journal
- International Journal of Automotive and Mechanical Engineering
- Published
- 2025-09-01
- DOI
- https://doi.org/10.15282/ijame.22.3.2025.2.0959
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Gandhi Institute of Technology and Management