Energy Efficiency Assessment in Plunge-Face Grinding of Cemented Tungsten Carbide Cutting Inserts

Author(s)

Carreira, L. A. S. ; Hassui, A. ; Ventura, C. E. H.

• Document type: Journal article
• Source: INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY; v. N/A, p. 10-pg., 2023-05-04.

Abstract

Due to the high demand for electricity in the manufacturing industry and the efforts to reduce environmental impact, investigations to increase energy efficiency in machining processes have been increasingly carried out. However, information on the behavior of insert grinding process is rarely found. Within this context, this work presents results related to the influence of grinding parameters and abrasive tool characteristics on the energy efficiency during plunge-face grinding of cemented tungsten carbide cutting inserts. For this, grinding forces and consumed electrical energy were measured during the process and sustainability indexes to analyze the relation between insert quality (surface and edge roughness) and consumed energy were calculated in different process conditions. As a result, it was observed that grinding parameters had little influence on insert quality, but an increase in the axial feed speed reduced the consumed energy in approximately 60%, leading to sustainability indexes next to one, i.e., to a greater equilibrium between energy consumption and quality properties. (AU)

• FAPESP's process: 17/12304-5 - Multi-user equipment approved in grant 15/15622-2: CNC grinding machine for cutting insert preparation
• Grantee: Carlos Eiji Hirata Ventura
• Support Opportunities: Multi-user Equipment Program
• FAPESP's process: 15/15622-2 - Influence of grinding parameters in the manufacturing of cemented tungsten carbide inserts on their performance in turning of a titanium alloy
• Grantee: Carlos Eiji Hirata Ventura
• Support Opportunities: Research Grants - Young Investigators Grants
• FAPESP's process: 17/12309-7 - Multi-user equipment approved in grant 15/15622-2: microscope for three-dimensional image analysis
• Grantee: Carlos Eiji Hirata Ventura
• Support Opportunities: Multi-user Equipment Program