Prediction of material removal rate in wire electrical discharge machining of Aluminum Composites for Automotive Components Sree Vidyanikethan Engineering College

Format:

Book

Conference/Event

Author/Creator:

Natarajan, Manikandan, author.

Contributor:

Joseph Selvi, Binoj

Katta Clement PhD, Varaprasad

Palampalle, Bhanu

Conference Name:

International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility (2020-09-25 : Chennai, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2020

Summary:

Wire Electrical Discharge Machining (WEDM) is a contemporary approach of material removal which is conceived from the concept of Spark Erosion Machining process. Wire Spark Erosion Machining which is known as WEDM, predominantly employed for removing material from hard materials and also especially used for making intricate shapes on any electrically conductive work material with irrespective of the hardness. Composite materials offers improved mechanical properties depends upon the constituents to be added. Graphene is identified as outstanding reinforcing element which provide support to enhance the desired properties of aluminium metal matrix composites in a considerable manner. In this present exploration an analysis has been performed on WEDM of Al-GNP composites. Pulse on time (s), pulse off time (s) and servo voltage (V) are deemed as input process parameters in this present exploration. Material removal rate is deemed as desired performance measure which is need to be improved. Taguchi's design approach has been adopted for designing and analyzing the experimental runs. An L27 Orthogonal Arrays was employed adopted to conduct the experimental runs. The influence of process variables on desired performance measures such as material removal rate were analyzed by Taguchi's single response analysis. The significance of independent process variables on desired performance measure is examined by ANOVA analysis. Multiple regression analysis has been developed for correlating the relationship among the selected input process variable and desired performance measures. The comparison results proved that the values envisaged from the developed regression models were closer with the experimental observations

Notes:

Vendor supplied data

Publisher Number:

2020-28-0399

Access Restriction:

Restricted for use by site license