An intelligent and automated system for EDM hole drilling of super alloys
This paper introduces an intelligent and automated system proposed for EDM hole drilling of super-alloys in manufacturing and re-manufacturing stages of products used in aerospace, die/mold and medical surgery. The system is a user-friendly computer-based program, which guides the end-user in order to perform sustainable and effective process. To accomplish the goals of the work, a well-planned workshop tests have been performed via drilling of micro and macro-scale holes (0.4-3 mm) on Ti-6AI-4V and Inconel 718 alloys, which are commonly used in aerospace industry and medical sector for manufacturing of highly critical components. The experimental data was refined and analysed using ANOVA to obtain parameter's relations and mathematical modelling for optimisation. ANFIS has been adopted to correlate the EDM hole drilling parameters (i.e. pulse current, pulse duration/interval, capacitance, material removal rate, electrode wear and surface roughness) for fulfilling reliable, cost/time effective and efficient hole making operations.
Multiple performance characteristics optimization for Al 7075 on electric discharge drilling by Taguchi grey relational theory
Electric discharge drill machine (EDDM) is a spark erosion process to produce micro-holes in conductive materials. This process is widely used in aerospace, medical, dental and automobile industries. As for the performance evaluation of the electric discharge drilling machine, it is very necessary to study the process parameters of machine tool. In this research paper, a brass rod 2 mm diameter was selected as a tool electrode. The experiments generate output responses such as tool wear rate (TWR). The best parameters such as pulse on-time, pulse off-time and water pressure were studied for best machining characteristics. This investigation presents the use of Taguchi approach for better TWR in drilling of Al-7075. A plan of experiments, based on L27 Taguchi design method, was selected for drilling of material. Analysis of variance (ANOVA) shows the percentage contribution of the control factor in the machining of Al-7075 in EDDM. The optimal combination levels and the significant drilling parameters on TWR were obtained. The optimization results showed that the combination of maximum pulse on-time and minimum pulse off-time gives maximum MRR.
Dimensional Errors of Fixtures, Locating and Measurement Datum Features in the Stream of Variation Modeling in Machining
Machining processes are usually multi-station processes involving a large number of operations and several locating datum changes. Machining errors are thus introduced, transformed and accumulated as the workpiece is being machined. This paper introduces procedures for expressing the influence of errors in fixtures, locating datum features and measurement datum features on dimensional errors in machining. These procedures are essential in the derivation of the Stream of Variation model of dimensional machining errors using the CAD/CAPP parameters of the machining process. The linear state space form of the Stream of Variation model allows for advanced control theory achievements to be employed in formal solutions to problems in multi-station machining. Modeling procedures presented in this paper were experimentally verified in machining of an automotive cylinder head.