Volume 13, Issue 3

The present paper deals the application of Taguchi method with grey relational analysis to optimize the machining parameters with multiple responses in electrochemical machining (ECM) of Al/B 4 C metal matrix composites. Experiments were conducted on a Metatech ECM setup and L 27 orthogonal array was chosen for the experiments. The electrochemical machining parameters namely applied voltage, feed rate, electrolyte concentration and reinforcement content were optimized based on multiple responses, i.e. material removal rate, surface roughness and radial over cut. The morphology of the machined surfaces was studied with scanning electron micrographs. The optimum machining parameters are calculated by using grey theory and results are compared with ANOVA. The results show that the feed rate and electrolyte concentration are the most significant parameters which affect the multiple machining responses simultaneously. Experimental results show that the responses in ECM can be improved effectively through this approach.

This paper proposes a set of four elliptical features that can enhance the programming capabilities of a modern CNC system. Namely, a real-time interpolation algorithm for motion generation along an ellipse and its offset, machining of an elliptical pocket, and drilling a series of equidistant holes along an elliptical path. The paper analytically describes the implementation of the new functions while the G-codes, along with their complementary requisite data needed to be introduced in the CNC part program, are exemplified with simulation and actual machining tests for each feature.

This paper presents a pragmatic approach to the study of the influence of tasks time variability in the performance of linear and parallel assembly lines. Discrete event simulation is used to assess the performance of several configurations for two assembly line balancing problems, and for four different levels of time variability. From the simulation studies, a set of equations were developed allowing the prediction of the assembly line performance, measured by the cycle time for common ALBPs, with considerable accuracy. These equations show the interactions between the sum of average task times, the balancing difficulty of the problem and the tasks time variability, as well as the number of workstations and their level of parallelism. With these equations it's possible to reduce the search for the best candidate solutions (number of workstations and level of parallelism) for a given target cycle time, considering the time variability level of the problem. With this approach, the assembly line designer is able to select beforehand the possible feasible solutions in a more practical way when using simulation software.

This work describes the development and manufacture of micro and meso extrusion dies used to extrude metal materials. The die design was based on different extrusion angles and diameters of input materials. An extrusion die was made to input material measuring 1 mm and for reduction to 0.8 mm with a 30° angle of extrusion. For the same diameter of material, another two dies were manufactured with extrusion angles of 45° and 60°. For meso sized extrusion, another three dies were made and the diameter of the input material was 4 mm with a reduction to 3 mm and extrusion angles of 30°, 45° and 60°. During the machining of the extrusion dies, high speed steel (HSS) drills were used with a tip angle according to the extrusion angles. After machining, the dies were treated thermally and polished to diminish the friction coefficient between the part to be extruded and the die. The results of the machining process indicate that extrusion dies can be manufactured using quick HSS drill and polishing can be done using diamond paste with satisfactory results.

Fused Deposition Modeling (FDM) is an additive manufacturing technology for rapid prototyping that can build intricate parts in minimal time with least human intervention. The process parameters such as layer thickness, orientation, raster angle, raster width and air gap largely influence on dimensional accuracy of built parts which can be expressed as change in length, width and thickness. This paper presents experimental data and a fuzzy decision making logic in integration with the Taguchi method for improving the dimensional accuracy of FDM processed ABSP 400 parts. It is observed that length and width decreases but thickness shows positive deviation from desired value of the built part. Experimental results indicate that optimal factor settings for each response are different. Therefore, all the three responses are expressed in a single response index through fuzzy logic approach. The process parameters are optimized with consideration of all the performance characteristics simultaneously. Finally, an inference engine is developed to perform the inference operations on the rules for fuzzy prediction model based on Mamdani method. Experimental results are provided to confirm the effectiveness of the proposed approach. The predicted results are in good agreement with the values from the experimental data with average percentage error of less than 4.5.

In the present work, an attempt has been made to solve the correlated multi-response optimization problem of wire electrical discharge machining (WEDM) of EN-31 steel. The experimental investigation have been carried out to evaluate the best process environment which could simultaneously satisfy multiple quality characteristics such as material removal rate (MRR), surface roughness (Ra) and dimensional deviation (DD). In view of the fact that traditional Taguchi method cannot solve a multi response optimization problem, weighted principal component analysis (WPCA) has been coupled with Taguchi method to overcome this limitation. The multiple responses are converted into a single response using principal component analysis so that influence of correlation among the responses can be eliminated. Values of individual principal components multiplied by their priority weight were added to calculate the composite principal component defined as multi-response performance index (MPI). MPI is used as response for optimization using Taguchi's L 27 orthogonal array. From analysis of variance, pulse on time was found to be the most significant parameter. Finally, the optimal result obtained was verified through confirmatory test.

Hard turning is the process of machining hardened steels that are above 45HRC. In manufacturing, hard turning has emerged as a potential area because of its many advantages over grinding as a finishing operation. In the present paper, a review is done on Design of Experiment (DOE) techniques that have been employed on various hard turning processes by researchers. DOE is one of the widely used methods for experimental study of many manufacturing processes in engineering. It is a statistical approach in which a mathematical model is developed through a minimum of experimental runs. DOE predicts the possible output, based on the given input parameters in an experiment. The present study predominantly focuses on the usage of Response Surface Method, Taguchi’s method and Factorial method in hard turning.