S.R. Karnik

Analysis of Machinability During Hard Turning of Cold Work Tool Steel (Type: AISI D2)

Hard turning is an attractive replacement for grinding operations due to numerous advantages such as low capital investment, shorter setup time, higher material removal rate, better surface integrity, and elimination of cutting fluids. As a potential alternative process, there is a need to assess the machinability in high-precision and high-hardened components. The current study establishes the relationships between the cutting conditions (cutting speed, feed rate, and machining time) on machinability aspects (machining force, power, specific cutting force, surface roughness, and tool wear). The response surface methodology-based mathematical models are proposed for modeling and analyzing the effects of process parameters on machinability during turning of high chromium AISI D2 cold work tool steel using CC650WG wiper ceramic inserts. The experiments have been planned as per full factorial design. From the parametric analysis, it is revealed that the power increases with increase in feed rate, while the specific cutting force decreases, whereas the requirement of machining force is low at low values of feed rate and machining time. The response surface analysis also indicates that the surface roughness can be reduced at lower values of feed rate and machining time with higher values of cutting speed, while the maximum tool wear occurs at a cutting speed of 150 m/min for all values of feed rate.

Prediction and Minimization of Delamination in Drilling of Medium-Density Fiberboard (MDF) Using Response Surface Methodology and Taguchi Design

In this article, an attempt has been made to predict and minimize the delamination in drilling of medium density fiberboard (MDF). The experiments are carried out on LAMIPAN PB panel based on orthogonal array with feed rate and cutting speed as process parameters. The second order delamination factor models at entry and exit of the holes have been developed using response surface methodology. The parametric analysis has been carried out to study the interaction effects of the machining parameters. Taguchis quality loss function approach has been employed to simultaneously minimize the delamination factor at entry and exit of the holes. From the analysis of means and analysis of variance, the optimal combination level and the significant parameters on delamination factor are obtained. The optimization results showed that the combination of low feed rate with high cutting speed is necessary to minimize delamination in drilling of MDF.

Multiperformance Optimization in Turning of Free-Machining Steel Using Taguchi Method and Utility Concept

This article presents the application of Taguchi method and the utility concept for optimizing the machining parameters in turning of free-machining steel using a cemented carbide tool. A set of optimal process parameters, such as feed rate, cutting speed, and depth of cut on two multiple performance characteristics, namely, surface roughness and metal removal rate (MRR) is developed. The experiments were planned as per L9 orthogonal array. The optimal level of the process parameters was determined through the analysis of means (ANOM). The relative importance among the process parameters was identified through the analysis of variance (ANOVA). The ANOVA results indicated that the most significant process parameter is cutting speed followed by depth of cut that affect the optimization of multiple performance characteristics. The confirmation tests with optimal levels of machining parameters were carried out to illustrate the effectiveness of Taguchi optimization method. The optimization results revealed that a combination of higher levels of cutting speed and depth of cut along with feed rate in the medium level is essential in order to simultaneously minimize the surface roughness and to maximize the MRR.

A study aimed at minimizing delamination during drilling of CFRP composites

The aim of this study is to present the methodology of Taguchi optimization technique for minimizing the delamination at the entrance of holes in high speed drilling of carbon fiber-reinforced plastics (CFRPs). The drilling process parameters evaluated are spindle speed, feed, and point angle. The experiments were performed as per Taguchi’s L27 orthogonal array using cemented carbide (K20) twist drills. The defects observed at the entrance of drilled holes of CFRP plates were measured and the delamination factor was computed for each trial of the orthogonal array. The analysis of means (ANOM) and analysis of variance (ANOVA) were employed to determine the optimal process parameter levels and to analyze the effect of parameters on delamination factor. The confirmation tests with the optimal levels of parameters were carried out to illustrate the effectiveness of Taguchi design. The optimization results indicate that point angle is the most significant factor followed by feed and spindle speed. The results also highlight the importance of employing the higher speeds to minimize the delamination defects.

Machinability Evaluation in Unreinforced and Reinforced PEEK Composites using Response Surface Models

Polyetheretherketone (PEEK) composite belongs to a group of high performance thermoplastic polymers and is widely used in structural components. In order to improve mechanical and tribological properties, short fibers are added to unreinforced thermoplastics. Both unreinforced and reinforced PEEK composites find potential applications in manufacturing processes due to high specific properties and hence it is necessary to investigate the machining performance. This paper presents the application of response surface methodology (RSM)-based approach to study the machinability aspects of unreinforced PEEK, reinforced PEEK with 30% of carbon fibers (PEEK CF30) and 30% of glass fibers (PEEK GF30) composites with cemented carbide (K10) tool machining. The experiments are planned as per full factorial design of experiments and second order mathematical models are developed to establish the relationships between cutting conditions (cutting speed and feed rate) and machinability aspects (cutting power and specific cutting force). Analysis of variance is performed to check the adequacy of the models. The parametric analysis indicates that cutting power increases with increase in feed rate while the specific cutting force decreases for both unreinforced and reinforced composites. The results show that K10 tool provides better machinability for PEEK and PEEK CF30 materials as compared to PEEK GF30 work material.

Taguchi Approach for Achieving Better Machinability in Unreinforced and Reinforced Polyamides

Polyamide composites find wide applications in engineering fields due to favorable properties and hence replaced many traditional metallic materials. In order to increase the properties, the glass fibers are added to unreinforced polyamides. Even though polyamides are produced as near net shapes, machining is required to get the finished products. Thus, the selection of tool and cutting conditions is important in the machining of unreinforced and reinforced polyamides. This article presents the application of Taguchis quality loss function approach, a multi-response optimization method, for achieving better machinability during turning of both unreinforced polyamide (PA6) and reinforced polyamide with 30% of glass fibers (PA66 GF30). The analysis of means (ANOM) and analysis of variance (ANOVA) on multi-response signal to noise (S/N) ratio are employed to determine the optimal parameter levels and to identify the level of importance of the parameters. The ANOVA results showed that the cutting speed is the most significant factor affecting machinability. Taguchi optimization results suggest that the optimal value of feed rate and cutting speed should be kept at a low level, whereas a polycrystalline diamond (PCD) tool is beneficial over cemented carbide (K10) for machining of both PA6 and PA66 GF30 polyamides to achieve better machinability.

Modeling and Analysis of Machinability Characteristics in PA6 and PA66 GF30 Polyamides through Artificial Neural Network

The traditional metallic materials are replaced by some applications for turning process in PA6 and PA66 GF30 polyamides due to excellent properties such as high specific strength and stiffness, wear resistance, dimensional stability, low weight and directional properties. The addition of short fibers to the polyamides improves the properties over the unreinforced polyamides. As a result of these improved properties and potential applications in several fields of engineering, there is a need to understand the machining of unreinforced and reinforced polyamides. Selection of cutting tool and process parameters is important in machining of these composites. This article presents the application of artificial neural network (ANN) modeling to assess the machinability characteristics of unreinforced polyamide (PA6) and reinforced polyamide with 30% of glass fibers (PA66 GF30). The effects of process parameters such as work material, tool material, cutting speed, and feed rate on three aspects of machinability, namely, machining force, power, and specific cutting force have been analyzed through a multilayer feed forward ANN. The input—output patterns required for training are obtained through turning experiments planned as per full factorial design. The model analysis revealed that the minimum machining force results at low feed rate and independent of cutting speed, whereas the power is minimal when both the cutting speed and feed rate are at low levels for PA6 and PA66 GF30 polyamides machining irrespective of the cutting tool. On the other hand, the specific cutting force is minimal at low cutting speed and high feed rate in case of PA6 material, whereas high values of cutting speed and feed rate are essential for minimizing the specific cutting force for PA66 GF30 polyamide machining.

Some Studies in Metal Matrix Composites Machining using Response Surface Methodology

The present study establishes the relationship between cutting conditions and machinability characteristics during the turning of metal matrix composites (MMC). The investigation aims at determining the effects of cutting speed and feed rate on machining force, cutting power, and specific cutting force by developing second-order mathematical models using response surface methodology (RSM). Aluminum alloy reinforced with 20% of SiC particulates (A 356/20/SiCp-T6) were machined using a polycrystalline diamond (PCD) tool. The experiments have been planned as a full factorial design of experiments (FFD). The analysis of variance (ANOVA) was performed to check the adequacy of the mathematical models. The parametric analysis reveals that the machining force and cutting power increase with increase in feed rate while the specific cutting force decreases.

Surface roughness analysis in high-speed drilling of unreinforced and reinforced polyamides

In this work, surface roughness study in high-speed drilling of unreinforced polyamide (PA6) and reinforced polyamide with 30% of glass fibers (PA66 GF30) using cemented carbide (K20) tool has been carried out. The experiments were planned as per full factorial design of experiments. The effects of cutting speed and feed rate on centerline average surface roughness, maximum peak to valley height, and peak counts have been analyzed by developing response surface methodology based third-order mathematical models. The parametric analysis clearly indicates the influence of reinforced fiber on surface finish when high-speed cutting in drilling is used.

OPTIMAL MQL AND CUTTING CONDITIONS DETERMINATION FOR DESIRED SURFACE ROUGHNESS IN TURNING OF BRASS USING GENETIC ALGORITHMS

The evolving concept of minimum quantity of lubrication (MQL) in machining is considered as one of the solutions to reduce the amount of lubricant to address the environmental, economical and ecological issues. This paper investigates the influence of cutting speed, feed rate and different amount of MQL on machining performance during turning of brass using K10 cemented carbide tool. The experiments have been planned as per Taguchis orthogonal array and the second order surface roughness model in terms of machining parameters was developed using response surface methodology (RSM). The parametric analysis has been carried out to analyze the interaction effects of process parameters on surface roughness. The optimization is then carried out with genetic algorithms (GA) using surface roughness model for the selection of optimal MQL and cutting conditions. The GA program gives the minimum values of surface roughness and the corresponding optimal machining parameters.