Bobby Oedy Pramoedyo Soepangkat

Optimization of Recast Layer Thickness and Surface Roughness in the Wire EDM Process of AISI H13 Tool Steel Using Taguchi and Fuzzy Logic

In this study, the optimization of recast layer thickness and surface roughness (SR) simultaneously in a Wire-EDM process by using Taguchi method with fuzzy logic has been applied. The Wire-EDM process parameters (arc on time, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., recast layer thickness and SR. Based on the Taguchi method, an L18 mixed-orthogonal array table was chosen for the experiments. Fuzzy reasoning of the multiple performance characteristics has been developed based on fuzzy logic, which then converted into a fuzzy reasoning grade or FRG. As a result, the optimization of complicated multiple performance characteristics was transformed into the optimization of single response performance index. Experimental results have shown that machining performance characteristics of Wire-EDM process can be improved effectively through the combination of Taguchi method and fuzzy logic.

The Use of Taguchi-Grey-Fuzzy to Optimize Performance Characteristics in Turning of AISI D2

In this paper, the optimization of surface roughness, cutting force, feed force and tool life in a turning operation was investigated by using Taguchi method and fuzzy logic. The experiment were conducted under varying cutting speeds, feed rates, depths of cut and noses radius. An orthogonal array, the signal-to-noise (S/N) ratio, grey relational analysis, grey-fuzzy reasoning grade and analysis of variance were employed to the study the performance characteristics in the turning AISI D2. Experimental results have shown that machining performance characteristics in turning process can be improved effectively through the combination of Taguchi method and fuzzy logic.

Optimization of Surface Roughness and Recast Layer Thickness in the Wire-EDM Process of AISI D2 Tool Steel Using Taguchi-Grey-Fuzzy

In this paper, the optimization of surface roughness and recast layer thickness of a WEDM process of AISI D2 steel was investigated by using Taguchi method, grey relational analysis and fuzzy logic. The experiments were conducted under varying flushing pressure, on time, open voltage, off time and servo voltage. An orthogonal array, signal-to-noise (S/N) ratio, grey relational analysis, grey-fuzzy reasoning grade and analysis of variance were employed to the study of the multiple performance characteristics. Experimental results have shown that machining performance characteristics in WEDM process of AISI D2 steel can be improved effectively through the combination of Taguchi method, grey relational analysis and fuzzy logic.

Optimization of Cable Ties Injection Molding Process Using Back Propagation Neural Network and Genetic Algorithm (BPNN-GA)

Setting parameters in the injection molding machine play an important role to the quality of cable ties product. They affect not only to the number of the rejection products but also to their tensile yield strength. The goal of this study is to obtain a combination of process parameters such as nozzle temperature, injection pressure, injection flow, and switch-over to holding pressure, which results the optimal tensile yield as the observed response using Back Propagation Neural Network-Genetic Algorithm (BPNN-GA). In this study, a 4-8-8-1 BPNN model was applied to predict the tensile yield based on a random combination of process parameters. The tensile yield then was optimized by genetic algorithm through several iterations. The optimal tensile yield of 28.44 MPa has been obtained using the following combination i.e. nozzle temperature of 250 oC, injection pressure of 1400 bar, injection flow of 40 cm3/s, and switch-over to holding pressure of 13,2 cm3.

Multi Response Optimization Using Taguchi-Grey-Fuzzy Method in Drilling of Kevlar Fiber Reinforced Polymer (KFRP) Stacked

A research was conducted for the optimization in the drilling process of KFRP stacked, with multiple performance characteristics based on the orthogonal array with Taguchi-grey-fuzzy method. The experimental study was conducted under varying the drilling process parameters (feeding speed (mm/min) and cutting speed (m/min)) and tool geometries (point geometry and point angle (degree)). The optimized multiple performances characteristics were thrust force, torque and surface roughness. The quality characteristics of thrust force, torque and surface roughness were smaller-is-better. The experimental design used L18 orthogonal array with two replications. Experimental results have shown that machining performance in the drilling process can be improved effectively through this method.

Multiple Performance Characteristics Optimization in the WEDM Process of SKD61 Tool Steel Using Taguchi Method Combined with Weighted Principal Component Analysis (WPCA)

This paper presents the optimization of a wire electrical discharge machining (WEDM) process of SKD61 tool steel (AISI H13). The use of the Taguchi method coupled with weighted principal component analysis (WPCA) has been applied. The WEDM machining parameters (arc on time, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., recast layer thickness (RL) and surface roughness (SR). The quality characteristics of both RL and SR were smaller-is-better. WPCA was applied to eliminate response correlation and to convert correlated responses into equal or less number of uncorrelated quality indices called principal components. Experimental results have shown that machining performance of the WEDM process can be improved effectively through the combination of Taguchi method and WPCA.

Optimization of Multiple Performance Characteristics in the Wire EDM Process of AISI D2 Tool Steel Using Taguchi and Fuzzy Logic

In this study, the optimization of material removal rate (MRR) and surface roughness (SR) simultaneously in a WEDM process by using Taguchi method with fuzzy logic has been applied. The Wire EDM process parameters (flushing pressure, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., MRR and SR. Based on the Taguchi method, an L18 mixed-orthogonal array table was chosen for the experiments. Fuzzy reasoning of the multiple performance characteristics has been developed based on fuzzy logic, which then converted into a fuzzy reasoning grade or FRG. As a result, the optimization of complicated multiple performance characteristics was transformed into the optimization of single response performance index. Experimental results have shown that machining performance characteristics of Wire EDM process can be improved effectively through the combination of Taguchi method and fuzzy logic.

An investigation of force, surface roughness and chip in surface grinding of SKD 11 tool steel using minimum quantity lubrication-MQL technique

This research aimed to analyze the viability of the minimum quantity of lubricant (MQL) technique towards normal force, tangential force, surface roughness and chip formation in surface grinding of SKD 11 tool steel. The three surface grinding parameters were varied including the type of cooling method (MQL and dry), table speed, and depth of cut. Based on statistical analysis, depth of cut is the most influential factor which affects the four responses in both dry and MQL grinding. MQL could reduce normal force and tangential force considerably, but produce higher surface roughness. In MQL grinding, the chips removal took place mostly by shearing and fracturing.

Application of Taguchi-grey method to optimize drilling of EMS 45 steel using minimum quantity lubrication (MQL) with multiple performance characteristics

Machining under minimum quantity lubrication (MQL) has drawn the attention of researchers as an alternative to the traditionally used wet and dry machining conditions with the purpose to minimize the cooling and lubricating cost, as well as to reduce cutting zone temperature, tool wear, and hole surface roughness. Drilling is one of the important operations to assemble machine components. The objective of this study was to optimize drilling parameters such as cutting feed and cutting speed, drill type and drill point angle on the thrust force, torque, hole surface roughness and tool flank wear in drilling EMS 45 tool steel using MQL. In this study, experiments were carried out as per Taguchi design of experiments while an L18 orthogonal array was used to study the influence of various combinations of drilling parameters and tool geometries on the thrust force, torque, hole surface roughness and tool flank wear. The optimum drilling parameters was determined by using grey relational grade obtained from gre...

Optimization of Multiple Response Characteristics in the WEDM Process of Buderus 2379 ISO-B Tool Steel Using Taguchi-Grey-Fuzzy Logic Method

In this study, the optimization of cutting width (Kerf), material removal rate (MRR), surface roughness (SR) and recast layer (RL) in WEDM was investigated by using Taguchi-Grey-Fuzzy logic method. The experiments have been conducted under varying arc on time, on time, off time, open voltage and servo voltage. An orthogonal array, signal-to-noise (S/N) ratio, grey relational analysis, grey-fuzzy reasoning grade and analysis of variance were employed to study the performance characteristics in the WEDM process of Buderus 2379 ISO-B tool steel. Experimental results show that on time gives the highest contribution for reducing the total variation of the multiple responses, followed by off time, open voltage, servo voltage and arc on time. The optimum performance characteristics could be obtained by using the values of AN, ON, OFF, OV and SV of 1 A, 1 µs, 15 µs, 95 V and 55 V respectively.