Dušan Petković

APPLICATION OF THE PERFORMANCE SELECTION INDEX METHOD FOR SOLVING MACHINING MCDM PROBLEMS

Complex nature of machining processes requires the use of different methods and techniques for process optimization. Over the past few years a number of different optimization methods have been proposed for solving continuous machining optimization problems. In manufacturing environment, engineers are also facing a number of discrete machining optimization problems. In order to help decision makers in solving this type of optimization problems a number of multi criteria decision making (MCDM) methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. performance selection index (PSI) method for solving machining MCDM problems. The main motivation for using the PSI method is that it is not necessary to determine criteria weights as in other MCDM methods. Applicability and effectiveness of the PSI method have been demonstrated while solving two case studies dealing with machinability of materials and selection of the most suitable cutting fluid for the given machining application. The obtained rankings have good correlation with those derived by the past researchers using other MCDM methods which validate the usefulness of this method for solving machining MCDM problems.

Selection Of Cutting Inserts For Aluminum Alloys Machining By Using MCDM Method

Abstract Machining of aluminum and its alloys requires the use of cutting tools with special geometry and material. Since there exists a number of cutting tools for aluminum machining, each with unique characteristics, selection of the most appropriate cutting tool for a given application is very complex task which can be viewed as a multi-criteria decision making (MCDM) problem. This paper is focused on multi-criteria analysis of VCGT cutting inserts for aluminum alloys turning by applying recently developed MCDM method, i.e. weighted aggregated sum product assessment (WASPAS) method. The MCDM model was defined using the available catalogue data from cutting tool manufacturers.

Pareto optimisation of certain quality characteristics in laser cutting by ANN-GA approach

Determining the optimal laser cutting conditions for simultaneous improvement of multiple cut quality characteristics is of great importance. The aim of the present research is to simultaneously optimise three cut quality characteristics such as surface roughness, kerf taper angle and burr height in CO2 laser cutting of stainless steel. The laser cutting experiment was conducted based on Taguchis experimental design using L27 experimental plan by varying four parameters such as laser power, cutting speed, assist gas pressure and focus position at three levels. Using the obtained experimental results three mathematical models for the prediction of cut quality characteristics were developed using artificial neural networks (ANNs). The developed response models for cut quality characteristics were taken as objective functions for the multi-objective optimisation based on the genetic algorithm. The obtained optimal solution sets were used to generate 2-D and 3-D Pareto fronts. The overall improvement of about 16% was registered in multiple cut quality characteristics.

The effects of passivation parameters on pitting potential of biomedical stainless steel

Passivation is a chemical process where electrochemical condition of passivity is gained on the surface of metal alloys. Biomedical AISI 316LVM stainless steel (SS) can be passivized by means of nitric acid immersion in order to improve a protective oxide layer on the surface and consequently increase corrosion resistance of the SS in the physiological solutions. In this study, multiple regression analysis and artificial neural network (ANN) were employed for mathematical modeling of the AISI 316LVM SS passivation process after immersion in the nitric acid solution. Pitting potential, which represents the measure of pitting corrosion resistance, was chosen as the response while passivation parameters were nitric acid concentration, temperature and passivation time. The comparison between experimental results and models predictions showed that only the ANN model provided statistically accurate predictions with a high coefficient of determination and a low mean relative error. Finally, based on the derived ANN equation, the effects of the passivation parameters on pitting potential were examined. [Projekat Ministarstva nauke Republike Srbije, br. ON174004 i br. TR35034]

Taguchi Approach for the Optimization of Cutting Parameters in Finish Turning of Medical Stainless Steel

Optimization of cutting parameters in finish turning of medical stainless steel 316LVM with coated carbide tools using Taguchi method is proposed in this paper. Four cutting parameters namely, insert radius, depth of cut, feed and cutting speed are optimized with considerations of surface roughness as performance characteristic. The effects of cutting parameters on the surface roughness were experimentally investigated. Experimentation was conducted as per Taguchis orthogonal array. Four cutting parameters with three levels are arranged in L27 orthogonal array. The orthogonal array, measured values of surface roughness, signal-to-noise ratios and analysis of variance are employed to study the surface roughness. Based on the analysis, the optimal cutting parameter settings were determined. Through the confirmation test with optimal cutting parameter settings the effectiveness of the optimization approach are validated. The obtained results have shown that Taguchi method is suitable for optimizing the cutting parameter levels with the minimum number of experiments.

Multi-Objective Optimization of Laser Cutting Using ROV-Based Taguchi Methodology

Multi-objective optimization of laser cutting for simultaneous improvement of performance characteristics is of great practical importance. In this study a range of value (ROV)-based Taguchi methodology is proposed for multi-objective optimization of laser cutting, i.e. surface roughness, kerf width and burr height in CO2 laser cutting of AISI 304 stainless steel. Laser cutting experiment was conducted based on Taguchi’s L27 experimental design by varying the laser power, cutting speed, assist gas pressure and focus position at three levels. In the proposed methodology based on the experimental data signal to noise ratios as per Taguchi’s method were calculated for each experimental trial upon which decision matrix was defined. Subsequently, multi-criteria decision making problem was solved by the ROV method. The proposed ROV-based Taguchi methodology has relatively simple computational procedure and can be easily applied by engineers for solving different multi-objective optimization problems that occur in real manufacturing environment.

Application of Recently Developed MCDM Methods for Materials Selection

It is well known fact that materials play an important role in engineering design. Nowadays over a hundred thousand available materials can be distinguished with constant tendency for increasing the novel designed materials. Therefore material selection process becomes a complex and time consuming task. Selection of the most suitable material for a given application can be regarded as a multi-criteria decision making (MCDM) problem with conflicting and diverse objectives. New MCDM methods have been developed, and existing methods improved, showing that research in the decision-making is important and still valuable. This paper describes the use of recently developed MCDM methods, i.e. Complex Proportional Assessment (COPRAS) and Weighted Aggregated Sum Product Assessment (WASPAS) for selecting the most suitable hard coating material.

Aspects of Machining Parameter Effect on Cut Quality in Abrasive Water Jet Cutting

Abrasive water jet machining is frequently used in industry. It is one of the most versatile processes in the world. The basic advantages of abrasive water jet machining is that no heat affected zones or mechanical stresses are left on an abrasive water jet cut surface, high flexibility and small cutting forces. Although this cutting technology includes many advantages, there are some drawbacks. For instance, abrasive water jet cutting can produce tapered edges on the kerf of workpiece being cut. This can limit the potential applications of abrasive water jet cutting, if further machining of the edges is needed to achieve the engineering tolerance required for the part. The machining parameters have a great influence on these phenomena. The aim of this paper is to investigate the cut quality of EN AW-6060 aluminium alloy sheets under abrasive water jets. The experimental results indicate that the feed rate (nozzle traverse speed) of the jet is a significant parameter on the surface morphology.