International Journal of Manufacturing Research (14 papers in press)
ANALYSIS OF REAL TIME VIBRATION ASSISTED TOOL CONDITION MONITORING IN DRILLING
by B. Srinivasa Prasad, Y. Rama Mohan Reddy
Abstract: Present work primarily focuses on identifying the presence of Drilling tool vibrations during the drilling process. A non-contact vibration transducer Laser Doppler Vibrometer is used as part of this approach. Values of cutting forces and vibration signal features with the progression cutting tool wear in dry machining of Ti-6Al-4V and Al7075 are recorded and analyzed. This paper presents a modified mathematical model in an attempt to understand tool life under vibratory cutting conditions. Identifying the relationship among tool wear, cutting forces and displacement due to vibration is a critical task in the present study. These results are used to predict the evolution of displacement and tool wear in the experiment. The effect of workpiece movement due to vibration on the tool wear is critically examined. Finally, tool wear is determined by the maximum displacement that can be borne in a process for an efficient tool condition monitoring system.
Keywords: Vibration; Acousto optic emission (AOE); Displacement; Tool wear; Fast Fourier Transform.
Development of semi empirical model on material removal rate in WEDM process for aluminum metal matrix material using dimensional analysis
by JAKSAN PATEL
Abstract: Wire electrical discharge machining is a non-conventional process for manufacturing complicated and intricate parts. In this paper dimensional analysis and nonlinear estimation method quassi newton was used to established semi empirical model for various aluminum metal matrix material considering pulse on time, wire diameter, peak current and various materials properties likes density, thermal conductivity, electrical conductivity, specific heat capacity, co efficient of thermal expansion, melting temperature, latent heat of fusion as model parameter. Taguchi L27 orthogonal array were used to perform the experiment for aluminum metal matrix. Semi empirical model shows more than 99% prediction than experiment data. Constant and power indices value of model shows wire diameter, peak current, pulse on time and work material properties such as thermal expansion of coefficient and melting point temperature are significant parameters for material removal rate.
Keywords: Wire electrical discharge machine; Taguchi design; Dimensional analysis; Orthogonal array; Material removal rate.
WEDM process parameter selection using preference ranking methods: A comparative study
by JAKSAN PATEL
Abstract: Wire electrical discharge machining process offer opportunities to manufacturers to improve their technology, competitiveness and profitability through a highly efficient and focused approach to manufacturing effectiveness. Justification, evaluation and selection of WEDM process parameter now have been receiving significant attention in the manufacturing environment. Evaluating alternative WEDM process parameter in the presence of multiple conflicting criteria and performance measures is often a difficult task for the decision maker. Preference ranking tools are special types of multi criteria decision-making methods in which the decision maker's preferences on criteria are aggregated together to arrive at the final evaluation and selection of the alternatives. This paper deals with the application of five most potential preference ranking methods for selecting the best WEDM process parameter for desired output characters ices for different aluminium metal matrix composite.
Keywords: Wire cut electrical discharge machining; Multi criteria decision making method; Aluminum metal matrix; and Taguchi design.
Discrete cuckoo search algorithm for solving the cell formation problem
by Bouchra KAROUM, Youssef B. El Benani
Abstract: The manufacturing cell formation problem is considered one of the rst issues in the designing of cellular manufacturing systems, that attempts to con- struct a set of machine cells and their corresponding product families. The aim is to minimize the inter-cell movements of the products while maximizing the ma- chine utilization. Recently developed cuckoo search algorithm is introduced in this paper to solve this kind of problems which is discrete in nature. The proposed method is combined with a local search mechanism in order to intensify the search and improve the quality of the solutions. In order to demonstrate the eectiveness of the proposed algorithm, a set of 35 benchmark problems is used; the results are then compared to dierent methods collected from the literature. The results demonstrate that the proposed algorithm is a very eective and performs well on all test problems since it can reach 32 out of 35 benchmark problems (91.43%).
Keywords: cell formation problem; cuckoo search algorithm; grouping efficacy; lévy flights; cellular manufacturing.
Statistical investigation of surface roughness and kerf on wire electrical discharge machining performance
by Jay Pujara, Kartik Kothari, Ashish Gohil
Abstract: This paper describes statistical investigation to optimize the process variables such as pulse duration (pulse on), pulse period and peak current that affects the output response surface roughness (SR) and kerf (k) on WEDM through Grey Relational Analysis(GRA). Taguchi L16 design matrix has been used to carry out the experimental work. Response Surface Methodology(RSM) is used to develop the empirical models from the experimental data. Analysis of variance(ANOVA) is used to check the adequacy of the developed models. Based on statistical analysis, it has been found that peak current and pulse off time has a positive influence on SR while pulse on time has a negative influence, as well as peak current and pulse on time, has a negative influence on kerf while pulse off time has a positive influence. Confirmation test shows the application of the optimization technique for predicting optimum conditions to obtained better output responses.
Keywords: WEDM; Taguchi Design; RSM; response surface methodology; ANOVA; Analysis of variance; GRA; grey relational analysis; kerf; surface roughness.
Analytical Modeling and Experimental Study of Machining of Smart Materials using Submerged Abrasive Waterjet Micromachining Process
by Sagil James, Anurag Mahajan
Abstract: Smart materials are new generation materials which possess great properties to mend themselves with a change in environment. Manufacturing of these materials is extremely challenging, particularly at micron scale due to their extreme mechanical properties. This research investigates Submerged Abrasive Waterjet Machining (SAWJMM) process for micromachining smart ceramic materials. This study presents the mathematical modeling to predict the material removal rate during SAWJMM process. The research also involves experimental study on micromachining of smart materials using an in-house fabricated SAWJMM setup. The study found that SAWJMM process is capable of successfully machining smart materials including shape memory alloys and piezoelectric materials at the micron scale. An analytical predictive model is developed to estimate the MRR during SAWJMM process, and the model is found to be capable of accurately predicting the machining results.
Keywords: Smart material; Abrasive waterjet micromachining; Material removal rate.
PREDICTION OF SURFACE RESIDUAL STRESS AND HARDNESS INDUCED BY BALL BURNISHING THROUGH NEURAL NETWORKS
by Carlos E. H. Ventura, Frederico C. Magalhães, A.M. Abrao, Berend Denkena, Bernd Breidenstein, Kolja Meyer
Abstract: Ball burnishing is a mechanical surface treatment used for surface finish improvement, surface work hardening and inducement of compressive residual stresses, nevertheless, a great level of interaction is observed among the most relevant factors. Within this scenario, artificial neural networks can be employed to determine the most recommended input parameters in order to achieve the required outcome. In this work, burnishing tests were performed using annealed and hardened AISI 1060 steel specimens and the obtained surface residual stress and hardness values were used to train an artificial neural network. The experimental results showed a nonlinear relationship between the input and output parameters for annealed AISI 1060 steel and support the applicability of artificial neural networks for the burnishing process, whereas a more linear relationship between the input and output parameters was observed for hardened AISI 1060 steel, though burnishing pressure seems to be the most relevant factor affecting residual stress. The artificial neural network and optimization procedure providedconsistent input parameters, thus leading to the inducement of compressive residual stress of higher intensity.
Keywords: ball burnishing; residual stress; hardness; neural network; optimization; AISI 1060 steel.
Optimization of resistance spot welding process for real unconstrained and constrained scenarios using cuckoo search algorithm
by Rushikesh Dandagwhal, C.V. Chavan, Chandrakant Wani
Abstract: The optimum selection of process parameters is essential for a designer, as it incur high initial investment, power and; operating and maintenance costs. This article presents optimisation aspects of resistance spot welding process using cuckoo search algorithm. The parameters are studied critically to obtain the optimum settings satisfying one or more quality characteristics. Some constrained and unconstrained single as well as multi-objective optimisation problems related to the practical case studies are solved. The obtained results are compared with those derived by the past researchers. It is found that the present results are better than the previous results in all the cases. The solved examples illustrated a novel effectiveness of the presented algorithm and its application suitability in the field of resistance spot welding.
Keywords: Resistance spot welding; Cuckoo search algorithm; Optimization; Parameters; Response.
Development of a model to compensate overcut during Electro Discharge Boring process
by Sudhanshu Kumar, Harshit Dave, Keyur Desai
Abstract: Electro discharge boring (EDB) process is novel concept of machining through X-Y tool actuation applied for boring of hard and difficult to machine materials. Unlike conventional boring machining, EDB process is free from vibration, cutting forces or tool deflection. Since, the removal of material takes place due to the action of repetitive sparks therefore overcut is observed in the bored cavity produced during EDB process. In the present study, an effort has been made to predict and reduce the overcut generated during EDB process. Effect of process parameters on overcut have been studied using Taguchi's experimental method and then significant process parameters have been identified using analysis of variance method. Further, a prediction model has been developed using multiple regression analysis for prediction of overcut produced during boring process on Inconel 718 material. Finally, an algorithm has been developed in MATLAB software for compensation of overcut by suggesting compensating orbital radius for specified target diameter of cavity. The test results obtained using proposed algorithm show that the cavities generated are very close to the specified target cavities.
Keywords: Electro discharge boring; orbital; overcut; ANOVA; regression; MATLAB.
Review on Modeling of Friction Stir Welding Using Finite Element Approach and Significance of Formulations in Simulation
by Vinayak Malik
Abstract: Friction Stir Welding (FSW) is a solid-state joining process which is gaining significance in many joining applications, by overcoming the limitations of other fusion welding processes. For successful incorporation of its potential during industrial applications, mechanism of joining needs to be properly comprehended. The solution lies in developing effective and reliable Finite Element (FE) model of the FSW process, which would help in getting an insight of the process phenomena (like material flow, heat generation, etc.,) during the process. Here a review is made to know the current state of various FE modeling techniques and identifying better techniques for simulating FSW and its variants. This review also highlights shortcomings (for e.g., mesh distortion, simulation time, the inability of defect prediction) of previous models and discusses on grey areas which are still to be addressed in the broader perspective of FSW and its allied processes using FE approach.
Keywords: FSW; FE Modeling; Industrial Scenario; Formulations; Defect Prediction.
Models framework for laser polishing surfaces obtained by milling and additive manufacturing processes
by Jean-Yves Hascoët, Benoit Rosa, Pascal Mognol
Abstract: The manufacturing chain is usually made of several processes, to create the final surface with regard to design specifications. Manufacturing processes are composed by a complex database, which contains the operating parameters and their settings combinations that impact on the surface parameters. This database may be composed by measured values and it is important to determine the non-measured values through modelling methods to master the final result. This paper aims at establishing a protocol to determine the laser polishing operating parameters for milled and additive laser-manufactured primary surfaces. Several experiments enable to propose models coming from polynomial regression calculus. The proposed models are 88
Keywords: Laser polishing; milling surfaces; additive manufacturing surfaces; operating parameters; modelling; framework of models.
Laser polishing of additive laser manufacturing surfaces: methodology for parameter setting determination
by Benoit Rosa, Jean-Yves Hascoët, Pascal Mognol
Abstract: This paper focuses on the improvement of thin and complex surfaces obtained with a direct metal deposition (DMD) process through the use of the laser polishing process on the same five-axis machine. This study aims at giving a methodology to determine laser polishing operating parameters and thus master the final topography improvement. On the basis of experiments and a polynomial regression method, the classification and methodology of some operating parameters models are obtained. The proposed methodology is efficient within the feasibility domain and several qualitative objective functions and interactions between the operating parameters are taken into consideration. The proposed operating parameters models, have a 77
Keywords: Laser polishing; additive manufacturing; modelling; methodology; parameter settings.
Supplier evaluation and selection based on quality matchable degree
by Wenli Qiang, LiPing Liu
Abstract: Supplier evaluation and selection is an important step during the manufacturing process for a product to meet quality requirements. This paper proposes a new supplier evaluation and selection model based on quality matchable degree. In this model, the quantitative and qualitative indicators are involved to describe the quality assurance of suppliers and the manufacturer. The matchable degree of the supplier is calculated according to the quality level of the manufacturer. The multivariate quality loss function method is used to determine the score of each supplier. The implementation of the proposed model is also given in details. An example is presented to illustrate the implementation of the proposed model. The proposed model is compared with other methods are summarized.
Keywords: supplier evaluation; supplier selection; matchable degree.
Branch and Bound algorithm for identical parallel machine scheduling problem to maximize system availability
by Asmaa Khoudi, Ali Berrichi
Abstract: In the majority of production scheduling studies, the objective is to minimise a criterion which is generally, function of completion times of production jobs. However, for some manufacturing systems, the reliability/availability of machines can be the most important performance criteria towards decision makers. In this paper, we deal with a production scheduling problem on identical parallel machines and the objective is to find the best assignment of jobs on machines maximising the system availability. We assume that the production system can be subject to potentially costly failures then PM actions are performed at the end of production jobs. We have proposed a branch and bound algorithm, dominance rules and an efficient upper bound to solve the proposed model optimally. Computational experiments are carried out on randomly generated test problems and results show the efficiency of the proposed upper bound and dominance rules.
Keywords: Identical Parallel Machines Preventive Maintenance System Availability Production Scheduling Branch and Bound.