International Journal of Manufacturing Research (19 papers in press)
Development of semi empirical model on material removal rate in WEDM process for aluminium metal matrix material using dimensional analysis
by Jaksan D. Patel, Kalpesh D. Maniya
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 aluminium metal matrix material considering pulse on time, wire diameter, peak current and various materials properties likes density, thermal conductivity, electrical conductivity, specific heat capacity, coefficient of thermal expansion, melting temperature, and latent heat of fusion as model parameter. Taguchi L27 orthogonal array were used to perform the experiment for aluminium 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.
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.
An integrated approach for multi-period manufacturing planning of job-shops
by VIRAJ TYAGI, AJAI JAIN, P.K. Jain
Abstract: In the present study, an integrated methodology of manufacturing planning has been formalised for a capacity constrained job-shop with consideration of capacity planning, loading, scheduling, and process plans flexibility for a given master production schedule. This study aims at generation of production schedules that are compatible with production plans developed at a higher level for feasible implementation at the shop floor. Performance of methodology is assessed for eight case studies from mean tardiness viewpoint. Results indicate that formalised integrated methodology is effective in the complex job-shop environment. Further, mean tardiness performance of integrated methodology is found better than that of the conventional hierarchical approach of manufacturing planning.
Keywords: Integrated; Manufacturing Planning; Loading; Scheduling and Job-Shop.
RESEARCH CLUSTERING AND THE STATE-OF-THE-ART IN MICRO SHEET METAL FORMING: A REVIEW
by Aida Mahmudah, Kiswanto Gandjar, Dedi Priadi
Abstract: Micro metal forming that offers solutions in micro part manufacturing has been developed rapidly for many years. In this paper, research clustering in the micro sheet metal forming system is elaborated, and the review is presented. A trending research focus in recent years is then discussed. The Investigation into the process is more interesting than other aspects due to size effect phenomena in micro level. It was concluded that more efforts are still needed to fill the gap in developing micro forming technology to meet the industrial application requirements, especially in producing final products with good quality that can be achieved only with good material properties, high tooling technology, proper working parameters, and sophisticated material handling held in precision forming machine.
Keywords: Micro sheet metal forming; Research clustering; Size effects.
Using of Least Square (LS) and Fuzzy Logic methods to estimate the cutting forces for a new tool in machining of SAE4140
by Aydin Salimi, Maghsoud Shalvandi, Esmaeil Seid
Abstract: In this paper, analytical-empirical and fuzzy logic based models were created to predict the cutting forces in turning process for a new tool. A dynamometer that measure static cutting forces was used for measuring the forces. AISI 4140 steel was used as the work piece material for conducting the experiments due to its most common applications in machining process industry. Cutting force, thrust force and radial force were measured for three combinations of cutting speeds (V), cutting feeds (f) and cutting depths (d). Full factorial method was used to design the experiments. For developing the analytical model the least square method (LS) was used to estimate the model constants. Experimental results were compared with the predicted results for both of the developed models. The comparing results show the efficiency of the both developed models. However, the results confirm that the accuracy of the fuzzy model is much higher than the analytical model in prediction of the cutting forces.
Keywords: Cutting forces; Modeling; Fuzzy logic; LSM.
Tool Design and Cutting Parameters Optimization for Plunge Milling Blisk
by Yaonan Cheng, Jinlong Yang, Diange Zuo, Xu Song, Xinmin Feng
Abstract: Because of its complex structure, narrow channel, large metal removal rate and its material belonging to difficult-to-machine material, the machining of blisk is very difficult. It is one of the effective methods to solve the above problems by applying the plunge milling technology, and the tool design and cutting parameters optimisation are of great significance. Firstly, the finite element method is used to design and analyse the geometrical structure, and the static and modal analysis is carried out to ensure the strength of the tool and the stability of the plunge milling. Secondly, the experimental research on the milling titanium alloy was finished by using the designed tool, and the influence of cutting parameters on the cutting force was analysed. Finally, based on the fuzzy comprehensive evaluation method, the cutting parameters are optimised, and the rationality of the tool designed is verified through the experimental study of tool wear.
Keywords: blisk; difficult-to-machine material; plunge milling tool; cutting parameters.
Workload based order acceptance in seru production system
by Zhe Zhang, Yong Yin, Yulong Wang
Abstract: This paper focuses on the seru loading problem considering order acceptance. In practice, manufacturing company may receive a certain number of orders before the planning period, and each of them has the different processing time, setup time, revenue, tardiness penalty and due date. Due to the limitation of production capacity, the manufacturing company need to make order acceptance and loading decision to maximise profits. According to the parallel structure of seru production system and the characteristics of proposed model, the genetic algorithm with matrix crossover (MCGA) is designed. Finally, two numerical examples are applied to show the practicability and effectiveness of proposed model and algorithm.
Keywords: seru production system; seru loading; order acceptance; genetic algorithm.
FEM Assessment of the Effects of Machining Parameters in Vibration Assisted Nano Impact Machining of Silicon by Loose Abrasives
by Jianfeng Ma, Nick Duong, Shuting Lei
Abstract: In this paper, the commercial FEM software package ABAQUS 6.14/EXPLICIT is used to model a vibration assisted nano impact machining process by loose abrasives (VANILA), in which an atomic force microscope (AFM) is used as a platform and the nanoabrasives (diamond particles) injected in slurry between the workpiece (silicon) and the vibrating AFM probe impact the workpiece and result in nanoscale material removal. The FEM model is validated first and then is used to investigate the influence of impact speed, impact angle, and the frictional coefficient between the workpiece and abrasives on the nanocavity's size and depth. It is concluded that the impact speed, impact angle, and frictional coefficient between the silicon workpiece and nanoabrasives have substantial influence on the nanocavity's size and depth, the optimal size of which along with material removal rate might be achieved by simultaneously considering impact speed, impact angle, and frictional coefficient.
Keywords: Finite Element Method (FEM); Nanomachining; Silicon; Vibration Assisted Nano Impact Machining.
Machining path research of thin-walled parts considering initial residual stress
by Yunan Liu, Min Wang, Xiangsheng Gao, Lili Wu, Xiaodong Jiang
Abstract: Thin-walled parts have the low stiffness characteristic. Initial residual stress of thin-walled blanks is an important influence factor on the machining stability. With the different machining paths, the release order of initial residual stress is also different so as to cause the different deformation of the workpiece at the end of machining. The present work outlines machining path research of thin-walled parts with initial residual stress. According to residual stress test by hole-drilling method for casting ZL205A aluminium alloy tapered thin-walled blank, the three-dimensional finite element model with initial residual stress is established to study the deformation of the thin-walled part in three machining paths. The results indicate that the deformation of workpiece in semicircle path is similar to that in straight path. The deformation in contour path is minimal.
Keywords: thin-walled parts; initial residual stress; machining paths; finite element; machining deformation.