International Journal of Manufacturing Research (17 papers in press)
Reliability Assessment of the Centrifugal Compressor Impeller Based on Monte Carlo Method
by Yifan Wang
Abstract: Abstract: Reliability assessment of centrifugal compressor impellers has been a critical issue in industrial practice and application. In this paper, cycling life of the impeller obtained by the fatigue test is substituted into the S-N formula to calculate a group of parameter b in the formula. Then b is fitted by a three-parameter Weibull distribution. After that, Monte Carlo method is used for random sampling from the three-parameter Weibull distribution. Every b acquired by the sampling is substituted back into the S-N formula, by which a large group of values of the cycling life are calculated to fit its distribution. The reliability of the impeller under operating condition is then obtained to provide a critical reference for the health monitoring of the centrifugal compressor impeller online.
Keywords: Key words: Impeller failures; Fatigue life; Life prediction; Reliability analysis.
New Dispatching Rules and Due Date Assignment Models for Dynamic Job Shop Scheduling Problems
by Aydin TEYMOURIFAR
Abstract: In this paper, new due date assignment models and dispatching rules have been designed for the dynamic job shop scheduling problem. All of them have competitive results compared to the models from previous studies. The proposed dispatching rules have been evolved based on the modified and composite features of jobs. They have been compared with successful methods from the literature in a simulated environment. The simulation model has been validated by comparing the results with an analytical method. One of the rules has the best results in comparison with the other dispatching rules from the literature cited in this study. Another important matter which is considered in this paper is that the due date assignment model must be compatible with the used dispatching rule. Based on this approach, new due date assignment models are developed, which have the best results when combined with some dispatching rules.
Keywords: Dynamic job shop scheduling; Dispatching rules; Due date assignment models; Regression; Neural networks; Simulation.
Strain Hardening Properties and the Relationship Between Strain and Hardness of Inconel 718
by XIAOHONG LU
Abstract: In micro-milling of Inconel 718, work hardening occurs and the strain hardening properties as well as the relationship between strain and hardness of Inconel 718 remain unclear. The quasi-static tensile tests are conducted in this paper. Through the experiments, the strength coefficient K and the strain-hardening exponent n in Hollomon formula, which describes the relationship between strain and stress of a material, are calculated. After the measurements of the micro-hardness of Inconel 718 under different plastic deformations, the relationship between micro-hardness and strain of Inconel 718 is established. This relationship is valuable in computation of the hardness based on the stress state of Inconel 718 and it also extends the application of the commercial finite element analysis software such as ABAQUS, since it tracks stress state but cannot acquire the hardness of the machined surface. The proposed equation then calculates the hardness value based on the simulation output of stress in the software.
Keywords: Strain; Hardness; Inconel 718; Work hardening.
Investigation on surface roughness and sub-surface damage in ISF
by Yicun Meng
Abstract: Incremental sheet forming is a potential technology in future manufacturing. However, the surface roughness increases during the process can limit the geometric accuracy and alter the mechanical properties of the product. The paper presents an extensive experimental investigation on the relevance between the surface roughness and sheet thickness using the two points incremental forming and an optical microscopy analysis the microstructure change in the sheet material during forming. Firstly, aluminium alloy sheets with different thickness were formed into a benchmark shape. Then the measurements of sheet thickness and wall angles were carried out to reveal the effects on the surface roughness that is further related to the mechanical properties. Finally, the microstructure of the sheets prior and after forming was investigated under microscope, considering the influence of grain size and clad layer. It is shown that a large wall angle leads to a worse surface finish. However, there was no direct relationship found between sheet thickness and surface roughness. Through the microstructure observation of processing sheets, it is found that the bounding of the clad layer remained intact and the deformation is constrained within the clad layer.
Keywords: Incremental sheet forming; sub-surface damage; orange peel effect; surface roughness.
Prediction of the cutting forces in gear hobbing and the wear behavior of the individual hob cutting teeth
by Carin Andersson
Abstract: In this paper, a mathematical model is presented, by which the cutting forces in a gear hobbing process and the wear behaviour of the hob's all cutting teeth are predicted. The load on each individual hob cutting tooth varies heavily in the gear hobbing process. To predict the cutting force, and subsequently the tool wear, a detailed determination of the chip geometry is needed. The undeformed chip geometry is continuously determined by analytical differential description presented in previous research. In the model all cut chips are determined for the full production cycle of a gear blank, where the gear blank boundaries are considered. Considering the full production cycle is needed to get an understanding of the load the tool will experience and the wear behaviour of the hob teeth.
Keywords: Gear Hobbing; Cutting Force Prediction; ToolWear; Chip Geometry; Chip Thickness Variation.
Predicting the Effect of Tool Configuration during Friction Stir Welding by Cellular Automata Finite Element (CAFE) Analyses
by R.GANESH NARAYANAN
Abstract: The present work aims at selecting the pin geometry for single-sided friction stir welding of steel, and modelling the double-sided FSW process, both through cellular automata finite element analyses. Cellular automata cells are used to hold initial grain size of the base sheets. The stirring action during the process is not modelled physically. Instead the heat flux and strain-rate attained are incorporated by models. In the first objective, by developing heat flux models, strain-rate and strain models for different pin profiles, and the final grain size distribution across the weld zone is predicted. The final pin profile predicted from the present work is not the same used by authors in the existing literature, as observed from grain size prediction. In the second objective, during double-sided friction stir welding, the grain size predictions are agreeing well with the existing data. The efficiency of the approach for tool selection has been demonstrated successfully.
Keywords: Modelling; Cellular automata; Friction stir welding; Tool selection; Grain size; Prediction; Welding; Temperature; Microstructure.
Experimental Study of the Effect of Light Source Spot Size on Measure Error of PSD
by Xiaohong Lu
Abstract: The energy distribution of incident light spot on position-sensitive detector (PSD) screen is uneven and the output coordinate value is the energy centre of light spot. Measurement error caused by the deviation between the geometric and gravity centre of light spot will occur. That deviation will increase with the increase of the diameter of the light spot. There is no quantitative research on the position error caused by the changes of the light spot diameter and the distance from the light spot to the PSD. To evaluate the magnitude of the error, the infrared spotlight is selected as the target light. The changing pattern that the spot diameter varies with the distance between the light source and lens is studied. Additionally, the effect of the spot size on the PSD measure error is also studied. The research provides reference for error evaluation of the distance and position detection of PSD.
Keywords: PSD; light spot; geometric centre; energy centre; measure error.
Iterated Greedy Insertion Approaches for the Flexible Job Shop Scheduling Problem with transportation times constraint
by Azzedine Bekkar
Abstract: This paper proposes two greedy heuristics based on an iterated insertion technique to solve the flexible job shop scheduling problem with transportation times constraint. The approaches deal with the both of the sub-problems of the assignment of machines to operations and the sequencing of the operations on the assigned machines. The idea is to start with a greedy construction method, then, apply an iterative destroy and recreate algorithm to minimize the completion time production (Makespan). The heuristics were tested on a benchmark that considers the transportation times between the machines and based on a real Flexible Job Shop "AIP-PRIMECA cell of Valenciennes University". The heuristics performance is evaluated by comparing its results with a Mixed Integer Linear Program (MILP) and the Potential Fields (PF) approach. The results obtained are very promising
Keywords: Flexible Job Shop; Scheduling; Production; Optimization; Greedy Heuristics.
Cooperative diagnostics for combinations of large-volume metrology systems
by Domenico Maisano
Abstract: Recent studies show that the combined use of Large-Volume Metrology (LVM) systems (e.g., laser trackers, rotary-laser automatic theodolites, photogrammetric systems, etc.) can lead to a systematic reduction in measurement uncertainty and a better exploitation of the available equipment. The objective of this paper is to present some diagnostic tests for combinations of LVM systems that are equipped with distance and/or angular sensors. Two are the tests presented: a global test to detect the presence of potential anomalies during measurement and a local test to isolate any faulty sensor(s). This diagnostics is based on the cooperation of sensors of different nature, which merge their local measurement data, and it can be implemented in real-time, without interrupting or slowing down the measurement process. The description of the tests is supported by several experimental examples.
Keywords: Large-volume metrology; Distributed sensors; Multi-system combination; Cooperative diagnostics; Statistical test; Measurement consistency.
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.
An evolutionary based hybrid approach for simultaneous optimization of multiple responses in self-propelled rotary turning process
by Thella Babu Rao, Naresh Baki
Abstract: This investigation focused on optimization of self-propelled rotary turning process conditions through and integrated multi-objective optimization approach. The machining experiments are conducted for machining hardened EN24 (SAE4340) steel with TiN-coated tungsten carbide rotary insert. Two important machining responses such as surface roughness and metal removal rate by varying the machining variables such as depth of cut, the inclination angle of the rotary tool, feed rate and spindle speed. To deal with the simultaneous optimization of two conflicting process characteristics governed by four process variables, an evolutionary based hybrid optimization approach is proposed. The method integrated Gray Relational Analysis (GRA) for deriving the overall process performance index, Response Surface Methodology (RSM) to analyze the significance and variation process variables and Genetic Algorithm (GA) to derive the optimal values of the process variables which will give maximum process performance. The derived optimal machining conditions were confirmed through validation machining experiments.
Keywords: Multi-response optimization Gray Relational Analysis Response Surface; Methodology Genetic Algorithms; Self Propelled Rotary Turning; Surface Roughness; Metal Removal Rate.
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.