International Journal of Manufacturing Research (16 papers in press)
A Novel Method for Flame Bending of Thick-Walled Pipes
by Seyed Ebrahim Moussavi Torshizi, Seyed Ehsan Chavoshi, Vahid Badali
Abstract: In the Flame Bending forming method, the thermal stresses caused by local heating lead to plastic deformation. Applying this method to thick and large diameter pipes leads to drastically low bending angle. The proposed methods for increasing the bending angle in these pipes require simultaneous control of two torches. In this study, a simple heating method is proposed that results in a significant increase in bending thick pipes. Also, a non-mechanical method is presented to create heating-induced pre-stress. Firstly, the heating within a longitudinal band (Band Heating) is investigated. Then, a heating step is added prior to the main Band Heating step to create pre-stress in the heating zone. Finite Element method is used to investigate the deformation mechanism and the effectiveness of different heating methods. The effective parameters are optimized to achieve the maximum bending. Also a heating test is carried out using a large perforated plate burner.
Keywords: Flame Bending; Pipe Straightening; Line Heating; Forming; Finite Element Method.
A Numerical Investigation of Friction Stir Welding Parameters in Joining Dissimilar Aluminum Alloys Using Finite Element Method
by Mahmoud Moradi, M.Saleh Meiabadi, Vincent Demers
Abstract: Friction stir welding is a relatively new solid-state welding process which has several superiorities over generic welding methods. In this study, aluminum alloys (AA5083-O and AA6061-T6) are selected to investigate effects of three welding variables namely tool rotation speed, tool traverse speed, and tool diameter on temperature distribution, weld width, weld depth, and heat affected zone width using finite element method. The Johnson-Cook plasticity model is implemented into Abaqus software to simulate the material plastic deformation occurring during welding process. The results demonstrated that increasing rotational speed and tool diameter lead in an increase in material temperature. Increasing traverse speed resulted in lower temperature distribution. Temperature distribution, as well as the size and shape of welding areas, are also different due to different mechanical and thermal properties. The wider heat affected zone predicted for the AA6061-T6 can be explained by its higher thermal conductivity and lower specific heat.
Keywords: Friction stir welding; Aluminum alloys; Simulation; Finite element method.
Experimental and statistical investigation into micro-EDM of Hastelloy-X using PVD diamond coated and AlTiN coated tungsten carbide electrodes
by Muhammad Pervej Jahan, Asma Perveen
Abstract: This paper investigates the effectiveness of electrode coating during the micro-electro-discharge machining (micro-EDM) of a nickel-based Hastelloy X (Ni-X) using uncoated, physical vapour deposition (PVD) diamond coated, and aluminium titanium nitride (AlTiN) coated tungsten carbide tool electrodes. The Box Behnken design (BBD) along with Response Surface Methodology (RSM) was used for modelling the effect of different machining parameters, i.e. capacitance, voltage, and tool rotational speed, and tool coating on the micro-EDM performance of Ni-X alloy. It was found that the crater size and surface microhardness increased with the increase of discharge energy, i.e. voltage and capacitance, irrespective of the tool coating. PVD diamond coating at the tool periphery was found to reduce the surface microhardness slightly due to the generation of comparatively smaller craters. The TiAlN coated electrodes provided lower machining time, whereas PVD diamond coated electrodes resulted in slightly smoother surface finish and lower tool wear.
Keywords: Micro-EDM; Ni alloy; Hastelloy X; Ni-X alloy; Micro-hole; Tool coating; Crater size; Machining time; Tool wear; Surface microhardness; Box Behnken design; Response Surface Methodology.
Effects of injection molding parameters on pattern performance of in mold decorative product
by Zhenghua Meng, Zhanwei Su, Wei Guo, Hui Wang, Lei Zhou
Abstract: Polyethylene terephthalate (PET) films with printed pattern were bonding with injected PC/ABS plastics substrate plates through different processing parameters. Research results show that the melt temperature has the most significant influence to the wear performance of the hardening layer and the pattern layer. However, the holding pressure dominates the bonding strength between pattern layer and substrate. With the increase of the melt temperature, the wear performance of the pattern increases significantly but the film bonding strength decreases. The abrasive resistance changes along with the processing parameters, but not obeys the same rules. It enhances significantly as the melt temperature elevated, but increases first and then decreases as the injection pressure strengthened, while decreases rapidly when the holding time lasts too long. The bonding strength gradually decreases with the elevated melt temperature, however, increases with the injection pressure. But generally the injection molding parameters have little effect on the bonding strength.
Keywords: In mold decorative; processing parameters; wear performance.
Machine learning algorithms benchmarking for real-time fault predictable scheduling on a shop floor
by Wei Ji, Wenda Wu, Lihui Wang, Liang Gao
Abstract: To select a proper machine learning algorithm for fault predictable scheduling on a shop floor, ten algorithms in machine learning field have been selected, implemented and compared in this research. Due to the lack of applicable real data to the authors, a data generation method is proposed in terms of data complexity, number of data attributes and data depth. On top of the method, six datasets are generated by selecting three-level data attributes and three-level data depths, and they are used to train the ten algorithms. The performances of the algorithms are evaluated by considering three indexes including training accuracy, testing time and training time. The results demonstrate that Naive Bayes classifier is suitable to low-complexity data, and that convolutional neural network and deep belief network fit well in high-complexity data, such as the real data.
Keywords: Machine learning; Benchmarking; Fault prediction;Scheduling.
Multi-objective optimization of friction stir welding parameters: Integration of FEM and NSGA-II
by Thella Babu Rao, Naresh Baki, C.S.P Rao
Abstract: In this investigation the friction stir welding (FSW) parameters were optimized by integrating the finite element analysis and non-dominated sorting genetic algorithm
Keywords: Friction stir welding; thermo-mechanical modelling; peak temperature; flow stress; response surface methodology; multi-response optimization; non-dominated sorting genetic algorithm-II.
Optimizing milled titanium alloy concave surface quality with micro-textured ball-end milling cutters
by Xin Tong, Xianli Liu, Shucai Yang, Lihui Wang, Chunsheng He
Abstract: The cutting speed at the lowest point of a ball-end milling cutter is zero, which results in poor workpiece surface quality and serious tool wear. To alleviate this problem, a micro-texture can be processed on the rake face of a ball-end milling cutter to provide an anti-friction and anti-wear mechanism. The objective of the work reported here is to reduce tool wear and optimize workpiece surface quality. By using a mathematical model of row spacing to analyze the differential geometric relationship between cutters and surfaces at their contact point, we have 4been able to obtain optimal cutter orientation. This was verified by simulating concave surface machining. Experiments were then conducted to verify the approach and the results showed that when the cutter orientation is adjusted to its optimum, the surface quality of the workpiece processed by a micro-textured ball-end milling cutter is at its best.
Keywords: Key words: titanium alloys; cutting temperature field models; blunt tool edge radius; temperature distribution.
Multi-criteria Process Optimization for better machinability in Turning Medium Carbon Steel using Composite Desirability Approach
by Prianka B. Zaman, Nikhil R. Dhar
Abstract: Machinability of a particular material can be assessed by different indices. Considering multiple indices or criteria concurrently for selecting optimum conditions helps to enhance the overall machinability. In this work, optimum cutting speed, feed rate and cooling environment were accomplished for minimum cutting temperature, chip reduction coefficient and surface roughness by using composite desirability technique in turning medium carbon steel by coated carbide insert. Before performing the optimization, quadratic models for different responses were developed by regression analysis and verified using R2 values which were above 99% for all the models and the % error values were less than 3% for each case. With respect to maximum composite desirability value (0.989), the process parameters were selected as 96.988 m/min cutting speed, 0.12 mm/rev feed rate and NFMQL environment. It is expected that optimum process parameters help to acquire better machinability in turning medium carbon steel by coated carbide insert.
Keywords: Composite desirability; Cutting temperature; MQL; Multi-criteria optimization; nano-fluid; chip reduction coefficient; Surface roughness.
Comprehensive Testing and Performance Evaluation of Chain-type Tool Magazine and ATC
by Xiaohong Lu, Steven Y. Liang, Yihan Luan, Pengzhuo Han, Z.O.U. Yun
Abstract: Considering that the failure of chain-type tool magazine and ATC (Automatic Tool Changer) usually associates with the change of some performance parameters, comprehensive laboratory testing and performance evaluation of chain-type tool magazine and ATC need to be studied. Firstly, the control system of the tool magazine and ATC is designed, including the magazine movement control, ATC motion control and the realization of NC system. Then, based on the failure data, the authors develop a comprehensive performance testing system for tool magazine and ATC. The system can realize the testing of angular rotation and axial shifts of manipulator, vibration of ATC, positioning error, vibration on the tool oriented part and noise. Finally, the system is applied in the testing of a tool magazine and ATC, and the experimental results show that the developed chain-type tool magazine and ATC comprehensive laboratory testing and performance evaluation system can be realized.
Keywords: Tool Magazine; ATC; Laboratory testing; Performance Evaluation.
Human Locomotion Activity Recognition using Spectral Analysis and Convolutional Neural Networks
by Ze Ji, Ahmad Amer
Abstract: To enable a collaborative robot or exoskeleton robot to better support humans more safely and efficiently, understanding human behaviours is an essential enabling technology for the machines to make decisions on optimal control strategies. This work introduces an algorithm for classification of human locomotion activities using inertial data captured with Inertial Measurement Unit (IMU) to support the control of robots, exoskeletons and many other applications. The proposed approach, to recognise human locomotion activities and gait events, includes two main steps: 1) applying spectral analysis on the inertial signals to transform the data into time-frequency representation; and 2) classify the time-frequency data of an image to be recognised using Convolutional Neural Networks (CNN). There are six activities considered in the work. The highest accuracy in classification with a sub-set of 3 classes is 99% demonstrating the promising result in being applicable for real applications.
Keywords: Locomotion Activity Recognition; Inertial Measurement Unit; Spectrogram; Convolutional Neural Networks.
Automatic Identification of Mechanical Parts for Robotic Disassembly Using the PointNet Deep Neural Network
by Marco Castellani, Senjing Zheng, Luca Baronti, Feiying Lan, Duc Pham
Abstract: This paper presents a study on the identification of objects from 3D scenes (point clouds) of mechanical components of automotive devices, using the PointNet deep neural network. PointNet was trained to recognize twelve parts of models of engine turbocharger. The twelve instances included different types of parts, as well as different models of the same part. The PointNet was trained using partial images of the objects generated from CAD models, and tested on unseen examples. Experimental trials indicated that PointNet is able to recognise with accuracy the mechanical parts, and that its learning procedure is consistent and effective. In presence of sensor imprecision, the accuracy in the recall phase can be increased adding stochastic error to the training examples. The possibility of training twelve independent classifiers to be employed separately or in one ensemble classifier was investigated. The results were comparable to those obtained using one classifier for all parts.
Keywords: Remanufacturing; Disassembly; Automotive; Machine Vision; Point Clouds; Deep Neural Networks.
Finite element modelling of large radius bending operation
by Vitalii Vorkov, Dirk Vandepitte, Joost R. Duflou
Abstract: The finite element method is the default choice for the prediction of complex forming processes. In this work, this method is applied to the prediction of large radius air bending of high-strength steels. Three distinct formulations are used for the prediction: plane, shell and solid. Appropriate mesh parameters and material implementation are used in order to obtain high prediction accuracy and to minimise the calculation time. A new law for the approximation of the hardening behaviour of high-strength steels is introduced and further used for the minimisation of the prediction error. Contact points position, springback, bending force and bend allowance are used for the comparison between experimental and simulation data. Obtained results show that the plane model is not a suitable option for the modelling of large radius air bending, due to an instable behaviour with respect to the number of elements through the thickness. Shell and solid formulations, however, provide high accuracy prediction for the considered bending characteristics with comparable predictive quality. [Submitted 21 August 2018; Accepted 27 January 2019]
Keywords: bending; sheet metal; springback; finite element modelling; high-strength steel; Aerens law.
Effect of parameters and optimisation of rotary ultrasonic drilling through desirability and PSO
by Vikas Kumar, Hari Singh
Abstract: In this paper, an attempt has been made to drill 'BK-7' using rotary ultrasonic machining (RUM). The effects of machining parameters namely feed, spindle speed and ultrasonic power were investigated on material removal rate (MRR) and chipping thickness (CT). Response surface methodology (RSM) was utilised for developing regression equations for output responses. The response observations were tested through analysis of variance (ANOVA) for recognising the significant input variables. The selected responses were found to be highly influenced by feed and exhibited opposite variation with increase in feed. Furthermore, the study also targets to improve the machining efficacy by optimising the machining parameters using desirability and particle swarm optimisation (PSO) approaches. Both the approaches were found to be equally viable. However, PSO exhibited an ease in obtaining the optimised solution with lesser time to cope up with industrial needs. [Submitted 15 April 2018; Accepted 23 December 2018]
Keywords: material removal rate; MRR; chipping; particle swarm optimisation; PSO; regression; desirability; rotary ultrasonic machining; RUM.
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. [Submitted 15 May 2016; Accepted 16 January 2019]
Keywords: thin-walled parts; initial residual stress; machining paths; finite element; ABAQUS; milling; cutting parameter; machining deformation.
Adapting whirling process for CNC manufacture of bespoke screws with variable pitch and diameters
by Jiaming Feng, Riliang Liu, Yikun Li
Abstract: Widely increased use of screws with variable pitch, flight and core in contemporary machinery makes it of great significance to explore an efficient way for manufacturing them. This paper proposes a whirling-based approach to manufacturing bespoke screws of kind. The machining is performed on a 3-axis CNC whirling machine. Unlike conventional whirling process which uses profiled cutters to cut the helical grooves, this approach employs tipped cutters which follow complicated toolpath to cut the screw out of a blank. In order to determine a continuous toolpath to approximate the screws cross-section profiles, one after another, the screw's cross-section profiles are considered as the envelope of the tipped cutters' trajectory and m CC points on each cross-section are relocated at several hypothetical cutting planes evenly. Finally, machining test using an example screw part is conducted to demonstrate the feasibility of the proposed approach. [Submitted 29 December 2018; Accepted 27 February 2019]
Keywords: bespoke screw; screw with variable pitch; tapered screw; thread whirling; CNC machining.
Reliability-oriented multi-resource allocation for seru production system with stochastic capacity
by Xinzi Han, Zhe Zhang, Yong Yin
Abstract: Seru production system, which can meet the demands characterised by varied product assortment and fluctuant volumes in Japanese production practice, consists of several serus where the capacity of each seru is not certain but stochastic. Therefore, the capacity of each seru has multiple operational states. In this situation, the system reliability is an important issue to evaluate the performance of this new type production mode. The reliability in this paper is defined as the probability that a seru production system with stochastic capacity can satisfy the given demands within a fixed period, and a resource allocation problem in a stochastic-flow network, i.e., how to allocate various resources to each seru from a reliable angle, is formulated to maximise the system reliability. An efficient solution method is designed according to the characteristic of network, and two cases are given to illustrate the proposed model and solution method. [Submitted 24 January 2019; Accepted 7 May 2019]
Keywords: seru production system; reliability; resource allocation; stochastic capacity.