International Journal of Manufacturing Research (15 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.
Exact and Meta-heuristic Approaches for the Single-machine Scheduling Problem with Flexible Maintenance under Human Resource Constraints
by Meriem Touat, Benbouzid-Sitayeb Fatima, Belaid BENHAMOU
Abstract: This paper tackles the scheduling problem of both production and flexible preventive maintenance activities on a single machine under human resource constraints. The considered human resources oversee the maintenance activities. They are characterized by a competence level and a timetabling that determines their availabilities. Our objective is to minimize a common and weighted objective function that involves both the tardiness and the earliness resulting from production and maintenance activities when considering maintenance workers. We first introduce a mathematical modeling for the studied problem that we implemented in Cplex in order to compute the optimal solutions of small instances of this problem. Secondly, we propose an improved Guided Local Search (GLS) metaheuristic to deal with relatively large instances of the problem. Cplex is used as a reference exact method to check the solution quality of the approached method GLS. The proposed methods are evaluated on a large number of randomly
Keywords: Single machine scheduling; Flexible maintenance planning; Mathematical modeling; Guided Local Search; Human resource constraints.
Efficiency evaluation of Manufacturing firms in China. The case of Patent-Intensive Industries
by Oswin Aganda Anaba, Mingxing Li, Zhiqiang Ma, Jialu Su, Benjamin Azembila Asunka
Abstract: In an environment where there is a consistent change in the flow of innovation improvement, the advancement of innovation and technology has turned into an inevitable subject of present day enterprises, yet there exists little knowledge about their efficiency from the view point of patent-intensive industries The level of technological innovation efficiency of patent-intensive industries has an effect on the industrial structure and industrial competitiveness This paper therefore evaluates the technology innovation efficiency of Chinas patent-intensive industries using the two-stage non-parametric Data Envelopment Analysis (DEA) over the period of 2006
Keywords: patent-intensive industries; technological innovation; efficiency evaluation; two-stage DEA model.
EFFECT OF PROCESS PARAMETERS ON THE MECHANICAL BEHAVIOUR OF FRICTION STIR WELDED 5083 AND 6061 T6 ALUMINUM ALLOYS
by Sabitha Jannet, Raja R
Abstract: Aluminum alloys are a significant material for research in joining process due to their applications in shipbuilding, aircraft, automobile industries. In this study a 31 run central composite design has been used to run the experiment and reduce errors. The mathematical model was developed for Ultimate tensile strength, elongation and wear and model fitness was analysed using ANOVA. The relationship also revealed the percentage effect of various process parameters on the mechanical properties.The microhardness tests revealed the harness in the welded zones. The process parameters had a profound effect on the mechanical properties of the welded joints. The micro hardness in the welded joints were lower compared to the base metals.
Keywords: Friction stir welding; CCD; tensile strength; elongation; process parameters mathematical model.
Rapid Casting using Alternative Approach of Pattern and Mold Making
by Ranjeet Kumar Bhagchandani, K.P. Karunakaran, Pushkar Kamble, B. Ravi, Sajan Kapil
Abstract: Evaporative Pattern Casting (EPC) process facilitates the production of parts with complicated geometries. Two major problems associated with EPC are the fabrication of the metal tooling and complicated mold preparation. To overcome these limitations, a novel Rapid Foam Casting (RFC) process is proposed. The complicated pattern geometries as selected on the basis of shape complexity are produced by the authors developed Rapid Prototyping machine namely Segmented Object Manufacturing. Patterns are then converted into metallic castings by adopting two alternative molding processes for EPC i.e. no-bake and green sand molding. Taguchis orthogonal array is used for the design of experiments to investigate the effect of the part geometry, pattern density and molding method on surface finish and dimensional accuracy of the casting. Analysis of variance (ANOVA) is also performed to find out the individual participation of each factor on the surface finish and dimensional accuracy of the casting.
Keywords: Rapid Foam Casting; Rapid Prototyping; Evaporative Pattern Casting; Segmented Object Manufacturing; Expanded Polystyrene.