International Journal of Manufacturing Research (28 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.
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.
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.
Exploiting the Drill Cutting Lip to Quantify the Contributions of Process Parameters To Cutting Pressures - A Response Surface Analysis
by Charbel Seif, Ramsey Hamade, Ilige Hage, Re-Mi Hage
Abstract: This work exploits the characteristically complex geometry along the lip of a chisel drill. Few dry drilling experiments are conducted on aluminium 6061-T6 workpieces pre-cored with holes of diameters ranging from 25% to 75% of the drill diameter. Based on the generated torque and thrust force drilling profiles, incremental tangential, Ktc, and normal, Knc, cutting pressures values are assigned to the radial position of each cutting lip element. The resulting pressures amounted to a large number (192) of equivalent oblique turning tests with each edge possessing individual cutting parameters of uncut chip thickness, cutting speed, normal rake angle, and oblique cutting angle, Statistical analyses were performed on collected data. Sensitivity of the found cutting pressures with respect to cutting parameters is validated against literature-reported findings based mainly on turning tests. The findings support this works approach of employing drilling as a data collection tool in lieu of orthogonal cutting experiments.
Keywords: drilling; cutting pressures; response surface design; data analysis.
A Modeling and Semantic Description Method of Cloud 3D Printing Order Task Ontology Based on Multidimensional Features
by Chenglei ZHANG
Abstract: Aiming at the demands of unified modeling and standardization description of Cloud 3D Printing order tasks which are heterogeneous, multidimensional, semantic and other characteristics in Cloud manufacturing environment, based on Web Service and Semantic Web Services, a semantic description and encapsulation method of 3D Printing order tasks is studied. It includes: proposes a modeling and semantic description method of Cloud 3D Printing order task ontology Based on multidimensional features. Through the this features of Cloud 3D Printing order resources, the attributes of Cloud 3D Printing order tasks are decomposed them into atomic tasks according to the purpose of order tasks; the Cloud 3D Printing order task meta-data ontology modeling method and service packaging technology are studied, and then the feasibility of the method is verified by an example of Cloud 3D Printing order task semantic description model.
Keywords: Multidimensional Features · Order Task · Web Services · C3DP · Semantic Description · Meta-data.
Flow field analysis of the measuring stability of the head of a pneumatic measuring instrument
by Xianjie Wei, Wei Long, Pu Ren, Wei Deng
Abstract: The existing air gauge structure often exhibits instability in measurement values, and the workpiece measurement process is prone to wear, thereby affecting the measurement accuracy and scope of the use of air gauges. Based on the principle of pneumatic measuring instruments, in this work, calculation results of the flow field between the large hole of the connecting rod and the probe are compared with measured results. It is found that the supporting air film at the guide surface of the existing probe is not complete and the airflow in the exhaust groove is disordered, thereby leading to the poor stability of the measurement process. Via further analysis of the flow field pressure, it is found that the edge of the exhaust groove near the end face of the nozzle will produce a local high-pressure zone, which will lead to the increase of the gas resistance and affect the measurement accuracy.
Keywords: pneumatic gauge; engine connecting rod; flow field stability; exhaust groove; gas resistance coefficient.
Emergency order replacement of substandard products under economic production quantity model, including shortages and backordering
by Harun Öztürk
Abstract: This paper concerns inventory control under the economic production quantity model, allowing for substandard products and shortages The imperfect manufacturing system creates a percentage of substandard products, treated as a random variable having a known probability distribution function All products produced are screened to identify substandard products. Restrictions such as production programming may make it impossible to rework substandard products, but the manufacturer has the option of replacing them by purchasing products of good quality from a domestic supplier, though these will normally have a higher unit cost. Three possible cases can occur, depending on the timing of adding emergency-purchased products to the inventory. The paper presents a numerical example and a sensitivity analysis to show how the three cases are applied within the proposed inventory model.
Keywords: inventory; economic production quantity; substandard products; shortages; reduced price; emergency purchase.
Dynamic seru order acceptance and scheduling with periodic worker assignment
by Zhe Zhang, Lili Wang, Yong Yin
Abstract: In this paper, we examine the dynamic seru order acceptance and scheduling problem with periodic worker assignment. To deal with the dynamic order arrival environment, a periodic dynamic adjustment strategy combined the technology of rolling window will be adopted. In other words, we periodically accept, schedule the coming orders and reassign workers in a periodic manner to decompose the dynamic problem into a series of continuous static sub-problems to maximize total net revenue. At the same time, an extended bi-level chromosome coding genetic algorithm combining order acceptance and scheduling results with worker assignment is designed which automatically constructs reactive adjustment strategy for the dynamic order acceptance and scheduling with worker assignment. In the end, the experimental results show that the improved genetic algorithm with rolling window technology (IGA-RWT) is feasible and effective.
Keywords: seru production system; order acceptance and scheduling; rolling window technology; worker assignment; improved genetic algorithm.
An adaptation of the Galaxy-based Search Algorithm for solving the Single Machine Total Weighted Tardiness Problem
by Mohamed HABIB ZAHMANI
Abstract: The single machine total weighted tardiness (SMTWT) problem (referred to as ) requires a given set of jobs to be sequenced on a single machine while minimising the sum of weighted tardiness, where the tardiness of a job is zero if it is completed before its due date and is equal to completion time minus its due date otherwise. In this article, the 'galaxy-based search algorithm' (GbSA) is adapted to solve the SMTWT benchmark problems and its results are compared with the best-known reported solutions. The GbSA is a newly developed optimisation tool and is considered a metaheuristic technique inspired by the dynamics of galactic arm spirals. It is robust, capable of avoiding being trapped in a local optimum, has a relative fast convergence, and is easily implementable. The experiments results show that the proposed adaptation of the GbSA is effective and obtains high-quality solutions within reasonable computation times.
Keywords: galaxy-based search algorithm; local search; single machine scheduling; total weighted tardiness; dispatching rules.
Determining favourable process parameters in Computer Numerically Controlled polishing of metal surfaces
by G.-C. Vosniakos, Panagiotis Avrampos, Theodore Mitropoulos
Abstract: Traditionally, metal surface polishing has been an important high precision process that has mostly been carried out manually, due to its high complexity and the difficulty in controlling many process parameters simultaneously. In this work a prototype polishing jig that offers elementary force control capability is utilised in order to perform flat metal surface polishing experiments based on trochoid toolpaths. The goal of this study is to optimise polishing speed, feed rate and force levels by designing Taguchi experiments and implementing subsequent ANOVA for three successive polishing stages (grinding, lapping and finishing) while following a certain polishing method (tool and diamond paste combination), which is standard knowledge contributed by domain experts. The Taguchi approach ultimately fine-tunes the polishing procedures, ensuring that the results are both consistent and optimal, the pertinent criterion being the roughness of the polished surface.
Keywords: polishing; Taguchi experiments; ANOVA; polishing rings; abrasive; jig; trochoid; toolpath.
An effective design method for mechanical metamaterials with negative Poissons ratios
by Jie Xu, Liang Gao, Mi Xiao, Hao Li
Abstract: This paper proposes an effective method for the design of mechanical metamaterials by combining the parametric level set method (PLSM) with the energy-based homogenisation method (EBHM), where the topologies and shapes of microstructures periodically distributed in the material with negative Poissons ratios are optimised simultaneously. Firstly, the effective properties of the materials are calculated by the EBHM under the topologies of microstructures, where the stress and strain theorems work as the basic theoretical framework rather than the asymptotic theory. Secondly, under the definition of the objective function to seek for the negative Poissons ratio, the PLSM is used to evolve the topological configurations of microstructures until the bulk material is to be featured with a negative Poissons ratio. Thirdly, the discrete wavelet transform (DWT) is utilised to deal with the full matrix of the globally supported radial basis function (GSRBF) interpolation. The proposed method can efficiently design the microstructure with the negative Poissons ratio on the premise of ensuring the calculation accuracy. Several numerical examples are provided to illustrate the effectiveness of the proposed method for design of microstructures considering the orthotropy and isotropy.
Keywords: metamaterials; topology optimisation; parametric level set method; PLSM; energy-based homogenisation method; EBHM; discrete wavelet transform; DWT.
A Genetic Algorithm for Designing an Integrated Cellular Manufacturing System Considering a Linear Double-Row Layout
by Mohammad Nagahisarchoghaei, Morteza Nagahi, Hamed Sharifi, Javad Rezaeian, Iraj Mahdavi, Mohammad Mahdi Paydar, Raed M. Jaradat
Abstract: To design an integrated cellular manufacturing system, cell formation (CF), cellular layout (CL), and cellular scheduling (CS) need to be determined efficiently. In this study, we propose a theoretical model for designing a cellular manufacturing system that will optimise the total completion time by making these three interrelated decisions concurrently. In the theoretical model, linear single-row and double-row cellular layouts were applied, and a genetic algorithm (GA) to solve real-sized problems was developed and tested. The results of the study indicate that the proposed model with the linear double-row layout provides more reliable results than the single-row layout, and the GA achieves acceptable solutions in a more reasonable time period compared to the traditional solution method.
Keywords: cellular manufacturing; cell formation; linear double-row layout; group scheduling; genetic algorithm.
Characteristics of Cross-Wire Welding Process Used for Welded Wire Mesh
by Huanbo Cheng, Xin Zhang, Xin Wang, Yancheng Zhu, Yu Sun, Jie Zhang
Abstract: Cross-wire welding of welded wire mesh was a complex process of interaction among thermal, electrical and mechanical field. The quantitative analysis of its welding characteristics was a difficult problem. The article presented a direct coupling analysis method of thermal, electrical and mechanical fields. The welding model was simplified to be used for simulating the actual working conditions of high temperature, strong pressure and high current. The cross-wire welding characteristics of welded wire mesh was investigated. The optimum combination and prioritisation of welding process parameters were obtained by using range analysis method, which provides reference for the selection of cross-wire welding process parameters in the actual production.
Keywords: cross-wire welding; projection welding; welding characteristic; quantitative analysis; direct coupling simulation.
A Framework for Planning a Reconfigurable Assembly System for Press Brake Production
by Olayinka Olabanji, Khumbulani Mpofu
Abstract: This article presents the design of a framework for the development of a reconfigurable assembly system (RAS) to facilitate the assembly of press brakes varieties. A consideration of press brake varieties is achieved by examining the parts taxonomy of press brakes from which a framework for assembly process plan is developed that considers all the types of press brakes identified from the classification. Also, a layout for the RAS is developed by considering a prototype of the major enabling equipment of the system which is a reconfigurable assembly fixture (RAF). The development of the assembly process plan and layout of the RAS enabled the design of a reconfiguration model for operation in the RAS. The designed assembly framework will provide; rapid and physical reconfiguration of the RAF in the RAS, generation of assembly sequence for press brake varieties and allocation of assembly operations to assembly work cells in the system.
Keywords: assembly planning; press brakes; reconfigurable assembly fixture; reconfigurable assembly system.
Computational Modeling of SLM Additive Manufacturing of Metals
by Shubham Chaudhry, JAMES WILLIAM TCHEUMANAK CHUITCHEU I.V. TCHOUAMBE, Azzeddine Soulaimani, Rajeev Das
Abstract: Additive manufacturing (AM) is a technology that can create 3D structures by depositing or melting material in a layer-by-layer manner. This paper focuses on the metal-based powder bed fusion AM approach, specifically the selective laser melting (SLM) technique. The repetitive hot and cold cycles associated with AM cause localised compression and tension giving rise to significant residual stresses, which can lead to shape loss, structural failure, etc. Numerous parameters determine the thermal gradient; these include the thermal characteristics of the powder, the bed temperature, and the part size. This investigation describes the associated problem formulation and numerical resolution in the SLM simulation. An ANSYS-additive model is developed to determine the parameter dependence on the process. An efficient parameter calibration algorithm is proposed to generate an accurate numerical model. Three numerical studies are conducted using a vertical prism, a horizontal prism, and an L-shaped structure also compared with the experimental data.
Keywords: selective laser melting; SLM; simulation; additive manufacturing; ANSYS-additive.
A deep learning model for the accurate prediction of the microstructure performance of hot rolled steel
by Binbin Wang, Yong Song, Jing Wang
Abstract: The prediction of microstructure performance can guide the adjustment of parameters during hot rolling. Scholars from all over the world has developed physical metallurgical models of rolling process based on the physical and thermodynamic characteristics of strip steel, but the prediction accuracy of the model is greatly affected by the complex production environment. In recent years, neural network method is used to build the prediction model of organisational performance. However, the prediction accuracy and robustness of the single hidden layer neural network model are poor. Deep learning method is introduced in this paper to establish the prediction model of hot rolling microstructure performance in this paper. The application results show that compared with the traditional model, the prediction accuracy of the hot rolled steels yield strength, tensile strength and elongation increased by 3.46%, 2.35%, and 5.11%, respectively.
Keywords: auto encoder; deep learning; hot rolled steel; microstructure prediction; steel properties.
A review: Finishing technologies of parts made by metal powder-bed additive manufacturing
by Li Liu, Guilian Wang, Jie Liu, Minke Cai
Abstract: Metal powder-bed additive manufacturing (AM) is known to possess good application prospects in the aerospace, medical and other fields. However, the furnishing of the surface quality of the AM parts is poor, and post-processing is required to meet the high applicability. Finishing processing is the main link in the post-processing for high-performance AM parts. In this report, the applications of machining, laser polishing, chemical and electrochemical polishing, abrasive flow machining and other typical finishing techniques used in the finishing of metal powder-bed AM parts are reviewed. Additionally, the evolution of surface roughness, material removal and residual stress of workpieces with different materials, different manufacturing processes (SLM, EBM, etc.) and different structural forms during the finishing process were analysed. An efficient and precise finishing technology can obviously improve the surface quality of the AM metal parts, which can be of great significance for the diverse applications of AM parts and reduce the costs.
Keywords: finishing technologies; additive manufacturing; metal parts; powder-bed.
A decision support system to define, evaluate, and guide the lean assessment and implementation at the shop floor level
by Saraswati Jituri, Ravneet Kaur, Brian Fleck, Dimitris Mourtzis, Rafiq Ahmad
Abstract: This article proposes a way to define leanness, a method to evaluate leanness and a guide to achieve leanness at manufacturing shop-floor level. The methodology evaluates the lean progress in terms of leanness index by considering lean manufacturing wastes and proposes lean rules for the improvement of leanness index. It is a support system for the people working at the shop-floor level in manufacturing firms to implement and practice lean manufacturing. The rapid leanness index evaluation is the unique feature of the proposed methodology. The leanness index helps users to understand the existing level of leanness and how much improvement in the leanness is needed. Lean rules advise users on how the improvements can be achieved. A case study in the Alberta Learning Factory (AllFactory) validates the proposed methodology. The methodology is also backed by a survey, which clarifies the current lean manufacturing practices in Alberta production and manufacturing industries thereby assists in target leanness index identification. Besides, a graphical user interface has been designed to support the quick leanness index evaluation addressing Lean 4.0 requirement.
Keywords: lean manufacturing; Lean 4.0; Industry 4.0; decision-support system; lean assessment; shop-floor control; production optimisation; productivity improvement.
A Batch Scheduling and Operator Assignment Model with Time-Changing Effects to Minimise Total Actual Flow Time
by Dwi Kurniawan, Andi Cakravastia, Suprayogi Suprayogi, Abdul Hakim Halim
Abstract: This paper investigates integrated problems of batch scheduling and operator assignment with time-changing effects due to the operators experiencing different degrees of learning and forgetting, and accumulating different degrees of fatigue. Each batch will be processed through a number of operations in a flow shop, where each operation can be performed by one of the alternative operators. Each operator will be assigned to a maximum of one machine, and a minimum of one operator will be assigned to each machine. The production process could produce a number of defective products that can be reworked. The problems are formulated in a model, and the decision variables are operators assignment to machines, the number of batches, batch sizes, items allocation to batches, and the schedule of the resulting batches. A proposed algorithm is developed to solve the model, and numerical examples show that the model and the algorithm work effectively for the investigated problem.
Keywords: batch scheduling; operator assignment; learning-forgetting; fatigue-recovery; actual flow time.
Prediction Model of Cutting Force in Micro-milling Single Crystal Copper
by Xiaohong Lu, Yihan Luan, Xiangyue Meng, Jianhui Feng, Steven Y. Liang
Abstract: Micro-parts of single crystal copper have been widely used in the fields of precision instruments and electricity, but little research has been done on the prediction of micro-milling force for single crystal copper. The accurate prediction of micro-milling force is the basis of studying the cutting process and tool wear. Experiments of micro-milling single crystal copper are carried out. Based on the experimental results, the effects of spindle speed, feed per tooth and axial cutting depth on the micro-milling force are analysed by using control variable method and Taguchi method. Based on the orthogonal experimental results, micro-milling force prediction models of three crystal orientations of single crystal copper are established. The exponential empirical formula between cutting force and cutting parameters is built. The coefficients of the formula are estimated by least square method. The experiment shows that the biggest relative errors are 29.38%, 32.09%, 30.30%, respectively. The average relative errors are 17.15%, 17.48%, 16.84%, respectively. Experiment verifies the validity of the model and provides a basis for subsequent single crystal materials research.
Keywords: single crystal copper; micro-milling; cutting force; crystal orientation.
Aggregated Models for Decision-support in Manufacturing Systems Management
by Leif Pehrsson, Marcus Frantzén, Tehseen Aslam
Abstract: Many industrial challenges can be related to the setup of manufacturing plants and supply chains. While there are techniques available for discrete event simulation of production lines, the opportunities of applying such techniques on higher manufacturing network levels are not explored to the same extent. With established methods for optimisation of manufacturing lines showing proven potential in conceptual analysis and development of production lines, the application of such optimisation methods on higher level manufacturing networks is a subject for further exploration. In this paper, an extended aggregation technique for discrete event simulation of higher level manufacturing systems is discussed, proposed, tested, and verified with real-world problem statements as a proof of concept. The contribution of the new technique is to enable the application of DES models, with reasonable computational requirements, at higher level manufacturing networks. The proposed technique can be used to generate valuable decision information supporting conceptual systems development.
Keywords: aggregation; discrete event simulation; DES; optimisation; decision-support; manufacturing systems management.
Improvement of Lean Manufacturing approach based on MCDM techniques for sustainable manufacturing
by Hichem Aouag, Soltani Mohyiddine
Abstract: The purpose of this paper is to propose an improved lean manufacturing approach to enhance the sustainability performances of manufacturing processes. To do that three phases are proposed. The first phase aims to propose an extended value stream mapping method to quantify the sustainability indicators and assess the manufacturing process. Secondly, entropy method is used to determine the weights of indicators. Finally, the weights obtained from entropy method are used in fuzzy evaluation based on distance from average solution (EDAS) and fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) to rank a set of kaizen events according to their ability to improve the sustainable indicators. The novelty and the main contributions of the proposed approach are proved by the development of an extended VSM method. Also, the proposed approach contributes by a new methodology for enhancing the application process of the conventional lean manufacturing approach.
Keywords: value stream mapping; VSM; lean manufacturing tools; entropy; fuzzy logic; evaluation based on distance from average solution; EDAS; TOPSIS; sustainable manufacturing.
A hybrid GA-PSO algorithm for seru scheduling problem with dynamic resource allocation
by Ling Shen, Zhe Zhang, Xiaoling Song, Yong Yin
Abstract: : As a new type flexible production mode, seru production is widely used in Japanese enterprises to deal with the manufacturing market with volatile and diversified demand. In practical seru production, product processing time may be related to resource allocation, i.e., more resource allocation, less processing time. Thus, this paper attempts to solve seru scheduling problems with dynamic resource allocation, along with which the learning effect of workers is also considered. A combinatorial optimisation model is proposed to minimise the makespan, and a hybrid GA-PSO algorithm with nonlinear inertia weight is specifically designed to solve the proposed model. Finally, a numerical example is presented to verify the effectiveness of hybrid algorithm. The computational results indicate that hybrid GA-PSO algorithm is efficient, and dynamic resource allocation should be considered in seru scheduling problems.
Keywords: seru scheduling; GA-PSO; dynamic resource allocation; learning effect.