Showing papers in "The International Journal of Advanced Manufacturing Technology in 2013"

Additive manufacturing and its societal impact: a literature review

Abstract: Thirty years into its development, additive manufacturing has become a mainstream manufacturing process. Additive manufacturing build up parts by adding materials one layer at a time based on a computerized 3D solid model. It does not require the use of fixtures, cutting tools, coolants, and other auxiliary resources. It allows design optimization and the producing of customized parts on-demand. Its advantages over conventional manufacturing have captivated the imagination of the public, reflected in recent mainstream publications that call additive manufacturing “the third industrial revolution.” This paper reviews the societal impact of additive manufacturing from a technical perspective. Abundance of evidences were found to support the promises of additive manufacturing in the following areas: (1) customized healthcare products to improve population health and quality of life, (2) reduced environmental impact for manufacturing sustainability, and (3) simplified supply chain to increase efficiency and responsiveness in demand fulfillment. In the mean time, the review also identified the need for further research in the areas of life-cycle energy consumption evaluation and potential occupation hazard assessment for additive manufacturing.

A review on 3D micro-additive manufacturing technologies

Abstract: New microproducts need the utilization of a diversity of materials and have complicated three-dimensional (3D) microstructures with high aspect ratios. To date, many micromanufacturing processes have been developed but specific class of such processes are applicable for fabrication of functional and true 3D microcomponents/assemblies. The aptitude to process a broad range of materials and the ability to fabricate functional and geometrically complicated 3D microstructures provides the additive manufacturing (AM) processes some profits over traditional methods, such as lithography-based or micromachining approaches investigated widely in the past. In this paper, 3D micro-AM processes have been classified into three main groups, including scalable micro-AM systems, 3D direct writing, and hybrid processes, and the key processes have been reviewed comprehensively. Principle and recent progress of each 3D micro-AM process has been described, and the advantages and disadvantages of each process have been presented.

Cuckoo search algorithm for the selection of optimal machining parameters in milling operations

Abstract: In this research, a new optimization algorithm, called the cuckoo search algorithm (CS) algorithm, is introduced for solving manufacturing optimization problems. This research is the first application of the CS to the optimization of machining parameters in the literature. In order to demonstrate the effectiveness of the CS, a milling optimization problem was solved and the results were compared with those obtained using other well-known optimization techniques like, ant colony algorithm, immune algorithm, hybrid immune algorithm, hybrid particle swarm algorithm, genetic algorithm, feasible direction method, and handbook recommendation. The results demonstrate that the CS is a very effective and robust approach for the optimization of machining optimization problems.

Influence of process parameters on surface roughness of aluminum parts produced by DMLS.

Abstract: Direct metal laser sintering (DMLS) is an additive manufacturing technique for the fabrication of near net-shaped parts directly from computer-aided design data by melting together different layers with the help of a laser source. This paper presents an investigation of the surface roughness of aluminum samples produced by DMLS. A model based on an L18 orthogonal array of Taguchi design was created to perform experimental planning. Some input parameters, namely laser power, scan speed, and hatching distance were selected for the investigation. The upper surfaces of the samples were analyzed before and after shot peening. The morphology was analyzed by means of field emission scanning electron microscope. Scan speed was found to have the greatest influence on the surface roughness. Further, shot peening can effectively reduce the surface roughness.

Relations between transformational leadership, organizational learning, knowledge management, organizational innovation, and organizational performance: an empirical investigation of manufacturing firms

Abstract: The aim of this study is to determine relations between transformational leadership, organizational learning, knowledge management, organizational innovation, and organizational performance among Iranian manufacturing companies through structural equation modeling. Two hundred eighty senior, executive, administrative, and other-level managers are selected from among 106 companies having more than 50 employees. Data are analyzed using structural equation modeling. The following findings are found: transformational leadership directly influenced organizational learning and knowledge management. Organizational learning directly and positively influenced knowledge management of manufacturing firms. Transformational leadership positively influenced organizational innovation and organizational performance of manufacturing firms. Organizational learning and knowledge management directly influenced organizational innovation; whereas organizational learning and organizational innovation directly influenced organizational performance among manufacturing firms. Meanwhile, transformational leadership positively and indirectly influenced organizational innovation through organizational learning and knowledge management. Knowledge management and organizational learning effected organizational performance indirectly by organizational innovation. The fit indices shows that the proposed model have an appropriate fit (χ2/df = 2.33, RMSEA = 0.069, NFI = 0.95, NNFI = 0.95, CFI = 97). If leaders of manufacturing firms undertake a transformational role and use organizational learning and knowledge management, this will facilitate organizational innovation and will consequently improve organizational performance to a great extent in manufacturing firms.

A new approach to the design and optimisation of support structures in additive manufacturing.

Abstract: Support structures are required in several additive manufacturing (AM) processes to sustain overhanging parts, in particular for the production of metal components Supports are typically hollow or cellular structures to be removed after metallic AM, thus they represent a considerable waste in terms of material, energy and time employed for their construction and removal This study presents a new approach to the design of support structures that optimise the part built orientation and the support cellular structure This approach applies a new optimisation algorithm to use pure mathematical 3D implicit functions for the design and generation of the cellular support structures including graded supports The implicit function approach for support structure design has been proved to be very versatile, as it allows geometries to be simply designed by pure mathematical expressions This way, different cellular structures can be easily defined and optimised, in particular to have graded structures providing more robust support where the object’s weight concentrate, and less support elsewhere Evaluation of support optimisation for a complex shape geometry revealed that the new approach presented can achieve significant materials savings, thus increasing the sustainability and efficiency of metallic AM

Density of Additively-Manufactured, 316L SS Parts Using Laser Powder-Bed Fusion at Powers Up to 400W

Abstract: Selective laser melting is a powder-based, additive-manufacturing process where a three-dimensional part is produced, layer by layer, by using a high-energy laser beam to fuse the metallic powder particles. A particular challenge in this process is the selection of appropriate process parameters that result in parts with desired properties. In this study, we describe an approach to selecting parameters for high-density (>99 %) parts using 316L stainless steel. Though there has been significant success in achieving near-full density for 316L parts, this work has been limited to laser powers 99 %, with the density reducing rapidly at high speeds due to insufficient melting, and less rapidly at low speeds due to the effect of voids created as the process enters keyhole mode.

A comparison of the tensile, fatigue, and fracture behavior of Ti–6Al–4V and 15-5 PH stainless steel parts made by selective laser melting

Abstract: In this work, Ti–6Al–4V and 15-5 PH steel samples were fabricated using selective laser melting (SLM) and their tensile, fatigue, and fracture properties were analyzed and compared. The tensile properties were compared with respect to the build orientation. The horizontally built samples showed relatively better tensile properties as compared with the vertically built samples. Fatigue performance was studied for the vertical build orientation and compared with standard wrought material data. The tensile and fatigue performance of SLM-built materials were comparable to their respective standard wrought materials. Fractography was carried out for all tensile and fatigue-tested samples. The fatigue fracture behavior of Ti–6Al–4V was different from 15-5 PH steel. For Ti–6Al–4V, the fatigue crack initiation occurred deep in the subsurface whereas for PH steel the fatigue crack was initiated from the surface.

Research on the fabricating quality optimization of the overhanging surface in SLM process

Abstract: Overhanging surface is inherent geometric restraint during selective laser melting (SLM), which is suitable for various complex parts fabrication. In order to improve the fabricating quality of overhanging surface, a series of experiments were designed to investigate the effects of inclined angle, scanning speed, laser power, accumulated residual stress, and scanning vector length on overhanging surface fabrication. Analysis found that overhanging surface would warp easier when the inclined angle and the scanning speed became smaller and the warping trend will be larger as the laser power became larger. The relationships of laser power, scanning speed, and the critical inclined angle were mutual restraint, that is, larger inclined angle will be designed when the laser power becomes larger and scanning speed gets smaller, or vice versa: the selection of the fabricating parameters will be determined by established inclined angle of the overhanging surface. More serious warp would happen as the processing layers increased as a result of residual stress accumulation, and it was found that longer scanning vector were more helpful to stress accumulation, leading to more serious warp than shorter vector. At last, two effective methods were adopted to optimize overhanging surface fabrication, including adjusting part orientation to improve the inclined angle at the key position, and controlling regional parameters to reduce energy input. Above two ways were adopted to manufacture complex parts with typical overhanging surface, the results proved that adjusting part orientation and controlling regional parameters were effective ways to improve the fabricating quality of overhanging surface. In this study, the basis for building overhanging surface by SLM was provided from the view of process and design, and the preliminary solutions were proposed to manufacture complex metal parts with lower risk.

A review of flank wear prediction methods for tool condition monitoring in a turning process

Abstract: Flank wear is the most commonly observed and unavoidable phenomenon in metal cutting which is also a major source of economic loss resulting due to material loss and machine down time. A wide variety of monitoring techniques have been developed for the online detection of flank wear. In order to provide a broad view of flank wear monitoring techniques and their implementation in tool condition monitoring system (TCMS), this paper reviews three key features of a TCMS, namely (1) signal acquisition, (2) signal processing and feature extraction, and (3) artificial intelligence techniques for decision making.

Robot machining: recent development and future research issues

Abstract: Early studies on robot machining were reported in the 1990s. Even though there are continuous worldwide researches on robot machining ever since, the potential of robot applications in machining has yet to be realized. In this paper, the authors will first look into recent development of robot machining. Such development can be roughly categorized into researches on robot machining system development, robot machining path planning, vibration/chatter analysis including path tracking and compensation, dynamic, or stiffness modeling. These researches will obviously improve the accuracy and efficiency of robot machining and provide useful references for developing robot machining systems for tasks once thought to only be capable by CNC machines. In order to advance the technology of robot machining to the next level so that more practical and competitive systems could be developed, the authors suggest that future researches on robot machining should also focus on robot machining efficiency analysis, stiffness map-based path planning, robotic arm link optimization, planning, and scheduling for a line of machining robots.

Sustainable manufacturing: evaluation and modeling of environmental impacts in additive manufacturing

Abstract: Cleaner production and sustainability are of crucial importance in the field of manufacturing processes where great amounts of energy and materials are being consumed Nowadays, additive manufacturing technologies such as direct additive laser manufacturing allow us to manufacture functional products with high added value Insofar as environmental considerations become an important issue in our society, as well as legislation regarding environment become prominent (Normalization ISO 14 044), the environmental impact of those processes have to be evaluated in order to make easier its acceptance in the industrial world Some studies have been conducted on electric consumption of machine tools (standby consumption, in process consumption, etc) but only a few studies take into account the whole existing environmental flows (material, fluids, electricity) This paper presents a new methodology where all flows consumed (material, fluids, electricity) are considered in the environmental impact assessment This method coupled a global view required in a sustainable approach and an accurate evaluation of flow consumption in the machine The methodology developed is based on a predictive model of flow consumption defined from the manufacturing path and CAD model of the part which will be produce In order to get an accurate model of the process, each feature of the machine is modeled The goal of this work is to integrate this model into the design loop for additive manufacturing parts

A review on the state-of-the-art microforming technologies

Abstract: Product miniaturization is an emerging trend for facilitating product usage, enabling unique product functions to be implemented in micro-scaled geometries and features, and further reducing product weight and volume. Recently, a demand for microparts increased significantly in many industry clusters. Development of the advanced micromanufacturing technologies for fabrication of such microparts has thus become a critical issue. Microforming, which offers attractive characteristics including high productivity, low cost and good quality of the formed parts, provides a promising approach to fabricating metallic microparts. In the last two decades, a lot of effort has been made to the researches on size effect related deformation behaviors in microforming process and the development of the process. Having a panorama of these researches is necessary to support micropart design and development via microforming, and further advance this micromanufacturing process. In this paper, an intensive review on the latest development of microforming technologies is presented. First of all, the paper is focused on the review of the size effect-affected deformation behaviors and the mechanisms of the changes of flow stress, flow behavior, fracture behavior, elastic recovery, tooling–workpiece interfacial friction and the surface finish of the formed parts. The state-of-the-art microforming processes, including micro deep drawing, microembossing, micropunching, microcoining, microextrusion, microheading, and micro progressive forming are then presented. Finally, some research issues from the implementation of mass production perspective are also discussed.

Cloud manufacturing service platform for small- and medium-sized enterprises

Abstract: In order to address the key problems faced by small- and medium-sized enterprises (SMEs), existing solutions and shortcomings were analyzed. The possibilities by using the new emerged technologies and theories (e.g., cloud computing, internet of things, service-oriented technology) to solve the bottlenecks faced by SMEs are investigated. The idea of manufacturing resource and capability sharing based on cloud computing for SME is discussed, and an SME-oriented cloud manufacturing service platform (SME-CMfgSP) is introduced. The architecture of SME-CMfgSP is proposed, and the key technologies for implementing SME-CMfgSP are introduced in details. The challenges for implementing cloud manufacturing service platform for SMEs were discussed. A case study is described to illustrate the application of the proposed SME-CMfgSP.

Multi-response optimization of process parameters based on response surface methodology for pure titanium using WEDM process

Abstract: This paper presents an investigation on WEDM of pure titanium (grade-2). An attempt has been made to model the four response variables, i.e., machining rate, surface roughness, dimensional deviation and wire wear ratio in WEDM process using response surface methodology. The experimental plan is based on Box–Behnken design. The six parameters, i.e., pulse on time, pulse off time, peak current, spark gap voltage, wire feed and wire tension have been varied to investigate their effect on output responses. These responses have been optimized using multiresponse optimization through desirability. The ANOVA has been applied to identify the significance of developed model. The test results confirm the validity and adequacy of the developed RSM model. Finally, the optimum parametric setting has been designed for the optimization of process.

An exploration of green supply chain practices and performances in an automotive industry

Abstract: During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection. Globalization and the increased number of countries entering the World Trade Organization (WTO) have promoted green supply chain management (GSCM) practices in manufacturing organizations. GSCM has emerged as an important organizational philosophy and a proactive approach to reduce environmental risks. Increasing pressures such as stricter regulations, increased community, and consumer pressures, and the developing country’s aim to enter the WTO have caused automotive supply chain managers to consider and to implement GSCM practices to improve both their economic and environmental performances. This paper explores the practices and performances of the GSCM based on the GSCM literature, and it considers the relationship between green supply chain practices (initiatives) and performance outcomes. In this paper, two questionnaires were developed and a survey conducted to assess the importance of GSCM practices and performances in an automotive company in a developing country using a fuzzy multiple criteria decision-making method. The result of this paper presents practical guidance for managers in performing GSCM practices by ranking GSCM practices according to their importance which leads to improving GSCM performances.

Analysis of interaction between the barriers for the implementation of sustainable supply chain management

Abstract: In the contemporary marketplace, it is essential for industries to offer environmentally conscious, "green" products. Because industries are aware of demands from both customers and from government policies towards en- vironmental products, Indian industries are particularly pressured regarding issues of environmental adoption. At this point, they presently have less detailed research on the effects of the adoption of environmental practices using traditional supply chain management (TSCM). One sector that is less aware of environmental initiation practices in the TSCM is the fastener manufacturing industry, but they are in a good position to adopt and to improve their environmental performance. Sustainable supply chain management (SSCM) is an important concept to improve environmental perfor- mance in TSCM and to provide a useful green image in industrial products. However, there are many barriers to the successful implementation of SSCM, and it should be noted that not all the barriers carry an equal impact. We need to identify the dominant factors required to adopt the SSCM concept, so that industries need to analyze the barriers and their impacts. The main aim of this paper is to determine the relationship between the barriers and to identify the most influential barriers from the recommended barrier list with the help of interpretive structural modeling. In this study, 13 barriers are considered from the extensive literature available. This study has been conducted in two fastener manufacturing industries that are located in the southern part of India.

Potential of cold gas dynamic spray as additive manufacturing technology

Abstract: In this paper, the application of cold spray (CS) coating deposition technology as additive manufacturing technique is discussed. Absence of material melting during CS deposition permits to obtain deposits with low value of residual stresses and to preserve the phase composition of source material which is a very important advantage. In this paper, the latest developments in the field of cold spray such as micronozzle device and new multimaterial deposition approach permitting to significantly enlarge the potential of cold spray as additive manufacturing technology is discussed.

Numerical modeling of friction stir welding process: a literature review

Abstract: This survey presents a literature review on friction stir welding (FSW) modeling with a special focus on the heat generation due to the contact conditions between the FSW tool and the workpiece. The physical process is described and the main process parameters that are relevant to its modeling are highlighted. The contact conditions (sliding/sticking) are presented as well as an analytical model that allows estimating the associated heat generation. The modeling of the FSW process requires the knowledge of the heat loss mechanisms, which are discussed mainly considering the more commonly adopted formulations. Different approaches that have been used to investigate the material flow are presented and their advantages/drawbacks are discussed. A reliable FSW process modeling depends on the fine tuning of some process and material parameters. Usually, these parameters are achieved with base on experimental data. The numerical modeling of the FSW process can help to achieve such parameters with less effort and with economic advantages.

Multiple process parameter optimization of wire electrical discharge machining on Inconel 825 using Taguchi grey relational analysis

Abstract: In this paper, an effective approach, Taguchi grey relational analysis, has been applied to experimental results of wire cut electrical discharge machining (WEDM) on Inconel 825 with consideration of multiple response measures. The approach combines the orthogonal array design of experiment with grey relational analysis. The main objective of this study is to obtain improved material removal rate, surface roughness, and spark gap. Grey relational theory is adopted to determine the best process parameters that optimize the response measures. The experiment has been done by using Taguchi’s orthogonal array L36 (21 × 37). Each experiment was conducted under different conditions of input parameters. The response table and the grey relational grade for each level of the machining parameters have been established. From 36 experiments, the best combination of parameters was found. The experimental results confirm that the proposed method in this study effectively improves the machining performance of WEDM process.

Optimization of micro-EDM drilling of inconel 718 superalloy

Abstract: In this study, the gray relational analysis method was used to optimize the micro-electrical discharge machining (EDM) drilling process of Inconel 718 nickel-based superalloy with multiperformance characteristics. In order to determine the best factor level conditions, a full factorial experimentation was performed based on the micro-EDM parameters of discharge current and pulse duration. The hole taper ratio (H t) and hole dilation (H d) were the measured performances. By analyzing the used optimization results, it was observed that the pulse current was more efficient on performance characteristics than pulse duration. The characteristics of drilled surfaces and tool electrodes were also investigated by using optical and scanning electron microscopy. A linear regression model was developed to estimate the performances. The measured and model results were in a good agreement with correlation coefficients of R 2 = 0.897 and R 2 = 0.929 for H t and H d, respectively. It is concluded that the EDMed hole quality can be improved effectively through this approach.

Optimization of production scheduling with time-dependent and machine-dependent electricity cost for industrial energy efficiency

Abstract: In many industrialized countries, manufacturing industries pay stratified electricity charges depending on the time of day (i.e., peak-load, mid-load, and off-peak-load). In contrast, the emerging smart grid concept may demand that industries pay real-time hourly electricity costs so as to use energy most efficiently. This paper deals with the production and energy efficiency of the unrelated parallel machine scheduling problem. This method allows the decision maker to seek a compromise solution using the weighted sum objective of production scheduling and electricity usage. Reliability models are used to consider the energy cost aspect of the problem. This paper aims to optimize the weighted sum of two criteria: the minimization of the makespan of production and the minimization of time-dependent electricity costs. We suggest a hybrid genetic algorithm with our blank job insertion algorithm and demonstrate its performance in simulation experiments.

Decision models of closed-loop supply chain with remanufacturing under hybrid dual-channel collection

Abstract: A number of factors, including environmental legislations and increasing global uncertainties, have led many companies to consider engaging in remanufacturing. In this paper, we mainly address a topical issue of choosing the appropriate reverse channel format for collecting used products from customers. We suppose a manufacturer who has three reverse hybrid collection channel structures to choose: (1) manufacturer and retailer collecting used products at the same time, (2) manufacturer contracting the collection of used products to a retailer and a third party, and (3) manufacturer and third party collecting used products at the same time. To generate managerial insights into this important issue, we develop a structural model to explore the appropriate reverse channel structure for the manufacturer. Numerical examples are presented to demonstrate the applicability of the presented model. The results show that, ceteris paribus, the manufacturer and the retailer hybrid collection channel is the most effective reverse channel structure for the manufacturer. We also find that, under the same conditions, the manufacturer and the retailer hybrid collection approach is obviously superior to the single channel collection approach. Finally, we explore the channel coordination mechanism to implement channel cooperation for the manufacturer and the retailer. Our results indicate that the strategic alliance between the manufacturer and the retailer can effectively achieve the desired channel coordination. Furthermore, the Nash bargaining model is utilized to implement profit sharing for the manufacturer and the retailer in the channel coordination of strategic alliance.

Scheduling optimization of flexible manufacturing system using cuckoo search-based approach

Abstract: In the present work, a cuckoo search (CS)-based approach has been developed for scheduling optimization of a flexible manufacturing system by minimizing the penalty cost due to delay in manufacturing and maximizing the machine utilization time. To demonstrate the application of cuckoo search (CS)-based scheme to find the optimum job, the proposed scheme has been applied with slight modification in its Levy flight operator because of the discrete nature of the solution on a standard FMS scheduling problem containing 43 jobs and 16 machines taken from literature. The CS scheme has been implemented using Matlab, and results have been compared with other soft computing-based optimization approaches like genetic algorithm (GA) and particle swarm optimization found in the literature. The results shown by CS-based approach have been found to outperform the results of existing heuristic algorithms such as GA for the given problem.

Energy density analysis on single tracks formed by selective laser melting with CoCrMo powder material

Abstract: Selective laser melting (SLM) is an advanced manufacturing technology based on layer by layer building to produce solid parts from metallic powder (Kruth et al., CIRP Ann Manuf Technol 56:730–760, 2007). Commercial SLM machines are configured to use specific parameters to process different metallic powder grades. This paper proposes a methodology that makes it possible to analyze the effect of energy density on the formation of single tracks from CoCrMo powder, using a noncommercial machine to select process parameters with open source technology. Full factorial experimental work was carried out to produce single tracks under different combinations of process parameters. A major application of this research work is to develop more flexible machine configurations applicable to different materials.

Advanced gas metal arc welding processes

Abstract: There is an increased requirement in the automotive, food and medical equipment industries to weld heat-sensitive materials, such as thin sheets, coated thin plates, stainless steel, aluminium and mixed joints. Nevertheless, relevant innovations in arc welding are not widely known and seldom used to their maximum potential. In the area of gas metal arc welding welding processes, digitalisation has allowed integration of software into the power source, wire feeder and gas regulation. This paper reviews developments in the arc welding process, particularly the effect of the set-up of the welding process parameters on waveform deposition. It is found that good weldability, good mechanical joint properties and acceptable process efficiency can be obtained for thin sheets through advanced power source regulation, especially over short circuiting, controlled polarity and electrode wire motion. The findings presented in this paper are valuable for waveform and deposition prediction. The need is furthermore noted for an algorithm that integrates gas flow parameters and wire motion control, as well as a variable sensor on the tip of the electrode, permitting flexibility of control of the current and the voltage waveform.

A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem.

Abstract: For environmentally conscious and sustainable manufacturing, manufacturers need to incorporate product recovery by designing manufacturing systems to include reverse manufacturing by considering both assembly and disassembly systems. Just as the assembly line is considered the most efficient way to assemble a product, the disassembly line is seen to be the most efficient way to disassemble a product. While having some similarities to assembly, disassembly is not the reverse of the assembly process. The challenge lies in the fact that it possesses unique characteristics. In this paper, we consider a sequence-dependent disassembly line balancing problem (SDDLBP) that is concerned with the assignment of disassembly tasks to a set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the effectiveness of several measures considering sequence-dependent part removal time increments. SDDLBP is not a trivial problem since it is proven to be NP-complete. Further complications occur by considering multiple objectives including environmental and economic goals that are often contradictory. Therefore, it is essential that an efficient methodology be developed. A new approach based on the particle swarm optimization algorithm with a neighborhood-based mutation operator is proposed to solve the SDDLBP. Case scenarios are considered, and comparisons with ant colony optimization, river formation dynamics, and tabu search approaches are provided to demonstrate the superior functionality of the proposed algorithm.

Machinability study of glass fibre-reinforced polymer composites during end milling

Abstract: Machining of composite materials is usually performed to achieve required geometrical shapes and dimensional tolerances. However, machinability evaluation of glass fibre-reinforced polymer (GFRP) composites in end milling has not yet received its due attention in the research community despite the extensive industrial use of this process. This work aims to elucidate the end milling machinability of GFRP composites with respect to surface roughness, tool life and machining forces. Experiments were conducted under different experimental parameters and their levels according to the Taguchi design of experiment method. Taguchi analysis combined with statistical analysis of variance (ANOVA) was performed to quantify the effects of spindle speed, feed rate and depth of cut on those characteristics. Multiple regression analysis (MRA) was also employed to establish parametric relationships between the experimental parameters and the machinability outputs. Results from ANOVA and MRA reveal that feed rate is the governing factor affecting all the machinability outputs. The calculated values from MRA have been found to be fairly close to experimental values in almost all cases. Validation tests under randomly selected machining conditions have further demonstrated the feasibility of the developed mathematical models with 8–12% error for tool life and machining forces predictions while >19% error for calculating the surface roughness.

A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method

Abstract: Plant location selection, the process of finding a suitable location for plant of a project has a strong influence on the success of industrial venture with the goal to minimize cost and maximize the use of resources. Thus, plant location selection problem is a multicriteria decision-making problem involving several conflicting criteria on which decision makers' knowledge is vague and imprecise. Therefore, in this study, the elimination and choice translating reality (ELECTRE) method is proposed with intuitionistic fuzzy sets for selection of appropriate plant location in group decision-making environment to tackle uncertainty of the information provided by decision makers and a plant location selection problem is considered to illustrate the proposed intuitionistic fuzzy-ELECTRE method. The ratings of alternatives with respect to each criterion and the weights of each criterion are taken as linguistic terms further characterized by triangular intuitionistic fuzzy sets.

Warehouse management with lean and RFID application: a case study

Abstract: This research presents the integration of lean production and radiofrequency identification (RFID) technology to improve the efficiency and effectiveness of warehouse management. More than ten million parts belonging to around 10,000 types in a distribution center were involved in this study. There are more than 10,000 storage and retrieval operations for hundreds of part types on a daily basis. Value stream mapping was used to draw current state mapping and future state mapping (with lean management and RFID) with material flow, information flow, and time flow. Preliminary experiments showed that the average reading rate of electric forklift and hydraulic cart are 99.3 and 99.1 % by fixed ultra-high frequency RFID readers with antenna installed at the receiving/shipping dock and passive tags mounted on box/pallet. The processing time of data transmitting to warehouse management system at receiving and shipping docks was reduced by 99 and 89 %, respectively. The total operation time from current stage to future stage with only lean can be saved by 79 %. With further integration of RFID to lean, the total operation time can be saved by 87 %. Moreover, performance on saving total operation time can be enhanced to 91 % with cross-docking. The benefit of using RFID in the warehouse management is realized and promoted.