Showing papers in "The International Journal of Advanced Manufacturing Technology in 2015"

Wire-feed additive manufacturing of metal components: technologies, developments and future interests

Abstract: Wire-feed additive manufacturing (AM) is a promising alternative to traditional subtractive manufacturing for fabricating large expensive metal components with complex geometry. The current research focus on wire-feed AM is trying to produce complex-shaped functional metal components with good geometry accuracy, surface finish and material property to meet the demanding requirements from aerospace, automotive and rapid tooling industry. Wire-feed AM processes generally involve high residual stresses and distortions due to the excessive heat input and high deposition rate. The influences of process conditions, such as energy input, wire-feed rate, welding speed, deposition pattern and deposition sequences, etc., on thermal history and resultant residual stresses of AM-processed components needs to be further understood. In addition, poor accuracy and surface finish of the process limit the applications of wire-feed AM technology. In this paper, after an introduction of various wire-feed AM technologies and its characteristics, an in depth review of various process aspects of wire-feed AM, including quality and accuracy of wire-feed AM processed components, will be presented. The overall objective is to identify the current challenges for wire-feed AM as well as point out the future research direction.

Investigation into the effect of process parameters on microstructural and physical properties of 316L stainless steel parts by selective laser melting

Abstract: Additive manufacturing by selective laser melting (SLM) was used to investigate the effect of laser energy density on 316L stainless steel properties. Point distance and exposure time were varied and their impact on porosity, surface finish, microstructure, density and hardness, was evaluated. The surface roughness was primarily affected by point distance with increased point distance resulting in increased surface roughness, R a, from 10 to 16 μm. Material hardness reached a maximum of 225 HV at 125 J/mm3 and was related to the material porosity; with increased porosity leading to decreased material hardness. Different types of particle coalescence leading to convex surface features were observed (sometimes referred to as balling); from small ball features at low laser energy density to a mixture of both small and large ball features at high laser energy density. Laser energy density was shown to affect total porosity. The minimum amount of porosity, 0.38 %, was observed at an energy density of 104.52 J/mm3.

Big Data in product lifecycle management

Abstract: Recently, “Big Data” has attracted not only researchers’ but also manufacturers’ attention along with the development of information technology. In this paper, the concept, characteristics, and applications of “Big Data” are briefly introduced first. Then, the various data involved in the three main phases of product lifecycle management (PLM) (i.e., beginning of life, middle of life, and end of life) are concluded and analyzed. But what is the relationship between these PLM data and the term “Big Data”? Whether the “Big Data” concept and techniques can be employed in manufacturing to enhance the intelligence and efficiency of design, production, and service process, and what are the potential applications? Therefore, in order to answer these questions, the existing applications of “Big Data” in PLM are summarized, and the potential applications of “Big Data” techniques in PLM are investigated and pointed out.

Effect of arc mode in cold metal transfer process on porosity of additively manufactured Al-6.3%Cu alloy

Abstract: In this study, the effect of arc mode in cold metal transfer (CMT) process on the porosity characteristic of additively manufactured Al-6.3%Cu alloy has been systematically investigated. The variants include conventional CMT, CMT pulse (CMT-P), CMT advanced (CMT-ADV) and CMT pulse advanced (CMT-PADV) and experiments were performed on both single layer deposits and multilayer deposits. The mechanism of porosity generation using the CMT arc mode variants is discussed. It was found that deposit porosity is significantly influenced by the arc mode type of CMT process. Conventional CMT is not suitable for the additive manufacturing process because it produces a large amount of gas pores, even in single layer deposit. CMT-PADV proved to be the most suitable process for depositing aluminium alloy due to its excellent performance in controlling porosity. With correct parameter, setting the gas pores can be eliminated. It was found that the key factors that enable the CMT-PADV process to control the porosity efficiently are the low heat input, a fine equiaxed grain structure and effective oxide cleaning of the wire.

Additive manufacturing-enabled design theory and methodology: a critical review

Abstract: As additive manufacturing (AM) process evolves from rapid prototyping to the end-of-use product manufacturing process, manufacturing constraints have largely been alleviated and design freedom has been significantly broadened, including shape complexity, material complexity, hierarchical complexity, and functional complexity. Inevitably, conventional Design Theory and Methodology (DTM) especially life-cycle objectives oriented ones are challenged. In this paper, firstly, the impact of AM on conventional DTM is analyzed in terms of design for manufacturing (DFM), design for assembly (DFA), and design for performance (DFP). Abundance of evidences indicate that conventional DTM is not qualified to embrace these new opportunities and consequently underline the need for a set of design principles for AM to achieve a better design. Secondly, design methods related with AM are reviewed and classified into three main groups, including design guidelines, modified DTM for AM, and design for additive manufacturing (DFAM). The principles and representative design methods in each category are studied comprehensively with respect to benefits and drawbacks. A new design method partially overcoming these drawbacks by integrating function integration and structure optimization to realize less part count and better performance is discussed. Design tools as a necessary part for supporting design are also studied. In the meantime, the review also identified the possible areas for future research.

Deformation and failure behaviour of Ti-6Al-4V lattice structures manufactured by selective laser melting (SLM)

Abstract: Selective laser melting (SLM) enables the manufacture of lattice structures with highly engineered mechanical properties that are optimised for the associated design requirements. Such lattice structures offer high specific strength and stiffness characteristics allowing design freedom beyond the capacity of solid materials. However, to apply lattices as space filling structural elements, it is necessary to quantify their mechanical properties such as compressive strength and stiffness under varying geometric conditions. This work provides an experimental investigation of the manufacturability of SLM Ti-6Al-4V lattice struts of varying diameter and inclination. From this investigation, lattice structures are manufactured for varying cell topology, cell size, number of unit cells and associated boundary conditions. The deformation and failure behaviour of these lattices is theoretically predicted and experimentally validated. The convergence of mechanical properties with increasing number of unit cells, as well as the effect of lattice topology on mechanical behaviour and observed failures mode are reported.

Maintenance policy optimization—literature review and directions

Abstract: Numerous of maintenance policies were developed due to the change in the manufacturing environment and the growing of technologies in the past few decades. Due to fluctuation (oscillation, instability) phenomena of the manufacturing industry, it is difficult to identify an optimal maintenance policy that actually suit for a manufacturing system. Thus, a lot of efforts have been done in order to assist manufacturing industry in finding an optimal maintenance policy. This paper attempts to review past and current research on optimal maintenance policy selection issues associated with methods used as well as the applications. Published literatures were systematically classified based on certainty theory in operation management classification model in term of certainty, uncertainty, and risk. Furthermore, a sub family had been classified based on the approaches used in determining the optimal maintenance policy. The possible gap occurred between academic research and industrial application in maintenance policy optimization is also discussed in detail, and several possible ideas are put forward to reduce the gap. More importantly, the paper is intended to provide a different view on classifying these models and give useful references for personnel working in industrial as well as researchers.

Standardization in additive manufacturing: activities carried out by international organizations and projects

Abstract: Standards have to satisfy the needs of the different groups represented, such as industrial, trade, and consumer groups of all of the countries involved. Most experts agree that the lack of additive manufacturing (AM) standards is a key point to take into account in the barriers to broad adoption of AM. Although over the past two decades several entities and groups of experts have demanded the development of specific standards for additive manufacturing, the most important steps forward have been taken in the last few years, mainly through the actions of international organizations such as International Organization for Standardization (ISO) and American Society for Testing and Materials (ASTM), with the support of technical groups and projects focused on the standardization of AM. This work, which is successfully providing new standards for AM, is expected to be reinforced by a global agreement between ASTM and ISO with the aim of collaboration on common AM standards. This paper presents a summary and review of actions carried out so far by different organizations and projects, based on the work of several road maps and workshops, with the aim of developing new standards in this particular field.

Reducing the energy consumption of industrial robots in manufacturing systems

Abstract: Reducing the energy consumption of industrial robots (IR) that are used in manufacturing systems has become a main focus in the development of green production systems. This is due to the reality that almost all automated manufacturing processes are using IR as the main component. Thus, reducing the energy consumption of IR will automatically reduce operating costs and CO2 emissions. Therefore, a method for reducing the energy consumption of IR in manufacturing systems is desired. Firstly, this paper presents a literature survey of the research in energy consumption analysis of IR that is used in manufacturing processes. The survey found that current research in this field is focused on the development of simulation models of IR that are able to be used to predict its energy consumption. Secondly, a modular model to analyze power consumption and dynamic behavior of IR is developed. Afterward, an experimental investigation is carried out to validate and estimate the accuracy of the model developed. The investigation shows that the developed modular model can be conveniently used to optimize the industrial robot’s operating parameters, which are commonly needed for production planning and at the process optimization stage. In addition, the investigation shows that the process constraints, environment layout, productivity requirement, as well as the robot payload and operating speed are the key factors that must be considered for optimizing the productivity and efficiency of IR.

Experimental research on the energy ratio coefficient and specific grinding energy in nanoparticle jet MQL grinding

Abstract: Nanoparticles are solid nanoscale particles with features such as antiwear, antifriction, and high load-carrying capacity. This research applied nanoparticles in the cooling lubrication of grinding and theoretically analyzed the impact of cooling lubrication on the grinding surface through the energy ratio coefficient and specific grinding energy. First, the workpiece surface temperature was measured using a thermal infrared imager. A three-dimensional dynamometer was used to identify the tangential grinding force during grinding. Results showed that, with different cooling lubrication approaches, the grinding surface was distributed to workpiece, grinding wheel, grinding fluid, and abrasive debris according to different energy ratio coefficients. The calculation demonstrated that the energy ratio coefficient of dry grinding reached 64.3 %. However, the energy ratio coefficient of flood lubrication, minimal quantities of lubricant (MQL), and nanoparticle jet MQL was 36.8, 52.1, and 41.4 %, respectively. These findings indicated that nanoparticle jet MQL realized a cooling effect close to that of flood lubrication. The specific grinding energy of nanoparticle jet MQL was 35 J/mm3, which was close to that of flood lubrication at 29.8 J/mm3. This finding indicated that the lubrication effects of nanoparticle jet MQL were also similar to those of flood lubrication. Moreover, molybdenum disulfide, carbon nanotube (CNT), and zirconium oxide nanoparticles were added in the grinding fluid to conduct the grinding experiment with nanoparticle jet MQL. The comparison of energy ratio coefficients showed that the cooling performance of CNT nanoparticles was satisfactory. CNT nanoparticles were subsequently added into the grinding fluid at the volume concentrations of 1, 2, and 3 % for the grinding experiment. The results showed that the best cooling effects occurred under the 2 % volume concentration of CNT nanoparticles. Through rounds of selections and optimizations, our research acquired the nanoparticle types and volume concentration that had satisfactory cooling effects and should therefore be added in the grinding fluid.

Parametric modeling and optimization for wire electrical discharge machining of Inconel 718 using response surface methodology

Abstract: Inconel 718 is a high-nickel-content superalloy which possesses excellent strength at elevated temperatures and resistance to oxidation and corrosion. This alloy has wide applications in the manufacturing of aircraft engine parts such as turbine disks, blades, combustors and casings, extrusion dies and containers, and hot work tools and dies, but the inherent problems in machining of superalloys with conventional techniques necessitate the use of alternative machining processes. The wire electrical discharge machining (WEDM) process has been recently explored as a good alternative of conventional machining methods, but there is lack of data and suitable models for predicting the performance of WEDM process particularly for Inconel 718. In the present work, empirical modeling of process parameters of the WEDM has been carried out for Inconel 718 using a well-known experimental design approach called response surface methodology. The parameters such as pulse-on time, pulse-off time, peak current, spark gap voltage, wire feed rate, and wire tension have been selected as input variables keeping others constant. The performance has been measured in terms of cutting rate and surface roughness. The models developed are found to be reliable representatives of the experimental results with prediction errors less than ±5 %. The optimized values of cutting rate and surface roughness achieved through multi-response optimization are 2.55 mm/min and 2.54 μm, respectively.

A curvature optimal sharp corner smoothing algorithm for high-speed feed motion generation of NC systems along linear tool paths

Abstract: Conventional tool paths for computer numerical-controlled (CNC) machine tools or NC positioning systems are mainly composed of linear motion segments, or the so-called G1 commands. This approach exhibits serious limitations in terms of achieving the desired part of geometry and productivity in high-speed machining. Velocity and acceleration discontinuities occur at the junction points of consecutive segments. In order to generate smooth and continuous feed motion, a geometric corner smoothing algorithm is proposed in this paper, which fits quintic B-splines to blend adjacent straight lines together. The proposed transition scheme ensures G 2 continuity transitions and optimal curvature geometry delivering fast cycle time without violating the axis acceleration limits. The cornering error is controlled analytically allowing the user to set the desired cornering tolerance. The feed profile along the corner-blended tool path is generated based on S-curve-type acceleration profile, and it is scheduled for minimum cycle time. At last, the corner-blended tool path is interpolated in real-time with minimum feed fluctuation for accurate and smooth feed motion. Proposed algorithms are implemented, and their effectiveness is tested on a CNC machine tool.

In situ monitoring of FDM machine condition via acoustic emission

Abstract: Fused deposition modeling (FDM) is one of the most popular additive manufacturing technologies for fabricating prototypes with complex geometry and different materials. However, current commercial FDM machines have the limitations in process reliability and product quality. In order to overcome these limitations and increase the levels of machine intelligence and automation, machine conditions need to be monitored more closely as in closed-loop control systems. In this study, a new method for in situ monitoring of FDM machine conditions is proposed, where acoustic emission (AE) technique is applied. The proposed method allows for the identification of both normal and abnormal states of the machine conditions. The time-domain features of AE hits are used as the indicators. Support vector machines with the radial basis function kernel are applied for state identification. Experimental results show that this new method can potentially serve as a non-intrusive diagnostic and prognostic tool for FDM machine maintenance and process control.

A review article: investigations on soft materials for soft robot manipulations

Abstract: In recent years, exploratory research on soft materials and their mechanism has been gaining in popularity. The investigations on soft materials are mostly done for two reasons: (a) to develop an anthropomorphic/prosthetic hand or soft hand with human skin-like material to perform soft manipulations and (b) to develop soft actuators. This paper presented a comprehensive investigation into researches on soft materials for robotic applications. The primary interest of using soft materials is not to leave any marks or damage to objects during the manipulation. The other advantage would be stable grasping due to an area contact. Natural rubber, synthetic rubber, elastomer, polymer composite and nanoparticulated polymer composite are some existing soft materials. Extensive research is required to prepare a high-strength but lighter soft material for robotic soft manipulation. Human skin and its mechanical properties are initially discussed. In addition, the need of soft material for soft manipulations and observations from previous researches over the past few decades, modelling of non-linear hyperelastic/viscoelastic materials and characterization are discussed. Finally, various soft materials including the polymer-matrix composites, available fillers and their advantages, processing methods and nanoparticulated polymer matrix and its significance in robotic application are presented.

A new FMEA method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process

Abstract: Failure mode and effect analysis (FMEA) model is a technique used to evaluate the risk. This paper aimed to propose a new FMEA model combining technique for order of preference by similarity to ideal solution (TOPSIS) and belief structure to overcome the shortcomings of the traditional index of FMEA. In this paper, the fuzzy belief TOPSIS method is combined with FMEA to introduce a belief structure FMEA to describe the expert knowledge by a number of linguists as a grammatical phenomenon. Moreover, the weights of components in FMEA index can be different from each other. Therefore, the flexibility of assigning weight to each factor in this method is more compatible to the real decision-making situation. In other word, TOPSIS method is applied to determine the preference of alternatives versus risk criteria. Using linguistic terms in the fuzzy belief approach, the risk factors described a more meaningful value and decision-makers’ judgment is assigned with belief degrees through evaluation of factors. Finally, a numerical case study about the preference of cause failures of steel production process is provided to illustrate the process of proposed method, and then result and discussion is performed for each case.

An Internet of Things (IoT)-based collaborative framework for advanced manufacturing

Abstract: This paper outlines an Internet of Things (IoT)-based collaborative framework which provides a foundation for cyber physical interactions and collaborations for advanced manufacturing domains A general framework for collaborative manufacturing is proposed followed by a discussion of such an IoT-based framework for the domain of micro devices assembly The design of this collaborative framework is discussed in the context of cloud computing as well as the emerging Next Internet which is the focus of recent initiatives in the USA, EU, and other countries The data/information exchange between the various software and physical components is modeled using the engineering Enterprise Modeling Language (eEML), which provides a structured foundation for designing and developing this IoT-based collaborative framework The key cyber physical components and modules are described followed by a discussion of the implementation of this framework

Travel time model for shuttle-based storage and retrieval systems

Abstract: This paper presents analytical travel time model for the computation of travel (cycle) time for shuttle-based storage and retrieval systems (in continuation SBS/RS). The proposed model considers the operating characteristics of the elevators lifting table and the shuttle carrier, such as acceleration and deceleration and the maximum velocity. Assuming uniform distributed storage rack locations and using the probability theory, the expressions of the cumulative distribution functions with which the mean travel time is calculated, have been determined. The proposed model enables the calculation of the mean travel (cycle) time for the single and dual command cycles, from which the performance of SBS/RS can be evaluated. The approximation model and a simulation model of SBS/RS have been used to compare the performances of the proposed analytical travel time model. The analysis shows that regarding all examined types of SBS/RS, the results of proposed analytical travel time model for SBS/RS correlate with the results of simulation models of SBS/RS.

Agile manufacturing: framework and its empirical validation

Abstract: The agile manufacturing is one of the operational strategies which organizations have adopted to beat environmental uncertainties resulting from worldwide economic recession, shortening of product life cycle, supplier constraints and obsolete technologies. In our study, we have adopted literature review to develop agile manufacturing (AM) framework. Our framework has six constructs that includes technologies, empowerment of workforce, customer focus, supplier relationship management, flexible manufacturing systems and organizational culture. To test our framework, we developed our instrument scientifically and collected data using Dillman’s (2007) total design test methods. We further performed a nonresponse bias test and then we checked the assumptions of constant variance, outliers and normality. Once we found that our dataset skewness and kurtosis values are within the defined range, we further performed a confirmatory factor analysis (CFA) test to check the validity of our constructs. Our multivariate statistical analyses suggest that our proposed framework constructs are valid. The goodness-of-fit indices suggest that our framework is a good fit. Once the model was tested, conclusion, limitations and further directions of our study were outlined.

Process characterisation of 3D-printed FDM components using improved evolutionary computational approach

Abstract: Fused deposition modelling (FDM) is an additive manufacturing technique deployed to fabricate the functional components leading to shorter product development times with less human intervention. Typical characteristics such as surface roughness, mechanical strength and dimensional accuracy are found to influence the wear strength of FDM fabricated components. It would be useful to determine an explicit numerical model to describe the correlation between various output process parameters and input parameters. In this paper, we have proposed an improved approach of multi-gene genetic programming (Im-MGGP) to formulate the functional relationship between wear strength and input process variables of the FDM process. It was found that the improved approach performs better than MGGP, SVR and ANN models and is able to generalise wear strength of the FDM prototype satisfactorily. Further, sensitivity and parametric analysis is conducted to study the influence of each input variable on the wear strength of the FDM fabricated components. It was found that the input parameter, air gap, has the maximum influence on the wear strength of the FDM fabricated component.

A review of cryogenic treatment on cutting tools

Abstract: Enhancing the performance of cutting tools is an important factor in reducing production costs. Cutting tools are subjected to processes such as heat treatment and coating in order to improve their performance. Cryogenic treatment, which is also known as sub-zero heat treatment, has made significant contributions to the improvement of wear resistance, tool life, dimensional integrity, and product quality of cutting tools. The mode of application of cryogenic treatment and the type of cutting tool both affect tool performance. Therefore, it is necessary to examine the way cryogenic treatment is applied to cutting tools and its effects on their performance. This study reviews the literature on the performance of cryo-treated cutting tools.

Effect of machining-induced residual stress on the distortion of thin-walled parts

Abstract: One of the main problems in the machining of thin-walled parts made of high-strength aluminum alloys is distortion and dimensional instability after machining, which leads to an increase in scraped parts and the cost of production. In general, distortion and dimensional instability in machined parts made of aluminum alloy is a function of the residual stresses. In this article, the correlation between machining-induced residual stresses and distortion in a thin-walled work pieces is investigated. Several experiments are carried out under different machining conditions using two carbide and polycrystalline diamond (PCD) tools on a thin-walled cylinder made of AL7075-T6 alloy. Rates of variations in geometrical tolerances and distortion for all work pieces are measured. To study the effect of mechanical and thermal loads on the residual stresses and distortion, the machining force and temperature of cutting area are measured. Finally, the correlation between the residual stress and distortion is studied by measurement of residual stress on some work pieces. Similarly, in order to investigate the effect of work pieces thickness on distortion, several tests are carried out on three work pieces with different thicknesses. The results indicate that the force and temperature have direct effect on the residual stresses and distortion in the thin-walled parts.

Review of improvements in wire electrode properties for longer working time and utilization in wire EDM machining

Abstract: Wire electrical discharge machining (WEDM) is an important technology, which demands high-speed cutting and high-precision machining to realize productivity and improved accuracy for manufacturing hard materials. WEDM has experienced explosive growth and complexity of equipment as well as rising demand for the basic process tool (the wire electrode). Greater taper angles, thicker workpieces, automatic wire threading, and long periods of unattended operation make the selection of the ideal wire a much more critical basis for achieving successful operation. This paper focuses on the evolution of EDM wire electrode technologies from using copper to the widely employed brass wire electrodes and from brass wire electrodes to the latest coated wire electrodes. Wire electrodes have been developed to help user demand and needs through maximum productivity and quantity by choosing the best wire. In the final part of the paper, the possible trends for future WEDM electrode research are discussed.

Hybrid multiobjective genetic algorithms for integrated dynamic scheduling and routing of jobs and automated-guided vehicle (AGV) in flexible manufacturing systems (FMS) environment

Abstract: The paper presents an algorithm for integrated scheduling, dispatching, and conflict-free routing of jobs and AGVs in FMS environment using a hybrid genetic algorithm. The algorithm generates an integrated schedule and detail routing paths while optimizing makespan, AGV travel time, and penalty cost due to jobs tardiness and delay as a result of conflict avoidance. The multi-objective fitness function use adaptive weight approach to assign weights to each objective for every generation based on objective improvement performance. Fuzzy expert system is used to control genetic operators using the overall population performance improvements of the last two previous generations. Computational experiments was conducted on the developed algorithm coded in Matlab to test the effectiveness of the algorithm. Integrated scheduling of jobs in FMS which are in synchrony with AGV dispatching, scheduling, and routing proved to ensure the feasibility and effectiveness of all the solutions of the integrated constituent elements.

Study on the influence of micro-EDM process parameters during machining of Ti–6Al–4V superalloy

Abstract: Ti–6Al–4V superalloy is an important engineering material having a wide range of applications in diverse fields of engineering due to its good machinability features and excellent physical and mechanical properties. These versatile properties of titanium alloy have caught the interest of researchers and industries personnel across the globe. Further, micromachining of Ti–6Al–4V has become the topic of interest for industrial production and engineering research in the precision manufacturing world due to its wide range of applications in various fields of engineering. However, the machining of Ti–6Al–4V requires in-depth knowledge of machining process as this involves various process variables which influence the machining criteria. Micro-electro discharge machining (micro-EDM) is one of the most successful micromachining processes, and the machined component is free from mechanical stresses as there involve no mechanical forces in the process because there is no direct contact between the tool and workpiece. Also, the specific energy requirement is very low in this process, and the accuracy is very good, i.e., in the order of 0.1 μm R max. Thus, in this research paper, an attempt has been made to study the influence of various process parameters on material removal rate (MRR), tool wear rate (TWR), overcut (OC), and taper of micro-EDM during machining of Ti–6Al–4V. To perform the experimentation, central composite design (CCD) has been used to design the experiment and response surface methodology (RSM) is utilized to map the relationship between the input process parameters with the resulting process response. It has been observed that RSM models have predicted the process criteria, namely, MRR, TWR, OC, and taper, satisfactorily and can be utilized to predict the response parameters within the range of the parameter selected in the present research investigation. Through multi-objective optimization, the optimal parametric setting for the micro-EDM process parameters during machining of Ti–6Al–4V has been obtained at pulse on time (Ton) of 1 μs, peak current (Ip) of 2.5 A, gap voltage (Vg) of 50 V, and flushing pressure (Fp) of 0.20 kg cm−2. The experimental values of MRR, TWR, OC, and taper at this optimal parametric setting have been obtained as 0.0777 mg/min, 0.0088 mg/min, 0.0765 mm, and 0.0013, respectively.

Microstructural aspects in Al–Cu dissimilar joining by FSW

Abstract: Sound AA2024-T3–Cu10100 dissimilar joints were obtained by friction stir welding offsetting the tool probe towards the aluminum sheet and employing selected processing parameters. Joint microstructure was analyzed by means of conventional optic microscopy as well as scanning electron microscopy. The weld bead exhibited welding zones and some features typically encountered in similar FSW. The nugget zone consisted of a mixture of recrystallized aluminum matrix and deformed and twinned copper particles. Onion rings and particle-rich zones, made of Cu particles dispersed in the Al matrix, were also observed. EDS analysis revealed that several Al–Cu intermetallic compounds, such as Al2Cu, AlCu, and Al3Cu4, chemically different w.r.t. compounds precipitated during the T3 aging treatment (Al3Cu), were formed during the process. Microstructure variation significantly affects the microhardness distribution in the cross-section of the joint.

An investigation on distortion of PLA thin-plate part in the FDM process

Abstract: In order to reveal the distortion mechanism of PLA thin-plate part in the FDM process, a theoretical model based on the theory of elastic thin plates in thermoelasticity was established, and an experimental research approach based on Taguchi method was presented. A special specimen was designed, and the flowchart of experimental procedure was elaborated. Moreover, 81 test specimens were prepared through FDM process and measured by a portable 3D laser scanner. Two statistical analysis methods, signal to noise ratio (S/N) and analysis of variance (ANOVA), were applied to optimize the process parameters in order to reduce the distortion of thin-plate part. The experimental results indicated that the optimal process parameters can be obtained and proposed theoretical model was proved efficient.

Investigating the electrical discharge machining (EDM) parameter effects on Al-Mg2Si metal matrix composite (MMC) for high material removal rate (MRR) and less EWR–RSM approach

Abstract: Al-Mg2Si composite is a new group of metal matrix composites (MMCs). Electrical discharge machining (EDM) is a nonconventional machining process for machining electrically conductive materials regardless of hardness, strength and temperature resistance, complex shapes, fine surface finish/textures and accurate dimensions. A copper electrode and oil-based dielectric fluid mixed with aluminum powder were used. The polarity of electrode was positive. Response surface methodology (RSM) was used to analyze EDM of this composite material. This research illustrates the effect of input variables (voltage, current, pulse ON time, and duty factor) on material removal rate (MRR), electrode wear ratio (EWR), and microstructure changes. The results show that voltage, current, two-level interaction of voltage and current, two-level interaction of current and pulse ON time, and the second-order effect of voltage are the most significant factors on MRR. Pulses ON time and second-order effect of pulse ON time are the most significant factors affecting EWR. Microstructure analysis of EDM on Al-Mg2Si samples revealed that voltage, current, and pulse ON time have a significant effect on the profile and microstructure of machined surfaced.

Finite element simulation and experimental investigation on the residual stress-related monolithic component deformation

Abstract: The principal influence factors on the monolithic component deformation were investigated by finite element simulation simulation and experiment. Initial residual stress of the blank, machining-induced residual stress, and coupling action of these two effect factors were considered. To study the effect of blank initial residual stress on component deformation, chemical milling was used to remove the machining-induced residual stress on the machined surface of the components. The research results show that the initial residual stress in the blank was the main factor of deformation for three-frame monolithic beam, and the coupling action of the initial residual stress and machining-induced residual stresses aggravated the deformation. The deformation caused by machining residual stress accounted for about 10 % of the total deformation of the component, and the deformation caused by the blank initial residual stress accounted for 90 % of the total deformation of the component. The finite element simulation results were compared with experimental results and found to be in good agreement.

Kinematic calibration of a six-axis serial robot using distance and sphere constraints

Abstract: This paper describes a kinematic calibration method developed to improve the accuracy of a six-axis serial industrial robot in a specific target workspace, using distance and sphere constraints. A simulation study demonstrates the ability of the calibration approach to identify the kinematic parameters, regardless of measurement noise. Experimental validation shows that the robot’s accuracy inside the target workspace is significantly improved by reducing the mean and maximum distance errors from 0.698 to 0.086 mm and from 1.321 to 0.127 mm, respectively. The experimental data are collected using a Renishaw precision touch probe mounted on the flange of a FANUC LR Mate 200iC and a special triangular plate with three datum 2-in spheres 300 mm apart. The calibration method uses an optimization model based on fitting several probed positions on spheres and minimizing the residual of the spheres’ center-to-center distances.

Monitoring the coefficient of variation using a variable sample size control chart in short production runs

Abstract: Monitoring the coefficient of variation (CV) is an effective approach to monitor a process when both the process mean and the standard deviation are not constant but, nevertheless, proportional. Until now, few contributions have investigated the monitoring of the CV for short production runs. This paper proposes an adaptive Shewhart control chart implementing a variable sample size (VSS) strategy in order to monitor the coefficient of variation in a short production run context. Formulas for the truncated average run length are derived. Moreover, a comparison is performed with a Fixed Sampling Rate Shewhart chart for the CV in order to evaluate the performance of each chart in a short run context. An example illustrates the use of this chart on real data.