Search

Vacuum laser beam welding utilises the advantages of both laser and electron beam welding. In this study, a numerical model was developed to simulate fume particle behaviour and the contamination o...

Simulation models of machine tool feed drive are utilized for process planning and optimization. In order to improve the estimation performance of such models, sophisticated parameter identification methods have been applied to capture the dynamic characteristics of feed drive precisely. However, the identification process, which comprises data gathering, data processing, and parameter estimation, is time-consuming and complex. Therefore, this paper presents a new rapid parameter identification algorithm based on the recursive least squares (RLS) method to identify feed drive mass and sliding friction. The proposed method simplifies the identification process by utilizing the measured data directly without data processing. A two-step identification technique is proposed for addressing the nonlinearity of the feed drive model, thus allowing for the application of the RLS method. The identification accuracy and fast convergence rate of the proposed algorithm were validated via simulations and experiments using a ball screw–driven feed drive testbed. The friction behavior and control characteristics estimated by the feed drive model were compared with experimental results to evaluate the estimation accuracy.

To deal with the compliance error that is structural deflection caused by an applied wrench in robotic applications, several compensation methods have been developed. However, conventional methods have limitations because they do not consider how compensation of one joint affects the compliance errors of the other joints. In this study, it is proposed that a joint compliance error compensation method that calculates the exact amount of compensation of each joint using a body frame. The effectiveness of the proposed method is evaluated using simulations.

The use of industrial robots is widespread in diverse manufacturing fields. Hence, there have been attempts to use robot for machining processes instead of machine tools. However, limited machining accuracy has been a major obstacle hampering the adoption of robotic machining systems. Recently, substantial research has been carried out to address this issue. In this paper, recent progress in robotic machining has been summarized, such as kinematic calibration and compliance error compensation to improve the accuracy of robotic machining. Auxiliary units for improving the performance of robotic machining systems are also discussed.

This study was undertaken for improving the corrosion resistance, hardness, and toughness of SKD11, using the developed plasma diode electron beam equipment (PD-Ebeam). The SKD11 in this study is 1.5 w.t.% high-carbon steel; however, X-ray powder diffraction (XRD) and transmission electron microscopy (TEM) analysis results after the PD-Ebeam treatment reveal that almost the entire iron matrix underwent an austenite phase transformation (F.C.C. crystal structure). Thus, an attempt is made to improve the hardness, toughness, and corrosion resistance using a characteristic of the austenite steel. A hardness enhancement of up to 680 (H.V.) could be achieved through PD-Ebeam heat and ultrasonic impact treatments. Further, the gamma structure sustainability and non-carbide formation were confirmed through the XRD and TEM analysis results. In addition, the friction coefficient in a wear test, was found to be lesser than that of vacuum heat-treated material, owing to the ductility of the gamma phase. As a result, it achieved 18% friction reduction, 47% reduction of wear, and corrosion resistance of level of the stainless steel (SUS304) compared to general vacuum heat treatment.

As product development cycles are getting shorter, faster determination of proper process conditions for the new designs and materials is increasingly important. To respond these requirements, a significant effort for cutting experiments are being replaced by simulation-based approaches called Virtual Machining (VM). Simultaneously, metal parts with thinner and smaller features being frequently used in electronic products has increased demands for precision machining of thin walls, which is vulnerable to post-machining deformation (PMD). In this study, a simulation procedure is discussed to incorporate the prediction of PMD after metal cutting into VM environments. The method uses a combination of the residual stress and thermal analysis of cutting process and the structural analysis of machined part. Machining experiments have been performed to demonstrate the effectiveness of the proposed PMD simulation as a part of VM for initial selection of the machining conditions.

Microchannels must have appropriate physical (e.g., shape, size and surface roughness) and chemical (e.g., functional groups and wettability) properties to be used in microfluidic devices. In general, microchannels, which are made of polymeric materials, are produced through a molding process and chemically treated to have proper wettability. However, mold fabrication and chemical treatment require a significant amount of time and cost. In this study, we used a micromilling process to fabricate a microchannel on polymer material. The contact angle on the machined surface was changed according to the wettability model by varying the surface roughness controlled by cutting parameters. By mechanical cutting of the naturally hydrophobic polymer, the contact angle could be physically changed from 76° to 109° by changing cutting parameters without any chemical change.

Mechanical machining of brittle material is difficult due to generation of fracture or cracks on machined surfaces. Glassy carbon (GC) is a brittle carbon material having outstanding mechanical and chemical characteristics making it suitable for use in glass molds. However, brittleness of GC makes its machining complicated and difficult. In order to fabricate GC surfaces with minimum cracks, hybrid machining processes utilizing electrochemical oxidation have been proposed. In the present study, a new, mixed acidic electrolyte incorporating a chemical oxidizer was utilized to improve the material removal rate of electrochemical oxidation assisted machining. Machining experiments were conducted to evaluate and to confirm the effect of the oxidizer-mixed electrolyte on material removal.

Vacuum laser beam welding enables deeper penetration depth and welding stability than atmospheric pressure laser welding. However, contaminated coupling glass caused by welding fumes in the vacuum space reduces laser transmittance, leading to inconsistent penetration depth. Therefore, a well-designed protective system is indispensable. Before designing the protective system, the contamination phenomenon was quantified and represented by a contamination index, based on the coupling glass transmittance. The contamination index and penetration depth behavior were determined to be inversely proportional. A cylindrical protective system with a shielding gas supply was proposed and tested. The shielding gas jet provides pressure-driven contaminant suppression and gas momentum-driven contaminant dispersion. The influence of the shielding gas flow rate and gas nozzle diameter on the performance of the protective system was evaluated. When the shielding gas flow was 2.0 L/min or higher, the pressure-driven contaminant suppression dominated for all nozzle diameters. When the shielding gas flow was 1.0 L/min or lower, gas momentum-driven contaminant dispersion was observed. A correlation between the gas nozzle diameter and the contamination index was determined. It was confirmed that contamination can be controlled by selecting the proper gas flow rate and supply nozzle diameter.

Environmental monitoring has become essential in order to deal with environmental resources efficiently and safely in the realm of green technology. Environmental monitoring sensors are required for detection of environmental changes in industrial facilities under harsh conditions, (e.g. underground or subsea pipelines) in both the temporal and spatial domains. The utilization of optical fiber sensors is a promising scheme for environmental monitoring of this kind, owing to advantages including resistance to electromagnetic interference, durability under extreme temperatures and pressures, high transmission rate, light weight, small size, and flexibility. In this paper, the optical fiber sensors employed in environmental monitoring are summarized for understanding of their sensing principles and fabrication processes. Numerous specific applications in petroleum engineering, civil engineering, and agricultural engineering are explored, followed by discussion on the potentials of OFS in manufacturing.

A process for femtosecond laser-based manufacturing was proposed to fabricate a long-period fiber grating (LPFG) with a screw shape. The screw-shaped LPFG was continuously inscribed by single laser scanning, which results in the improvement of fabrication time. For the single laser scanning, an optical fiber was traveled along fiber axis and rotated about the fiber axis. The 44.65-mm-long LPFG with a screw shape and the period of 450 $\mu \text{m}$ was fabricated about 17 min, and its sensitivity was 48 ~ 51 nm/RIU for the glycerin solutions. The proposed process enables us to produce the screw-shaped LPFGs with fast manufacturing time and reliable performance compared with the process with multi-path scanning.

Polydimethylsiloxane (PDMS) is widely used in the fabrication of fluidic chips. Recently, a direct mechanical micromilling process using cryogenic cooling was considered to cut PDMS in order to reduce development time and prototyping costs. In this paper, the characteristics of cryogenic machining of PDMS were experimentally studied. The machined surface was analyzed with a variety of machining parameters, such as spindle speed and feed per tooth, and their effects on cutting temperature were examined. To improve geometric accuracy, a tool path compensation method that takes into account the shrinkage of PDMS at cryogenic temperatures was developed. Based on the preliminary results, the fabrication of a PDMS fluidic chip demonstrated that fluidic flow can be controlled by differences in the flow friction.

Cast iron is relatively cheap and highly machinable and is thus used for various mechanical parts. However, cast iron (H2 grade) is a high-carbon steel that shows cracks or craters owing to the martensitic transformation during conventional surface heat treatments. In this study, we investigated electron-beam (e-beam)-based direct preheating for preventing the formation of craters and cracks during the heat treatment of cast iron using a plasma diode e-beam. Scanning electron microscopy, X-ray diffraction analysis, energy-dispersive X-ray spectroscopy, and hardness measurements were performed to elucidate the crater and crack formation mechanism. Craters were formed within the graphite phase, owing to the low-melting-point elements and compounds. It was also observed that crack and crater formation was correlated to the distortion of the primary gamma phase, based on a significant decrease in the d-spacings. The direct preheating process resulted in a lower degree of distortion of the gamma phase. As a result, we could achieve a hardness as high as 800 HV without cracks or craters in cast iron, which is a cheap material. Moreover, the results of potentiodynamic polarization tests showed that the corrosion resistance increased after the surface treatment, owing to the removal of the low-melting-point impurities and grain refinement.

Rhenium disulfide (ReS2) has attracted immense interest as a promising two-dimensional material for optoelectronic devices owing to its outstanding photonic response based on its energy band gap’s insensitivity to the layer thickness. Here, we theoretically calculated the electrical band structure of mono-, bi-, and trilayer ReS2 and experimentally found the work function to be 4.8 eV, which was shown to be independent of the layer thickness. We also evaluated the contact resistance of a ReS2 field-effect transistor using a Y-function method with various metal electrodes, including graphene. The ReS2 channel is a strong n-type semiconductor, thus a lower work function than that of metals tends to lead to a lower contact resistance. Moreover, the graphene electrodes, which were not chemically or physically bonded to ReS2, showed the lowest contact resistance, regardless of the work function, suggesting a significant Fermi-level pinning effect at the ReS2/metal interface. In addition, an asymmetric Schottky...

Recently, many studies have been actively conducted to improve the mechanical properties of metallic materials through surface heat treatment with an electron beam. Thermionic focused electron beam equipment is mainly used in industrial manufacturing machines such as e-beam welders. However, such equipment is expensive, and the filament lifetime is limited. In this study, the austenite transformation in an iron matrix was investigated after surface heat treatment of SKD11 with plasma diode focused electron beam equipment, which is a recently developed alternative based on a plasma diode cold cathode. X-ray diffraction (XRD) and transmission electron microscopy (TEM) results revealed that the iron matrix transformed to an austenite structure without Cr-rich carbide formation. After the surface heat treatment using the plasma diode focused electron beam equipment, a positive residual stress was confirmed by XRD residual stress measurements. This result was obtained because impurities in the iron matrix such as carbon existed in alloy form rather than composite form. The average hardness at a depth of 300 μm from the surface was measured to be approximately 480 Hv.

Optimizing the machining condition is one of the effective ways for reducing the energy consumption of machine tools at a unit process level. Based on statistical approaches with design of experiments, various methods have been developed to reduce the energy consumption by optimizing the machining condition. However, the methods cannot be easily utilized when the optimization target or machine tool design is modified because the optimal solution is determined based on the experimentally measured data. In this study, a simulation-based method that utilizes a virtual machine tool (VMT) to optimize the machining condition is proposed. The VMT model is designed to focus on estimating the energy consumption during machining and is developed by replicating real machine tools. Based on the VMT model, a genetic algorithm is used to optimize the machining condition to reduce the energy consumption. The changes in the optimization target or machine tool design are easily considered by modifying the cost function or component model, respectively. The proposed method is applied to reduce the energy consumption of a three-axis milling machine. The optimal feed rate and spindle speed are obtained for each line of the part program when the thrust force is limited. An experimental setup of the machine tool with an energy consumption monitoring system is constructed to demonstrate the effectiveness of the proposed method. The results show that the total energy consumption of the machine tool reduces by 13% owing to the optimization.

Carbon Fiber Reinforced Polymer (CFRP) is a light-weight material with high strength and highly corrosion resistance, and hence is widely applied in aerospace industries. However, milling of CFRP usually generates machining defects (for instance, delamination and pull-out fibres), making processed surface unqualified to meet the requirement of aerospace application. Therefore, prediction for machining quality should be conducted before milling processing to avoid potential loss in massive production. Fracture behaviours of micro-scale fibres and matrix have a significant influence on the final machined surface, and such material removal mechanism can be mainly determined by micro-scale geometrical relationships between carbon fibers and milling teeth. In this paper, a micro-scale geometrical calculation software for CFRP milling is provided based on Dexel model. The software can generate geometrical parameters, for example, cutting angle, cutting length and engagement angle, for the whole milling process. Milling defects and milling forces can be conducted based on those micro-scale geometrical parameters.

CFRP (Carbon Fiber Reinforced Plastic) and CFRP-metal stacks have recently been widely used in the aerospace and automobile industries. When CFRP is machined by a brittle fracture mechanism, defect generation behaviors are different from those associated with metal cutting. The machining quality is strongly dependent on the properties of CFRP materials. Therefore, process control for CFRP machining is necessary to minimize the defects of differently manufactured CFRPs. In this study, defects in drilling of CFRP substrates with a variety of fiber directions and resin types are compared with respect to thrust force. An experimental study on material interface detection is carried out to investigate its benefits in process control.

In smart factories, the entire manufacturing process from design to the final product is simulated in a virtual manufacturing environment and optimized before starting production. Suppliers and customers make decisions based on the simulation results. Therefore, effective rendering of the information of the virtual products to suppliers and customers is essential for this manufacturing paradigm. In this study, a method of rendering the surface roughness of the virtual products using a tactile display is presented. A tactile display device comprising a 3 x 3 array of individually controlled piezoelectric stack actuators is constructed. The surface topology of the virtual products is rendered directly by controlling the piezoelectric stack actuators. A series of experiments is performed to evaluate the performance of the tactile display device. An electrical discharge machined surface is rendered using the proposed method.

Ultrafast laser induced refractive index (RI) change in the core of a standard telecommunication fiber is quantified using the spectral shift of an in-fiber Bragg grating (FBG) based Fabry–Perot cavity. Measured RI change is used to design and then fabricate long period grating (LPG) in pure silica core single mode fiber (SMF) employing identical laser irradiation conditions used in core index characterization. A core length of 100 µm within the 10 mm long cavity structure is scanned with ultrafast laser pulses, and the corresponding spectral shift is used to calculate index modification. The index change of 0.000449 found in characterization process is used to simulate the LPG in pure silica fiber. Identical index modulation written in pure silica fiber by femtosecond laser radiation provides a rejection band that is in good agreement with the simulation results. The fabricated LPG sensors are also characterized for ambient temperature and RI.

The load applied to a machine tool feed drive changes during the machining process as material is removed. This load change alters the Coulomb friction of the feed drive. Because Coulomb friction accounts for a large part of the total friction the friction compensation control accuracy of the feed drives is limited if this nonlinear change in the applied load is not considered. This paper presents a new friction compensation method that estimates the machine tool load in real time and considers its effect on friction characteristics. A friction observer based on a Kalman filter with load estimation is proposed for friction compensation control considering the applied load change. A specially designed feed drive testbed that enables the applied load to be modified easily was constructed for experimental verification. Control performance and friction estimation accuracy are demonstrated experimentally using the testbed.

Nonlinear friction is a dominant factor of the complexity growth of feed drive dynamic behavior. In particular, a feed drive system equipped with rolling contact components such as ball screws and linear motion (LM) guides undergoes impalpable friction behavior. Therefore, proper modeling and compensation of friction in feed drive components play a crucial role in improving the precision of a feed drive system. In this study, to overcome the accuracy limitation of the simplified feed drive model, a distributed component friction model (DCFM) of a feed drive system is developed. Friction has been modeled as a single element of entire feed drive system in the conventional model. However, the proposed DCFM is composed of models of individual feed drive components such as ball screw and LM guide including their friction behaviors. To take advantage of the DCFM by considering both presliding and sliding friction behaviors of each component, LuGre model is applied. For experimental verification of the accuracy of the proposed DCFM, a specially designed feed drive testbed is constructed. Using the testbed, the friction forces of ball screws and LM guides are measured independently. Using the DCFM, a friction observer is built for real-time monitoring and compensation of the friction force. A proportional-derivative feed drive position controller with an observer-based friction compensator is implemented and the experimental results are presented.

This paper presents a real-time tool deflection compensation technique to improve micromilling machining accuracy. Lateral and axial errors of the cutter location (CL) caused by tool deflection were estimated using the cutting force and compensated by applying an additional feed to the workpiece that is equivalent to the estimated CL errors. To evaluate the proposed method, a workpiece holder comprising a three-axis stage and a tool dynamometer was installed on the work table of a machine tool. A proportional derivative (PD) position controller with a model-based tool deflection estimator was designed and implemented on a real-time computer to control the workpiece holder. Lateral and axial machining errors in side milling and radii errors in circular slot milling are discussed to demonstrate the effect of tool deflection compensation.

Design and application of hardware-in-the-loop simulation (HILS) for design of CNC-controlled machine tool feed drives is discussed. The CNC machine tool is a complex mechatronics system where the complexity results from the software-based controller composed of a variety of functionalities and advanced control algorithms. Therefore, using a real CNC controller in the control simulation has merits considering the efforts and accuracy of the simulation modeling. In this paper challenges in HILS for a CNC controlled feed drive, such as minimization of time delay and transmission error that are caused by discretization of the feed drive model, is elaborated. Using an experimental HILS setup of a machine tool feed drive applications in controller gain selection and CNC diagnostics are presented.

Magnetorheological (MR) fluid jet polishing is a material removal process for precision products such as optical elements. It is characterized by a jet flow that is stabilized by a magnetic field, and a highly predictable machining spot. The behavior of the particles in an MR fluid slurry near a target wall surface is conceptually described. In experiments with a BK7 glass specimen, various removal spots are created by impingement of MR fluid jets at velocities of 10~30 m/s, using MR fluids of different compositions, and different processing durations. The tangential MR fluid flow along the part surface is assumed to be responsible for material removal, and theoretical models for the prediction of material removal are developed, using the conventional wear model and granular flow theory. The constitutive relation between the shear stress and the shear rate changes as the jet velocity increases, which has a critical effect on the behavior of material removal. CFD analysis is performed to calculate the wall shear rate. The proposed models agree with the experimental results with respect to the distribution of the material removal rate. Additionally, the surface topographies of polished parts are discussed, with regards to the particle behavior.

Glassy carbon (GC) has merits to be used as mold material for glass molding press because of its superior chemical and thermal properties. However, it is difficult to machine GC mechanically because of its brittleness and hardness. Undesired fractures and cracks are frequently generated on the machined surfaces. A novel micromachining process for precision machining of GC that combines mechanical micromachining and electrochemical oxidation has been developed. In the proposed process, an oxide layer is generated on the GC surface and removed mechanically. In the contact area between the tool and workpiece, the generation and removal of the oxide layer are repeated. A number of experimental results are presented to investigate the machining characteristics and to show the feasibility of the proposed process.