• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.2
• /
• pp.45-50
• /
• 2021

In the recent fourth industrial revolution, the demand for additive processes has emerged rapidly in many mechanical industries, including the aircraft and automobile industries. Additive processes, in contrast to subtractive processes, can be used to produce complex-shaped products, such as three-dimensional cooling systems and aircraft parts that are difficult to produce using conventional production technologies. However, the limitations of additive processes include nonuniform surface quality, which necessitates the use of post-processing techniques such as subtractive methods and grinding. This has led to the need for hybrid machines that combine additive and subtractive processes. A hybrid machine uses additional additive and subtractive modules, so product deformation, for instance, deflection, is likely to occur. Therefore, structural analysis and design optimization of hybrid machines are essential because these defects cause multiple problems, such as reduced workpiece precision during processing. In this study, structural analysis was conducted before the development of an additive/subtractive hybrid processing machine. In addition, structural optimization was performed to improve the stability of the hybrid machine.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.21 no.6
• /
• pp.74-80
• /
• 2022

The surface status of a workpiece determines its functionality, product quality, and manufacturing costs. Thus, several finishing technologies have been widely investigated and applied to improve surface characteristics. In this study, rotational electro-magnetic abrasive finishing (REMAF) was suggested as a non-contact finishing process to achieve high geometric precision. To verify the effects of the REMAF process on burr removal on the surface of Al6061, experiments were conducted using the Taguchi method. Based on the experimental results analyzed by the S/N ratio and ANOVA, the optimal conditions were defined as A₃B₂C₃D₃ that corresponded to 1,800 rpm of rotational speed, 1.5 kg of abrasive particle weight, 0.7 mm of abrasive diameter, and 15 min of working time. In addition, the particle weight was a key attribute for deburring, whereas the working time was less effective.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.12
• /
• pp.151-157
• /
• 1996

The tool condition monitoring is one of the most important aspects to improve productivity and quality of workpiece. In this study, the wear of ceramic tool (A1$_{2}$0$_{3}$-TiC Series) cutting the hardened die material(SKD11) was investigated. Flank wear was more dominant than crater wear. Therefore the modeling of cutting force related to flank wear has been performed. The cutting force model was construct- ed by an assumption that the stress distribution on the tool face is affected by tool wear. The relationship between characteristics as cutting force and tool wear can be suggested by machining parameters depending on cutting conditions. Experiments were performed under the various cutting conditions to ensure the validity of force models. The theoretical predictions on the flank wear are approximately in good agreement with experimental results.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.607-610
• /
• 2005

A remeshing algorithm using tetrahedral elements has been developed, which is adapted to the mesh density map constructed by a posteriori error estimation. In the finite element analyses of metal forging processes, numerical error increases as deformation proceeds due to severe distortion of elements. In order to reduce the numerical error, the desired mesh sizes in each region of the workpiece are calculated by a posteriori error estimation and the density map is constructed. Piecewise density functions are then constructed with the radial basis function in order to interpolate the discrete data of the density map. The sample mesh is constructed based on the point insertion technique which is adapted to the density function and the mesh size is controlled by moving and deleting nodes to obtain optimal distribution according to the mesh density function and the quality optimization function as well. After finishing the redistribution process of nodes, a tetrahedral mesh is constructed with the redistributed nodes, which is adapted to the density map and resulting in good mesh quality. A goodness and adaptability of the constructed mesh is verified with a testing measure. The proposed remeshing technique is applied to the finite element analyses of forging processes.

• Journal of the Korean Society of Industry Convergence
• /
• v.5 no.2
• /
• pp.111-118
• /
• 2002

In GMAW(Gas Metal Arc Welding) processes, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality, Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWD (contact-tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using neuro-fuzzy algorithm. Neural networks was applied to design FLC(fuzzy logic control), The parameters of input membership functions and those of consequence functions in FLC were tuned through the method of learning by backpropagation algorithm, Bead geometry could he reasoned from welding current, arc voltage, travel speed on FLC using the results learned by neural networks. On the developed inference system of bead geometry using neuo-fuzzy algorithm, the inference error percent of bead width was within ${\pm}4%$, that of bead height was within ${\pm}3%$, and that of penetration was within ${\pm}8%$, Neural networks came into effect to find the parameters of input membership functions and those of consequence in FLC. Therefore the inference system of welding quality expects to be developed through proposed algorithm.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.2
• /
• pp.84-90
• /
• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• Design & Manufacturing
• /
• v.17 no.2
• /
• pp.22-26
• /
• 2023

As Light-Emitting Diodes(LEDs) continue to advance in performance, their application in automotive lamps is increasing. Automotive LEDs utilize light guides not only for aesthetics but also to control light quantity and direction. Light guides employ patterns of a few hundred micrometers(㎛) to regulate the light, and the surface roughness(Ra) of these patterns can reach tens of nanometers(nm). Given that these light guides are produced through injection molding, mold processing technology with high surface quality micro-patterns is required. This study serves as a preliminary investigation into the development of high surface quality micro-pattern processing technology. It examines the surface roughness of the workpiece based on the cutting direction of the pattern and the cutting fluid type when cutting micro-patterns on STAVAX steel using cubic Boron Nitride(cBN) tools. The experiments involved machining a step-shaped micro-pattern with a height of 60 ㎛ and a pitch of 400 ㎛ in a 22×22 mm area under identical cutting conditions, with only the cutting direction and cutting fluid type being varied. The machining results of four cases were compared, encompassing two cases of cutting direction(parallel to the pattern, orthogonal to the pattern) and two cases of cutting fluid type (flood, mist). Consequently, the Ra value was found to be the highest(Ra 128.33 nm) when machining with the flood type in parallel to the pattern, while it was the lowest(Ra 95.22 nm) when machining with the mist type orthogonal to the pattern. These findings confirm that there is a difference of up to 25.8 % in the Ra value depending on the cutting direction and cutting fluid type.

• Journal of Korean Institute of Industrial Engineers
• /
• v.38 no.3
• /
• pp.220-226
• /
• 2012

The Electric discharge machining (EDM) process is used to minimize the difference between designed feature and machined feature while the most workpiece is removed through the cutting processes. The tiny-deep hole machining and perpendicular wall machining in mold and die are good applications of EDM. Among EDM equipment, the super drill uses the hollowed electrode to eliminate the debris which causes the second discharge with the electrode and degrades the machining quality. Through the hollow, the high pressured discharge oil is supplied to remove the debris together with the spindle rotation. The thin-hollow electrode tends to easily wear out compared to the sold die-sinking electrode and its wear rate is might not allowed to monitor in real time during discharging. Up to now, the wear amount is measured by off line method, which leads machining time to increase because the hole pass-through moment can be check by visual (manually) with the extra tool path. Therefore, this study suggests the attractive method to evaluate the hole pass-through moment in which the gap voltage and z-axis encoder pulse are monitored to predict the moment. The commercial super drill is used to validate the proposed method and the experiment is carried out.

• Journal of Computational Design and Engineering
• /
• v.1 no.3
• /
• pp.187-193
• /
• 2014

One of the hottest challenges in automotive industry is related to weight reduction in sheet metal forming processes, in order to produce a high quality metal part with minimal material cost. Stamping is the most widely used sheet metal forming process; but its implementation comes with several fabrication flaws such as springback and failure. A global and simple approach to circumvent these unwanted process drawbacks consists in optimizing the initial blank shape with innovative methods. The aim of this paper is to introduce an efficient methodology to deal with complex, computationally expensive multicriteria optimization problems. Our approach is based on the combination of methods to capture the Pareto Front, approximate criteria (to save computational costs) and global optimizers. To illustrate the efficiency, we consider the stamping of an industrial workpiece as test-case. Our approach is applied to the springback and failure criteria. To optimize these two criteria, a global optimization algorithm was chosen. It is the Simulated Annealing algorithm hybridized with the Simultaneous Perturbation Stochastic Approximation in order to gain in time and in precision. The multicriteria problems amounts to the capture of the Pareto Front associated to the two criteria. Normal Boundary Intersection and Normalized Normal Constraint Method are considered for generating a set of Pareto-optimal solutions with the characteristic of uniform distribution of front points. The computational results are compared to those obtained with the well-known Non-dominated Sorting Genetic Algorithm II. The results show that our proposed approach is efficient to deal with the multicriteria shape optimization of highly non-linear mechanical systems.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.16 no.2
• /
• pp.28-33
• /
• 2017

Recently, the operation of precision pocket machining has been studied for the high speed and accuracy in industry to increase production and quality. Moreover, the demand for products with complex 3D free-curved surface shapes has increasing rapidly in the development of computer systems, CNC machining, and CAM software in various manufacturing fields, especially in automotive engineering. The type of aluminum (Al6061) that is widely used in aerospace fields was used in this study, and end-mill down cutting was conducted in fillet cutting at a corner with end-mill tools for various process conditions. The experimental results may demonstrate that the end mill cutter with four blades is more advantageous than that of the two blades on shape forming in the same condition precise machining conditions. It was also found that cutting forces and tool deformation increased as the cutting speed increased. When the tool was located at $45^{\circ}$ (four locations), the corner was found to conduct the maximum cutting force rather than the start point of the workpiece. The experimental research is expected to increase efficiency when the economical precision machining methods are required for various cutting conditions in industry.