• The Journal of the Convergence on Culture Technology
• /
• v.10 no.6
• /
• pp.829-847
• /
• 2024

The automotive industry is undergoing a major transformation with the advent of electric vehicles and autonomous vehicles, and the demand for advanced automotive semiconductor technologies is increasing. This study analyzes the patenting and joint development activities of automotive semiconductor technologies in five industries: automobile manufacturing, auto parts, automotive semiconductor, integrated semiconductor, and information technology. The study analyzed 421,802 single patents and 22,342 co-patents of 40 companies over the 12-year period from 2010 to 2021 and found two important findings. First, the analysis of joint patents shows that the automobile manufacturing industry and the information technology industry are active in securing joint patents through collaborative activities. Second, the community analysis of the co-patent network over the 12-year period shows that while technical cooperation relationships have been steadily maintained to secure changing automotive semiconductor technologies, the collaborative activities of companies within the community have changed according to technological changes and the need to complement capabilities. Based on this research, we proposed some collaboration strategies for either strengthening a company's capability or compensating for weakness.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.16 no.1
• /
• pp.166-174
• /
• 2008

Recently, the automotive industry has been developing rapidly. With the progress parts of the automobile components need high quality and the reliability. Among them, braking unit is essential device, and acquire the reliability through the performance test of brake. This study was aimed to design the performance-test-bench to measure the drag torque which has effect on caliper in braking unit. In this progressive technology, it is vital importance to use hydraulic and pneumatic, and to combine test bench with instrumentation engineering technology. This system to construct the design of hydraulic and pneumatic circuit, interface technique between sensors and personal computer, data acquisition and display design, and integrated control are very important technology. Moreover, reliable data are obtained through vacuum system and hydraulic and pneumatic system by using of booster and brake master cylinder which are actually applied to automobile. Then, data signal detector sensors for speed, pressure and torque is attached on this system. Therefore, in this study, we designed a performance-test-bench by and we also made an total control system using personal computer which is more progressive and flexible method than existing PLC control.

• Journal of the Korean Society for Precision Engineering
• /
• v.34 no.2
• /
• pp.145-150
• /
• 2017

Air brake valves are widely used in automotive braking systems and the Korean automobile industry depends on importing them. Therefore, we should develop the technical expertise for their domestic production. In this study, air brake valves were analyzed that can be used in a variety of automobiles. Computational fluid dynamics analysis, static structural analysis, and hyper-elastic analysis were carried out. Before production of an air brake valve system, the performance of different parts has to be evaluated, for instance by using finite element analysis. The structural stability of the product can be determined using static dynamics. The compression behavior of the O-ring is predictable by nonlinear hyper elastic analysis, although errors are possible due to one-way loading. This simulation study can both save time and reduce costs compared to the development of experimental prototypes.

• Journal of Distribution Science
• /
• v.18 no.9
• /
• pp.31-43
• /
• 2020

Purpose: This study examined a comprehensive model for assessing the success probability of electric vehicle (EV) commercialization in the Korean market. The study identified three risks associated with successful commercialization which were technology, social, policy, environmental, and consumer risk. Research design, methodology: The assessment of the riskiness was represented by a Bayes belief network, where the probability of success at each stage is conditioned on the outcome of the preceding stage. Probability of success in each stage is either dependent on input (i.e., investment) or external factors (i.e., air quality). Initial input stages were defined as the levels of investment in product R&D, battery technology, production facilities and battery charging facilities. Results: Reasonable levels of investment were obtained by expert opinion from industry experts. Also, a survey was carried out with 78 experts consisting of automaker engineers, managers working at EV parts manufacturers, and automobile industry researchers in government think tanks to obtain the conditional probability distributions. Conclusion: The output of the model was the likelihood of success - expressed as the probability of market acceptance - that depended on the various input values. A model is a useful tool for understanding the EV industry as a whole and explaining the likely ramifications of different investment levels.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.8
• /
• pp.342-347
• /
• 2020

Recently, as the collaborative robot has been introduced into the domestic industrial robot market, it is installed mainly in the manufacturing industry. Collaborative robots are subject to the safety regulations of industrial robots by Article 93 of the Safety Inspection of the Industrial Safety and Health Act. The sites where collaborative robots are to be installed must perform risk assessments for robots-humans, work environments, and work methods and reduce the risks according to ISO 10218-2 and ISO 12100. On the other hand, because it is early in the introduction of collaborative robots, new risks for collaborative robots have not been issued, and risk assessments are unfamiliar and difficult to apply in the workplace. The risk assessment of collaborative robots aims to identify and reduce the risk of a high probability of occurrence by focusing on the abnormal behavior of humans, human errors, equipment defects, and interlock functions. In this study, a risk assessment was applied to a domestic automobile parts production plant, and improvement measures were drawn. This risk assessment is expected to be useful for improving the safety of small businesses by continuously discovering risk assessment examples of collaborative robots.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.4123-4141
• /
• 2019

Autonomous driving technology is divided into 0~5 levels. Of these, Level 5 is a fully autonomous vehicle that does not require a person to drive at all. The automobile industry has been trying to develop Level 5 to satisfy safety, but commercialization has not yet been achieved. In order to commercialize autonomous unmanned vehicles, there are several problems to be solved for driving safety. To solve one of these, this paper proposes 'A Deep Learning Part-diagnosis Platform(DLPP) based on an In-vehicle On-board gateway for an Autonomous Vehicle' that diagnoses not only the parts of a vehicle and the sensors belonging to the parts, but also the influence upon other parts when a certain fault happens. The DLPP consists of an In-vehicle On-board gateway(IOG) and a Part Self-diagnosis Module(PSM). Though an existing vehicle gateway was used for the translation of messages happening in a vehicle, the IOG not only has the translation function of an existing gateway but also judges whether a fault happened in a sensor or parts by using a Loopback. The payloads which are used to judge a sensor as normal in the IOG is transferred to the PSM for self-diagnosis. The Part Self-diagnosis Module(PSM) diagnoses parts itself by using the payloads transferred from the IOG. Because the PSM is designed based on an LSTM algorithm, it diagnoses a vehicle's fault by considering the correlation between previous diagnosis result and current measured parts data.

• Journal of the Korean Society for Precision Engineering
• /
• v.28 no.4
• /
• pp.482-489
• /
• 2011

In practical design process, designer needs to find an optimal solution by using full factorial discrete combination, rather than by using optimization algorithm considering continuous design variables. So, ANOVA(Analysis of Variance) based on an orthogonal array, i.e. Taguchi method, has been widely used in most parts of industry area. However, the Taguchi method is limited for the shape optimization by using CAE, because the multi-level and multi-objective optimization can't be carried out simultaneously. In this study, a combined method was proposed taking into account of multi-level computational orthogonal array and TOPSIS(Technique for Order preference by Similarity to Ideal Solution), which is known as a classical method of multiple attribute decision making and enables to solve various decision making or selection problems in an aspect of multi-objective optimization. The proposed method was applied to a case study of the multi-level shape optimization of lower arm used to automobile parts, and the design space was explored via an efficient application of the related CAE tools. The multi-level shape optimization was performed sequentially by applying both of the neural network model generated from seven-level four-factor computational orthogonal array and the TOPSIS. The weight and maximum stress of the lower arm, as the objective functions for the multi-level shape optimization, showed an improvement of 0.07% and 17.89%, respectively. In addition, the number of CAE carried out for the shape optimization was only 55 times in comparison to full factorial method necessary to 2,401 times.

• Korean Journal of Materials Research
• /
• v.19 no.9
• /
• pp.457-461
• /
• 2009

Recently, metal molding has become essential not only for automobile parts, but also mass production, and has greatly influenced production costs as well as the quality of products. Its surface has been treated by carburizing, nitriding and induction hardening, but these existing treatments cause considerable deformation and increase the expense of postprocessing after treatment; furthermore, these treatments cannot be easily applied to parts that requiring the hardening of only a certain section. This is because the treatment cannot heat the material homogeneously, nor can it heat all of it. Laser surface treatment was developed to overcome these disadvantages, and, when the laser beam is irradiated on the surface and laser speed is appropriate, the laser focal position is rapidly heated and the thermal energy of surface penetrates the material after irradiation, finally imbuing it with a new mechanical characteristic by the process of self-quenching. This research estimates the material characteristic after efficient and functional surface treatment using HPDL, which is more efficient than the existing CW Nd:YAG laser heat source. To estimate this, microstructural changes and hardness characteristics of three parts (the surface treatment part, heat affect zone, and parental material) are observed with the change of laser beam speed and surface temperature. Moreover, the depth of the hardened area is observed with the change of the laser beam speed and temperature.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.5
• /
• pp.817-823
• /
• 2020

In recent, the machining of difficult-to-cut materials such as titanium alloys, stainless steel, Inconel, ceramic, glass, and carbon fiber reinforced plastics (CFRP) used in aerospace, automobile, medical industry is actively researched. Abrasive waterjet is a non-traditional processing method in which ultra-high pressure water and abrasive particles are mixed in a mixing chamber and shoot out jet through a nozzle, and removed by erosion due to collision with a material. In particular, the nozzle of the abrasive waterjet is one of the most important parts that affect the machining quality as with a cutting tool in general machining. It is very important to monitor the condition of the nozzle because the workpiece is uncut or the surface quality deteriorates due to wear, expanding of the bore, damage of the nozzle and clogging of the abrasive, etc. Therefore, in this paper, we propose a monitoring system based on Acoustic Emission(AE) sensor that can detect nozzle condition in real time during AWJ processing.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.2_2
• /
• pp.181-189
• /
• 2020

As production, distribution, consumption and processing increase with the development of industrial societies, the importance of resource depletion and environmental problems is increasing day by day. This has led to increased research and interest in remanufacturing that can satisfy both environmental and economic aspects. Currently, the remanufacturing industry is progressed in Korea with automobile parts with as the central figure, and it needs to be expanded into various areas. In this study, the failure type analysis and FMEA were performed on the hydraulic pumps used in construction and industrial sites for the development of the standard remanufacturing process plan, and the actual disassembly and reassembly process was carried out. Remanufacturing products were manufactured through the analysis contents and drawing process, performance tests were conducted in accordance with RS B1501 criteria to evaluate performance, and all of these products passed the test criteria.