• Korean Journal of Computational Design and Engineering
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• v.9 no.4
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• pp.387-396
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• 2004

In order to keep and increase a competitive potential, industrial enterprises have to reduce their costs for product development as well as shorten lead time in product development processes. Moreover they have to respond to market factors and conditions such as increasing demands for functionality and individuality of products, short product life cycles, high pressure on prices and time to market. The improved functional requirement in connection with high time and cost pressure lead to high risk in product development. Technological fine improvements in connection with high time and cost pressure lead to high development risk. To cope with these challenges many enterprises have to collaborate globally. The collaborative engineering in product development is aimed to create distributed collaborative corporations and to facilitate the management of design conflicts. This paper provides a methodology for analyzing collaborative design process as well as the tools and the framework to support collaborative product development. The methodology can identify the interdependences among design tasks and teams. The tools and framework are implemented to facilitate the management of product development process.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.479-483
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• 2005

BBU is the weapon system for the extension of range through the reduction of base drag in 155mm. It has been mass-produced since 2000. The purpose of this research is productivity increase through the reduction of process lead time. Development process is as follows. First, formulation tests about propellent and liner, Second, spin test and final firing test about end products.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.342-345
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• 2003

Due to the rapid development of manufacturing and information technology, traditional supply chain scheme has been changed dramatically Most companies have been forced to relocate or redesign their logistics network in different countries. A supply chain partnership is a relationship formed between two independent members in supply chain through information sharing to achieve specific objectives and benefits in terms of reductions in total costs and inventories. This study illustrates the benefits of supply chain partnerships based on information sharing and lead-time patterns. We consider three level of information sharing: (1) immediate order information; (2) demand information; (3) inventory information. Given a fixed total lead-time, how lead-time distribution will affect the bullwhip effect and inventory cost under information sharing strategies. The results can help improving supply chain performance and selecting suitable direction for the re-configuration of supply chain network.

• International Journal of Quality Innovation
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• v.8 no.2
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• pp.115-131
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• 2007

The vehicle development process (VDP) is iterative in nature with numerous interactions and information flows between design groups and between development phases. The VDP has been changed from a sequential-functional development to a concurrent-team based approach. Concurrent execution of design activities may reduce the development lead-time, but it increases the managerial complexity in the VDP. A system dynamics model was developed to understand the transient behavior of parallel, overlap, and sequential processes in the VDP and to determine the optimal level of overlapping considering the development lead-time and total number of reworks. The simulation results showed that different execution processes should be used, depending upon the intensity of reworks.

• Journal of Fisheries and Marine Sciences Education
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• v.22 no.4
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• pp.501-507
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• 2010

The ceramic contained paint was made to replace the lead sinker for gill-net with coated lead sinker. The ceramic contained paints were coated in various conditions on the lead sinker with 19g of weight and the optimal coating condition was studied. The adaptability of the coated lead sinker was checked through the anti durability test and fishing operation with gill-net. The case of "Main material 70 wt% + Urethane thinner 30 wt% (Main material 700 $m{\ell}$ + Thinner 300 $m{\ell}$)" showed the best in the coating characteristics depending on the combination ratio of the ceramic paint contained. The coated lead sinker dried at $100^{\circ}C$ inside oven was superior to the drying in the room temperature in its surface glossiness and anti durability and faster drying time than the one dried in normal temperature. The quadruple layers of coating on lead sinker with 4 times of dipping and drying application showed the super anti durability in the coating characteristics depending on the frequency of dipping. When press is applied to the coated lead sinker, the coated layer is not detached from the sinker. In addition, the coated lead sinker was not damaged or peeled at the fishing operation about 2 months in various depths within 50m and by the materials at the bottom (sand, stone and gravel stone) and it was in good condition.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.97-110
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• 2017

This study investigates the efficiencies of machine learning models, including artificial neural network (ANN), generalized regression neural network (GRNN), adaptive neuro-fuzzy inference system (ANFIS) and random forest (RF), for reservoir water level forecasting in the Chungju Dam, South Korea. The models' efficiencies are assessed based on model efficiency indices and graphical comparison. The forecasting results of the models are dependent on lead times and the combination of input variables. For lead time t = 1 day, ANFIS1 and ANN6 models yield superior forecasting results to RF6 and GRNN6 models. For lead time t = 5 days, ANN1 and RF6 models produce better forecasting results than ANFIS1 and GRNN3 models. For lead time t = 10 days, ANN3 and RF1 models perform better than ANFIS3 and GRNN3 models. It is found that ANN model yields the best performance for all lead times, in terms of model efficiency and graphical comparison. These results indicate that the optimal combination of input variables and forecasting models depending on lead times should be applied in reservoir water level forecasting, instead of the single combination of input variables and forecasting models for all lead times.

• Ocean and Polar Research
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• v.40 no.3
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• pp.99-114
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• 2018

In the present study, we assess the GloSea5 (Global Seasonal Forecasting System version 5) near-surface ocean current forecasts using globally observed surface drifter dataset. Annual mean surface current fields at 0-day forecast lead time are quite consistent with drifter-derived velocity fields, and low values of root mean square (RMS) errors distributes in global oceans, except for regions of high variability, such as the Antarctic Circumpolar Current, Kuroshio, and Gulf Stream. Moreover a comparison with the global high-resolution forecasting system, HYCOM (Hybrid Coordinate Ocean Model), signifies that GloSea5 performs well in terms of short-range surface-current forecasts. Predictions from 0-day to 4-week lead time are also validated for the global ocean and regions covering the main ocean basins. In general, the Indian Ocean and tropical regions yield relatively high RMS errors against all forecast lead times, whilst the Pacific and Atlantic Oceans show low values. RMS errors against forecast lead time ranging from 0-day to 4-week reveal the largest increase rate between 0-day and 1-week lead time in all regions. Correlation against forecast lead time also reveals similar results. In addition, a strong westward bias of about $0.2m\;s^{-1}$ is found along the Equator in the western Pacific on the initial forecast day, and it extends toward the Equator of the eastern Pacific as the lead time increases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.224-230
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• 2006

As business competition gets together, there is much pressure on product development service organizations and manufacturing to become more productive and efficient. Product developers need to create innovative products in less time, even though the products may be very complex. To get this purpose, Six sigma methodology can be used. Six sigma is a strategic approach that works across all processes, all products, and all industries. The purpose of this paper is to develop the innovation strategy for shortening the lead time of the new product using six sigma method.

• Journal of the Korea Safety Management & Science
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• v.20 no.3
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• pp.11-19
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• 2018

This study suggests a model of production information system that can reduce manufacturing lead time and uniformize quality by using DNC S/W as a part of constructing production information management system in the industrial field of the existing marine engine block manufacturing companies. Under the effect of development of this system, the NC machine interface device can be installed in the control computer to obtain the quality information of the workpiece in real time so that the time to inspect the process quality and verify the product defect information can be reduced by more than 70%. In addition, the reliability of quality information has been improved and the external credibility has been improved. It took 30 minutes for operator to obtain, analyze and manage the quality information when the existing USB memory is used, but the communication between the NC controller computer and the NC controller in real time was completed to analyze the workpiece within 10 seconds.