• 한국디지털정책학회:학술대회논문집
• /
• 2004.11a
• /
• pp.99-109
• /
• 2004

Key goal of the study is to analyze the economical ripple effect by the digital contents industry. In this study, the results of analysis of multiplier effects of digital contents industry can be summaries as follows: (1) Output multiplier for the manufacturing sector was the highest with value of 3.0509 while that of digital contents industry is the lowest at 1.6511. (2) Employment multiplier is the lowest for the manufacturing sector with value of 4.2895, while that of digital contents industry is the lowest with value of 1.0238. (3) Income multiplier is the lowest for the manufacturing sector with value of 5.3331, while that of digital contents industry is the lowest with value of 1.0081. Therefore, digital contents industry is clearly a new-growth power industry in the future rather than in the present.

• Journal of Korean Institute of Industrial Engineers
• /
• v.22 no.2
• /
• pp.231-245
• /
• 1996

Semiconductor manufacturing line includes several batch processes which are to be controlled effectively to enhance the productivity of the line. The key problem in batch processes is a dynamic batch sizing problem which determines number of lots processed simultaneously in a single botch. The batch sizing problem in semiconductor manufacturing has to consider delay of lots, setup cost of the process, machine utilization and so on. However, an optimal solution cannot be attainable due to dynamic arrival pattern of lots, and difficulties in forecasting future arrival times of lots of the process. This paper proposes an efficient batch sizing heuristic, which considers delay cost, setup cost, and effect of the forecast errors in determining the botch size dynamically. Extensive numerical experiments through simulation are carried out to investigate the effectiveness of the proposed heuristic in four key performance criteria: average delay, variance of delay, overage lot size and total cost. The results show that the proposed heuristic works effectively and efficiently.

• Proceedings of the Materials Research Society of Korea Conference
• /
• 2011.05a
• /
• pp.2.1-2.1
• /
• 2011

Electrospray deposition (ESD) technique is fast finding its applicability in the field of thin film device manufacturing processes and the ease and cost efficiency attached to ESD process with possible integration with batch manufacturing technologies is the potential future of thin film device manufacturing. As the name suggests, the deposition phenomenon should solely be a spray achieved through electrostatic forces. In fact it is an imbalance between the surface forces arising because of the surface tension of the liquid to be sprayed and Maxwell stresses which are induced because of the electric field, that pull the liquid downwards from the capillary into a stable jet which further disintegrates into smaller droplets because of coulomb forces and hence a cloud of charged, mono-dispersed and extremely diminutive (sometimes up to femtolitres) droplets is achieved. The present talk is going to be exclusively about the electrospray process concepts, generation and possible applications.

• Korean Chemical Engineering Research
• /
• v.46 no.3
• /
• pp.571-580
• /
• 2008

Little attention has been given to semiconductor manufacturing in the chemical engineering and process systems engineering perspective in spite of the fact that it consists of numerous chemical processes. This paper particularly investigates the issues in semiconductor manufacturing supply chain management. From the personal industrial experience and research progresses, relevant research and information will be introduced to address the key issues and challenges. Some remarks for future research challenges are made in the end.

• Journal of Industrial Technology
• /
• v.23 no.A
• /
• pp.21-27
• /
• 2003

The bio-micro pin is usually used for biochemistry analysis. The capability of manufacturing the micro-pin and array with effective and low-cost way is very important to developers. The micro-pin is composed of "sample channel" putting liquid into already fixed volume, "flat tip" having connection with printing quantity, and "head part" for preventing it from rotation of pin in the holder. We analyzed out printing variation in accordance with shape and tip size of the micro-pin point channel, In this study, we suggested the manufacturing progress and shape demand condition of the micro-pin which could put $0.2{\mu}{\ell}$-biochemistry material into the sample volume, and will be able to produce the micro-pin which can put $10n{\ell}$-biochemistry material into the sample volume in the future.

• Journal of Information Technology Applications and Management
• /
• v.24 no.2
• /
• pp.55-70
• /
• 2017

A key factor of competitiveness of a firm is technology innovation including product and process innovation. This paper explores the importance and performance of innovation in IT industry across manufacturing and service business. Using importance-performance analysis based on a survey of Korean manufacturing and service firms, we find the characteristics of innovation in IT under the context of industry difference. Out study indicate that Korean IT firms need to recognize the importance of technology innovation and enhance the performance in some areas. In future research, we will expand the boundary of innovation into non-technology innovation as well as service-specific innovation.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.5 no.4
• /
• pp.90-97
• /
• 1996

The thermal deformation of a machine tool spindle influences the performance of the manufacturing systems for precision products. In this research, thermal analysis of a high speed machine tool spindle with the rolling bearing and the built-in motor is carried out by using Finite Difference Method. The thermal boundary conditions describing the heat generation in the bearing and built-in motor are considered in the simulation. And various convective boundary conditions are assumed with the empirical formula in the references. From the simulation results, the characteristics of each element affecting the dynamic thermal behaviour of the machine tool spindle system have been clarified. Therefore, this model can be well applied to the future development of the high speed spindle systems.

• Journal of the Korea Safety Management & Science
• /
• v.19 no.1
• /
• pp.227-236
• /
• 2017

Smart Manufacturing Factory is a paradigm of the future lead to the fourth industrial revolution that led Germany and the United States. Now the automation of the production facility and won a certain degree, and through the process of integrating the entire process, including planning, design, distribution of information and communication technology products in emerging as a core competitiveness of the national economy. In particular, the company accelerated the smart factory building in order to improve the manufacturing industry, cost savings and productivity simply to incorporate internet of things(IoT),Robot, artificial intelligence, big data technology as a factory automation level of sophistication of the system and out to progress to the level that replaces human labor have. In this we should look at the trend of promoting domestic and foreign factories want to present these smart strategies for Korea.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.2
• /
• pp.215-222
• /
• 2014

This paper provides a real-time loading strategy for batch processing machines in which a number of jobs are simultaneously processed as a batch. The batch processing machines can be seen in both manufacturing industries (e.g., semiconductor, automobile and metal working) and service industries (transportation vehicles, mail shipment and theme park). This paper focuses on batch processing machines in semiconductor manufacturing. We present a look-ahead loading strategy for tardiness minimization where future arrivals and due dates are taken into consideration. Simulation tests are performed on the presented strategy and some existing loading heuristics under various production settings with different traffic intensities and forecasting errors. Experimental results show that our strategy provides the performance of good quality.

• Journal of information and communication convergence engineering
• /
• v.20 no.4
• /
• pp.295-302
• /
• 2022

This paper contains the development of a smart power device designed to collect load power data from industrial manufacturing machines, predict future variations in load power data, and detect abnormal data in advance by applying a machine learning-based prediction algorithm. The proposed load power data prediction model is implemented using a Long Short-Term Memory (LSTM) algorithm with high accuracy and relatively low complexity. The Flask and REST API are used to provide prediction results to users in a graphical interface. In addition, we present the results of experiments conducted to evaluate the performance of the proposed approach, which show that our model exhibited the highest accuracy compared with Multilayer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM) models. Moreover, we expect our method's accuracy could be improved by further optimizing the hyperparameter values and training the model for a longer period of time using a larger amount of data.