• The Microorganisms and Industry
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• v.19 no.2
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• pp.34-41
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• 1993

Industrial strain improvement is concerned with developing or modifying microorganisms used in production of commercially important fermentation products. The aim is to reduce the production cost by improving productivity of a strain and manipulating specific characteristics such as the ability to utilize cheaper raw materials or resist bacteriophages. The traditional empirical approach to strain improvement is mutation combined with selection and breeding techniques. It is still used by us to improve the productivity of organisms in amino acids, organic acids and enzymes production. The breeding of high L-lysine-producing strain Au112 is one of the outstanding examples of this approach. It is a homoserine auxotroph with AEC, TA double metabolic analogue resistant markers. The yield reaches 100 g/l. Besides, the citric acid-producing organism Aspergillus niger, Co827, its productivity reaches the advanced level in the world, is also the result of a series mutations especially with $^60Co{\gamma}$-radiation. The thermostable .alpha.-amylase producing strain A 4041 is the third example. By combining physical and chemical mutations, the strain A 4041 becomes an asporogenous, catabolite derepressed mutant with rifamycin resistant and methionine, arginine auxotroph markers. The .alpha.-amylase activity reaches 200 units/ml. The fourth successful example of mutation in strain improvement is the glucoamylase-producing strain Aspergillus niger SP56, its enzyme activity is 20,000 units/ml, 4 times of that of the parental strain UV-11. Recently, recombinant DNA approach provides a worthwhile alternative strategy to industrial strain improvement. This technique had been used by us to increase the thermostable .alpha.-amylase production and on some genetic researches.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.257-266
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• 2014

The semiconductor manufacturing industry is managed by a number of parameters from the FAB which is the initial step of production to package test which is the final step of production. Various methods for prediction for the quality and yield are required to reduce the production costs caused by a complicated manufacturing process. In order to increase the accuracy of quality prediction, we have to extract the significant features from the large amount of data. In this study, we propose the method for extracting feature from the cell level data of probe test process using OPTICS which is one of the density-based clustering to improve the prediction accuracy of the quality of the assembled chips that will be placed in a package test. Two features extracted by using OPTICS are used as input variables of quality prediction model because of having position information of the cell defect. The package test progress for chips classified to the correct quality grade by performing the improved prediction method is expected to bring the effect of reducing production costs.

• Journal of Surface Science and Engineering
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• v.40 no.1
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• pp.32-38
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• 2007

Ni coating layers were formed using a newly developed electroless Ni plating solution. The properties of Ni coating layer such as internal stress, hardness, surface roughness, crystallinity, solderability and surface morphology were investigated using various tools. Results revealed that internal stress decreased with plating time and reached $40N/mm^2$ at 20 minutes of the plating time. Hardness increased with increasing P content and thickness. Surface roughness of the pad decreased with Ni and Ni/Au plating. Crystallinity decreased with increasing P content. Solderability based on wettability decreased with Ni and Ni/Au plating. Based on surface morphology, it is expected that Ni coating layer formed using a newly developed electroless Ni plating solution is lower than that formed using a commercial electroless Ni plating solution in possibility of black pad occurrence.

• Journal of Korea Port Economic Association
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• v.30 no.2
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• pp.77-92
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• 2014

The focus of this study is to analyse dynamic relationship among BDI(Baltic Dry-bulk Index, hereafter BDI), forex market and industrial production using monthly data from 2003-2013. Specifically, we have focused on the investigations how monetary and real variable affect shipping industry during recession period. To compare performance between general VAR and Bayesian VAR we first examine DAG(Directed Acyclic Graph) to clarify causality among the variables and then employ MSFE(mean squared forecast error). The overall estimated results from impulse-response analysis imply that BDI has been strongly affected by other shock, such as forex market and industrial production in Bayesian VAR. In particular, Bayesian VAR show better performance than general VAR in forecasting.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.152-161
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• 2015

Until a recent date, Toyota Production System (called TPS) was introduced by many domestic companies to remove waste and reduce manufacturing cost. However, cases of substantial and effective improvement after the introduction are not much. Even though many companies have actively conducted TPS during that time, the outcome is not satisfactory. In this paper, we show the problems and core contents to consider in applying of TPS as follows. First, the innovative organizational culture formed by active participation of employees and leadership of the CEO is very important for a successful introduction of TPS above all. Second, it is necessary to prepare various training programs optimized for the field in order to continuously improve the competency of employees in each class, and to train skilled personnel through that programs. Third, it is necessary to improve the maturity level of TPS application through the construction of correct evaluation system on accomplishment of the production system. In addition, the problems that occur should be solved through the continuous improvement activities. These results will help to TPS introduction of the domestic small-medium companies. Therefore, this study will contribute to strengthen and improve the global competitiveness in the related industries.

• Land and Housing Review
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• v.11 no.3
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• pp.33-37
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• 2020

The aim of this paper is to scrutinize the relation between Business Survey Index and Industrial Production Index in construction industry, stated in another way, the relation between CEO's expectations of future business status and real business activity in construction industry. Previous papers on this research area have been examined the relation between released BSI and released IPI. However, this paper focuses 'the relation between released BSI and the long-run component of IPI' and 'the relation between released BSI and the short-run component of IPI'. The first step is to decompose released IPI by unobserved component model. The long-run component of IPI is set up as a random walk process. And short-run component is set up as a stationary AR(1) process. The findings are as follows. First, released BSI Granger causes unidirectionally released IPI. Second, there exists one-way Granger causality from released BSI to long-run component of IPI. Third, Granger causality does not exist between released BSI and 'short-run component of IPI'. BSI increases IPI in the second or third month. These findings of this paper mean that CEO's expectations may influence industrial production in construction industry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.116-123
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• 2024

In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.99-99
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• 1995

• Journal of Industrial Technology
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• v.5
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• pp.91-96
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• 1985

This paper presents a problem of a Wagner-Whitin type in which there are several options for setup and production in a period. Theorems that efficiently decrease the computational effort required to find optimal policies and a Planning Horizon Theorem are developed.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.1
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• pp.7-12
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• 2010

This paper considers a dynamic lot-sizing problem with backlogging under a minimum replenishment policy. For general concave production costs, we propose an O($T^5$) dynamic programming algorithm. If speculative motive is not allowed, in this case, a more efficient O($T^4$) algorithm is developed.