• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.64-73
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• 2019

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.558-565
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• 2021

The Republic of Korea Navy has deployed naval fleets in the East, West, and South seas to effectively respond to threats from North Korea and its neighbors. However, it is difficult to allocate proper missions due to high uncertainties, such as the year of introduction for the ship, the number of mission days completed, arms capabilities, crew shift times, and the failure rate of the ship. For this reason, there is an increasing proportion of expenses, or mission alerts with high fatigue in the number of workers and traps. In this paper, we present a simulation model that can optimize the assignment of naval vessels' missions by using a continuous time absorbing Markov chain that is easy to model and that can analyze complex phenomena with varying event rates over time. A numerical analysis model allows us to determine the optimal mission durations and warship quantities to maintain the target operating rates, and we find that allocating optimal warships for each mission reduces unnecessary alerts and reduces crew fatigue and failures. This model is significant in that it can be expanded to various fields, not only for assignment of duties but also for calculation of appropriate requirements and for inventory analysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.15-22
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• 2020

Economic indicators are a factor that affects air cargo volume. This study analyzes the different factors affecting air cargo volume by each Chinese cities according to the main characteristics. The purpose of this study is to help companies related to China, airlines, and other stakeholders predict and prepare for the fluctuations in air cargo volume and make optimal decisions. To this end, 20 economic data were used, and the entire data was reduced to 5 dimensions through factor analysis to build a dataset necessary and evaluated the influencing factors by multi regression. The result shows that Macro-Economic Indicators, Production/Service indicators are significant for every cities and Chinese manufacture/Customer indicators, Korean manufacture/Oil Price indicators, Trade/Current indicators are significant for each other city. All adjusted R2 values are high enough to explain our model and the result showed excellent performance in terms of analyzing the different factors which affects air cargo volume. If companies that are currently doing business with China can identify factors affecting China's cargo volume, they can be flexible in response to changes in plans such as plans to enter China, production plans and inventory management, and marketing strategies, which can be of great help in terms of corporate operations.

• The Korean Journal of Rehabilitation Nursing
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• v.3 no.1
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• pp.43-58
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• 2000

Pain management is a major issue in caring of cancer patients. Patients' concerns for reporting pain and taking analgesics are patient-related barriers to the management of cancer pain. Since such study has not been done at all in Korea, it is clearly needed to study on these problems. The purpose of this study is to attain basic data in order to improve cancer pain management in Korea. This is done by: 1) examining the extent of patients' concerns that might be barriers to the optimal pain management, and the extent of related factors (pain management hesitancy, adequacy of using analgesics, pain severity and pain interference); 2) identifying the relationship between patients' concerns and the related factors. The data has been collected from 180 cancer patients who were hospitalized in medical wards of one university hospital in Seoul, Korea during the period from November 1, 1997 to February 28, 1998. The data has been collected through interviews with (1) Barriers Questionnaire - Korean Version (BQ-K); (2) Hesitancy Experience Questionnaires (HQ); (3) Pain Management Index (PMI); (4) Brief Pain Inventory (BPI); and (5) Demographic Data. The data were analyzed by descriptive statistics and by t-test, One-way ANOVA, Pearson correlation using SPSSWIN program. The Results are as following: 1) The mean scores of Pain Management Concerns (PMC) by BQ-K were toward the moderate with a little high points(2.59). Most of the patients (99.4%) had some extent of concerns (over lout of maximum 5 points). Among the eight subscales of BQ-K, the Pain Management Concerns (PMC) about 'Fear of tolerance' was the highest (3.80) and 'Worry about side effects' was the least (1.40). 2) The extent of Pain Management Hesitancy (PMH) by HQ of wnom had pain on the day of the interview was a little higher than moderate score(5.53 out of maximum 10 points). 6.7% of the patients with experiencing pain used less adequate analgesics for the severity of pain than they were expected. 27.8% of them never used any analgesics at all. The mean score of pain severity by BPI was 16.59 (maximum: 40), and that of the interference with daily life by BPI was 32.03 (maximum: 70). 3) The patients who were older, less educated, and in low socio-economic status were likely to have more concerns. Pain Management Concerns (PMC) was positively correlated with Pain Management Hesitancy (PMH) (r=.75), pain severity (r=.44) and pain interference (r=.50). Those who were not using adequate analgesics had higher Pain Management Concerns (PMC) than did those who were using adequate analgesics (t=-5.42). The patients who had more Pain Management Concerns (PMC) tended to hesitate more to report pain and to use analgesics. They used more inadequate analgesics for the severity of pain and also had experienced more pain severity and interference with daily life. In conclusion, the patients' concerns for reporting pain and for using analgesics are major patient-related barriers to cancer pain management in Korea. The patients' concerns were correlated significantly with the level of the hesitancy experience, inadequate use of analgesics, the pain severity and the interference with daily life. Considering this, an educational program for cancer patients under the treatment with analgesics should be developed in order to solve these problems.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.139-146
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• 2015

WSN has been utilized in various directions from basic infrastructure of environment composition to business models including corporate inventory, production and distribution management. However, as energy organizations' private information, which should be protected safely, has been integrated with ICT such as WSN to be informatization, it is placed at potential risk of leaking out with ease. Accordingly, it is time to need secure sensor node deployment strategies for stable enterprise business. Establishment of fragmentary security enhancement strategies without considering energy organizations' security status has a great effect on energy organizations' business sustainability in the event of a security accident. However, most of the existing security level evaluation models for diagnosing energy organizations' security use technology-centered measurement methods, and there are very insufficient studies on managerial and environmental factors. Therefore, this study would like to diagnose energy organizations' security and to look into how to accordingly establish strategies for planning secure sensor node deployment strategies.

• Korean Journal of Psychosomatic Medicine
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• v.14 no.1
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• pp.47-52
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• 2006

Backgrounds : Depression has been prevalent in women and maintaining optimal glycemic control is an important goal of diabetes management. Although depression is common in adults with diabetes, its relationship to glycemic control remains unclear, espacilly in Korean women. The current study examined the relationship of depressive symptomatology with glycemic control in Korean women. Methods : Beck depression inventory (BDI), $HbA_{1c}$ as an index of long-term glycemic control, fasting glucose level and body mass index (BMI) were measured in sample of 4,567 women of whom 4.7%, 216 women had diabetes, and the relationship between depression and glycemic control was analyzed. BDI Scores of 16 and above is a cut off point to indicate possible clinical depression. Results The frequency of depressed women (p<0.001) and the mean score of BDI (p<0.001) were significantly higher in diabetic women. The mean level of $HbA_{1c}$ (p<0.01) and fasting glucose (p<0.05) were higher in depressed women. There was a graded relationship between the percentile of depressed women and a degree of glycemic control impairment (p=0.001). Conclusion : The current study found the relationship of depressive symptomatology with glycemic control in Korean women. This relationship may be mediated by decreased self-care behaviors or by neurobiological dysregulation. Improving identification and treatment of depression in women with diabetes might have favorable effects on diabetic outcomes.

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.316-329
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• 2008

Recently the increased attention pays on the processing of multiple, relatively low quantity, high value-added products resulted in adoption of batch process in the chemical process industry such as pharmaceuticals, polymers, bio-chemicals and foods. As there are more possibilities of the improvement of operations in batch process than continuous processes, a lot of effort has been made to enhance the productivity and operability of batch processes. But the chemical process industry faces a range of uncertainties factors such as demands for products, prices of product, lead time for the supply of raw materials and in the production, and the distribution of product. And global competition has made it imperative for the process industries to manage their supply chains optimally. Supply chain management aims to integrate plants with their supplier and customers so that they can be managed as a single entity and coordinate all input/output flows (of materials, information) so that products are produced and distributed in the right quantities, to the right locations, and at the right time.The objective of this study is to solve the purchase, distribution, production planning and scheduling problem, which minimizes the total costs of production, inventory, and transportation under uncertainty. And development of SCM model in chemical industry including batch mode operations. Through that, the enterprise can respond to uncertainty. Also integrated process optimal planning and scheduling model for manufacturing supply chain. The result shows that, the advantage of supply chain integration are quality matters seen by customers and suppliers, order schedules, flexibility, cost reduction, and increase in sales and profits. Also, an integration of supply chain (production and distribution system) generates significant savings by trading off the costs associated with the whole, rather than minimizing supply chain costs separately.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.