• Korean Journal of Environmental Biology
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• v.34 no.2
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• pp.73-78
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• 2016

Bhutanese forests have been well preserved and can sequester the atmospheric carbon (C). In spite of its importance, understanding Bhutanese forest C dynamics was very limited due to the lack of available data. However, forest C model can simulate forest C dynamics with comparatively limited data and references. In this study, we aimed to simulate Bhutanese forest C dynamics at 6 plots with the Forest Biomass and Dead organic matter Carbon (FBDC) model, which can simulate forest C cycles with small amount of input data. The total forest C stock ($Mg\;C\;ha^{-1}$) ranged from 118.35 to 200.04 with an average of 168.41. The C stocks ($Mg\;C\;ha^{-1}$) in biomass, litter, dead wood, and mineral soil were 3.40-88.13, 4.24-24.95, 1.99-20.31, 91.45-97.90, respectively. On average, the biomass, litter, dead wood, and mineral soil accounted for 36.0, 5.5, 2.5, and 56.0% of the total C stocks, respectively. Although our modeling approach was applied at a small pilot scale, it exhibited a potential to report Bhutanese forest C inventory with reliable methodology. In order to report the national forest C inventory, field work for major tree species and forest types in Bhutan are required.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.305-312
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• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.273-284
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• 2007

This paper studies a periodic review inventory model with an e-MarketPlace transaction in reconfigurable manufacturing system(RMS). A decision maker can expand/reduce production capacity/quantities and/or replenish/dispose inventories from/to e-MarketPlace urgently to satisfy the stochastic demands. If inventories are replenished or disposed through e-MarketPlace, this leadtime is shorter than the production leadtime, but unit purchasing or selling cost is more expensive than that of expanding capacity or reducing production quantities respectively. Henceforth, trade-off on these alternatives is considered. In addition to this, in order to consider the economy of scale, our model includes the fixed cost for purchasing from e-MarketPlace and capacity expansion. We use dynamic programming and K convexity methods to characterize the nature of the optimal policy. Finally, We present the optimal inventory control policy which is composed by the combinations of a base stock and (s,S) type policy.

• The Journal of Bigdata
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• v.5 no.2
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• pp.111-120
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• 2020

Despite the recent economic contraction caused by the Corona 19 incident, interest in the residential environment is growing as more people live at home due to the increase in telecommuting, thereby increasing demand for remodeling. In addition, the government's real estate policy is also expected to have a visible impact on the sales of the interior and furniture industries as it shifts from regulatory policy to the expansion of housing supply. Accurate demand forecasting is a problem directly related to inventory management, and a good demand forecast can reduce logistics and inventory costs due to overproduction by eliminating the need to have unnecessary inventory. However, it is a difficult problem to predict accurate demand because external factors such as constantly changing economic trends, market trends, and social issues must be taken into account. In this study, LSTM model and 1D-CNN model were compared and analyzed by artificial intelligence-based time series analysis method to produce reliable results for manufacturers producing furniture components.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.153-167
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• 2022

Purpose: The purpose of this study is to guide the operation managers who plan daily production of large mass-processing facility that services multi-customers with multi-product, small-batch item characteristics by providing the practical best production quantity and the inventory allowed to build. Methods: Close observation of a subcontract paint-shop operator captured the daily decision process which was reflected in the subcontractor-unique mathematical model and the system dynamics simulation model. Multiple simulations were run to find the practical best production quantity and the maximum allowable stock level of inventory that did not undermine the profit from practical best daily production. Actual data and a few constant values were obtained from the firm under study. Results: While the inventory holding cost for the customer-owned material harms the total profit of the subcontractor, the running cost of the processing facility hinders production in small batches. This balances the maximum possible productions and results in practical best daily production which can be found through simulation runs with actual data. The maximum level of stocked inventory is deduced from the practical best daily production. Conclusion: To build a large volume that enables economy-of-scale production, operators should deal with multi-product small-batch items from multiple customers. When the planned schedule of the time and amount of material in-flow tend not to be reliable, operators can find it practical to execute level production across the planning horizon instead of adjusting to day-to-day in-flow fluctuations.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.398-407
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• 2014

Shortages and delays in a humanitarian logistics system can contribute to the pain and suffering of survivors or other affected people. Humanitarian logistics budgets should be sufficient to prevent such shortages or delays. Unlike commercial supply chain systems, the budgets for relief supply chain systems should be able to satisfy demand. This study describes a comprehensive model in an effort to satisfy the total relief demand by minimizing logistics operations costs. We herein propose a strategic model which determines the locations of distribution centers and the total inventory to be stocked for each distribution center where a flood or other catastrophe may occur. The proposed model is formulated and solved as a mixed-integer programming problem that integrates facility location and inventory decisions by considering capacity constraints and time restrictions in order to minimize the total cost of relief operations. The proposed model is then applied to a real flood case involving 47 disaster areas and 13 distribution centers in Thailand. Finally, we discuss the sensitivity analysis of the model and the managerial implications of this research.

• Korean Management Science Review
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• v.31 no.2
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• pp.33-48
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• 2014

It is important to maintain on operational availability of aircraft during wartime. The KF-16 fighter, the backbone of the ROKAF (Republic Of Korea Air Force), has a single engine. Therefore, the engine has a critical influence on operational availability. The purpose of this study is to estimate optimal levels of spare part inventories concerning both engines and modules. That is provided by linear programming methods utilizing a developed meta-model. For drawing out the meta-model, we develop a simulation model which can consider wartime demands. In the previous study, $2^k$ factorial design method is used to check the influence of each independent variable. That method requires relatively many scenarios because every extreme value combination of independent variables should be checked. However, this study adopts NOLH (Nearly Orthogonal Latin Hypercube) as an experimental design. By adopting NOLH, this study increases not only efficiency but also accuracy. That is proven by comparing the validity of the developed meta-model on both experimental designs. This study also utilizes the OptQuest simulation tool in ARENA to derive the optimal level of spare stocks. By comparing the result of OptQuest to that of the developed meta-model, the validity of this study is secured.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.802-810
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• 1998

The purpose of this study is to find the analytic solution of determining the optimal capacity of processes and storages to meet the product demand. Recent trend to reduce product delivery time and to provide high quality product to customer requires the increasing capacity of storage facilities. However, the cost of constructing and operating storage facilities is becoming substantial because of increasing land value, environmental and safety concern. Therefore, reasonable decision making about the capacity of processes and storages is important subject for industries. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ(Economic Order Quantity) model, trimmed with practical experience but the unrealistic assumption of EOQ model is not suitable for the chemical plant design with highly interlinked processes and storages. This study, a first systematic attempt for this subject, clearly overcomes the limitation of classical lot sizing method. The superstructure of the plant consists of the network of serially and/or parallelly interlinked processes and storages. A novel production and inventory analysis method, PSW(Periodic Square Wave) model, is applied. The objective function of optimization is minimizing the total cost composed of setup and inventory holding cost. The advantage of PSW model comes from the fact that the model provide a set of simple analytic solution in spite of realistic description of material flow between process and storage. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for the preliminary plant design confronting diverse economic situation.

• Journal of Korean Academy of Nursing
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• v.53 no.3
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• pp.309-323
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• 2023

Purpose: This study aimed to develop and test a model for posttraumatic growth among cured patients with COVID-19. This model was based on Calhoun and Tedeschi's Posttraumatic Growth model and a literature review. Methods: The participants comprised 223 patients cured from COVID-19 who were ≥ 19 years of age. The data were collected through an online questionnaire from March 21 to 24, 2022. The assessment tools included the Impact of Event Scale: Revised Korean version, the Connor-Davidson Resilience Scale, the Distress Disclosure Index, the Multidimensional Scale of Perceived Social Support, the Korean version of the Event-related Rumination Inventory, and the Korean version of the Post-traumatic Growth Inventory. Data were analyzed using the IBM SPSS version 24.0 and IBM AMOS 26.0. Results: The modified model showed appropriate goodness of fit (χ² = 369.90, χ² /degree of freedom = 2.09, SRMR = .09, RMESA = .07, CFI = .94, TLI = .93). The post-traumatic growth of cured patients with COVID-19 was explained through distress perception, self-disclosure, and deliberate rumination, with the explanatory power being 70.0%. Conclusion: This study suggests preparing a disaster psychology program involving experts who can activate deliberate rumination is necessary. Further, this study may serve as basic data for developing a program to enhance the post-traumatic growth of patients cured from COVID-19.

• Journal of Distribution Science
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• v.18 no.5
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• pp.89-98
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• 2020

Purpose: The growth of online commerce is now becoming a major threat and a new opportunity for retailers. Existing offline retailers struggle to cope with new online retailers' threats by utilizing offline infrastructure. Besides, online retailers expand their online strengths to offline sales by opening their offline stores. Many retailers are paying close attention to the O2O business and the resulting changes. Thus, this research focuses on the O2O business model and process that retailers can adopt. Research design, data and methodology: Considering the features of products that retailers sell, this paper divides O2O business process with the following criteria: delivery lead-time and delivery area. And This research uses the business model canvas to define the features of O2O commerce business process. This paper also uses nine key elements in the business model canvas for analyzing the structure of O2O commerce business. Results: This paper suggests the delivery model of retailers respond to offline customer orders and summarizes the following results. (1) Considering characteristics such as logistics process, delivery area, and product type, we define the features of O2O business models: wide-area (warehouse) based O2O business model, regional area (store) based O2O business model and time-separated O2O business model. (2) This study checks the availability of the business model through the business cases of O2O business models. (3) This study also analyzes the O2O business model of domestic retail companies by the factors defined in the business model canvas. Conclusions: Retailers can adopt the O2O business process to fit their business requirements and strategy. The online retailers who deal with normal consumer products mainly have the wide-area based O2O business model. The wide-area based O2O business model can be suitable for retailers who manage inventory centrally. The time-separated O2O business model can be a good solution for fresh food retailers to operate the logistics process efficiently. And to shorten the delivery lead-time of fresh foods, the regional area based O2O business model can be fit to the retailer that utilizes its offline logistics or sales infrastructure. It may be much more important for retailers to share the inventory information with other branches and to change the role of offline stores.