• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.50 no.7
• /
• pp.303-308
• /
• 2001

This paper presents algorithm to plan construction and expanding of substation considering contingency accidents by proposing utilization factor according to configuration of substation bank system. In this paper, firstly, proper sphere of supply area by each district which could be standardized with respect to its supply capacity is established under assumption of long term load forecasting. Secondly, goal of utilization ratio based on configuration of substation bank was set to keep reliability by remaining sound bank when it happen to one bank accidents. Finally, it is set up for optimal construction and expanding of substation considering economy and reliability simultaneously about substation to exceed these ratio. To verify proposed algorithm, at first, after adopting a part of Kangnam area in Seoul as area for testing, it is divided into several regions for this area according to power branches of power utility. Secondly, by deriving correlation factor between load demand and economic indicators in these region respectively, the regional load forecasting was performed with economic growth and city plan scenario. Finally, based on the predicted load demand by region and land use data which is identified from air-photographic, the load demand by district was predicted. Also, planning for substation considering contingency is formulated to expand taking into account computing utilization factor which is based on configuration of substation bank respectively.

• The Journal of Information Systems
• /
• v.30 no.1
• /
• pp.151-177
• /
• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• IE interfaces
• /
• v.13 no.3
• /
• pp.378-387
• /
• 2000

As the globalization of manufacturing companies continues, the scope of dependence between these companies and distributors, and other suppliers are growing very rapidly since no one company manufactures or distributes the whole product by themselves. And, the need to increase the efficiency of the whole supply chain is increasing. This paper deals with a multi-plant lot-sizing problem(MPLSP) which happens in a decentralized manufacturing system of a supply chain. In this study, we assume that the whole supply chain is driven by a single source of independent demand and many levels of dependent demands among manufacturing systems in the supply chain. We consider setup cost, transportation cost and time, and inventory holding cost as a decision factor in the MPLSP. The MPLSP is decomposed into two sub-problems: a planning problem of the whole supply chain and a lot-sizing problem of each manufacturing system. The supply chain planning problem becomes a pure linear programming problem and a Generalized Goal Decomposition method is used to solve the problem. Its result is used as a goal of the lot-sizing problem. The lot-sizing problem is solved using the CPLEX package, and then the coefficients of the planning problem are updated reflecting the lot-sizing solution. This procedure is repeated until termination criteria are met. The whole solution process is similar to Lagrangian relaxation method in the sense that the solutions are approaching the optimum in a recursive manner. Through experiments, the proposed closed-loop hierarchical planning and traditional hierarchical planning are compared to optimal solution, and it is shown that the proposed method is a very viable alternative for solving production planning problems of decentralized manufacturing systems and in other areas.

• IE interfaces
• /
• v.16 no.4
• /
• pp.441-449
• /
• 2003

In this paper we propose a distribution planning method aiming the use in the real-life situations. The assumed form of the distribution network is arborescence. At every node in the distribution network, orders are placed periodically. At each renewal of planning horizon, demand informations of periods in the horizon are updated. The objective of the problem is to minimize the total cost, which is the sum of holding and backorder costs of all sites during planning horizon. For such a situation, this study addressed an effective distribution plan when demands for demand-sites are provided for a given planning horizon.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.116-116
• /
• 2020

Gilgit-Baltistan (GB) is a highly mountainous and remote region covering 45% of Upper Indus Basin (UIB) with around 1.8 million population is vulnerable to climate change and socio-economic growth makes water resources management and planning more complex. To understand the water scarcity in the region this study is carried out to project water supply and demand for agricultural and domestic sector under various climate-socio-economic scenarios in five sub catchments of GB i.e., Astore, Gilgit, Hunza, Shigar and Shyok for a period of 2015 to 2050 using Water Evaluation and Planning (WEAP) model. For climate change scenario ensembled mean of three global climate models (GCMs) was used under three different Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP6.0 and RCP8.5). The Shared Socioeconomic Pathways (SSPs) and agricultural Land Development (LD) scenarios were combined with climate scenarios to develop climate-socio-economic scenario. Our results indicate that the climate change and socio-economic growth would create a gap between supply and demand of water in the region, with socio-economic growth (e.g. agricultural and population) as dominant external factor that would reduce food production and increase poverty level in the region. Among five catchments only Astore and Gilgit will face shortfall of water while Shyoke would face shortfall of water only under agricultural growth scenarios. We also observed that the shortfall of water in response to climate-socio-economic scenarios is totally different over two water deficient catchments due to its demography and geography. Finally, to help policy makers in developing regional water resources and management policies we classified five sub catchments of UIB according to its water deficiency level.

• IE interfaces
• /
• v.16 no.3
• /
• pp.280-290
• /
• 2003

Many firms are trying to optimize their production and distribution functions separately, but possible savings by this approach may be limited. Nowadays, it is more important to analyze these two functions simultaneously by trading off the costs associated with the whole. In this paper, I treat a production and distribution planning problem for single-period inventory products comprised of a single production facility and multiple customers, with the aim of optimally coordinating important and interrelated decisions of production sequencing and vehicle routing. Then, I propose a hybrid genetic algorithm incorporating several local optimization techniques, HGAP, for integrated production-distribution planning. Computational results on test problems show that HGAP is effective and generates substantial cost savings over Hurter and Buer's decoupled planning approach in which vehicle routing is first developed and a production sequence is consequently derived. Especially, HGAP performs better on the problems where customers are dispersed with multi-item demand than on the problems where customers are divided into several zones based on single-item demand.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.546-549
• /
• 1995

Recently, electric utility is facing substantially new stream of business environment, such as pressure of business restructuring, competition with private IPPs, diversification of supply-side and demand-side resource options, environmental externalities and uncertainties. Integrated resource planning(IRP) is very useful and powerful approach for solving complex and diversified electricity supply and demand problems. This paper presents a standardized IRP procedure using multi-attribute decision analysis approach. The selection of the most desirable plan is based on multi-attribute trade-off/risk analysis method and score ranking method. As a case study, 50 plans with 12 scenarios are analyzed.

• Journal of Korean Society of Rural Planning
• /
• v.25 no.4
• /
• pp.1-11
• /
• 2019

This study conducted a survey on the recognition and demand such as recognition level, policy necessity, service demand and policy demand by supply types in order to provide the basic data for successful settlement of agro-healing services. According to the survey on awareness, 45.2% of respondents were aware of the healing farming, and 31.3% of respondents had experience in participating in the agro-healing services. 63.6% of respondents replied that they were experiencing reasons for participating in agro-healing services. Respondents who had no knowledge of agro-healing services responded that 76.7% of respondents said they would not participate. More than two-thirds of respondents in all types indicated that they needed agro-healing services. As a result of evaluating the maximum willingness to pay, there was a willingness to pay for farm work healing about 15,800 won, horticulture healing about 14,800 won, forest healing about 13,400 won, and animal assisted healing about 17,000 won. Improving accessibility and strengthening awareness were high priorities for inconveniences and improvements. 70.1% of the respondents said that policies for agro-healing services are needed. Development of agro-healing programs and contents was the first priority for support policy. The result of this study is expected to provide reference data that can be suggested for agro-healing policy establishment.

• Journal of Korean Society of Rural Planning
• /
• v.14 no.2
• /
• pp.33-42
• /
• 2008

Recently, rural leisure by urban dwellers has been recognized as a catalyst for regional development or restoration. The federal government implemented several regional planning policies attempting to address this phenomenon in the late nineties. However, most of these policies focused on supply-centered planning, which caused a diverse set of problems relating to the sustainability and economic validity of the planning. Instead, this study focuses on the re-visitation one of the demand variables, with the intention of analyzing the character of rural leisure demand and its re-visitation choice attributes. For these reasons, this study investigates the character of current rural leisure demand, and develops functional equations about urban people who visit rural areas, using logit model. The results of this study can be summarized as follow: Urban people are visiting rural areas from nearby cities or metropolitan areas that are within 3 hours driving distance, and over 80% of rural visitors are one-day visitors. Therefore, most of their visitation activities should be understood as rural leisure, including rural tourism. In addition, the likelihood of the rural tourist to make a return visit is influenced by their transportation means, product purchasing, staying period and travel time. The results of such rural leisure demand can provide information for regional planning strategies, such as selection of target market, type of market segments, improvement of recognition level, activity program price, facility and space planning, produce sale and connection with tour site.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.38 no.2
• /
• pp.43-63
• /
• 2013

Remanufacturing is a process of recovering end-of-life products into serviceable parts for producing new products. Due to the limited supply of recovery cores to remanufacture, a remanufacturing firm also needs to produce or procure new parts for fulfilling the demand. This paper is targeted for solving the problem of determining the optimal amount of newly produced and remanufacturing parts, which is called production and remanufacturing planning (PRP) problem, under uncertain supply of recovery cores. The new production mitigates the risk of insufficient core supply while it takes more costs than the remanufacturing. The PRP model in this paper also considers disassemble-to-order (DTO) environment, in which multiple kinds of parts are remanufactured from multiple products on order of the parts. Whereas existing studies presents only heuristic solutions for DTO remanufacturing, this paper provides an exact solution for this problem and analytical sensitivity of the involved cost parameters, adopting multi-dimensional newsvendor modeling and stochastic linear programming techniques. The result shows that production and remanufacturing plans for multiple products are mutually dependent, and a change of cost parameters involved in only one part is propagated to all other parts.