• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.77-88
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• 2021

The development history of China's big data is relatively short, and it has only been ten years so far. Although the application level of big data in real life is not high, some achievements have been made in the supply chain. Various kinds of data will be generated in the actual operation of the supply chain. If these data can be effectively classified and used, the "bullwhip effect" of the operation of the supply chain can be also effectively improved. Thus this paper proposes the development of a supply chain collaborative inventory management model and application framework using big data. In this study, we analyzed the supply chain of beer industry, which is the most prominent consumption industry with "bullwhip effect", and further established a big data collaborative inventory management model for the supply chain of beer industry based on system dynamics. We used the Vensim software for simulation and sensitivity test and after appling our model, we found that the inventory fluctuations of the participants in the beer industry supply chain became significantly smaller, which verified the effectiveness of the model. Our study can be also applied to the possible problems of the large data supply chain collaborative inventory management model, and gives certain countermeasures and suggestions.

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.479-489
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• 1992

A mathematical model for a long range water supply planning is develoted as a dynamic capacitated facility location problem, in which operation costs and two types of fixed costs are considered. The fixed costs are for water supply systems such as dams and reservoirs and for water conveyance systems of waterways or conduits from each water supply points. A Spreadsheet model is developed to support the efficiency of user interface and to implement a heuristic solution procedure. The proposed solution procedure utilizes SOLVER tool and it has been applied to a system with fictitious data but with reality and applicability in mind. As a result of the mathematical analysis, not only the most economic construction timings of surface water supply facilities and distribution systems but also the most economical water supply operating patterns are identified.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.3
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• pp.224-240
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• 2004

Supply chain management(SCM) has been recognized as a major strategy in today's market place. A growing number of researchers have begun to realize the strategic importance of model construction, planning, controlling and operation for SCM. Also various researches of supply chain model building are going on. In this paper, we synthesis key elements of supply chain model such as performance factors, decision variables and constraints. We have reviewed past and present supply chain models and then analyzed those in view of environment factors, operations, solution approaches.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.69-84
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• 2011

In this study, based on the principal-agent paradigm, we investigate a joint cost reduction activity in a buyer-supplier supply chain where a buyer motivates its operations department and a supplier to reduce the supply chain's production cost. We construct a benefit-sharing model based on the target cost scheme, a basic philosophy in practice which has not been explored in previous studies. The model also incorporates various supply chain issues such as the cooperation of multiple agents, the opportunity loss, and the degree of strategic relationship between the buyer and the supplier. Based on the analysis of the principal-agent model, we investigate the benefit-sharing rule to control agents' actions, and we also provide important managerial implications into supply chain practices via extensive comparative static analyses.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.6
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• pp.588-598
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• 2015

In this paper, a simulation model for assessing the impact of alternative field service engineer replenishment policies is introduced. The end-to-end supply chain simulation model is created using a discrete-event and agent-based simulation model, which enables accurate description of key individual entities in the investigated supply chain, such as field service engineers. Once the model is validated with the historical data, it is used to assess the impacts of field service engineer replenishment policies for a major printing equipment manufacturing firm.In the case study, newly proposed replenishment policies for post-sale distribution supply chain are assessed for the level of service improvement to end customers.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.3-15
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• 2022

In this study, we develop a simulation model for Supply Chain Management (SCM) of modular construction based steel bridge. To this end, first, Factory Production/Site Construction system data for the steel bridge construction were collected, and supply chain, entities, resources, processes were defined based on the collected data. After that, a steel bridge supply chain simulation model was developed by creating data, flowchart, and animation modules using Arena software. Finally, verification and validation of the model were performed by using animation check, extreme condition check, average value test, Little' s law test, and actual case value test. As a result, the developed simulation model appropriately expressed the processes and characteristics of the steel bridge supply chain without any logical errors, and provided accurate performance evaluation values for the target system. In the future, we expect that the model will faithfully play a role as a performance evaluation platform in developing management techniques for optimally operating the steel bridge supply chain.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.5
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• pp.421-430
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• 2017

In this study, a model was developed to predict for Disinfection By-Products (DBPs) generated in water supply networks and consumer premises, before and after the introduction of advanced water purification facilities. Based on two-way ANOVA, which was carried out to statistically verify the water quality difference in the water supply network according to introduce the advanced water treatment process. The water quality before and after advanced water purification was shown to have a statistically significant difference. A multiple regression model was developed to predict the concentration of DBPs in consumer premises before and after the introduction of advanced water purification facilities. The prediction model developed for the concentration of DBPs accurately simulated the actual measurements, as its coefficients of correlation with the actual measurements were all 0.88 or higher. In addition, the prediction for the period not used in the model development to verify the developed model also showed coefficients of correlation with the actual measurements of 0.96 or higher. As the prediction model developed in this study has an advantage in that the variables that compose the model are relatively simple when compared with those of models developed in previous studies, it is considered highly usable for further study and field application. The methodology proposed in this study and the study findings can be used to meet the level of consumer requirement related to DBPs and to analyze and set the service level when establishing a master plan for development of water supply, and a water supply facility asset management plan.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.3
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• pp.281-290
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• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.54-69
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• 2012

Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.

• The Journal of Fisheries Business Administration
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• v.47 no.4
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• pp.65-75
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• 2016

The purpose of this study was to analyze the production and marketing control effects of aqua-cultured flounder required for stable income growth of aqua-cultured household. We analyzed the supply and demand structure of cultured flounder using the partial equilibrium model approach. And we estimated the optimal yield of cultured flounder and analyzed the effect of marketing control through constructed model. The main results of this study are summarized as follows. First, the fitness and predictive power of the estimated model showed that the RMSPE and MAPE values were less than 5% and Theil's inequality coefficient was very close to 0 rather than 1. It was evaluated that the prediction ability of the aqua-cultured flounder supply and demand model by dynamic simulation was excellent. Second, dynamic simulation based on policy simulation was conducted to analyze the price increase effect of production and shipment control of cultured flounder. As a result, if the annual production volume is reduced by 1%, 5%, and 10% among 32,852~37,520 tons, it is analyzed that the price increase effect is from 1.2% to 12.5%. Finally, this study suggests that the production and marketing control can increase the price of aqua-cultured flounder in the market. In this paper, we propose a policy implementation of the total supply system instead of conclusions.