• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.133-141
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• 2020

Up to date cosmetic OEM/ODM (original equipment manufacturing/original development manufacturing) industry receives attention as a future growth engine due to steady growth. However, because of limited research and development capability, many companies have employed commercial management platforms specialized for large-sized companies; thus, overall system effectiveness and efficiency is low. Especially, MRP (material requirement planning) system introduced originally in 1970s is employed to calculate the requirement of the parts. However, dynamic nature of production lead time usually results in incorrect requirements. In addition, its algorithm does not consider the capability of the production resources. Also, because the commercial MRP system calculates all subcomponent for fixed period, the more goods have subcomponent, the slower calculation is. Therefore, conventional MRP system cannot respond complicated situation in time. In this study, we will suggest a new method that can respond to complicated situations resulting from short lead time and urgent production order in Korean cosmetic market. In particular, a distributed MRP system is proposed, that consists of multi-functional and operational modules, based on the characteristic of the BOM (bill of material). The distributed MRP system divides components (i.e. products and parts) into several fields and decrease the problem size; thus, we can respond to dynamically changed data any time. Through this solution, we can order components quickly, adjust schedules and planned quantity, and manage stocks reasonably. In addition, a prototype of the distributed MRP system is presented in this paper, in which ERP (enterprise resource planning) sever data is associated with an excel spreadsheet via MSsql. System user interface is implemented by a VBA (visual basic for applications) tool. According to a case study, response rate for delivery and planning achievement rate were enhanced about 20%, and inventory turnover was also decreased. Consequently, the proposed system improves overall profit.

• Journal of Industrial Technology
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• v.19
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• pp.301-312
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• 1999

The purpose of this paper is to study the effects of container size with multi-stage and multi-item on average inventory and customer service level in Kanban systems. We use the different distributions of demand and interarrival time for each item to show that we had better to change the container size depending on different type of item for this simulation study. The small lot size can be used for container size of a single item if there is no setup time. The container size should be identical with average order size as setup time increases. The fill rate increases if the container size is large with multi-item. However, it is difficult to establish the effective container size because the effects of the container size on the order queue time are not clear. It is suitable to use the average order size as the container size for each item if the variance of demand and interarrival time of each item is relatively small. It is effective to sue the average container size if the variance of them is relatively large.

• Industrial Engineering and Management Systems
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• v.11 no.3
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• pp.288-298
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• 2012

Lot sizing and shipment scheduling are two interrelated decisions made by a manufacturing plant and a third-party logistics distribution center. This paper analyzes a dynamic inbound ordering problem and shipment problem with a freight container cost, in which the order size of multiple products and single container type are simultaneously considered. In the problem, each ordered product placed in a period is immediately shipped by some freight containers in the period, and the total freight cost is proportional to the number of containers employed. It is assumed that the load size of each product is equal and backlogging is not allowed. The objective of this study is to simultaneously determine the lot-sizes and the shipment schedule that minimize the total costs, which consist of production cost, inventory holding cost, and freight cost. Because the problem is NP-hard, we propose three meta-heuristic algorithms: a simulated annealing algorithm, a genetic algorithm, and a new population-based evolutionary meta-heuristic called self-evolution algorithm. The performance of the meta-heuristic algorithms is compared with a local search heuristic proposed by the previous paper in terms of the average deviation from the optimal solution in small size problems and the average deviation from the best one among the replications of the meta-heuristic algorithms in large size problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.153-161
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• 2016

Semiconductor manufacturing has suffered from the complex process behavior of the technology oriented control in the production line. While the technological processes are in charge of the quality and the yield of the product, the operational management is also critical for the productivity of the manufacturing line. The fabrication line in the semiconductor manufacturing is considered as the most complex part because of various kinds of the equipment, re-entrant process routing and various product devices. The efficiency and the productivity of the fabrication line may give a significant impact on the subsequent processes such as the probe line, the assembly line and final test line. In the management of the re-entrant process such as semiconductor fabrication, it is important to keep balanced fabrication line. The Performance measures in the fabrication line are throughput, cycle time, inventory, shortage, etc. In the fabrication, throughput and cycle time are the conflicting performance measures. It is very difficult to achieve two conflicting goal simultaneously in the manufacturing line. The capacity of equipment is important factor in the production planning and scheduling. The production planning consideration of capacity can make the scheduling more realistic. In this paper, an input and scheduling rule are to achieve the balanced operation in semiconductor fabrication line through equipment capacity and workload are proposed and evaluated. New backward projection and scheduling rule consideration of facility capacity are suggested. Scheduling wafers on the appropriate facilities are controlled by available capacity, which are determined by the workload in terms of the meet the production target.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.1157-1163
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• 2012

This study was performed a comparative life cycle assessment (LCA) among three rice production systems in order to analyze the difference of greenhouse gases (GHGs) emissions and environment impacts. Its life cycle inventory (LCI) database (DB) was established using data obtained from interview with conventional, without agricultural chemical and organic farming at Gunsan and Iksan, Jeonbuk province in 2011. According to the result of LCI analysis, $CO_2$ was mostly emitted from fertilizer production process and rice cropping phase. $CH_4$ and $N_2O$ were almost emitted from rice cultivation phase. The value of carbon footprint to produce 1 kg rice (unhulled) on conventional rice production system was 1.01E+00 kg $CO_2$-eq. $kg^{-1}$ and it was the highest value among three rice production systems. The value of carbon footprints on without agricultural chemical and organic rice production systems were 5.37E-01 $CO_2$-eq. $kg^{-1}$ and 6.58E-01 $CO_2$-eq. $kg^{-1}$, respectively. Without agricultural chemical rice production system whose input amount was the smallest had the lowest value of carbon footprint. Although the yield of rice from organic farming was the lowest, its value of carbon footprint less than that of conventional farming. Because there is no compound fertilizer inputs in organic farming. Compound fertilizer production and methane emission during rice cultivation were the main factor to GHGs emission in conventional and without agricultural chemical rice production systems. In organic rice production system, the main factors to GHGs emission were using fossil fuel on machine operation and methane emission from rice paddy field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.130-139
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• 2016

The purpose of this paper is to analyze the problems and the sources of defective products and draw improvement plans in a small plastic boat manufacturing process using TOC (Theory Of Constraints) and statistical analysis. TOC is a methodology to present a scheme for optimization of production process by finding the CCR (Capacity Constraints Resource) in the organization or the all production process through the concentration improvement activity. In this paper, we found and reformed constraints and bottlenecks in plastic boat manufacturing process in the target company for less defect ratio and production cost by applying DBR (Drum, Buffer, Rope) scheduling. And we set the threshold values for the critical process variables using statistical analysis. The result can be summarized as follows. First, CCRs in inventory control, material mix, and oven setting were found and solutions were suggested by applying DBR method. Second, the logical thinking process was utilized to find core conflict factors and draw solutions. Third, to specify the solution plan, experiment data were statistically analyzed. Data were collected from the daily journal addressing the details of 96 products such as temperature, humidity, duration and temperature of heating process, rotation speed, duration time of cooling, and the temperature of removal process. Basic statistics and logistic regression analysis were conducted with the defection as the dependent variable. Finally, critical values for major processes were proposed based on the analysis. This paper has a practical importance in contribution to the quality level of the target company through theoretical approach, TOC, and statistical analysis. However, limited number of data might depreciate the significance of the analysis and therefore it will be interesting further research direction to specify the significant manufacturing conditions across different products and processes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.113-127
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• 2021

Topic modeling has been receiving much attention in academic disciplines in recent years. Topic modeling is one of the applications in machine learning and natural language processing. It is a statistical modeling procedure to discover topics in the collection of documents. Recently, there have been many attempts to find out topics in diverse fields of academic research. Although the first Department of Industrial Engineering (I.E.) was established in Hanyang university in 1958, Korean Institute of Industrial Engineers (KIIE) which is truly the most academic society was first founded to contribute to research for I.E. and promote industrial techniques in 1974. Korean Society of Industrial and Systems Engineering (KSIE) was established four years later. However, the research topics for KSIE journal have not been deeply examined up until now. Using topic modeling algorithms, we cautiously aim to detect the research topics of KSIE journal for the first half of the society history, from 1978 to 1999. We made use of titles and abstracts in research papers to find out topics in KSIE journal by conducting four algorithms, LSA, HDP, LDA, and LDA Mallet. Topic analysis results obtained by the algorithms were compared. We tried to show the whole procedure of topic analysis in detail for further practical use in future. We employed visualization techniques by using analysis result obtained from LDA. As a result of thorough analysis of topic modeling, eight major research topics were discovered including Production/Logistics/Inventory, Reliability, Quality, Probability/Statistics, Management Engineering/Industry, Engineering Economy, Human Factor/Safety/Computer/Information Technology, and Heuristics/Optimization.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.162-168
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• 2010

Information is known to be a key element for the successful operation of a supply chain, which is required of the efficient ordering strategies and accurate predictions of demands. This study proposes a method to effectively utilize the meteorological forecast information in order to make decisions about ordering and prediction of demands by using the Taguchi experimental design. It is supposed that each echelon in a supply chain determines the order quantity with the prediction of precipitation in the next day based on probability forecast information. The precipitation event is predicted when the probability of the precipitation exceeds a chosen threshold. Accordingly, the choice of the threshold affect the performances of a supply chain. The Taguchi method is adopted to deduce a set of thresholds for echelons which is least sensitive to changes in environmental conditions, such as variability of demand distributions and production periods. A simulation of the beer distribution game was conducted to show that the set of thresholds found by the Taguchi method can reduce the cumulative chain cost, which consists of inventory and backlog costs.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.2
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• pp.237-241
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• 2010

Many policies have been implemented to mitigate the greenhouse gases in atmosphere overall of sectors. With considering the distinct characteristics of the food security, agricultural sector is no exception to this situation. To this regard, total amount of carbon which is emitted through all of the agricultural production process is calculated, and being based on this result, the demand for the introduction of agricultural production system with low carbon has been rising. Case studies on the application of life cycle assessment (LCA) technique to agricultural sector are found in many countries. For example, life cycle inventory (LCI) data bases of crop, farm infrastructure, fertilizer, farm machinery, and etc., have been constructed and provided by Ecoinvent (Swiss centre for life cycle inventories) of Swiss. In Japan, Top-down typed LCA methodology for agriculture is developed based on the inter-industry analysis, and is evaluated according to the productive method of crop. On the other hand, environmental impact assessment of agricultural system using LCA in Korea is just in the beginning stages. So it is required to assess environmental impact on agricultural fertilizer and pesticide, and to develop their flow modeling, and methodology of LCA of agricultural sector. Environmental impact assessment on agricultural materials, machinery, and infrastructure will also be carried out.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.131-145
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• 2010

The framework for making a coordinated decision for large-scale facilities has become an important issue in supply chain(SC) management research. The competitive business environment requires companies to continuously search for the ways to achieve high efficiency and lower operational costs. In the areas of production/distribution planning, many researchers and practitioners have developedand evaluated the deterministic models to coordinate important and interrelated logistic decisions such as capacity management, inventory allocation, and vehicle routing. They initially have investigated the various process of SC separately and later become more interested in such problems encompassing the whole SC system. The accurate quotation of ATP(Available-To-Promise) plays a very important role in enhancing customer satisfaction and fill rate maximization. The complexity for intelligent manufacturing system, which includes all the linkages among procurement, production, and distribution, makes the accurate quotation of ATP be a quite difficult job. In addition to, many researchers assumed ATP model with integer time. However, in industry practices, integer times are very rare and the model developed using integer times is therefore approximating the real system. Various alternative models for an ATP system with time lags have been developed and evaluated. In most cases, these models have assumed that the time lags are integer multiples of a unit time grid. However, integer time lags are very rare in practices, and therefore models developed using integer time lags only approximate real systems. The differences occurring by this approximation frequently result in significant accuracy degradations. To introduce the ATP model with time lags, we first introduce the dynamic production function. Hackman and Leachman's dynamic production function in initiated research directly related to the topic of this paper. They propose a modeling framework for a system with non-integer time lags and show how to apply the framework to a variety of systems including continues time series, manufacturing resource planning and critical path method. Their formulation requires no additional variables or constraints and is capable of representing real world systems more accurately. Previously, to cope with non-integer time lags, they usually model a concerned system either by rounding lags to the nearest integers or by subdividing the time grid to make the lags become integer multiples of the grid. But each approach has a critical weakness: the first approach underestimates, potentially leading to infeasibilities or overestimates lead times, potentially resulting in excessive work-inprocesses. The second approach drastically inflates the problem size. We consider an optimized ATP system with non-integer time lag in supply chain management. We focus on a worldwide headquarter, distribution centers, and manufacturing facilities are globally networked. We develop a mixed integer programming(MIP) model for ATP process, which has the definition of required data flow. The illustrative ATP module shows the proposed system is largely affected inSCM. The system we are concerned is composed of a multiple production facility with multiple products, multiple distribution centers and multiple customers. For the system, we consider an ATP scheduling and capacity allocationproblem. In this study, we proposed the model for the ATP system in SCM using the dynamic production function considering the non-integer time lags. The model is developed under the framework suitable for the non-integer lags and, therefore, is more accurate than the models we usually encounter. We developed intelligent ATP System for this model using genetic algorithm. We focus on a capacitated production planning and capacity allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using an evolutionary system to solve it efficiently. This method makes it possible for the population to reach the approximate solution easily. Moreover, we designed and utilized a representation scheme that allows the proposed models to represent real variables. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solutions converge to the optimum quickly.