• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.1-10
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• 1998

Process planning is a very complex task and requires the dynamic informatioon of shop foor and market situations. Process plan selection is one of the main problems in the process planning. In this paper, we propose a new process plan selection model considering operation flexibility for the computer aided process planing. The model is formulated as a 0-1 integer programming considering realistic shop factors such as production volume, machining time, machine capacity, transportation time and capacity of tractors such as production volume, machining time, machine capacity, transportation time capacity of transfer device. The objective of the model is to minimize the sum of the processing and transportation time for all parts. A genetic algorithm a, pp.oach is developed to solve the model. The efficiency of the proposed a, pp.oach is verified with numerical examples.

• Journal of the Korea Safety Management & Science
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• v.7 no.2
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• pp.41-56
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• 2005

A study is for the approach that we could reduce the logistics costs through uprising the efficiency, complying to the demand in time, stock management based on the general production plan in the point of SCM. We will take following steps to get the goal. First, we will overview the physical distribution expenses annually. Second, will find the main cause of optimal load loss by improper container and lack of delivery flexibility to the demand. Third, the goal will be inferred through the fast information share based on organic relationship, the establishment of general production plan, the improvement of stock management plan. By way of this process, it can be accomplished expense reduction as well as flexible establishment of the reduction of worker's load.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.103-106
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• 2007

Recently, production and application of ortho image using high resolution image are increasing by acquired high quality data from development of photogrammetry and IT technology. Generally, An ortho image has some problems that cannot remove completely to relief displacement about cultural feature like building and overpass because of performance rectification using DEM. Therefore, in this study, I generated DSM each of four experiment cases for production of true ortho image which is removed relief displacement of building using digital photogrammetry technique and LiDAR data, presented the plan of DSM production that is appropriate to production true ortho image by analyzing an accuracy after manufacture an ortho image each of DSM.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.424-427
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• 2014

In this paper, we consider a production system in which the items are produced by batch. For a production planning of the system, we formulate a lot-sizing problem in which each production should be a multiple of a given unit batch and backlogging is allowed. We propose an optimal dynamic programming algorithm for the plan whose complexity is $O(T^2)$ where T is the maximum number of periods in a plan.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.157-158
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• 2021

Recently, there have been a growing number of cases using precast concrete construction methods to efficiently carry out construction projects. In order to efficiently carry out PC construction, it is necessary to establish a production plan of PC components that effectively reflect various design alternatives during the initial design stage. Because the production plan of PC components is based on productivity of PC members, the use of PC production simulations that can effectively predict productivity for design alternatives is necessary. Therefore, this paper propose a method to efficiently generate design alternatives which is necessary to perform to production simulations using parametric modeling techniques and BIM.

• Journal of Korean Society for Quality Management
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• v.42 no.3
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• pp.311-324
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• 2014

Purpose: It can deduce improvement plan that recognizes any risk factors in initial production and mass production by using FMEA and through this process, the appropriate criteria for defence items can be established. Methods: It proposes two methodology - Apply DT/OT data achieved from the beginning mass production stage based on FMECA data of the design stage, to risk management, and risk management plan that reflected line and field faliure data in case of is offered. Results: It proposes the risk management plan through Bayesian method and the risk identification that considered MTTF estimated value in case of initial production process. In case of mass production process, both risk identification by using fault occurrence frequency scores and Byaesian method, In case of the Initial production and mass production, it proposes use both two methods. Conclusion: A more realistic risk identification method can be applied, and by this method the quality improvement effect is expected.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.97-103
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• 1987

Skip-Lot sampling plan is formulated in terms of renewal process. This approach facilitates studying the average outgoing quality in a short production run of length t, AOQ (t). By numerical studies it is found that the long-run average outgoing quality (AOQ) greatly overestimates AOQ (t) for short runs.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.167-175
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• 2020

The net income per unit area from crop production could be the most critical consideration for agricultural producers during cultivation planning. This paper proposes a scheme for predicting the net income per unit area based on machine learning and related calculations. This scheme predicts rice production and operation costs by applying climate and price index data. The rice price is also predicted by applying rice production and operation cost data. Finally, these predicted results are employed to calculate the predicted net income, which is compared with the actual net income. Consequently, the proposed scheme shows a meaningful degree of conformity, which indicates the potential of machine learning for predicting various aspects of agricultural production.

• IE interfaces
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• v.23 no.1
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• pp.12-23
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• 2010

A semiconductor market is one of the most competitive markets in the world. To survive this competition, important targets for production planning are on-time delivery and profit maximization. In our research, we modify the linear programming model for the current production planning by adding new objective functions that maximize the profit. In addition, we propose a production planning process that gives a priority to new products, reflecting daily fluctuations in demand to weekly production planning. We validate our model with real data sets obtained from a major company semiconductor manufacturer and performed the paired t-test to verify the results. The results showed that our model forecasted profit and loss with 93.2% accuracy and improved the due date satisfaction by 10%.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.3
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• pp.275-286
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• 2015

In this paper, we propose a practical method for setting up a daily production plan which can operate semiconductor fabrication factories more stably and linearly by determining work in process (WIP) targets and movement targets. We first adjust cycle times of the operations to satisfy the monthly production plan. Second, work in process (WIP) targets are determined to control the production progress of operations: earliness and tardiness. Third, movement targets are determined to reduce cumulated differences between WIP targets and actual WIPs. Finally, the determined movement targets are modified through a simulation model which considers capacities of the equipments and allocations of the WIPs in the fab. The proposed daily production planning method can be easily adapted to the memory semiconductor fabs because the method is very simple and has straightforward logics. Although the proposed method is simple and straightforward, the power of the method is very strong. Results from the shop floor in past few periods showed that the proposed methodology gives a good performance with respect to the productivity, workload balance, and machine utilization. We can expect that the proposed daily production planning method will be used as a useful tool for operating semiconductor fabrication factories more efficiently and effectively.