• The Journal of Bigdata
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• v.2 no.1
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• pp.49-58
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• 2017

The inventory location is the mos important factor which decide the efficiency of picking orders. According to the inventory location, it is possible to optimize the route for picking order, and then it makes us to expect the cost reduction and efficiency improvement. However, it is practical situation to make decisions where to keep the products based on manager's intuition and experience, not based on the systematical or analytical approach. In this research, with the practical order data of cropper product and layout for the storage yard, the association rules have found, and then the new methodology has been devised to make the decision where to keep the inventory. By utilizing the practical order data for a year, it has been proved that the proposed approach can reduce the total distance of the all routes for picking order and solve the problem of delayed delivery.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.3
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• pp.1-16
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• 2008

This paper considers a scheduling problem to minimize the total tardiness in the two-stage assembly-type flowshop. The system is composed of multiple fabrication machines in the first stage and a final-assembly machine in the second stage. Each job consists of multiple tasks, each task is performed on the fabrication machine specified in advance. After all the tasks of a job are finished, the assembly task can be started on the final-assembly machine. The completion time of a job is the time that the assembly task for the job is completed. The objective of this paper is to find the optimal schedule minimizing the total tardiness of a group of jobs. In the problem analysis, we first derive three solution properties to determine the sequence between two consecutive jobs. Moreover, two lower objective bounds are derived and tested along with the derived properties within a branch-and-bound scheme. Two efficient heuristic algorithms are also developed. The overall performances of the proposed properties, branch-and-bound and heuristic algorithms are evaluated through numerical experiments.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.427-431
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• 2002

Nowadays in Korea, there has been extreme competition due to market reduction in the domestic construction industry. As a result every company try to change rapidly to secure competitive power, Although it isn't betterment for the way of construction project management then there has many problem such as a delay of the appointed date of delivery and go over the budget. In this study, we suggest an introduction of CCPM which is based on TOC to construction projects.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.131-142
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• 2014

Phone camera lens module is assembled with a barrel, multiple lenses, multiple spacers and a shield. The major processes of manufacturing system are injection molding, coating and assembly processes, and each process has multiple machines. In this paper, we introduce a scheduler based on simulation model which can be used for frequent rescheduling problem caused by urgent orders, breaking down of molds and failures of machines. The scheduling algorithm uses heuristic Backward-Forward method, and the objective is to minimize the number of tardy orders.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of KIISE
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• v.45 no.3
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• pp.242-250
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• 2018

For high-quality software development, it is necessary to detect and fix the defects inserted. If defect management activities are not properly performed, it will lead to the project delay and project failure due to rework. Therefore, organizations need to establish defect management process and institutionalize it. Process standard models handle defect management in the area of project monitoring and control. However, small organizations experience difficulties in implementing and applying defect management process in a real situation. In this paper, we propose a defect management process for small organization which is designed in accordance with the characteristics of a small projects such as few participants and short development period. The proposed defect management process will be based on a tool chain with open source software such as Redmine, Subversion, Maven, Jenkins that support a defect management process and SW Visualization in systematic way. We also proposed a way of constructing defect database and various methods of analyzing and controlling defect data based on it. In an effort to prove the effectiveness of the proposed process, we applied the process and tool chain to a small organization.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.181-192
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• 2010

We develop a dispatching policy for stochastic scheduling simulation especially for a continuous manufacturing system with machine breakdowns. The proposed dispatching policy computes an urgency index with the consideration of re-heating, setup cost and remaining due date. Prioritized by the index, we execute swapping or reassigning material sequences so as to minimize the total penalty cost. To evaluate the performance of the proposed policy, a discrete event simulation is developed. With 200 data sets and 20 iterations, we compare the performance of the urgency policy with those of SPT (Shortest Processing Time) and FCFS (First Come First Serve) which are the most common policies. The result shows that the proposed policy consistently gives the lowest total costs by reducing the penalty costs for lateness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.33-40
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• 2019

This study focuses on a job-shop scheduling problem with the objective of minimizing total tardiness for the job orders that have different due dates and different process flows. We suggest the dispatching rule based scheduling algorithm to generate fast and efficient schedule. First, we show the delay schedule can be optimal for total tardiness measure in some cases. Based on this observation, we expand search space for selecting the job operation to explore the delay schedules. That means, not only all job operations waiting for process but also job operations not arrived at the machine yet are considered to be scheduled when a machine is available and it is need decision for the next operation to be processed. Assuming each job operation is assigned to the available machine, the expected total tardiness is estimated, and the job operation with the minimum expected total tardiness is selected to be processed in the machine. If this job is being processed in the other machine, then machine should wait until the job arrives at the machine. Simulation experiments are carried out to test the suggested algorithm and compare with the results of other well-known dispatching rules such as EDD, ATC and COVERT, etc. Results show that the proposed algorithm, MET, works better in terms of total tardiness of orders than existing rules without increasing the number of tardy jobs.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.1-11
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• 2023

Smart factory environments and digital twin environments are established, and today's factories accumulate vast amounts of production data and are managed in real time as visualized results suitable for user convenience. Production simulation techniques are in the spotlight as a way to prevent delays in delivery and predict factory volatility in situations where production schedule planning becomes difficult due to the diversification of production products. With the development of the digital twin environment, new packages are developed and functions of existing packages are updated, making it difficult for users to make decisions on which packages to use to develop simulations. Therefore, in this study, the concept of Discrete Event Simulation (DES) performed based on discrete events is defined, and the characteristics of various simulation packages were compared and analyzed. To this end, studies that solved real problems using discrete event simulation software for 10 years were analyzed, and three types of software used by the majority were identified. In addition, each package was classified by simulation technique, type of industry, subject of simulation, country of use, etc., and analysis results on the characteristics and usage of DES software were provided. The results of this study provide a basis for selection to companies and users who have difficulty in selecting discrete event simulation package in the future, and it is judged that they will be used as basic data.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.41-59
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• 2022

The timely procurement of military supplies is essential to maintain the military's operational capabilities, and contract work is the first step toward timely procurement. In addition, rapid signing of a contract enables consumers to set a leisurely delivery date and increases the possibility of budget execution, so it is essential to improve the contract process to prevent early execution of the budget and transfer or disuse. Recently, research using big data has been actively conducted in various fields, and process analysis using big data and process mining, an improvement technique, are also widely used in the private sector. However, the analysis of contract work in the military is limited to the level of individual analysis such as identifying the cause of each problem case of budget transfer and disuse contracts using the experience and fragmentary information of the person in charge. In order to improve the contract process, this study analyzed using the process mining technique with data on a total of 560 contract tasks directly contracted by the Department of Finance of the Air Force Logistics Command for about one year from November 2019. Process maps were derived by synthesizing distributed data, and process flow, execution time analysis, bottleneck analysis, and additional detailed analysis were conducted. As a result of the analysis, it was found that review/modification occurred repeatedly after request in a number of contracts. Repeated reviews/modifications have a significant impact on the delay in the number of days to complete the cost calculation, which has also been clearly revealed through bottleneck visualization. Review/modification occurs in more than 60% of the top 5 departments with many contract requests, and it usually occurs in the first half of the year when requests are concentrated, which means that a thorough review is required before requesting contracts from the required departments. In addition, the contract work of the Department of Finance was carried out in accordance with the procedures according to laws and regulations, but it was found that it was necessary to adjust the order of some tasks. This study is the first case of using process mining for the analysis of contract work in the military. Based on this, if further research is conducted to apply process mining to various tasks in the military, it is expected that the efficiency of various tasks can be derived.