• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.33-46
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• 2000

The problem of scheduling n independent jobs on serial stages with identical parallel machines at each stage is considered. Each job lot is allocated evenly to all machines at each stage for processing and moved in transfer batches between states., This scheduling strategy is called an identical production pattern. The objective is to find a permutation schedule that minimizes makespan. A branch and bound algorithm is suggested to find an optimal permutation schedule for a transformed problem A number examples is presented to illustrate the branch and bound algorithm, Computational results for 640 problems generated randomly show that within a resonable time the suggested algorithm can be used for transfer batch scheduling in a flexible flowshop.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.1-16
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• 1997

This paper improves the autonomy for supplier's schedule and the flexibility of the final assembly line. The final assembly line is a single work station and each product taking different assembly time is considered. In the assembly schedule, the heuristic method based on the goal chasing method is used. Consequently, suppliers can independently determine their output rates and thus, change their workload pattern according to their needs and priorities. Moreover, this flexibility can help to avoid expensive final-assembly-line stoppages in case of sudden part supply disruptions. The sequencing method can be easily implemented into an existing just-in-time system. In addition, the mathematical model was formulated and the algorithm was explained through the flow chart. The numerical example was given and the efficiency of this method is shown through the analysis of computational results of that example.

• IE interfaces
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• v.13 no.2
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• pp.246-252
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• 2000

As moulds and dies are manufactured through complex processes under the make-to-order production environment, it is very difficult that the manufacturing activities as like observance of the due date, trace of the progress, etc are controlled with a real time. In this paper, a schedule-planning system using the commercial software Microsoft Project 98 is developed to control the procedures of mould and die manufacturing with real time. Once an initial schedule is planned from the BOM information in the intranet, it is rescheduled by data collected from machines on the shop floor. The system is suitable to medium- or small-sized manufacturing companies as well as large-sized ones, because it can be installed with a low cost.

• IE interfaces
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• v.7 no.3
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• pp.171-180
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• 1994

Defined is a Multi-level Parallel Machine Flow-Shop (MPMFS) which reflects some real world manufacturing situations. Just-In-Time (JIT) philosophy is applied to the MPMFS scheduling in order to achieve lowering work-in-process inventory level as well as meeting due dates. A schedule generating simulator is developed. The latest start time of each operation is determined by a backward simulation followed by another forward simulation to analyze the schedule feasibility and actual inventory level. Reasonable schedules are available through adjusting some parameters for allowance factors such as set-up times of machines and other environmental changes. The SLAMSYSTEM under Window is employed for this processing with some input/output data handling processes devised under DOS.

• IE interfaces
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• v.18 no.1
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• pp.35-43
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• 2005

A production system in domestic shoes companies has difficulty in achieving automation and information because of insufficiency of flexibility and standardization. Particularly small and medium sized shoes companies producing by OEM have tendency to chase the given production schedule blindly without considering major factors that may affect the production. Therefore, the production schedules or the process conditions can not be optimally set and are extemporized by the experience in the past. These behaviors cause low productivity and financial loss. To maximize efficiency and productivity of the shoe-making process, we develop a simulation model based on a production system in small and medium sized shoes companies. The model has been developed using ARENA which has been demonstrated to be a powerful tool to simulate various manufacturing systems. Using the simulation model, we find out several problems for the production process, and then suggest several alternatives to improve the system.

• The Journal of Information Systems
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• v.26 no.2
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• pp.143-164
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• 2017

Purpose The purpose of this study is to investigate to investigate the effects of cloud system on the efficiency improvement and cost-saving of production processes. It also tries to provide small- and medium-sized companies and IT practitioners with a practical guideline for a successful implementation of could systems. Design/methodology/approach This study was conducted by observing and analyzing a case of implementing a cloud system at a small-sized company having multiple job sites in terms of the improvement in data-sharing efficiency and cost-saving of production processes. Findings This study found that cloud system was an effective way of sharing data between and among production processes of geographically scattered job sites and thus, helped the company to remedy problems of work schedule and load-balance along sequential production processes. Cloud system also allowed the company to reduce the number of visits made by 3-inspectors to four job sites by 75% and the personnel cost related to inspectors' site visit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.159-165
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• 2023

The entire industry is increasing the use of big data analysis using artificial intelligence technology due to the Fourth Industrial Revolution. The value of big data is increasing, and the same is true of the production technology. However, small and medium -sized manufacturers with small size are difficult to use for work due to lack of data management ability, and it is difficult to enter smart factories. Therefore, to help small and medium -sized manufacturing companies use big data, we will predict the gross production time through machine learning. In previous studies, machine learning was conducted as a time and quantity factor for production, and the excellence of the ExtraTree Algorithm was confirmed by predicting gross product time. In this study, the worker's proficiency factors were added to the time and quantity factors necessary for production, and the prediction rate of LightGBM Algorithm knowing was the highest. The results of the study will help to enhance the company's competitiveness and enhance the competitiveness of the company by identifying the possibility of data utilization of the MES system and supporting systematic production schedule management.

• 한국해양학회지
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• v.11 no.2
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• pp.57-63
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• 1976

It was attempted to analyze the sensitivity of the oil prospect place named MARIA which placed inside Gulf of Alaska. For the analysis, P6031090, ECOANA( computer) which installed in the head office, Shell Oil Co was used and the data needed for computer programming were 1) Unit of Production data 2) Production Schedule 3) Total Gross Yearly Expenses and 4) Total Gross Capital and so on. The important data among the computer output 1) PVPAT (Present Value After Tax): $1,167,077,500 2) Payout After Tax: 3.14 Years (256,284,810 BBL Production) 3) Earning Power: 42% (After Tax) 4) PVPAT/BBL : $1.22 5) Capital/BBL : $2.00. On the other hand, the effect acted upon PVPAT with varying the Platform cost, Facility cost, Pipeline cost and Well cost was observed in comparion with the basic for range from 50% to 200%. Resultantly, the order was 1) Pipeline cost 2) Facility cost 3) Well cost 4) Platform cost for range form 100% to 200%. This project was completed by the contract with Shell Oil Co., and the geological data needed for this analysis were given by the head office and the development project started from Jan. 1976.