• 대한산업공학회지
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• 제4권2호
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• pp.91-96
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• 1978

A modeling framework and its computational methodology for an industrial sector of the economy are investigated. The suggested industrial sector model is characterized by a programming (process analysis) representation of a production sector and an econometric estimation of the price sensitive (own and cross-prices) demands. By introducing the price sensitive demands into the process analysis representation of the production sector, it becomes possible to analyze and plan the pricing policy, the optimal production schedules and capacity expansion plans within a single framework. The computational scheme suggested in the report is based on the iterative approach each of which solves a separable convex programming problem.

• 산업경영시스템학회지
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• 제37권3호
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• pp.16-23
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• 2014

Most of metal cutting and processing companies are going through the difficulties such as frequent downtime and high failure rates by missing times to replace parts of CNC equipment. The reason is that the correct operation times of expensive CNC equipment can't be calculated. In this paper, to solve this problem, we try to construct the intelligent production information system for a case company and analyze its expected effects. The effects are as follows. First, it saves money about 3 million won each year during the useful life of three years by reducing downtime and failure rates, and increasing production rates etc. Second, it makes easily find and fix the cause of faulty through traceability of the production process, and enables to perform a systematic facility management through the calculation of reliable equipment's overall efficiency. This case can be easily applied in similar industries, and will contribute greatly to enhancing the competitiveness of related industries.

• 대한산업공학회지
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• 제40권3호
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

• Nuclear Engineering and Technology
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• 제42권5호
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• pp.600-607
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• 2010

Rhenium-186, having a half-life of 90.64 h, is an important radionuclide, used in metabolic radiotherapy and radio immunotherapy. $^{186}Re$ hydroxyethylidene diphosphonate (HEDP) is a new compound used for the palliation of painful skeletal metastases. Its production is achieved via charged-particle-induced reactions; the data are available in EXFOR library. For the work discussed in this paper, production of $^{186}Re$ was done via $^{nat}W(p,n)^{186}Re$ nuclear reaction. Pellets of $^{nat}W$ were used as targets and were irradiated with 15, 17.5, 20, 22.5, 25 MeV proton beams at 5 ${\mu}A$ current. The radiochemical separation was performed by the ion exchange chromatography method. The production yield achieved at 25 MeV was 1.91 $MBq{\cdot}{\mu}A^{-1}{\cdot}h^{-1}$. Excitation functions for the $^{186}Re$ radionuclide, via $^{186}W(p,n)^{186}Re$ and $^{186}W(d,2n)^{186}Re$ reactions were calculated by ALICE-ASH and TALYS-1.0 codes to validate and fit the experimental data and to obtain a recommended set of data for $^{186}W(p,n)^{186}Re$ reaction. Required thickness of the targets was obtained by SRIM code for each reaction.

• 대한안전경영과학회지
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• 제19권2호
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• pp.107-115
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• 2017

As the industrial society develops, the management of the production line becomes more and more important. There are also diversifying Management methods by industry. In addition, National Competency Standards (NCS) have also been developed. As a result, It has been created standards for each job and provide education and training standards for industrial production management tasks. Customer satisfaction is an ever-growing concern of management throughout the world. In addition, Colleges are focusing on vocational education. Because of the opening of the education market, They are competing in various ways. And, To survive in this competition. They are making great efforts to improve the lecture satisfaction. If education is regarded as an industry, it can be classified as a representative service industry. Because it is formed as a perfect competition between colleges. And then in this paper, This will focus on the mechanical production Manager duties of industrial engineering department related NCS. This study also conducted empirical studies to analyze factors affecting the curriculum using the KANO analysis.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.

• 농촌계획
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• 제10권1호
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• pp.41-55
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• 2004

The purpose of this study is to investigate a causal relationship between the mode of production and change of rural society. While dominant theories of social change have stressed variation of contingencies and periodical contexts, this theoretical paper drives a new insight paralleling diverse theoretical arguments of each mode of production with rural and urban changes. Investigating the drifts of intellectual ideologies of the mode of production, we get through diverse paradigm shifts of the production accumulation and its trigger effects on rural change. More specifically, the present study investigates change of rural society by way of investigating such fluctuations of societal changes as ancient society, slavery society, feudal society, industrial society, post-industrial society, and information society. We find that transportation and communication technologies have had a key role in the changes, however, the effects of the technologies on social changes have been different between rural- and urban-society. While we take it for granted that flexible accumulation in post-industrial society and time-space compression and informatization in information society will reduce developmental gap between rural- and urban-society, we also found that there have been big differences of actual application of the technologies between theory and reality in each era of mode of production.

• 대한안전경영과학회지
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• 제25권2호
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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.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2018년도 추계학술대회
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• pp.204-204
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• 2018

• 산업공학
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• 제16권3호
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• pp.280-290
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• 2003

Many firms are trying to optimize their production and distribution functions separately, but possible savings by this approach may be limited. Nowadays, it is more important to analyze these two functions simultaneously by trading off the costs associated with the whole. In this paper, I treat a production and distribution planning problem for single-period inventory products comprised of a single production facility and multiple customers, with the aim of optimally coordinating important and interrelated decisions of production sequencing and vehicle routing. Then, I propose a hybrid genetic algorithm incorporating several local optimization techniques, HGAP, for integrated production-distribution planning. Computational results on test problems show that HGAP is effective and generates substantial cost savings over Hurter and Buer's decoupled planning approach in which vehicle routing is first developed and a production sequence is consequently derived. Especially, HGAP performs better on the problems where customers are dispersed with multi-item demand than on the problems where customers are divided into several zones based on single-item demand.