간행물
한국산업경영시스템학회지 KCI 등재 Journal of Society of Korea Industrial and Systems Engineering
- 발행기관 한국산업경영시스템학회
- 자료유형 학술지
- 간기 계간
- ISSN 2005-0461 (Print)2287-7975 (Online)
- 수록기간 1978 ~ 2024
- 주제분류 공학 > 산업공학 공학 분류의 다른 간행물
- 십진분류KDC 530DDC 620
권호리스트/논문검색
Vol. 40 No. 4 (2017년 12월) 30건
21.
2017.12
구독 인증기관 무료, 개인회원 유료
This paper proposes a dynamic magnetic field emulator (DMFE), which can electrically emulate information for the magnetic stripes of most widely used credit cards. Payment transactions with most common credit cards are performed by reading the card’s information, encoded in magnetic stripes, using the reader head of a point-of-sale (POS) system. A stripe-type permanent magnet is attached to the back side of the credit card, and information for payments or value-added service is reorganized by exposing it to strong magnetic field. The process of data recording and retrieving as stated above has been pointed out as a major cause of illegal credit card use, because the information on the magnetic stripe is always exposed, and is thus vulnerable to forgery or alteration. A dynamic magnetic field emulator displays card information only when necessary by using the principle of solenoidal magnets. The DMFE proposed in this paper can prevent fraudulent use if it is operated with a device, like a smart phone, or a separate user-authentication procedure. In addition, because it is possible to display various information as needed, it can be utilized for a smart multi-card application, in which information for multiple cards is stored in one card, and can be selected and used as needed. This paper introduces the necessity of the DMFE and its manufacturing principles. As a result, this study will be helpful for making various application cases in payment, which is a core area of the Fintech (a newly-coined word of finance and technology) industry.
4,000원
22.
2017.12
구독 인증기관 무료, 개인회원 유료
Competency Modeling Using AHP Methodology and Improvement of National Technical Qualification System
The purpose of this study is to develop an engineer competency model using Analytical Hierarchy Process (AHP) to improve the national technical qualification system. Korea has managed technical human resources at the government level through the operation of a national technical qualification system that certifies engineers with national certificates or technical grades by laws. However, there have been increasing concerns that the government system is separated from global standards and does not reflect an engineer’s comprehensive capabilities. For these reasons, the new architecture of the system has been continuously discussed and becomes a major policy issue of the Korean government. For the development of the engineer competency model, domestic and global models were separately structured using 554 valid questionnaires with a consistency ratio (CR) of 0.1 or less. The relative importance of engineer competency factors in a domestic model was career (0.383), qualification (0.253), academic degree (0.195), and job training (0.169) whereas the order in the global model was career (0.308), global ability (0.237), job training (0.175), domestic qualification (0.147), and academic degree (0.134). The results of AHP analysis indicated that the evaluation factors and methods recognized by engineers were different from a current government model focusing on domestic qualifications. There was also perceptual difference in the importance of engineer evaluation factors between groups depending on the type of organizations and markets. This means that it is necessary to reflect the characteristics of organizations and markets when evaluating engineer competency. Based on AHP analysis and literature reviews, this paper discussed how to develop a new engineer competency index (ECI) and presented two effective index models verified by simulation test using 59,721 engineers’ information. Lastly, the paper discussed major findings of our empirical research and proposed policy alternatives for the improvement of a national engineer qualification system. The paper contributes to the management of technical human resources since it provides quantitative competency models that are objectively developed by reflecting market recognition and can be effectively used by the policy makers or firms.
4,300원
23.
2017.12
구독 인증기관 무료, 개인회원 유료
Data clustering is one of the most difficult and challenging problems and can be formally considered as a particular kind of NP-hard grouping problems. The K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, it has high possibility to trap in local optimum and high variation of solutions with different initials for the large data set. Therefore, we need study efficient computational intelligence method to find the global optimal solution in data clustering problem within limited computational time. The objective of this paper is to propose a combined artificial bee colony (CABC) with K-means for initialization and finalization to find optimal solution that is effective on data clustering optimization problem. The artificial bee colony (ABC) is an algorithm motivated by the intelligent behavior exhibited by honeybees when searching for food. The performance of ABC is better than or similar to other population-based algorithms with the added advantage of employing fewer control parameters. Our proposed CABC method is able to provide near optimal solution within reasonable time to balance the converged and diversified searches. In this paper, the experiment and analysis of clustering problems demonstrate that CABC is a competitive approach comparing to previous partitioning approaches in satisfactory results with respect to solution quality. We validate the performance of CABC using Iris, Wine, Glass, Vowel, and Cloud UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KABCK (K-means+ABC+K-means) is better than ABCK (ABC+K-means), KABC (K-means+ABC), ABC, and K-means in our simulations.
4,000원
24.
2017.12
구독 인증기관 무료, 개인회원 유료
The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.
4,000원
25.
2017.12
구독 인증기관 무료, 개인회원 유료
In the international businesses human resource elements acquired in different countries might have different values in varied industries due to the different quality of education and experiences in the original countries. Using selection models to evaluate expected values in earnings equation of human resource elements such as education and experiences etc. acquired in sending countries, system equations are expanded to examine also the values of science and engineering degrees in technology jobs with selectivity bias correction. This paper used the US census survey data of 2015 on earnings, academic degrees, occupations etc. The US has long maintained the policy of accepting more STEM workers than any other countries and helped maintaining own technological leadership. Assuming per capita GDP gap between the sending country and the US downgrades immigrant human resource quality, it rarely affects occupational selection but depresses earnings on average by two or more years’ worth of education. Immigrant quality index in the sense of GDP gap appears to be a valid tool to assess the expected earnings of the worker with. Engineering degrees increase significantly the probability of selecting not only engineering jobs but also general management jobs, as well as increasing the expected earning additionally over nine years’worth of education. Getting a technology job is additionally worth about four years of education. Economics and business degrees are worth additionally almost six years of education but humanities degrees depress expected earnings. Since years after immigration does not very fast enhance earnings capacity, education level and English language ability might be more useful criteria to expect better future earnings by.
4,000원
26.
2017.12
구독 인증기관 무료, 개인회원 유료
The recent domestic construction market is in a difficult situation due to reduction of the government's SOC budget and new orders from public-sector, and the deterioration of housing supply situation in the private sector etc. In addition, the number of disasters in the construction industry has increased in recent years with 26,570 people (up 5.7% from the previous year) in 2016, unlike other industries that are in a declining trend. As such, the construction industry has unique characteristics and problems such as high industrial accidents rate, abnormal subcontracting structure, excessive working hours and work intensity. As a result, the construction workers have a lot of job stresses. Job stress has been recognized as one of the major causes of industrial accidents and many researches have been conducted on that. However, most of the researches were about the factors that induce job stress and how these factors affect disaster occurrence, job satisfaction, job performance, turnover intentions, and job exhaustion. The purpose of this study is to investigate the effect of positive psychological capital on job stress, which is emerging as a new human resources development paradigm useful in corporate management in order to find ways to reduce job stress. To do this, 347 data collected from construction workers in Daejeon, Sejong, and Chungcheong provinces were analyzed using statistical package(IBM SPSS 22) for basic statistical analysis, reliability analysis, and regression analysis. As a result, positive psychological capital has shown an alleviate effect on job stress. In particular, the higher the optimism, hope, and resiliency of positive psychological capital, the lower the job stress. However, the higher the self - efficacy, the higher the job stress.
4,000원
27.
2017.12
구독 인증기관 무료, 개인회원 유료
Our research is aimed at predicting recent trend and leading technology for the future and providing optimal Nano technology trend information by analyzing Nano technology trend. Under recent global market situation, Users’ needs and the technology to meet these needs are changing in real time. At this point, Nano technology also needs measures to reduce cost and enhance efficiency in order not to fall behind the times. Therefore, research like trend analysis which uses search data to satisfy both aspects is required. This research consists of four steps. We collect data and select keywords in step 1, detect trends based on frequency and create visualization in step 2, and perform analysis using data mining in step 3. This research can be used to look for changes of trend from three perspectives. This research conducted analysis on changes of trend in terms of major classification, Nano technology of 30’s, and key words which consist of relevant Nano technology. Second, it is possible to provide real-time information. Trend analysis using search data can provide information depending on the continuously changing market situation due to the real-time information which search data includes. Third, through comparative analysis it is possible to establish a useful corporate policy and strategy by apprehending the trend of the United States which has relatively advanced Nano technology. Therefore, trend analysis using search data like this research can suggest proper direction of policy which respond to market change in a real time, can be used as reference material, and can help reduce cost.
4,000원
28.
2017.12
구독 인증기관 무료, 개인회원 유료
In the defense acquisition, a company’s goal is to maximize profits, and the government’s goal is to allocate budgets efficiently. Each year, the government estimates the ratio of indirect cost sector to defense companies, and estimates the ratio to be applied when calculating cost of the defense articles next year. The defense industry environment is changing rapidly, due to the increasing trend of defense acquisition budgets, the advancement of weapon systems, the effects of the 4th industrial revolution, and so on. As a result, the cost structure of defense companies is being diversifying. The purpose of this study is to find an alternative that can enhance the rationality of the current methodology for estimating the ratio of indirect cost sector of defense companies. To do this, we conducted data analysis using the R language on the cost data of defense companies over the past six years in the Defense Integrated Cost System. First, cluster analysis was conducted on the cost characteristics of defense companies. Then, we conducted a regression analysis of the relationship between direct and indirect costs for each cluster to see how much it reflects the cost structure of defense companies in direct labor cost-based indirect cost rate estimates. Lastly a new ratio prediction model based on regularized regression analysis was developed, applied to each cluster, and analyzed to compare performance with existing prediction models. According to the results of the study, it is necessary to estimate the indirect cost ratio based on the cost character group of defense companies, and the direct labor cost based indirect cost ratio estimation partially reflects the cost structure of defense companies. In addition, the current indirect cost ratio prediction method has a larger error than the new model.
4,000원
29.
2017.12
구독 인증기관 무료, 개인회원 유료
Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity , ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.
4,000원
30.
2017.12
구독 인증기관 무료, 개인회원 유료
Quantum-inspired Genetic Algorithm (QGA) is a probabilistic search optimization method combined quantum computation and genetic algorithm. In QGA, the chromosomes are encoded by qubits and are updated by quantum rotation gates, which can achieve a genetic search. Asset-based weapon target assignment (WTA) problem can be described as an optimization problem in which the defenders assign the weapons to hostile targets in order to maximize the value of a group of surviving assets threatened by the targets. It has already been proven that the WTA problem is NP-complete. In this study, we propose a QGA and a hybrid-QGA to solve an asset-based WTA problem. In the proposed QGA, a set of probabilistic superposition of qubits are coded and collapsed into a target number. Q-gate updating strategy is also used for search guidance. The hybrid-QGA is generated by incorporating both the random search capability of QGA and the evolution capability of genetic algorithm (GA). To observe the performance of each algorithm, we construct three synthetic WTA problems and check how each algorithm works on them. Simulation results show that all of the algorithm have good quality of solutions. Since the difference among mean resulting value is within 2%, we run the nonparametric pairwise Wilcoxon rank sum test for testing the equality of the means among the results. The Wilcoxon test reveals that GA has better quality than the others. In contrast, the simulation results indicate that hybrid-QGA and QGA is much faster than GA for the production of the same number of generations.
4,000원
1
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