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. 43 No. 2 (2020년 6월) 16건
1.
2020.06
구독 인증기관 무료, 개인회원 유료
There are several methods of peak-shaving, which reduces grid power demand, electricity bought from electricity utility, through lowering “demand spike” during On-Peak period. An optimization method using linear programming is proposed, which can be used to perform peak-shaving of grid power demand for grid-connected PV+ system. Proposed peak shaving method is based on the forecast data for electricity load and photovoltaic power generation. Results from proposed method are compared with those from On-Off and Real Time methods which do not need forecast data. The results also compared to those from ideal case, an optimization method which use measured data for forecast data, that is, error-free forecast data. To see the effects of forecast error 36 error scenarios are developed, which consider error types of forecast, nMAE (normalizes Mean Absolute Error) for photovoltaic power forecast and MAPE (Mean Absolute Percentage Error) for load demand forecast. And the effects of forecast error are investigated including critical error scenarios which provide worse results compared to those of other scenarios. It is shown that proposed peak shaving method are much better than On-Off and Real Time methods under almost all the scenario of forecast error. And it is also shown that the results from our method are not so bad compared to the ideal case using error-free forecast.
4,500원
2.
2020.06
구독 인증기관 무료, 개인회원 유료
Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade’s biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.
4,200원
3.
2020.06
구독 인증기관 무료, 개인회원 유료
Data on patent and scientific paper is considered as a useful information source for analyzing technological information and has been widely utilized. Technology big data is analyzed in various ways to identify the latest technological trends and predict future promising technologies. Clustering is one of the ways to discover new features by creating groups from technology big data. Patent includes refined bibliographic information such as patent classification code whereas scientific paper does not have appropriate bibliographic information for clustering. This research proposes a new approach for clustering data of scientific paper by utilizing reference titles in each scientific paper. In this approach, the reference titles are considered as textual information because each reference consists of the title of the paper that represents the core content of the paper. We collected the scientific paper data, extracted the title of the reference, and conducted clustering by measuring the text-based similarity. The results from the proposed approach are compared with the results using existing methodologies that one is the approach utilizing textual information from titles and abstracts and the other one is a citation-based approach. The suggested approach in this paper shows statistically significant difference compared to the existing approaches and it shows better clustering performance. The proposed approach will be considered as a useful method for clustering scientific papers.
4,000원
4.
2020.06
구독 인증기관 무료, 개인회원 유료
Anomaly detection of Machine Learning such as PCA anomaly detection and CNN image classification has been focused on cross-sectional data. In this paper, two approaches has been suggested to apply ML techniques for identifying the failure time of big time series data. PCA anomaly detection to identify time rows as normal or abnormal was suggested by converting subjects identification problem to time domain. CNN image classification was suggested to identify the failure time by re-structuring of time series data, which computed the correlation matrix of one minute data and converted to tiff image format. Also, LASSO, one of feature selection methods, was applied to select the most affecting variables which could identify the failure status. For the empirical study, time series data was collected in seconds from a power generator of 214 components for 25 minutes including 20 minutes before the failure time. The failure time was predicted and detected 9 minutes 17 seconds before the failure time by PCA anomaly detection, but was not detected by the combination of LASSO and PCA because the target variable was binary variable which was assigned on the base of the failure time. CNN image classification with the train data of 10 normal status image and 5 failure status images detected just one minute before.
4,000원
5.
2020.06
구독 인증기관 무료, 개인회원 유료
Postural stability can reduce the likelihood of critical slip and fall accidents in workplaces. The present study aimed to analyze the effect of shoes type on the ability of postural control during quiet standing. The effect of workload on the body balance was also of primary concern. Thirteen healthy male undergraduate students participated voluntarily in the experimental study. Standing on a force plate with wearing slippers, sports shoes, or safety shoes, two-axis coordinate on subjects’ center of pressures (COP) was obtained in the two levels, rest and workload. For the workload level, subjects performed treadmill exercise to reach the predetermined level of physical workload. By converting the position coordinates of COPs, the postural sway length in both anterior-posterior (AP) axis and medio-lateral (ML) axis was assessed. ANOVA results showed that, in AP direction, wearing slippers significantly increased the postural sway length compared to wearing sports shoes or safety shoes. No significant difference in the mean sway length in AP axis was observed between sports shoes and safety shoes. In ML direction, both the workload and the shoes type did not significantly affect the mean length of postural sway. However, the postural sway length increased marginally with the slippers especially during the workload condition. This study explains wearing slippers may interfere with the ability of postural control during quiet standing. Physical workload decreases the ability of postural stability further.
4,000원
6.
2020.06
구독 인증기관 무료, 개인회원 유료
Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.
4,000원
7.
2020.06
구독 인증기관 무료, 개인회원 유료
This paper is a follow up to the previous study which reveals that smartphone users are divided into three subcategories according to their usage characteristics. In this paper, these groups are called as ‘general’, ‘entertainment’, and ‘work-assistant’, taking into account their respective characteristics. The ‘general’ is a group whose smartphone usage characteristics are not focused on a specific purpose, the ‘entertainment’ is focused on music, internet, SNS, picture, and e-banking, and the ‘work-assistant’ is on work, GPS, diary. Inter-relation between the importance and satisfaction for the purchase determinants to the groups is investigated. In addition, Kano analysis of quality attributes is also performed, which includes quality type, satisfaction/dissatisfaction index, and PCSI (Potential Customer Satisfaction Improvement) index. The analysis result are as follows. Firstly, inter-relation between importance and satisfaction differs by user group. ‘Internet’, ‘Ease of use’, and ‘Performance’ purchase determinants are evaluated as competitive determinants in ‘work-assistant’ user group. Secondly Kano quality types of quality characteristics also differs by user group. ‘Application’ was classified as an attractive (A) types to ‘entertainment’ group and so on. ‘Internet’ ‘Failure/Bug’, ‘Touch response rate’ and ‘Charging’ are located in ‘Nice’ Region of S-PCSI Diagram and have to be considered as strategic quality characteristics. The results of this study is expected to give some helps in establishing a customer tailored quality strategy.
4,000원
8.
2020.06
구독 인증기관 무료, 개인회원 유료
Worldwide plant market keeps maintaining steady growth rate and along with this trend, domestic plant market and its contractors also maintain such growing tendency. However, in spite of its external growth, win-win growth of domestic material industry that occupies the biggest share in plant industry cost portion is extremely marginal in reality. Domestic plant material suppliers are required to increase awareness of domestic material brand by securing quality and reliability of international standard through improvement of design quality superior to that of overseas material suppliers. Improvement of design quality of plant material becomes an essential element, not an option, for survival of domestic plant industry and its suppliers. Under this background, in this study, priority and importance by each evaluation index was analyzed by materializing plant design stage through survey of experts and defining evaluation index by each design stage and based on this analysis result, evaluation index of stage-gate based decision-making process that may improve design quality of plant material was suggested. It is considered that by utilizing evaluation index of stage-gate based decision-making process being suggested in this study, effective and efficient decision-making of project decision-makers would be enabled and it would be contributory to improve design quality of plant material.
4,000원
9.
2020.06
구독 인증기관 무료, 개인회원 유료
Demand for cosmetics with functionality and eco-friendliness has increased dramatically due to recent aging, well-being trends, and increased interest in beauty. Cosmetics production in 2014 was 8,970.4 billion won, an increase of about 50% compared to 6,014.6 billion won in 2010. In the midst of this, similar companies in intense competition are pursuing differentiated strategies and innovation activities to solve quality, price and delivery problems. In particular, cosmetics packaging work is getting more difficult due to the increasing bill of materials (BOM) and difficult assembly methods. Therefore, in this study, the following problems were identified and suggestions for the improvement of the packaging Many research laboratories such as biotechnology, chemistry, and pharmaceuticals, which are undergoing various studies, are equipped with ready-made laboratory safety equipments such as bio-safety workbenches, aseptic bases, and exhaust workbenches. However, most researchers are disadvantaged in using existing safety equipment. This is because existing safety equipment can not take into account all of the unique characteristics of the research. For this reason, researchers are demanding the development of customized safety equipment that is well suited to their research needs. process of Company C, which is facing difficult situation to respond to the customer 's delivery due to the 52 - hour work week. First, we used the stopwatch to find the difficulty process in the packaging process and show ways to improve it. Second, to improve the efficiency of line balancing in the packaging process, we integrate processes, improve work methods, and perform simple automation. As a result, the prepare loss for replacement was reduced by 1 minute from 5 minutes, resulting in a 23% increase in productivity from 112 ea./hour to 137ea./ hour per person. At this time, the LOB of the packaging process was improved from 70% to 82% by operating one more production line through one person per line, total 9 people saving.
4,000원
10.
2020.06
구독 인증기관 무료, 개인회원 유료
To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.
4,000원
11.
2020.06
구독 인증기관 무료, 개인회원 유료
The purpose of this study is to suggest the characteristics of online shopping malls and find a way to establish a differentiated marketing Strategy for online shopping malls in China. This study investigated the effect on the loyalty by applying the perceived shopping value (Hedonic Value, Utilitarian Value) of consumers in online shopping malls. In addition, In order to grasp the factors affecting consumer loyalty in online shopping malls, the characteristics of online shopping malls are multidimensional, consisting of product characteristics, recommended quality, benefit services, and community services. In order to obtain the purpose of the study, a questionnaire was surveyed for chinese online shopping experience and the research model was verified through empirical analysis method. Statistical analysis program was used together with SPSS 24.0 and AMOSS 24.0. Looking at the results of the analysis, firstly, the recommended quality and benefit service of online shopping malls are positive for the perceived hedonic value of consumers. The product characteristics and community service were found to have no effect on the hedonic shopping value. Secondly, the product characteristics, recommended quality, benefit service, and community service of online shopping malls on the utilitrian value perceived by consumers were positively affected. Thirdly, the perceived hedonic value has a positive effect on loyalty. Finally, it was confirmed that perceived utilitrian value affects loyalty. Based on the results of this study, a differentiated marketing strategy was established for existing chinese online shopping mall operators and potential new operators as well.
4,200원
12.
2020.06
구독 인증기관 무료, 개인회원 유료
What is purchase motivation for luxury brands? and what kind of process through makes higher cult intention(i.e.,loyalty). How does consumption value affect loyalty? Theoretically, it was studied whether it could be explained. The luxury products and services were divided into categories and surveys were conducted at the national level. This research analyzed the influence of positive affect on cult intention by mediating luxury consumption value with S-O-R frame. The logic was developed with excitation transfer theory. Positive affect, compatibility mediating effect were investigated. Unlike the previous studies that have been recognized as important in terms of symbolic value in luxury brands, it was confirmed that experiential consumption value had the greatest impact. In addition, the influence of functional value and symbolic value had a significant effect. The effect of consumption value on cult intention was mediated by positive affect and compatibility. Therefore, emotional response can be seen as having an effect on cult intention through excitement transfer. These findings suggest that luxury brand marketers need to develop consumer values that can lead to arousal and positive emotional responses to suit consumer lifestyle. The research results are expected to contribute to the experience marketing and the hospitality service of luxury brands.
4,300원
13.
2020.06
구독 인증기관 무료, 개인회원 유료
In order to provide priorities of the factors affecting the introduction of Smart Factory, This study reconstructed the factors and calculated the priorities through AHP (Analytic Hierarchy Process). The first layer of the hierarchy have 4 factors; productivity increase, brand image improve, marketing improve, cost reduction. The second layer of the hierarchy have 3 factors belong to the first layer, so the total number of second layer is 12. We divided the characteristics of enterprises into type of manager and age. The C.R. (consistency ratio) values of the respondents were found to be less than 0.1 and were judged to be a 'reasonable test'. As a result, the weights of the higher layer and the lower layer were obtained respectively, and then the weights of the higher layer and the weights of the lower layer were multiplied to obtain the total weights. Unlike previous studies that only surveyed factors that companies consider when introducing smart factory, (1) weighing and prioritizing factors were achieved. There are differences in priorities, (2) smart factory can be studied with the type of manager and firm age. When establishing policies, it is a practical implication (3) to assess its strategy not only for government officials but also for executives.
4,000원
14.
2020.06
구독 인증기관 무료, 개인회원 유료
Supply chain managers seek to achieve global optimization by solving problems in the supply chain's business process. However, companies in the supply chain hide the adverse information and inform only the beneficial information, so the information is distorted and cannot be the information that describes the entire supply chain. In this case, supply chain managers can directly collect and analyze supply chain activity data to find and manage the companies described by the data. Therefore, this study proposes a method to collect the order-inventory information from each company in the supply chain and detect the companies whose data characteristics are explained through deep learning. The supply chain consists of Manufacturer, Distributor, Wholesaler, Retailer, and training and testing data uses 600 weeks of time series inventory information. The purpose of the experiment is to improve the detection accuracy by adjusting the parameter values of the deep learning network, and the parameters for comparison are set by learning rate (lr = 0.001, 0.01, 0.1) and batch size (bs = 1, 5). Experimental results show that the detection accuracy is improved by adjusting the values of the parameters, but the values of the parameters depend on data and model characteristics.
4,000원
15.
2020.06
구독 인증기관 무료, 개인회원 유료
Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.
4,200원
16.
2020.06
구독 인증기관 무료, 개인회원 유료
Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.
4,000원
