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. 44 No. 2 (2021년 6월) 15건
1.
2021.06
구독 인증기관 무료, 개인회원 유료
It is highly challenging to measure the efficiency of electric vehicle charging stations (EVCSs) because factors affecting operational characteristics of EVCSs are time-varying in practice. For the efficiency measurement, environmental factors around the EVCSs can be considered because such factors affect charging behaviors of electric vehicle drivers, resulting in variations of accessibility and attractiveness for the EVCSs. Considering dynamics of the factors, this paper examines the technical efficiency of 622 electric vehicle charging stations in Seoul using data envelopment analysis (DEA). The DEA is formulated as a multi-period output-oriented constant return to scale model. Five inputs including floating population, number of nearby EVCSs, average distance of nearby EVCSs, traffic volume and traffic congestion are considered and the charging frequency of EVCSs is used as the output. The result of efficiency measurement shows that not many EVCSs has most of charging demand at certain periods of time, while the others are facing with anemic charging demand. Tobit regression analyses show that the traffic congestion negatively affects the efficiency of EVCSs, while the traffic volume and the number of nearby EVCSs are positive factors improving the efficiency around EVCSs. We draw some notable characteristics of efficient EVCSs by comparing means of the inputs related to the groups classified by K-means clustering algorithm. This analysis presents that efficient EVCSs can be generally characterized with the high number of nearby EVCSs and low level of the traffic congestion.
4,600원
2.
2021.06
구독 인증기관 무료, 개인회원 유료
Most of the open-source decision tree algorithms are based on three splitting criteria (Entropy, Gini Index, and Gain Ratio). Therefore, the advantages and disadvantages of these three popular algorithms need to be studied more thoroughly. Comparisons of the three algorithms were mainly performed with respect to the predictive performance. In this work, we conducted a comparative experiment on the splitting criteria of three decision trees, focusing on their interpretability. Depth, homogeneity, coverage, lift, and stability were used as indicators for measuring interpretability. To measure the stability of decision trees, we present a measure of the stability of the root node and the stability of the dominating rules based on a measure of the similarity of trees. Based on 10 data collected from UCI and Kaggle, we compare the interpretability of DT (Decision Tree) algorithms based on three splitting criteria. The results show that the GR (Gain Ratio) branch-based DT algorithm performs well in terms of lift and homogeneity, while the GINI (Gini Index) and ENT (Entropy) branch-based DT algorithms performs well in terms of coverage. With respect to stability, considering both the similarity of the dominating rule or the similarity of the root node, the DT algorithm according to the ENT splitting criterion shows the best results.
4,000원
3.
2021.06
구독 인증기관 무료, 개인회원 유료
Due to increasing awareness on the treatment of end-of-use/life products, disassembly has been a fast-growing research area of interest for many researchers over recent decades. This paper introduces a novel lot-sizing problem that has not been studied in the literature, which is the service-parts lot-sizing with disassembly option. The disassembly option implies that the demands of service parts can be fulfilled by newly manufactured parts, but also by disassembled parts. The disassembled parts are the ones recovered after the disassembly of end-of-use/life products. The objective of the considered problem is to maximize the total profit, i.e., the revenue of selling the service parts minus the total cost of the fixed setup, production, disassembly, inventory holding, and disposal over a planning horizon. This paper proves that the single-period version of the considered problem is NP-hard and suggests a heuristic by combining a simulated annealing algorithm and a linear-programming relaxation. Computational experiment results show that the heuristic generates near-optimal solutions within reasonable computation time, which implies that the heuristic is a viable optimization tool for the service parts inventory management. In addition, sensitivity analyses indicate that deciding an appropriate price of disassembled parts and an appropriate collection amount of EOLs are very important for sustainable service parts systems.
4,300원
4.
2021.06
구독 인증기관 무료, 개인회원 유료
This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.
4,000원
5.
2021.06
구독 인증기관 무료, 개인회원 유료
Smart factories can be defined as intelligent factories that produce products through IoT-based data. In order to build and operate a smart factory, various new technologies such as CPS, IoT, Big Data, and AI are to be introduced and utilized, while the implementation of a MES system that accurately and quickly collects equipment data and production performance is as important as those new technologies. First of all, it is very essential to build a smart factory appropriate to the current status of the company. In this study, what are the essential prerequisite factors for successfully implementing a smart factory was investigated. A case study has been carried out to illustrate the effect of implementing ERP and MES, and to examine the extensibilities into a smart factory. ERP and MES as an integrated manufacturing information system do not imply a smart factory, however, it has been confirmed that ERP and MES are necessary conditions among many factors for developing into a smart factory. Therefore, the stepwise implementation of intelligent MES through the expansion of MES function was suggested. An intelligent MES that is capable of making various decisions has been investigated as a prototyping system by applying data mining techniques and big data analysis. In the end, in order for small and medium enterprises to implement a low-cost, high-efficiency smart factory, the level and goal of the smart factory must be clearly defined, and the transition to ERP and MES-based intelligent factories could be a potential alternative.
4,800원
6.
2021.06
구독 인증기관 무료, 개인회원 유료
Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.
4,000원
7.
2021.06
구독 인증기관 무료, 개인회원 유료
Companies widely use survey to identify customer requirements, but the survey has some problems. First of all, the response is passive due to pre-designed questionnaire by companies which are the surveyor. Second, the surveyor needs to have good preliminary knowledge to improve the quality of the survey. On the other hand, text mining is an excellent way to compensate for the limitations of surveys. Recently, the importance of online review is steadily grown, and the enormous amount of text data has increased as Internet usage higher. Also, a technique to extract high-quality information from text data called Text Mining is improving. However, previous studies tend to focus on improving the accuracy of individual analytics techniques. This study proposes the methodology by combining several text mining techniques and has mainly three contributions. Firstly, able to extract information from text data without a preliminary design of the surveyor. Secondly, no need for prior knowledge to extract information. Lastly, this method provides quantitative sentiment score that can be used in decision-making.
4,300원
8.
2021.06
구독 인증기관 무료, 개인회원 유료
In addition to physical risks such as electrical, chemical, and mechanic ones in the workplace, psychosocial risks are also raising as an important issue in recent years in connection with human rights and work-life balance policies. The purpose of this study is to confirm the degree of effect of the psychosocial risk management plan at the workplace on workers through logistic regression analysis. Input data for logistic regression analysis is the results of a survey of 4,558 people conducted by the Institute for Occupational Safety and Health were used. There are 9 independent variables, including the change a workplace and confidential counseling, and the dependent variable is whether the worker feels the effect on the psychosocial risk management plan. As a result of this study, changes in work organization, dispute resolution procedures, provision of education program, notification of the impact of psychosocial risks on safety and health, and the persons in charge of solving psychosocial problems are shown effective in reducing worker’s psychosocial risks. This study drives which of the management plans implemented to reduce the psychosocial risk of workers in the workplace are effective, so it can contribute to the development of psychosocial risk management plans in the future.
4,000원
9.
2021.06
구독 인증기관 무료, 개인회원 유료
Ambient Air Vaporizer (AAV) is an essential facility in the process of generating natural gas that uses air in the atmosphere as a medium for heat exchange to vaporize liquid natural gas into gas-state gas. AAV is more economical and eco-friendly in that it uses less energy compared to the previously used Submerged vaporizer (SMV) and Open-rack vaporizer (ORV). However, AAV is not often applied to actual processes because it is heavily affected by external environments such as atmospheric temperature and humidity. With insufficient operational experience and facility operations that rely on the intuition of the operator, the actual operation of AAV is very inefficient. To address these challenges, this paper proposes an artificial intelligence-based model that can intelligent AAV operations based on operational big data. The proposed artificial intelligence model is used deep neural networks, and the superiority of the artificial intelligence model is verified through multiple regression analysis and comparison. In this paper, the proposed model simulates based on data collected from real-world processes and compared to existing data, showing a 48.8% decrease in power usage compared to previous data. The techniques proposed in this paper can be used to improve the energy efficiency of the current natural gas generation process, and can be applied to other processes in the future.
4,000원
10.
2021.06
구독 인증기관 무료, 개인회원 유료
The purpose of this study is to analyze the adequacy of production capacity of the assembly process system of mobile bath vehicle’s top box panel and process design through a simulation analysis. Towards this end, the layout of the facility designed with pre-verification job using a simulation modeling and an experiment, and facility, logistics process, and personnel input method were made into a simulation model, and the design system’s adequacy was evaluated through an experiment. To produce 120 mobile bath vehicles annually, it was analyzed that 14 general workers and seven skilled workers were adequate through the experiment. It was also identified that three painting process lines carried out through outsourcing were adequate. Production lead time was 201.7 hours on average and it was 230 hours maximum. To meet customer delivery service level of 95% within the deadline when establishing a customer order and vehicle delivery plan, it was analyzed that more than 215 hours of lead time is needed minimum. If the process cycle time is reduced to 85% upon system stabilization and skillfulness improvement, it was analyzed that annual output of 147 vehicles can be achieved without additional production line expansion.
4,000원
11.
2021.06
구독 인증기관 무료, 개인회원 유료
NDF (No Defect Found) is a phenomenon in which defects have been found in the manufacturing, operation and use of a product or facility, but phenomenon of defects is not reproduced in the subsequent investigation system or the cause of the defects cannot be identified. Recently, with the development of the fourth industrial revolution, convergence of hardware and software technologies in various fields is spreading to products such as aircraft, home appliances, and mobile devices, and the number of parts is increasing due to functional convergence. The application of such convergence technologies and the increase in the number of parts are major factors that lead to an increase in NDF phenomena. NDF phenomena have a significant negative impact on cost, reliability, and reliability for both manufacturers, service providers and operators. On the other hand, due to the nature of NDF phenomena such as difficult and intermittent cause identification and ambiguity in judgment, it is common to underestimate the cost of NDF or fail to take appropriate countermeasures in corporate management. Therefore, in this paper, we propose a methodology for estimating NDF costs by the PAF model which is a quality cost analysis model and ABC (Activity Based Costing) technique. The methodology of this study suggests a detailed procedure and the concept to accurately estimate the NDF costs, using ABC analysis, accounting system information, and IT system data. In addition case studies have validated the methodology. We think this could be a valid methodology to refer to when estimating the cost of other parts. And, it is meaningful to provide important judgment information in the decision-making process based on quality management and ultimately reduce NDF costs by visualizing them separately by major variable factors.
4,500원
12.
2021.06
구독 인증기관 무료, 개인회원 유료
A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.
4,000원
13.
2021.06
구독 인증기관 무료, 개인회원 유료
In the recent business environment, risks related to product safety problems are increasing. These are arising from various factors such as increasing product and production complexity, supply chain diversification, enhanced PL (product liability) law and strengthening regulations of the government. Accordingly, ISO (international organization for standardization) published standards of PSMS (product safety management system) for suppliers such as ISO 10377 and ISO 10393. Meanwhile, the ISO 9001 QMS (quality management system) was revised in 2015, and it has established itself as an effective tool that can consistently meet the various requirements of stakeholders and promote customer satisfaction. This study aims to suggest an integration framework of QMS and PSMS based on the recent ISO international standards. To this end, firstly, the relationship between QMS and PSMS is studied based on the quality and product safety definitions, PDCA (plan-do-check-act) cycle and risk-based thinking. Secondly, the requirements of ISO 10377 and ISO 9001 are compared and classified as the common and ISO 10377 specific requirements. Finally, integration steps of two systems are suggested and guidelines that can systemize the integrated requirements are presented in the aspect of processes and documentation. This study is expected to be used as a guideline that helps companies those have already acquired QMS certification to build an international-level product safety management system early.
4,000원
14.
2021.06
구독 인증기관 무료, 개인회원 유료
The purpose of this study is to investigate the effect of organizational safety and health management activities on safety and health performance by using the results of safety activity level evaluation of public organizations. To this end, a research model was established by using three fields as independent variables among the four areas of the safety activity level evaluation index: safety and health system, safety and health activity plan, and safety and health activity level, and the safety and health activity performance field as a dependent variable. Correlation analysis and regression analysis between major variables were performed. As a result of the correlation analysis, the safety and health activity performance had a significant positive (+) correlation with all of the safety and health system, safety and health activity plan, and safety and health activity level. The safety and health system had a significant positive (+) correlation with the safety and health activity plan and safety and health activity level, and the safety and health activity plan had a significant positive (+) correlation with the safety and health activity level. And as a result of the regression analysis, it was found that the organization’s safety and health system, safety and health activity plan, and safety and health activity level all had a significant positive (+) effect on safety and health activity performance.
4,000원
15.
2021.06
구독 인증기관 무료, 개인회원 유료
During the shift from gasoline vehicles to electric ones, auto parts manufacturing companies have realized the importance of improvement in the manufacturing process that does not require any layout changes nor extra investments, while maintaining their current production rate. Due to these reasons, for the auto part manufacturing company, I-company, this study has developed the simulation model of the PUSH system to conduct a process analysis in terms of production rate, WIP level, and logistics work’s utilization rate. In addition, this study compares the PUSH system with other three manufacturing systems -KANBAN, DBR, and CONWIP- to compare the performance of these production systems, while satisfying the company’s target production rate. With respect to lead-time, the simulation results show that the improvement of 77.90% for the KANBAN system, 40.39% for the CONWIP system, and 69.81% for the DBR system compared to the PUSH system. In addition, with respect to WIP level, the experimental results demonstrate that the improvement of 77.91% for the KANBAN system, 40.41% for the CONWIP system, and 69.82% for the DBR system compared to the PUSH system. Since the KANBAN system has the largest impacts on the reduction of the lead-time and WIP level compared to other production systems, this study recommends the KANBAN system as the proper manufacturing system of the target company. This study also shows that the proper size of moving units is four and the priority allocation of bottleneck process methods improves the target company’s WIP and lead-time. Based on the results of this study, the adoption of the KANBAN system will significantly improve the production process of the target company in terms of lead-time and WIP level.
4,500원
