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 ~ 2026
- 주제분류 공학 > 산업공학 공학 분류의 다른 간행물
- 십진분류KDC 530DDC 620
권호리스트/논문검색
Vol.49 No.1 (2026년 3월) 11건
1.
2026.03
구독 인증기관 무료, 개인회원 유료
Automated storage/retrieval systems (AS/RS) remain essential in various industries, including smart factories and distribution centers. This study analyzes the flow time of a twin crane AS/RS (TC-AS/RS) with connected material handling systems such as automated guided vehicles (AGVs). To account for system variability, we developed a discrete-event simulation model considering factors such as arrival and service rates. The simulation data is further analyzed using a G/G/1 queueing model to evaluate system performance. Experimental results show that analyzing TC-AS/RS at the crane-level improves estimation accuracy compared to system-level G/G/1 model. Additionally, the input/output (I/O) configuration significantly impacts flow times, with the Both ends I/O layout help prevent bottlenecks under high demand in the connected material handling system.
4,000원
2.
2026.03
구독 인증기관 무료, 개인회원 유료
This study presents the development of an AI-based real-time on-device segmentation system designed to support recyclable waste sorting. A lightweight semantic segmentation model was implemented by combining the MobileViT-x-small backbone with the DeepLabV3 architecture, enabling pixel-level classification of recyclable items and intuitive visualization on a smartphone screen. A total of 200 real-world images were collected, with 150 used for training and 50 for testing. To enhance generalization under limited data conditions, the training set was expanded to 750 images through geometric and color-based augmentation techniques. The trained model was subsequently converted into ONNX format and deployed within a Flutter-based mobile application, allowing real-time inference directly on the device without reliance on external servers. The proposed system overlays semi-transparent masks and class labels onto the live camera feed, thereby reducing sorting errors and promoting active user participation in everyday recycling practices.
4,200원
3.
2026.03
구독 인증기관 무료, 개인회원 유료
Sungho Kim, Inseob Hong, Jungyu Park, Geunhyung Do, Seunghoon Yoo, Kyujin Moon, Seongyeop Ryu, Younggun Lee
With the evolving nature of modern warfare and the rapid advancement of technology, Manned-Unmanned Teaming (MUM-T) has emerged as a core element of future air power. This study systematically identifies evaluation measures for assessing the mission effectiveness of MUM-T in the context of Air Force operations. To this end, a survey of experienced fighter pilots was conducted to derive mission scenarios suitable for MUM-T, and statistical analysis led to the selection of five scenarios. Subsequently, comprehensive evaluation measures for each selected scenario were derived through literature review and expert interviews, and their validity and expert consensus were verified using the Delphi method. Finally, the Analytic Hierarchy Process (AHP) was employed to calculate the relative importance of the evaluation measures (secondary measures only) for each scenario, and a formula-based model was proposed. The findings of this study provide a quantitative evaluation framework for verifying MUM-T mission effectiveness using Modeling and Simulation (M&S) tools, and are expected to serve as a foundational basis for weapon system acquisition and the development of operational concepts.
4,000원
4.
2026.03
구독 인증기관 무료, 개인회원 유료
To achieve competitive design, it is essential to develop an optimization method that ensures both high customer satisfaction and robustness for products with multiple criteria. While several studies have proposed optimization methods that integrate TOPSIS with Taguchi method or desirability function, no single study has yet combined all three methods into a unified optimization framework. Therefore, this study proposes an integrated optimization method that combines TOPSIS, Taguchi method and desirability function. The overall process of proposed method is based on the TOPSIS framework. To incorporate Taguchi method and desirability function into TOPSIS, we propose using desirability function for normalization, replacing the traditional vector normalization used in standard TOPSIS. In addition, Signal-to-Noise(S/N) ratios are calculated to evaluate the degree of customer satisfaction. To demonstrate the effectiveness of the proposed method, a hypothetical example is generated under specific conditions, and the resulting rankings are compared with those derived using the original TOPSIS approach. The comparison revealed that the rankings of design alternatives differed between the original TOPSIS and the proposed method. This difference is attributed to the influence of the desirability function’s threshold points, the specific type of desirability function applied (from Kano’s perspective), and the Taguchi S/N ratio used to assess satisfaction levels. These factors enabled a more nuanced evaluation of customer satisfaction and robustness, thereby validating the effectiveness of the proposed optimization method.
4,200원
5.
2026.03
구독 인증기관 무료, 개인회원 유료
This study comparatively analyzes the energy generation performance and economic evaluation of monofacial and bifacial photovoltaic (PV) modules, utilizing empirical data obtained from the Saemangeum project. The analysis is based on field data collected over a three-year period from 2022 to 2024. The results indicate that bifacial modules achieved an average power generation increase of approximately 8.27% compared to monofacial modules, attributed to the additional energy yield from rear-side irradiance. For the economic assessment, the Levelized Cost of Electricity (LCOE) and the Break-Even Point (BEP) were analyzed. Although the initial investment cost for bifacial modules was approximately 7.4% higher than that of monofacial modules, the LCOE was found to be lower for bifacial modules (114.7 KRW/kWh) compared to monofacial modules (117.8 KRW/kWh) over a 20-year operation period, due to the benefits of increased energy generation. The BEP analysis revealed that bifacial modules reach a break-even point relative to monofacial modules after 7.02 years. Furthermore, the study examined the trends of the BEP in response to variations in electricity selling prices and bifacial gain. In conclusion, this study confirms that bifacial PV modules demonstrate superior results in both power generation performance and economic analysis within the testbed environment. Consequently, these findings suggest a high potential for the application of bifacial modules in future domestic and international photovoltaic projects.
4,000원
6.
2026.03
구독 인증기관 무료, 개인회원 유료
This study examines the operational performance of a Manufacturing Execution System (MES)-based smart factory and presents a case study to provide practical insights for the effective adoption of smart factories by small- and medium-sized enterprises (SMEs) in Korea. While Industry 4.0 and Korea’s Manufacturing Innovation 3.0 policy have accelerated the digital transformation of manufacturing sites, the emerging paradigm of Industry 5.0 places greater emphasis on human-centricity, sustainability, and resilience. The case company, S Corporation, is a mid-sized automotive parts manufacturer that implemented an MES-based integrated platform encompassing production management, materials management through a Warehouse Management System (WMS), quality management via a Quality Management System (QMS), and equipment management. This integration enabled real-time monitoring and control of shop-floor operations, thereby enhancing data-driven decision-making. The case analysis, supported by a review of related literature, identifies significant quantitative improvements, including increased productivity, reduced defect rates, shorter lead times, and improved inventory turnover. In addition, several qualitative benefits were observed, such as enhanced process visibility, operational standardization, faster managerial decision-making, and a reduced workload for shop-floor operators. Overall, this study demonstrates a smart factory operational model that integrates the technological foundations of Industry 4.0 with the value-oriented principles of Industry 5.0. The findings provide meaningful implications for SMEs seeking to achieve sustainable and human-centered digital transformation in manufacturing.
4,000원
7.
2026.03
구독 인증기관 무료, 개인회원 유료
Recently, changes in the electric vehicle transition policy have necessitated improved user acceptance by securing the competitiveness of electric vehicles over internal combustion engine vehicles. In particular, the importance of reliable condition diagnosis technology to prevent safety accidents such as battery pack fires has been receiving significant attention. However, lithium-ion battery packs, primarily used in domestic electric vehicles, require the development of battery pack health diagnosis technology that considers real-world driving characteristics, such as high energy density and irregular and incomplete charge/discharge patterns. This study utilized OBD-II data from 100 real-world electric vehicles to extract health indicators for assessing battery pack aging over time using IC curves. Using IC curves during charging, the most stable environment during real-world driving, key factors associated with battery pack aging were identified. The IC curves confirmed that aging increased with mileage from 30,000 km to 260,000 km, demonstrating the potential for developing integrated aging maps for the same vehicle model. Furthermore, this study is considered a practical tool for immediate condition assessment of electric vehicles without the need for additional equipment.
4,000원
8.
2026.03
구독 인증기관 무료, 개인회원 유료
The adoption of generative artificial intelligence (AI) has attracted growing attention across industries due to its potential to transform organizational processes and value creation. Despite its high applicability, however, the diffusion of generative AI in the telecommunications industry remains limited. Existing studies have largely focused on identifying individual barriers to AI adoption, providing insufficient understanding of how these barriers interact and form a complex hierarchy of constraints. Addressing this gap, this study investigates the structural interrelationships among barriers to generative AI adoption in the telecommunications industry. Based on a comprehensive literature review and expert validation, fifteen key barriers were identified. Using a Delphi-based Interpretive Structural Modeling (ISM) approach, this study examined the hierarchical influence structure among the barriers. Subsequently, the Matrix Impact Cross-reference Multiplication Applied to Classification (MICMAC) technique was employed to classify the barriers according to their driving power and dependence. The results reveal a four-level hierarchical structure in which environmental barriers play a foundational role. In particular, the absence of alignment in institutional frameworks and technical standards emerges as a root-level barrier exerting strong influence on higher-level constraints. Regulatory uncertainty and concerns about job displacement function as independent drivers linking foundational environmental conditions to execution- level constraints. Most technical, organizational, and economic barriers are concentrated at the intermediate level, forming a highly interdependent execution layer. At the top level, delays and uncertainties in decision-making regarding generative AI adoption appear as outcome-oriented barriers resulting from the cumulative effects of lower-level constraints. By highlighting that barriers to generative AI adoption in the telecommunications industry operate as a structurally connected system rather than isolated factors, this study extends existing adoption research through a structural perspective. The findings provide practical insights for telecommunications firms in prioritizing adoption strategies and offer implications for addressing institutional and regulatory conditions that shape the diffusion of generative AI.
4,500원
9.
2026.03
구독 인증기관 무료, 개인회원 유료
Tactical data link (TDL) is one of the key means for enabling real-time exchange of tactical information among weapon systems operated by the Army, Navy, and Air Force. Most messages consist of position information of participating nodes, with latitude and longitude fields designed to enable worldwide operation. Given the limited operational area of Korean army, enabling worldwide operation requires an excessive number of data bits, which cause data overhead and reduced network efficiency. Therefore, in this paper, we investigate the current coordinate transmission methods used in TDL and propose a relative coordinate-based transmission scheme within a designated area to enhance network efficiency. The proposed method is optimized for the operational characteristics of the Korean military and improves both network efficiency and positional accuracy compared to existing TDL.
4,000원
10.
2026.03
구독 인증기관 무료, 개인회원 유료
This study develops a Skip-Connected Temporal Contextual Deep Learning (SC-TCDL) model to forecast monthly inbound foreign tourist arrivals to South Korea, targeting demand volatility and structural shocks such as COVID-19 while supporting planning-oriented decision making. SC-TCDL adopts a dual-stream architecture that disentangles inputs by function: an LSTM branch encodes a 12-month rolling history of arrivals with calendar indicators, while an encoder-only Transformer processes forward-looking exogenous variables with positional encodings. The LSTM temporal representation is injected into the Transformer and fused with the Transformer output via an MLP through skip connections. COVID-period distortion (Mar 2020 Dec 2023) is addressed by virtual demand restoration using a counterfactual LSTM trained on pre-pandemic data. Probabilistic forecasts are generated via Monte Carlo Dropout. Using monthly data (Feb 2013 Apr 2025), SC-TCDL outperforms SARIMA, vanilla LSTM, and a Transformer on the test period (May 2024 Apr 2025), achieving MAE 78,626, RMSE 94,019, and MAPE 6.94%, reducing MAE by 30.5% relative to SARIMA, 28.3% relative to vanilla LSTM, and 24.9% relative to the Transformer, with statistically significant improvements by Wilcoxon signed-rank tests. By structurally separating temporal and contextual learning while enabling controlled fusion and uncertainty quantification, SC-TCDL offers a robust framework for tourism demand forecasting in shock-prone environments.
5,100원
11.
2026.03
구독 인증기관 무료, 개인회원 유료
This study empirically examines the differential impacts of government support on firms’ innovation performance. Government support is categorized into financial support (tax, funding, and finance) and non-financial support (technology and human resources), and their respective effects on market performance and innovation capability are analyzed. Using data from the 2022 Korean Innovation Survey (KIS) conducted by the Science and Technology Policy Institute (STEPI), the analysis applies propensity score matching and logistic regression, along with moderation tests using Hayes’ process macro. The results indicate that both financial and non-financial support significantly enhance market performance, while only non-financial support exerts a meaningful influence on innovation capability. Furthermore, Non-financial support exhibited a positive moderating effect on market performance when market-based information sources were utilized, while its impact on innovation capability varied with the level of utilization. In contrast, the use of science-based information sources had significant positive effects on both market performance and innovation capability, with the latter strengthened particularly at higher levels of utilization. Additional mediation analysis shows that non-financial support enhances market performance through innovation capability, whereas financial support exhibits no such effect, highlighting the need for firms to build internal capabilities for sustainable outcomes. These findings suggest that government policies should be tailored to the type of support provided and that integrated strategies combining external knowledge sources are essential. In addition, strengthening innovation capability is critical for achieving sustainable innovation outcomes in the long term.
4,900원
