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.2 (2026년 6월) 15건
1.
2026.06
구독 인증기관 무료, 개인회원 유료
Jun-Ho Lee, Hoon Jang
This study investigates the non-cyclic scheduling problem of dual-gripper robotic cells, which is becoming increasingly critical in high-mix low-volume manufacturing environments. While optimal algorithms have been developed, their exponential computational complexity limits their applicability to large-scale industrial scenarios. To bridge this gap, we propose two efficient heuristic approaches: a Dominance Property-based Heuristic Algorithm and a Heuristic by Beam Search. They relax the strict dominance conditions to accelerate the search process and employ an estimated average workload as a guide to prune the search tree. Experimental results on robotic cells with up to 500 jobs demonstrate that the proposed heuristics consistently generate high-quality schedules within a practical computation time.
4,000원
2.
2026.06
구독 인증기관 무료, 개인회원 유료
Joonha Jang, Sangmin Lim, Kwangjin Yang, Kihoon Kwak, Hwajong Jin, Donghyouk Shim
This study proposes a McCormick-based mixed-integer linear programming (MILP) model for real-time dynamic weapon-target assignment (DWTA) in multi-layer missile defense systems. The proposed model simultaneously considers engagement time windows (ETWs), time-varying interception effectiveness, and inter-layer dependency based on the shoot-look-shoot (SLS) doctrine. To reflect operational engagement conditions, a K-factor-based effectiveness model is introduced by incorporating trajectory progress, engagement geometry, missile kinematics, and environmental conditions. Since the survival probability formulation results in nonlinear and nonconvex multilinear terms, the problem is reformulated into an MILP framework using binary-tree decomposition and McCormick linearization. In addition, a rolling horizon strategy and warm-start mechanism are applied to support real-time decision making under dynamically changing battlefield conditions. Numerical experiments on various threat scenarios demonstrate that the proposed approach significantly reduces computation time compared to nonlinear optimization methods while maintaining high solution quality. In particular, the proposed method achieves near optimal solutions within sub-second computation time even for large-scale instances.The results indicate that the proposed McCormick-based MILP framework provides an effective and practical solution for real-time DWTA problems in multi-layer missile defense systems.
4,300원
3.
2026.06
구독 인증기관 무료, 개인회원 유료
Hong-Mo Yang, Moonsoo Shin
There is a growing need for adaptive operational control to manage stochastic sample arrivals and strict turnaround deadlines in molecular diagnostics systems. Conventional static dispatching rules, however, often struggle to accommodate sudden surges in urgent samples, leading to bottleneck propagation across serial diagnostic processes. The primary objective of this study is to develop a multi-agent reinforcement learning framework for dynamic scheduling within a discrete event simulation environment. In this framework, independent deep Q-network agents at six serial diagnostic stages dynamically select from three dispatching rules―first-in-first-out, urgent-first, and earliest due date. These decisions are based on continuous-state observations of queue congestion, urgency mix, and remaining deadline, with hyperparameters determined through random search. The simulation environment was preliminarily validated by comparing Gantt-chart-based field schedules with simulation outcomes using a paired t-test. The proposed model was evaluated against a rule-based baseline, a genetic algorithm policy, and a tabular Q-learning model under three urgency-ratio regimes. During overload scenarios, the proposed framework demonstrated a statistically significant improvement in the high-urgency on-time rate compared to the rule-based baseline, while simultaneously reducing average waiting times. The genetic algorithm converged to a static, rule-equivalent mapping, whereas the critical-urgency on-time rate remained consistent across all four models. Overall, these results imply that continuous-state multi-agent reinforcement learning provides superior adaptive responsiveness in high-load regimes. Future research should focus on extending this framework to facility-level dispatching to address load imbalance among parallel machines.
4,500원
4.
2026.06
구독 인증기관 무료, 개인회원 유료
Byungyeon Kim, Nahye Lee, Jaeha Park, Taegu Kim, Soon Hyung Park, Lae Eun Kim
The growing sophistication of adversarial ballistic missile threats, along with the development of multilayered defense systems to counter them, has increased the importance of establishing efficient operational concepts. However, existing studies on multilayered defense and weapon allocation have mainly focused on dynamic allocation procedures or time constraints, and have not sufficiently reflected the uncertainty of detection information and its changes over time, which serve as key grounds for decision- making. This study proposes a dynamic command-system-based operational concept for multilayered defense that allows command decisions to be revised in response to changes in detection information, and develops an effectiveness simulation tool to implement it. The proposed operational concept is designed to reflect real operational environments in which detection information is updated progressively over time, enabling the continuous reassessment of existing engagement plans and weapon-target allocation results. In addition, comparative experiments were conducted by varying the timing of information utilization in order to verify the feasibility and effectiveness of the proposed concept. The results show that an early response increases unnecessary allocations and cancellations due to low information accuracy, whereas a delayed response limits interception opportunities because of reduced available response time. A strategy that responds after a certain level of information accuracy has been secured was found to be superior in terms of both resource utilization efficiency and defense effectiveness. These findings demonstrate that an operational concept adaptive to changes in information can have a meaningful impact on actual defense effectiveness, and they provide implications for establishing command-and-control structures and procedures for future multilayered defense systems.
4,600원
5.
2026.06
구독 인증기관 무료, 개인회원 유료
Won Duk Jung, Dong Hyun Baek
This study develops and prioritizes a Baldrige-based evaluation structure for semiconductor material suppliers using an integrated Delphi method and Analytic Hierarchy Process (AHP) approach. Rather than treating AHP as an isolated mathematical procedure, the study positions it as a practical weighting tool within a broader model-development process. First, the seven-category Baldrige framework and prior supplier-evaluation studies were reviewed to derive candidate domains and items. Next, a first-round Delphi survey identified core industry-specific domains, and a second-round Delphi survey verified the importance and adequacy of the structured items. Finally, AHP was applied to calculate the relative priorities of the validated factors. The results show that customer-related factors received the highest weight, followed by workforce and measurement, analysis, and knowledge management factors. In the global ranking, customer quality issue response system, customer satisfaction and voice of customer (VOC) management, response to customer requirements, securing specialized experts, and root-cause analysis and improvement were identified as the most important factors. Additional analysis based on stricter consistency-ratio thresholds confirmed that the overall priority structure remained stable. These findings suggest that semiconductor material supplier evaluation should move beyond a conventional quality-cost-delivery (QCD) perspective and incorporate customer responsiveness, data-driven management, workforce capability, and operational stability in an integrated manner. The study contributes by translating the Baldrige framework into an industry- specific evaluation structure and by providing a practical weighting basis for supplier assessment.
4,300원
6.
2026.06
구독 인증기관 무료, 개인회원 유료
Moon-Gul Lee, Sang-Min Jeon
This study proposes an integrated Multi-Criteria Decision-Making (MCDM) model using AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to select the optimal alternative for the Next-Generation Korean Rifle project. While the current K2 and K2C1 platforms have served as the backbone of the Republic of Korea Armed Forces, evolving operational environments and global trends toward modularity and high-power ammunition necessitate a systematic modernization strategy. The research defines seven major criteria—including combat effectiveness, ergonomics, reliability, and networking fusion—to evaluate four strategic alternatives. The analysis reveals that a new 5.56mm modular platform is the most viable optimal choice, offering a superior balance between ergonomic design, technological scalability for the Warrior Platform, and operational reliability. While 6.8mm platforms offer higher lethality, they face challenges regarding cost and technical readiness. The findings provide a quantitative framework for decision-makers in weapon system acquisition, emphasizing the transition from a standalone firearm to an integrated combat system for the future’s war environment.
4,300원
7.
2026.06
구독 인증기관 무료, 개인회원 유료
Dasol Lee, Taeho Kim, Jeman Boo
As artificial intelligence (AI) technologies continue to advance, AI chatbots have become a key digital interface in customer service environments. However, users exhibit heterogeneous levels of acceptance and continued usage, indicating the need for an integrated perspective that considers both technology acceptance and service quality. This study aims to provide a multidimensional understanding of AI chatbot acceptance by integrating the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with the SERVQUAL framework. Using survey data collected from AI chatbot users, this study first employs cluster analysis based on UTAUT2 factors to classify users into three clusters: high, medium, and low levels. Analysis of variance reveals statistically significant differences in perceived service quality across clusters, with higher acceptance clusters reporting more favorable SERVQUAL evaluations, particularly in terms of responsiveness. Subsequent multiple regression analyses demonstrate that the effects of SERVQUAL dimensions on behavioral intention to use AI chatbots vary across clusters. The results indicate that AI chatbot user clusters differ significantly in their perceptions of service quality, and that the SERVQUAL factors affecting behavioral intention to use AI chatbots are not uniform across clusters. This study contributes to the literature by empirically linking technology acceptance levels with service quality perceptions in AI chatbot contexts. Practically, the findings suggest that firms should adopt cluster-specific strategies to enhance chatbot design, service quality management, and user engagement.
4,000원
8.
2026.06
구독 인증기관 무료, 개인회원 유료
Jiwan Jeong, Kwanghui Shin, Yongsoo Kim
Weak fault detection in bearing vibration signals remains a challenging task due to the low energy of fault-induced impulses and their susceptibility to noise and interference. To address this issue, this study proposes a Bearing fault diagnosis framework that integrates Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA), envelope analysis, and a Convolutional Neural Network (CNN). First, characteristic fault frequencies derived from bearing geometry are used to determine fault-specific periods, and MOMEDA is applied to selectively enhance periodic impulsive components corresponding to each fault type. The enhanced signals are then processed using the Hilbert Transform to extract the envelope, followed by Fourier Transform to obtain the envelope spectrum. Finally, the extracted frequency-domain features are used as inputs to the CNN-based deep learning model for fault classification. The proposed approach effectively enhances weak fault signatures and improves their representation in the frequency domain, enabling more reliable fault identification under noisy conditions.
4,200원
9.
2026.06
구독 인증기관 무료, 개인회원 유료
Sanggook Kim, Kyungran Noh, Boong Kee Choi, Huk Hahn
This study analyzes the effects of communicative role differentiation and web-search-based evidence utilization on deliberation quality in LLM (Large Language Model) multi-agent policy deliberation. Drawing on Habermas's theory of communicative action as a theoretical framework, the study evaluates deliberation outcomes not merely by whether or how quickly final responses converge, but by the procedural quality of mutual understanding, validity examination, evidence integration, and productive argumentation. The research design employs a 2×2 full factorial design crossing role differentiation (present/absent) and web search (present/absent), analyzing a total of 48 LLM multi-agent policy deliberation cases. The analytical indicators include Variance and Jensen-Shannon Divergence (JSD) for measuring belief convergence; rapid convergence (CON-R), non-convergence (DIV), and oscillation (OSC) for classifying deliberation patterns; Communicative Differentiation Index (CDI) for measuring communicative act differentiation; Evidence Integration Ratio (EIR) for measuring evidence integration; and deliberative (DEL) and groupthink (GRP) patterns. The analysis found that H1, which posited that role differentiation directly increases final belief convergence, was not supported by either Variance or JSD. However, H2, which posited that role differentiation increases communicative act differentiation, was supported by CDI, and H3, which posited that web search increases external evidence integration, was supported by EIR. H4, which posited that productive deliberation patterns (DEL) are strengthened in the C4 condition combining role differentiation and web search, was also supported. H5, which posited that role differentiation reduces groupthink, was inconclusive due to the absence of GRP cases throughout the entire experiment. Pattern analysis further revealed condition-dependent differences in deliberation pattern distributions: DEL proportions increased under role differentiation conditions, while CON-R and OSC were observed under homogeneous conditions. Although this study is limited by a small sample size and a single LLM environment, it contributes by shifting the evaluative focus of LLM multi-agent policy deliberation from final answers or consensus achievement to the quality of the communicative process. In particular, the study proposes an analytical framework for multidimensional evaluation of deliberation quality through diverse process indicators including CDI, EIR, JSD, and DEL. Future research should incorporate expert validation, sensitivity analysis, and replication across diverse models and policy agendas.
4,600원
10.
2026.06
구독 인증기관 무료, 개인회원 유료
JeongSup Kum, Hee Joo, Hyoungtae Kim
In the modern economy, venture companies serve as key drivers of national competitiveness by fostering innovation, creating employment, and accelerating technological advancement across diverse industries. Despite their critical role, previous venture certification systems have shown limited effects on improving profitability or resolving technical inefficiencies, primarily due to their reliance on static evaluation criteria and one-size-fits-all support frameworks that fail to account for the heterogeneous characteristics of individual firms. To address these limitations, this study proposes an automatic diagnosis and customized growth guide system that integrates multi-source data integration technology, dynamic weight allocation, and multi-objective optimization algorithms. The proposed system collects and harmonizes data from multiple sources, including financial statements, patent databases, and market trend indicators, to construct a comprehensive diagnostic profile for each venture company. A dynamic weight allocation mechanism adjusts evaluation criteria in real time based on industry-specific conditions and firm-level growth stages, thereby enhancing diagnostic accuracy and relevance. Simulation results using 10,000 virtual datasets demonstrated that the OCR-combined data pipeline achieved a 98.5% missing value completion rate, while the dynamic weight model attained 92.4% prediction accuracy in classifying firm growth potential. Furthermore, the optimal action plan recommendation utilizing the Knapsack algorithm reduced the required budget by 34.2% and time by 38.1%, significantly alleviating technical inefficiencies. These findings suggest that the proposed system can serve as a practical and scalable policy tool for enhancing the effectiveness of venture support programs, ultimately contributing to sustainable growth and improved resource allocation in the national innovation ecosystem.
4,000원
11.
2026.06
구독 인증기관 무료, 개인회원 유료
Hyun-sup Lee, Min-kyu Lee, Woon-seek Lee
The “space economy” refers to the technologies and industries related to the space sector which has recently emerged as a major global sector. As the Korean government is currently implementing various policies to foster the space economy, the research on the economic effects of the domestic space economy has become important. This study analyzed the economic effects of the Korean space economy using the input-output analysis, a framework for capturing inter-industry dependencies within an economy. The results of the analysis are as follows: a production inducement effect of 1.657, a value-added inducement effect of 0.641, and an employment inducement effect of 4.379 persons per 1 billion KRW. Compared with other nations that have conducted the input-output analysis for their space economy, the space economy of Korea has a relatively higher value-added inducement effect and employment inducement effect than those of other nations. Forward and backward linkage effects can classify the space economy as a ‘generally independent industry’ implying that this sector is in its early stages of development and that sustained investment by the government or private corporations is a critical factor for this sector’s growth. This study provides evidence-based groundwork to support policymakers in strengthening the Korean space economy.
4,500원
12.
2026.06
구독 인증기관 무료, 개인회원 유료
Seungwoo Lee, Byungheon Lee, Sunghyun Sim
The Northern Sea Route (NSR), increasingly navigable as Arctic sea ice retreats, can substantially shorten shipping distance, but route planning is difficult because navigability and risk at a location depend on a ship's arrival time. In practice it is rarely a single-route problem: forecasts are uncertain and frequently updated, and operators must weigh many departure times and time-cost trade-offs, so a planner is queried repeatedly. Graph-search and metaheuristic methods recompute a full solution per query and become the bottleneck, while prior reinforcement learning studies on Arctic routes assume static ice and ignore arrival-time-dependent risk. This study proposes a framework in which ST-A* (Space-Time A*) generates demonstration trajectories for different time-cost weights, and DQfD (Deep Q-Learning from Demonstrations) uses them to learn weight-specific policies that produce routes for new ice conditions by inference, without the full space-time re-search. On 51 unseen test cases from 2023-2025, the learned policies reached the destination in every case with lower objective values than a baseline trained without demonstrations. Relative to ST-A*, they produced routes about 700 times faster at a mean objective 1.57 times higher, a bounded loss in per-route optimality that makes large numbers of route evaluations tractable.
4,200원
13.
2026.06
구독 인증기관 무료, 개인회원 유료
Jonghyeon Chun, Bosung Kim, Min Hong, Soondo Hong
The stocker is a critical material handling system for transporting work-in-process materials in a display fab. Efficient dispatching is particularly challenging in twin-crane systems. The cranes share a single track while jobs arrive dynamically. In this study, we consider a weight-based dispatching method that combines multiple dispatching rules. The weight set determines the relative importance of multiple dispatching rules with competing objectives such as job priority and travel time, and its effectiveness varies with system dynamics. Evaluating weight sets requires simulation in stochastic and dynamic systems, which is computationally expensive. We therefore propose a simulation optimization framework to efficiently search the best weight set. Gaussian process- based Bayesian optimization is employed to guide the search under a limited simulation budget. Experimental results show that the relative importance of dispatching rules changes across scenarios. The proposed framework consistently identifies effective weight sets across diverse operating conditions.
4,200원
14.
2026.06
구독 인증기관 무료, 개인회원 유료
Insoo Kim, Joonsoo Bae, Yeonjoo Chae
This study aims to empirically identify the structural patterns of social support exchanged by cancer survivors in online communities and their unmet socio-economic needs during labor market reintegration, by analyzing YouTube vlog comments as a form of naturally occurring unstructured big data. As Korea's five-year cancer survival rate has reached 72.1%, cancer survivors increasingly face challenges of employment discontinuity and job instability, yet existing social safety nets fail to adequately address these needs. We collected 164,850 raw comments from 150 cancer survivor vlog videos posted between January 2020 and December 2024, employing a dual sourcing strategy combining YouTube Data API v3 and Selenium web drivers. Data collection was completed by February 2025, and preprocessing and analysis were finalized by November 2025. Following a four-stage preprocessing pipeline grounded in pilot-tested thresholds, 148,708 valid comments were analyzed using TF-IDF, Latent Dirichlet Allocation (LDA) topic modeling, binomial logistic regression, and KOSAC -based sentiment analysis. LDA topic modeling (K=5, coherence score Cv=0.52) revealed that ‘emotional solidarity and support’ constituted the largest latent topic (29.6%), demonstrating that cancer survivors prioritize emotional bonding over medical information exchange in online communities. Logistic regression confirmed that emotional support vocabulary significantly predicted empathic responses measured by comment ‘like’ counts (beta=1.847, p<.001), while medical information terms showed no statistical significance. Sentiment analysis revealed dominant positive sentiment (65%) with coexisting ambivalence structures in uncertainty-related topics. Theoretically, based on the observed complex support behaviors specific to vocational reintegration contexts, we propose ‘vocational rehabilitation support’ as a new subtype extending House's (1981) social support typology. From an industrial and systems engineering perspective, the findings provide an empirical foundation for designing return-to-work (RTW) process models and job redesign decision frameworks within human resource management (HRM) systems. Practically, we derive evidence-based policy recommendations including peer support programs, flexible work arrangements, and an incentive-penalty system modeled on Germany’s Schwerbehinderten-Ausgleichsabgabe.
4,000원
15.
2026.06
구독 인증기관 무료, 개인회원 유료
Changho Son
The fit of military apparel affects soldiers' mobility, protection, and musculoskeletal health, while poor fit inflates logistics costs through excess inventory and exchanges. Conventional sizing relies on a bivariate percentile grid over one or two control dimensions, which cannot reflect multivariate body-shape diversity. This study formulates sizing-system design as a multivariate p-median (facility-location) problem and develops a data-driven, explainable framework using the publicly available 2012 U.S. Army Anthropometric Survey (ANSUR II; 6,068 personnel, 93 measurements). Over a ten-dimension garment-fit space with grading- based tolerances, three size generators—the traditional percentile grid, k-means (centroid prototypes), and p-median/k-medoids (real-body prototypes)—are compared on a size-count versus fit trade-off curve. The data-driven generators dominate the percentile grid: k-means attains with only 15 sizes a higher mean dimensional accommodation than the grid achieves with 30 sizes, and reduces the mean misfit ratio by about 14% at an equal number of sizes, while p-median offers interpretable prototypes that correspond to actual soldiers usable as fit models. A measurement-minimization pipeline then reconstructs the full fit space from a few low-cost measurements using machine learning and builds the sizing system on the reconstructed bodies, evaluating accommodation on the true dimensions to avoid circularity; three measurements (weight, neck circumference, stature) recover 97% of the full-measurement accommodation, and two recover 94.5%. Permutation importance and SHAP (SHapley Additive ex- Planations) identify weight and neck circumference as the most informative measurements. A bootstrap analysis shows that gender-integrated sizing is marginally but significantly better than gender-separated sizing, justifying a unified system for stock-keeping simplicity.
4,000원
