• International journal of advanced smart convergence
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• 제12권2호
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• pp.173-181
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• 2023

Data collection is an essential element in the construction and operation of a smart factory. The quality of data collection is greatly influenced by network conditions, and existing wireless network systems for IoT inevitably lose data due to wireless signal strength. This data loss has contributed to increased system instability due to misinformation based on incorrect data. In this study, I designed a distributed MQTT IoT smart sensor and gateway structure that supports wireless multicasting for smooth sensor data collection. Through this, it was possible to derive significant results in the service latency and data loss rate of packets even in a wireless environment, unlike the MQTT QoS-based system. Therefore, through this study, it will be possible to implement a data collection management system optimized for the domestic smart factory manufacturing environment that can prevent data loss and delay due to abnormal data generation and minimize the input of management personnel.

• Asia pacific journal of information systems
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• 제33권4호
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• pp.957-976
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• 2023

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

• 전자통신동향분석
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• 제39권4호
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• pp.32-41
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• 2024

Building energy management plays a crucial role in improving energy efficiency and optimizing energy usage. To achieve this, it is important to monitor and analyze energy-related data from buildings in real time using sensors to understand energy consumption patterns and establish optimal operational strategies. Because of the uncertainties in building energy-related data, there are challenges in analyzing these data and formulating operational strategies based on them. Artificial intelligence (AI) technology can help overcome these challenges. This paper investigates past and current research trends in AI technology and examines its future prospects for building energy management. By performing prediction and analysis based on energy consumption or supply data, the future energy demands of buildings can be forecasted and energy consumption can be optimized. Additionally, data related to the surrounding environment, occupancy, and other building energy-related factors can be collected and analyzed using sensors to establish operational strategies aimed at further reducing energy consumption and increasing efficiency. These technologies will contribute to cost savings and help minimize environmental impacts for building owners and operators, ultimately facilitating sustainable building operations.

• 한국콘텐츠학회논문지
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• 제12권1호
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• pp.59-67
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• 2012

소프트웨어 변경관리는 시스템의 변경된 내용을 프로그램이나 설명문서와 같은 특정 개체의 특성 변경에 초점을 둔 것이다. 변경관리 시 요구사항간의 상호종속적인 관계를 가지고 최적의 상태를 위하여 복잡한 의사결정을 필요로 한다. 본 논문은 소프트웨어 변경관리를 분산환경에서 컴포넌트들간에 시간과 상황에 따른 변화를 관리하는 모델을 설계 한다. 그리고 각 컴포넌트들간의 관계성들에 대한 정의를 하고 ANP 기법을 이용하여 분산환경에서의 각 컴포넌트가 변화되어 참조되는 상호 의존성을 고려하여 종속관계와 피드백을 이용하여 최적의 대안을 선택할 수 있다. 즉, 서로간의 관계된 의존도를 분석하여 3가지 형태의 변경관계를 나타내도록 하였다. 또한 의존도 분석을 통해 이러한 접근 방법의 유효성을 검증하였다.

• 설비공학논문집
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• 제20권8호
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• pp.556-562
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• 2008

The building HVAC systems have very different qualities of performance and durability with the superintendent's ability for management and maintenance. The poor management of these systems finally lead to the shortening of the life expectancy and result in the increase of operating costs and energy consumptions due to low efficiencies. This study presents an example of appropriate use of the LCC(Life Cycle Cost) analysis in a process of maintaining and repairing old HVAC equipments, by demonstrating the difference of optimal economic life, decrease of running cost, and energy consumption according to the management level of the HVAC equipments. But there are no reliable life expectancy and performance history data at present for optimal management of various building service equipments. Therefore, it is necessary to construct long-term database on operation results of them for more accurate and optimized LCC analysis.

• 로봇학회논문지
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• 제17권4호
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• pp.407-416
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• 2022

Multiple AMRs have been proved to be effective in improving warehouse productivity by eliminating workers' wasteful walking time. Although Multi-agent Path Finding (MAPF)-based solution is an optimal approach for this task, its deployment in practice is challenging mainly due to its imperfect plan-execution capabilities and insufficient computing resources for high-density environments. In this paper, we present a MAPF-based fleet management system architecture that robustly manages multiple robots by re-computing their paths whenever it is necessary. To achieve this, we defined four events that trigger our MAPF solver framework to generate new paths. These paths are then delivered to each AMR through ROS2 message topic. We also optimized a graph structure that effectively captures spatial information of the warehouse. By using this graph structure we can reduce computational burden while keeping its rescheduling functionality. With proposed MAPF-based fleet management system, we can control AMRs without collision or deadlock. We applied our fleet management system to the real logistics warehouse with 10 AMRs and observed that it works without a problem. We also present the usage statistic of adopting AMRs with proposed fleet management system to the warehouse. We show that it is useful over 25% of daily working time.

• 한국산업융합학회 논문집
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• 제27권1호
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• pp.25-37
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• 2024

The objective of this study was to create intelligent rail robots that are optimized for facility management and implement digital twin systems for smart road tunnel management. An autonomous surveillance system is formed by combining the sensing platform consisting of railing robots, fixed cameras and environmental detection sensors with the digital twin data platform technology for tunnel monitoring and early fire suppression. In order to develop mobile rail robots for fire extinguishing, we also designed and manufactured robots for extinguishing & monitoring and fire extinguishing devices, and then we examined the optimization of all parts. Our next step was to build a digital twin for road tunnel management by developing continuous image display system and implementing 3D modeling. After constructing prototypes, we attempted simulations by configuring abnormal symptom scenarios, such as vehicles fires. This study's proposal proposes high-accuracy risk prediction services that will enable intelligent management of risks in the tunnel with early response at each stage, using the data collected from the intelligent rail robots and digital twin systems.

• 산업경영시스템학회지
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• 제40권3호
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• pp.18-26
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• 2017

Defense industries which require high reliability need an optimized quality management system with well-planned implementation. And the government should examine the overall status of defense industries, then establish practical policies with a proper support plan in required areas to upgrade the quality management level of manufacturers. Thus, DTaQ developed the model for 2 years from 2014, which specialized in quality management level analysis for defense industries. And a survey has been undertaken with that model by DTaQ and Korea Research Center in 2016. The surveyed companies randomly sampled among those which have more than 30 employees and delivery history over past 3 years, and finally 106 defense industries were selected. This paper present survey method and indexes for survey of defense industry quality management level. The survey was conducted in the order of planning, data collection and data processing, and the validity and reliability of the data were verified to increase objectivity of survey results. The survey contents mainly consist of system quality and management quality. System quality includes Product Development Management, Production Operation Management, supply chain quality management, Safety & Environment Management and Reliability Management, on the other hand, management quality includes Strategic Leadership, Human Resource Management, Customer Market Management and Information & Knowledge Management. Thus this proposes the current overall quality management status of the 106 defense industries and shows level differences by company sizes and manufacturing sectors based on the result of survey. Specifically, this paper enables to track the areas which need prompt government support with the policy directions to make quality management level higher. Therefore, it is expected that this can be used as reference data in establishing quality policies for military supplies in the future.

• International Journal of Quality Innovation
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• 제7권3호
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• pp.46-57
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• 2006

The desirability function approach to multiple response optimization is a useful technique for the analysis of experiments in which several responses are optimized simultaneously. But the existing methods have some defects, and have to be modified to some extent. This paper proposes a new method to combine the individual desirabilities.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.441-442
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• 2010