• Corrosion Science and Technology
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• 제23권2호
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• pp.131-138
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• 2024

This paper introduces Primetals Technologies' Through-Process Optimization (TPO) Services and Through-Process Quality Control (TPQC) System, which integrate domain knowledge, software, and automation expertise to assist steel producers in achieving operational excellence. TPQC collects high-resolution process and product data from the entire production route, providing visualizations and facilitating quality assurance. It also enables the application of artificial intelligence techniques to optimize processes, accelerate steel grade development, and enhance product quality. The main objective of TPO is to grow and digitize operational know-how, increase profitability, and better meet customer needs. The paper describes the contribution of these systems to achieving operational excellence, with a focus on quality assurance. Transparent and traceable production data is used for manual and automatic quality evaluation, resulting in product quality status and guiding the product disposition process. Deviation management is supported by rule-based and AI-based assistants, along with monitoring, alarming, and reporting functions ensuring early recognition of deviations. Embedded root cause proposals and their corrective and compensatory actions facilitate decision support to maintain product quality. Quality indicators and predictive quality models further enhance the efficiency of the quality assurance process. Utilizing the quality assurance software package, TPQC acts as a "one-truth" platform for product quality key players.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.248-268
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• 2018

The performance of smartphone applications are usually constrained in user interactions due to resource limitation and it promises great opportunities to improve the performance by exploring the smartphone built-in and embedded sensing techniques. However, heterogeneity in techniques, semantic gap between sensor data and usable context, and complexity of contextual situations keep the techniques from seamless integration. Relevant studies mainly focus on feasibility demonstration of emerging sensing techniques, which rarely address both general architectures and comprehensive technical solutions. Based on a proposed functional model, this investigation provides a general architecture to deal with the dynamic context for context-aware automation and decision support. In order to take advantage of the built-in sensors to improve the performance of mobile applications, an ontology-based method is employed for context modelling, linguistic variables are used for heterogeneous context presentation, and semantic distance-based rule matching is employed to customise functions to the contextual situations. A case study on mobile application authentication is conducted with smartphone built-in hardware modules. The results demonstrate the feasibility of the proposed solutions and their effectiveness in improving operational efficiency.

• 전기학회논문지P
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• 제64권4호
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• pp.220-230
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• 2015

Rolling stock RAMS is a field of engineering which integrates reliability, availability, maintainability and safety (RAMS) characteristics into an inherent product design property through rolling stock system engineering process. It is implemented to achieve operational objectives successfully, and recently the RAMS has become a rapidly growing engineering discipline because it has a great potential to ensure safety and improve cost effectiveness. However, the Korean rolling stock industry has not yet implemented RAMS management in the rolling stock engineering process, despite the issue having been addressed since the introduction of the KTX. Thus, this paper discusses the processes, methods and techniques for RAMS assessment in three parts. Firstly, it outlines a process of the overall RAMS performance assessment for achieving technical RAMS design criteria. Secondly, it discusses a process for assessing the operational RAM and allocating the RAM. This paper also proposes a model for assessing safety-based risk management, which includes five analytic techniques for identifying the causes and consequences of a system failure. Finally, a case example is provided for the risk assessment of the pneumatic braking device.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.579-593
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• 2010

Low-power radio frequency (RF) chip transceiver technology and the associated structural health monitoring platforms have matured recently to enable high-rate, lossless transmission of measurement data across large-scale sensor networks. The intrinsic value of these advanced capabilities is the allowance for high-quality, rapid operational modal analysis of in-service structures using distributed accelerometers to experimentally characterize the dynamic response. From the analysis afforded through these dynamic data sets, structural identification techniques can then be utilized to develop a well calibrated finite element (FE) model of the structure for baseline development, extended analytical structural evaluation, and load response assessment. This paper presents a case study in which operational modal analysis is performed on a three-span prestressed reinforced concrete bridge using a wireless sensor network. The low-power wireless platform deployed supported a high-rate, lossless transmission protocol enabling real-time remote acquisition of the vibration response as recorded by twenty-nine accelerometers at a 256 Sps sampling rate. Several instrumentation layouts were utilized to assess the global multi-span response using a stationary sensor array as well as the spatially refined response of a single span using roving sensors and reference-based techniques. Subsequent structural identification using FE modeling and iterative updating through comparison with the experimental analysis is then documented to demonstrate the inherent value in dynamic response measurement across structural systems using high-rate wireless sensor networks.

• Computers and Concrete
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• 제10권3호
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• pp.277-294
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• 2012

The aim of the study is to determine the modal parameters of a prototype damaged arch dam by operational modal analysis (OMA) method for some damage scenarios. For this purpose, a prototype arch dam-reservoir-foundation model is constructed under laboratory conditions. Ambient vibration tests on the arch dam model are performed to identify the modal parameters such as natural frequency, mode shape and damping ratio. The tests are conducted for four test-case scenarios: an undamaged dam with empty reservoir, two different damaged dams with empty reservoirs, and a damaged dam with full reservoir. Loading simulating random impact effects is applied on the dam to crack. Cracks and fractures occurred at the middle of the upper part of the dams and distributed through the abutments. Sensitivity accelerometers are placed on the dams' crests to collect signals for measurements. Operational modal analysis software processes the signals collected from the ambient vibration tests, and enhanced frequency domain decomposition and stochastic subspace identification techniques are used to estimate modal parameters of the dams. The modal parameters are obtained to establish a basis for comparison of the results of two techniques for each damage case. Results show that approximately 35-40% difference exists between the natural frequencies obtained from Case 1 and Case 4. The natural frequencies of the dam considerably decrease with increasing cracks. However, observation shows that the filled reservoir slightly affected modal parameters of the dam after severe cracking. The mode shapes obtained are symmetrical and anti-symmetrical. Apparently, mode shapes in Case 1 represent the probable responses of arch dams more accurately. Also, damping ratio show an increase when cracking increases.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.232-238
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• 2011

Hazard analysis provides the basic foundation for system safety. Hazard analysis is performed to identify hazards, hazard effects, and hazard causal factors. Hazard analysis is used to determine system risk, to determine the significance of hazards, and to establish design measures that will eliminate or mitigate the identified hazards. Hazard analysis is used to systematically examine systems, subsystems, facilities, components, software, personnel, and their interrelationships, with consideration given to logistics, training, maintenance, test, modification, and operational environments. This paper present hazard analysis techniques which is commonly used in railway signalling, comparised their benefits and limitations.

• 한국화재소방학회논문지
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• 제24권2호
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• pp.9-20
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• 2010

본 연구는 아직 초보수준인 국내기업의 업무연속성 유지를 위한 재해경감 활동계획 수립 및 실행에 대한 방향을 제시하였으며, 조기대응체계 구축을 통하여 어떠한 재난에도 안전을 기할 수 있는 기업 연속성 유지 방안을 모색하였다. 이를 실현하기 위하여 국내 재난관리 표준으로 채택된 사고대비 및 업무연속성 관리의 가이드라인을 분석하였고, 국내기업에 쉽게 적용할 수 있는 실행지침을 제시하였으며, A기업을 대상으로 재해경감활동계획 수립 및 정보기술을 활용하는 방안을 연구하였다. 특히 사고대비 및 업무연속성 관리의 가이드라인 5단계 주요 절차 중 계획수립단계의 위험 평가, 영향분석, 예방경감계획 및 대응관리계획 수립에 대한 모델을 제시하였고, 국내 재해경감활동이 활성화되기 위한 방안을 도출하였으며, 재난대응 수준을 향상시키기 위하여 필요한 정보기술 부분도 제시하였다.

• 경영과학
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• 제20권2호
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• pp.1-16
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• 2003

Previous research on data extraction and integration for data warehousing has concentrated mainly on the relational DBMS or partly on the object-oriented DBMS. Mostly, it describes issues related with the change data (deltas) capture and the incremental update by using the triggering technique of active database systems. But, little attention has been paid to data extraction approaches from other types of source systems like hierarchical DBMS, etc. and from source systems without triggering capability. This paper argues, from the practical point of view, that we need to consider not only the types of information sources and capabilities of ETT tools but also other factors of source systems such as operational characteristics (i.e., whether they support DBMS log, user log or no log, timestamp), and DBMS characteristics (i.e., whether they have the triggering capability or not, etc), in order to find out appropriate data extraction techniques that could be applied to different source systems. Having applied several different data extraction techniques (e.g., DBMS log, user log, triggering, timestamp-based extraction, file comparison) to S bank's source systems (e.g., IMS, DB2, ORACLE, and SAM file), we discovered that data extraction techniques available in a commercial ETT tool do not completely support data extraction from the DBMS log of IMS system. For such IMS systems, a new date extraction technique is proposed which first creates Index database and then updates the data warehouse using the Index database. We illustrates this technique using an example application.

• 한국시뮬레이션학회논문지
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• 제19권4호
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• pp.309-318
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• 2010

Simulation-based acquisition(SBA)는 획득의 제단계에 모델링 및 시뮬레이션(M&S)를 적용함으로써 획득기간을 단축하고 무기체계 총 소유비용을 낮추며 소요군이 요구하는 성능목표를 가진 무기체계를 획득하고자 하는 새로운 획득 패러다임이다. 우리 군이 SBA의 정착을 위해 다각도의 노력을 기울이고 있음에도 불구하고 SBA의 성공적인 실행을 보장해 주는 청사진 역할을 하는 SBA 아키텍처 프레임워크에 대한 연구는 미진한 상황이다. 본 연구에서는 MND-AF를 기반으로 SBA 아키텍처 프레임워크 개념모델을 제안하였으며, 우리 군의 획득 프로세스를 근간으로 운영 뷰에 대한 모델링을 수행하였다. 또한 운영 뷰에 포함된 각종 운영활동들이 임무 완수를 위해 활용하게 될 도구와 기술을 식별했으며, 데이터들간의 상호운용성을 보장해주는 표준화된 데이터 모델을 제안해 시스템 뷰에 포함시켰다. 특히 시스템 뷰에는 통합사업 관리팀과 운영활동의 주체들이 분산되어 있는 M&S 도구들을 활용할 수 있는 SBA AF 포털이 포함되어 있다. 또한 SBA 아키텍처 프레임워크 개념모델에는 기술 뷰와 아키텍처 구축을 위한 최상위 지침서로서의 역할을 하는 올 뷰가 포함되어 있다.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1422-1431
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• 2015

The reliability of power system components can be affected by a numbers of factors such as the health level of components, external environment and operation environment of power systems. These factors also affect the electrical parameters of power system components for example the thermal capacity of a transmission element. The relationship of component reliability and power system is, therefore, a complex nonlinear function related to the above-mentioned factors. Traditional approaches for reliability assessment of power systems do not take the influence of these factors into account. The assessment results could not, therefore, reflect the short-term trend of the system reliability performance considering the influence of the key factors and provide the system dispatchers with enough information to make decent operational decisions. This paper discusses some of these important operational issues from the perspective of power system reliability. The discussions include operational reliability of power systems, reliability influence models for main performance parameters of components, time-varying reliability models of components, and a reliability assessment algorithm for power system operations considering the time-varying characteristic of various parameters. The significance of these discussions and applications of the proposed techniques are illustrated by case study results using the IEEE-RTS.