Earticle

This study proposes a distributed integrated control architecture based on Direct Digital Control(DDC) as an alternative to conventional centralized Distributed Control System(DCS) structures for a Canadian oil sands pilot plant, and theoretically analyzes its control characteristics and operational optimization potential. The target process consists of production and circulation, separation, water treatment, partial upgrading, and utility systems, and exhibits complex characteristics such as multiphase flow, high viscosity, time delay, strong coupling, and operation under extreme environmental conditions. In this study, an integrated control architecture combining independent DDC nodes for each process unit with a supervisory control layer is presented. A control model considering the coupling relationships among production, separation, water treatment, and upgrading processes is formulated, along with an objective function for energy optimization. Furthermore, through literature-based comparison and system architecture analysis, it is demonstrated that the DDC-based structure is suitable for oil sands pilot plants in terms of responsiveness, scalability, fault isolation, and energy efficiency.

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC re-duces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This paper considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an IMA(1,1) model with a step shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied according to the predicted deviation from target. For detecting special causes the exponentially weighted moving average control chart is applied to the observed deviations. It was assumed that the adjustment under the presence of a special cause may increase the process variability or change the system gain. Reasonable choices of parameters for the IPC procedure are considered in the context of the mean squared deviation as well as the average run length.

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for process quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation, while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been need for an integrated process control (IPC) procedure which combines the two strategies. This article considers a scheme that simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process disturbance model under consideration is an IMA(1,1) model with a location shift. The EPC part of the scheme adjusts the process, while the SPC part of the scheme detects the occurrence of a special cause. For adjusting the process repeated adjustment is applied by compensating the predicted deviation from target. For detecting special causes the two kinds of exponentially weighted moving average (EWMA) control chart are applied to the observed deviations: One for detecting location shift and the other for detecting increment of variability. It was assumed that the adjustment of the process under the presence of a special cause may change any of the process parameters as well as the system gain. The effectiveness of the IPC scheme is evaluated in the context of the average cost per unit time (ACU) during the operation of the scheme. One major objective of this article is to investigate the effects of the process parameters to the ACU. Another major objective is to give a practical guide for the efficient selection of the parameters of the two EWMA control charts.

다변량 통합공정관리의 기본절차는 잡음이 내재하는 공정에 수정조치를 취하여 공정편차벡터를 백색잡음벡터로 전환하도록 하여 공정제곱편차벡터를 최소화하게 되는 것이며, 이러한 다변량 통합공정관리의 수정활동을 하는 경우 공정에 이상원인이 발생하면 관리도를 통해 이를 탐지하고 제거하게 된다. 수정된 공정은 이상원인 발생 전에는 백색잡음이지만, 이상원인 발생 후 다양한 형태의 시계열 모형으로 변환하게 된다. 만약 수정된 공정을 탐지하여 이상원인의 신호가 발생한 경우 교정활동을 통하여 이를 제거해야 하지만, 구조적으로 교정이 불가능 하거나 교정활동의 비용이 많이 발생하는 경우에는 이상원인의 효과를 감안하여 수정활동을 재조정해야할 것이다. 이 논문에서는 공정모형으로 다변량 IMA(1,1)모형을 가정하고 다변량 통합공정관리 절차를 수행하는 경우 이상신호가 발생한 후 재수정 절차에서 필요한 모수추정을 하고자 한다.

This paper considers the multivariate integrated process control procedure for detecting special causes in a multivariate IMA(1, 1) process. When the multivariate control chart signals, the special cause will be detected and eliminated from the process. However, when the elimination of the special cause costs high or is not practically possible, an alternative action is to readjust the process with approximately modified adjustment scheme. In this paper, we estimate parameters in the readjustment procedure after having a true signal in the multivariate integrated process control.

정부차원에서 한국형 'K-Smart City'모델을 활용하여 건설과 ICT산업의 융합사업인 해외 Smart City시장 진출을 적극 추진하고 있다. Smart City사업의 특성상 시설물 시공품질과 ICT시스템 개발품질이 동시에 확보되어야 Smart City시설물의 품질향상이 가능하다. 그러나 Smart City사업 특성에 맞는 통합된 품질관리 프로세스 및 가이드가 미흡한 실정이다. 이로인해 국내 실증 프로젝트에서는 건설 품질관리와 ICT 품질관리가 분리된 형태로 관리되어 Smart City시공품질이 저하되는 문제점이 발생되고 있다. 본 연구에서는 Smart City프로젝트 구축단계의 시공품질 향상을 위하여 현장시공(통합운영센터 및 현장설비)과 ICT시스템 개발공정이 융합된 통합품질관리 프로세스를 연구하였다. Smart City사례 프로젝트에 본 연구에서 제안한 통합품질관리 프로세스를 적용한 결과, 시공검측시 시설물 부적합건 발생이 22% 감소하였고, ICT인프라 납품자재의 품질시험을 추가로 실시하여 18%의 부적합 사항을 설치전에 조치하여 시공품질이 향상되는 것을 확인하였다. 본 연구에서 제안한 통합품질관리 프로세스는 향후 Smart City 현장에 활용이 가능할 것으로 기대한다.

Korean government is promoting "K-Smart City" to overseas market which is an integrated solution of construction industry with ICT(Information and Communciations Technologies) industry. Due to nature of Smart City, construction quality and the development quality of the facilities need to be established to improve the overall quality. However, guidelines and regulations to initiate quality control for Smart City are behind the actual demand. This deficiency is bringing quality control for construction and ICT to be controlled separately causing lack of synergy and resulting in overall quality degradation. This research is designed to improve the construction quality of Smart City during its establishment stage by integrating ICT system with on-site construction (Integrated control center and on-site equipment). The adoption of this research to a real Smart City case had resulted in 22% reduction of construction inspection failure (Audit), and also allowed Construction Company to pre-align quality control of all purchased items of ICT Infra that resulted in 18% reduction of nonconformity, thus contributing to an overall quality improvement. This research is expected to be used widely among all construction industry of Smart City.

Traditional statistical process control(SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control(EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted variable sampling interval(VSI) to change sampling intervals in a predetermined fashion on the predicted process levels for integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA(1,1) disturbance model and zero-order (responsive) dynamic system. The properties of twelve control rules under three patterns of process change(sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

최근 공사관리의 효율성을 제고하기 위하여 CM제도의 도입, EVMS기법의 도입 등이 추진되고 있으며 제도적, 효율적인 공정관리를 위해서 필수적인 공정관리의 운영실태와 공정관리 수행을 저해하는 전반적인 문제점과 개선방안을 모색, WBS를 포함한 기존의 건설분야 정보분류시스템들이 토목부분의 적용에 문제점을 갖고 있는 점을 고려하여 새로운 정보분류체계의 개발 둥에 대한 연구 둥이 이루어지고 있으며, 국내 건설환경에 적합한 EVMS에 의한 공정-공사비 통합관리 프로세스모델이나 건축공사 등에서 적용사례 분석을 중심으로 공정-비용 통합관리 실용화를 위한 통합모델 개선방안을 제시하고 있다. 본 논문에서는 공정 공사비 통합관리를 효율적으로 할 수 있도록 교량의 예시를 통하여 WBS(Work Breakdown Structure) 및 Activity를 구축하고, 공정관리 전산프로그램을 이용하여 성과분석을 수행하여 유사공사의 계획수립에 일조하고자 한다.

This study refers to development of WBS(Work Breakdown Structure) and Activity sample for integrated cost and schedule control system of sample bridge work in the field. The conclusions from this study may be summarized as following 1. It showed that the level of detail to network's activities depend upon schedule's intended purpose. 2. It is more effective 'activity to cost package model' than 'activity to resource model', for integrated cost and schedule control reflect the characteristics of domestic construction industry.

Traditional statistical process control (SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control (EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted by variable sampling interval (VSI) to change sampling intervals in a predetermined fashion on the predicted process levels under integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA (1,1) disturbance model and zero-order (responsive) dynamic system. Properties of twelve control rules under three patterns of process change (sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

6시그마는 지난 20여 년간 제조 및 서비스 등의 산업에서 프로세스 개선을 위하여 꾸준히 적용되어왔다. 그럼에도 불구하고 6시그마는 Define 단계에서 의미있는 프로젝트를 계속 발굴하기 힘들고 Control 단계에서 지속적인 측정 및 통제가 쉽지 않다는 문제가 지적되었다. 이를 해결하기 위하여 개선 프로세스의 지속적인 통제와 관리를 원활히 할 수 있는 체계가 요구되며, 비즈니스 프로세스 관리(BPM) 시스템이 효과적 대안이 될 수 있다. 본 연구에서는 프로세스 운영 및 분석에서 누적된 데이터를 중심으로 지속적 프로세스 개선을 실현하기 위한 목적으로 6시그마와 BPM의 통합 모형을 제시하고, 프로젝트 수행을 위하여 상호 데이터 기반으로 프로세스를 분석, 개선, 모니터링하는 과정을 설명한다. 이를 통하여 6시그마와 BPM의 장점을 결합하여, 지속적으로 업무를 개선하고 관리함으로써 전사적인 경영성과를 극대화할 수 있을 것으로 기대한다.

Six Sigma has been adopted for the last two decades in many industries of manufacturing and service business to implement processs improvement. The methodology has difficulties in discovering target projects in the Define step and in controlling continuous measure and control in the Control step. To address the problem, more advanced system is required to support continuous control and management, and business process management (BPM) can be an effective solution for this problem. In this research, we introduce integrated models of Six Sigma and BPM for the purpose of realizing continuous process improvement, and explain the procedure of analyzing, improving, and monitoring the processes based on the data which has been accumulated in business process execution. It is expected that this integrated approach can maximize business performance by improving and managing business continuously on the integrated platform of two business innovation strategies, Six Sigma and BPM.