Quantification of Model-Form, Predictive, and Parametric Uncertainties in Simulation-Based Design

Traditional uncertainty quantification techniques in simulation-based analysis and design focus upon on the quantification of parametric uncertainties-inherent natural variations of the input variables. This is done by developing a representation of the uncertainties in the parameters and then efficiently propagating this information through the modeling process to develop distributions or metrics regarding the output responses of interest. However, in problems with complex or newer modeling methodologies, the variabilities induced by the modeling process itself-known collectively as model-form and predictive uncertainty-can become a significant, if not greater source of uncertainty to the problem. As such, for efficient and accurate uncertainty measurements, it is necessary to consider the effects of these two additional forms of uncertainty along with the inherent parametric uncertainty. However, current methods utilized for parametric uncertainty quantification are not necessarily viable or applicable to quantify model-form or predictive uncertainties. Additionally, the quantification of these two additional forms of uncertainty can require the introduction of additional data into the problem-such as experimental data-which might not be available for particular designs and configurations, especially in the early design-stage. As such, methods must be developed for the efficient quantification of uncertainties from all sources, as well as from all permutations of sources to handle problems where a full array of input data is unavailable. This work develops and applies methods for the quantification of these uncertainties with specific application to the simulation-based analysis of aeroelastic structures

A Semantic Data Model to Represent Building Material Data in AEC Collaborative Workflows

The specification of building material is required in multiple phases of engineering and construction projects towards holistic BIM implementations. Building material information plays a vital role in design decisions by enabling different simulation processes, such as energy, acoustic, lighting, etc. Utilization and sharing of building material information between stakeholders are some of the major influencing factors on the practical implementation of the BIM process. Different meta-data schemas (e.g. IFC) are usually available to represent and share material information amongst partners involved in a construction project. However, these schemas have their own constraints to enable efficient data sharing amongst stakeholders. This paper explains these constraints and proposes a methodological approach for the representation of material data using semantic web concepts aiming to support the sharing of BIM data and interoperability enhancements in collaboration workflows. As a result, the DICBM (https://w3id.org/digitalconstruction/BuildingMaterials) ontology was developed which improves the management of building material information in the BIM-based collaboration process.:Abstract 1. Introduction and Background 1.1 Building Information Modeling for collaboration 1.2 Information management in AEC using semantic web technologies 2 DICBM: Digital Construction Building Material Ontology 2.1 Building Material Data in IFC 2.2 Overview of the building material ontology 2.3 Integration of external ontology concepts and roles 2.4 Material Definition 2.5 Material, Material Type, and Material Property 2.6 Data Properties in DICBM 3 Conclusions Acknowledgments Reference

A Service Life Analysis of Coast Guard C-130 Aircraft

The U. S. Coast Guard, much like the rest of the Armed Services, is facing a dramatic transformation of its forces to meet current and future service requirements. The Coast Guard has responded to this transformation by initiating the Deepwater System, a complete review of the offshore mission requirements and the modernization of its infrastructure. In particular, Deepwater will review and modernize the Coast Guard\u27s aviation assets, improving aircraft systems, airborne sensors, and communications and information management systems. However, these capability advancements will take time and money to implement, and will require careful management of the current resources to ensure a smooth transition. One of the oldest and most versatile Coast Guard aircraft is the C-130, which the Coast Guard uses for Long Range Surveillance missions (LRS), as well as for logistics transport. Service life decisions regarding the C-130 are complicated by aging aircraft issues, and the forced introduction of a new generation C-130. It will be difficult for Coast Guard decision makers to select how program funding should be executed within the C-130 fleet. This study examines how long the current airframes can safely remain in service, how much the remaining service life will cost, and what level of availability can be realized for the rest of the service life. Once these questions can be reasonably answered, it will then be possible to perform an insightful and justifiable analysis of alternatives for modernizing, sustaining, and if necessary retiring the C-130s.46 Leaders at the United States Coast Guard\u27s Aircraft Repair and Service Center (ARSC) in Elizabeth City, North Carolina recently formalized their planning and analysis functions by adding a dedicated branch to their command structure. The Planning and Analysis Branch intends to apply computer modeling and simulation to study the impact of process changes to the various Programmed Depot Maintenance (PDM) lines. This research considers the applicability of this type of modeling and simulation, using ARENA to study the current HH-6OJ PDM process. The contribution of this research is a methodology specific to ARSC needs, an analysis of methodology based on a discrete event simulation model of PDM lines, and a specific case study demonstrating the methodologies. The response variable of interest is average PDM process time as a function of either in-sourcing or out-sourcing labor for a major process step. The research includes development and evaluation of a macro-level process model using ARENA 5.0

BIM Integrated and Reference Process-based Simulation Method for Construction Project Planning

Die Verwendung von Simulationen zur Unterstützung traditioneller Planungsverfahren für Bauprojekte hat viele Vorteile, die in verschiedenen akademischen Forschungen vorgestellt wurden. Viele Anwendungen haben erfolgreich das Potenzial der Simulationsmethode zur Verbesserung der Qualität der Projektplanung demonstriert. Doch eine breite Anwendung der Simulationsmethoden zur Unterstützung der Planung von Bauprojekten konnte sich in der Praxis bis zum jetzigen Zeitpunkt nicht durchsetzen. Aufgrund einiger großer Hindernisse und Herausforderungen ist der Einsatz im Vergleich zu anderen Branchen noch sehr begrenzt. Die Komplexität sowie die dynamischen Wechselprozesse der unterschiedlichen Bauvorhaben stellen die erste Herausforderung dar.Die Anforderungen machen es sehr schwierig die verschieden Situationen realistisch zu modellieren und das Verhalten von Bauprozessen und die Interaktion mit den zugehörigen Ressourcen für reale Bauvorhaben darzustellen. Das ist einer der Gründe für den Mangel an speziellen Simulationswerkzeugen in der Bauprojektplanung. Die zweite Herausforderung besteht in der großen Menge an Projektinformationen, die in das Simulationsmodell integriert und während des gesamten Lebenszyklus des Projekts angepasst werden müssen. Die Erstellung von Simulationsmodellen, Simulationsszenarien sowie die Analyse und Verifizierung der Simulationsergebnisse ist langwierig. Ad-hoc Simulation sind daher nicht möglich. Zur Erstellung zuverlässiger Simulationsmodelle sind daher umfangreiche Ressourcen und Mitarbeiter mit speziellen Fachwissen erforderlich. Die vorgestellten Herausforderungen verhindern die breite Anwendung der Simulationsmethode zur Unterstützung der Bauprojektplanung und das Einsetzen der Software als wesentlicher Bestandteil des Arbeitsablaufes für die Bauplanung in der Praxis. Die Forschungsarbeit in dieser Arbeit befasst sich mit diesen Herausforderungen durch die Entwicklung eines Ansatzes sowie einer Plattform für die schnelle Aufstellung von Simulationsmodellen für Bauprojekte. Das Hauptziel dieser Forschung ist die Entwicklung eines integrierten und referenzmodellbasierten BIM Simulationsansatz zur Unterstützung der Planung von Bauprojekten und die Möglichkeit der Zusammenarbeit aller am Planungs- und Simulationsprozess beteiligten Akteure. Die erste Herausforderung wird durch die Einführung eines RPM-Konzepts (Reference Process Model) durch die Modellierung von Konstruktionsprozessen unter Verwendung von Business Process Modeling and Notation (BPMN) angegangen. Der Vorteil der RPM Modelle ist das sie bearbeitet und modifiziert können und dass sie automatisch als einsatzbereite Module in Simulationsmodelle umgewandelt werden können. Die RPM-Modelle enthalten auch Informationen zu Ressourcenanforderungen und andere verwandte Informationen für verschiedene Baubereiche mit unterschiedlichen Detaillierungsgraden. Die Verwendung von BPMN hat den Vorteil, dass die Simulationsmodellierung für das Projektteam, einschließlich derjenigen, die sich nicht mit der Simulation auskennen, flexibler, interoperabler und verständlicher ist. Bei diesem Ansatz ist die Modellierung von Referenzprozessmodellen vollständig von den Simulationskernkomponenten getrennt, um das Simulations-Toolkit generisch und erweiterbar für verschiedenste Konstruktionsbereiche wie Gebäude und Brücken. Der vorgestellte Forschungsansatz unterstützt die kontinuierliche Anwendung von Simulationsmodellen während des gesamten Projektlebenszyklus. Die Simulationsmodelle, die zur Unterstützung der Planung in der frühen Entwurfsphase erstellt werden, können von Simulationsexperten während der gesamten Planungs- und Bauphase weiter ausgebaut und aktualisiert werden. Die zweite Herausforderung wird durch die direkte Integration der Building Information Modeling (BIM) -Methode in die Simulationsmodellierung auf der Grundlage des Industry Foundation Classes-IFC (ISO 16739) , dem am häufigsten verwendeten BIM-Austauschformat, angegangen. Da die BIM-Modelle einen wichtigen Teil der Eingabeinformationen von Simulationsmodellen enthalten, können sie als Grundlage für die Visualisierung von Ergebnissen in Form von 4D-BIM-Modellen verwendet werden. Diese Integration ermöglicht die schnelle und automatische Filterung und Extraktion sowie die Umwandlung notwendiger Informationen aus BIM Entwurf-Modellen. Um die Erstellung detaillierter Projektmodelle zu beschleunigen, wurde eine spezielle Methode für die halbautomatische Top-Down-Detaillierung von Projektstammmodelle entwickelt, die notwendige Eingangsdaten für die Simulationsmodelle sind. Diese Methode bietet den Vorteil, dass Konstruktionsalternativen mit minimalen Änderungen am Simulationsmodell untersucht werden können. Der entwickelte Ansatz wurde als Software- Prototyp in Form eines modularen Construction Simulation Toolkit (CST) basierend auf der Discrete Event Simulation (DES)- Methode und eines Collaboration- Webportals (ProSIM) zum Verwalten von Simulationsmodellen implementiert. Die so eingebettete Simulation ermöglicht mit minimalen Änderungen die Bewertung von Entwurfsalternativen und Konstruktionsmethoden auf den Bauablauf. Produktions- und Logistiksvorgänge können gleichzeitig in einer einheitlichen Umgebung simuliert werden und berücksichtigen die gemeinsam genutzten Ressourcen und die Interaktion zwischen Produktions- und Logistikaktivitäten. Es berücksichtigt auch die Änderungen im Baustellenlayout während der Konstruktionsphase. Die Verifizierung und Validierung des vorgeschlagenen Ansatzes wird durch verschiedene hypothetische und reale Bauprojekten durchgeführt.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 ReferencesUsing simulation to support construction project planning has many advantages, which have been presented in various academic researches. Many applications have successfully demonstrated the potential of using simulation to improve the quality of construction project planning. However, the wide adoption of simulation has not been achieved in practice yet. It still has very limited use compared with other industries due to some major obstacles and challenges. The first challenge is the complexity of construction processes and projects planning methods, which make it very difficult to develop realistic simulation models of construction processes and represent their dynamic behavior and the interaction with project resources. This led to lack of special simulation tools for construction project planning. The second challenge is the huge amount of project information that has to be integrated into the simulation model and to be maintained throughout the design, planning and construction phases. The preparation of ad-hoc simulation models and setting up different scenarios and verification of simulation results usually takes a long time. Therefore, creating reliable simulation models requires extensive resources with advanced skills. The presented challenges prevent the wide application of simulation techniques to support and improve construction project planning and adopt it as an essential part of the construction planning workflow in practice. The research work in this thesis addresses these challenges by developing an approach and platform for rapid development of simulation models for construction projects. The main objective of this research is to develop a BIM integrated and reference process-based simulation approach to support planning of construction projects and to enable collaboration among all actors involved in the planning and simulation process. The first challenge has been addressed through the development of a construction simulation toolkit and the Reference Process Model (RPM) method for modelling construction processes for production and logistics using Business Process Modelling and Notation (BPMN). The RPM models are easy to understood also by non-experts and they can be transformed automatically into simulation models as ready-to-use modules. They describe the workflow and logic of construction processes and include information about duration, resource requirements and other related information for different construction domains with different levels of details. The use of BPMN has many advantages. It enables the understanding of how simulation models work by project teams, including those who are not experts in simulation. In this approach, the modelling of Reference Process Models is totally separated from the simulation core components. In this way, the simulation toolkit is generic and extendable for various construction types such as buildings, bridges and different construction domains such as structural work and indoor operations. The presented approach supports continuous adoption of simulation models throughout the whole project life cycle. The simulation model which supports project planning in the early design phase can be continuously extended with more detailed RPMs and updated information through the planning and construction phases. The second challenge has been addressed by supporting direct integration of Building Information Modelling (BIM) method with the simulation modelling based on the Industry Foundation Classes IFC (ISO 16739) standard, which is the most common and only ISO standard used for exchanging BIM models. As the BIM models contain the biggest part of the input information of simulation models and they can be used for effective visualization of results in the form of animated 4D BIM models. The integration between BIM and simulation enables fast and semi-automatic filtering, extraction and transformation of the necessary information from BIM models for both design and construction site models. In addition, a special top-down semi-automatic detailing method was developed in order to accelerate the process of preparing detailed project schedules, which are essential input data for the simulation models and hence reduce the time and efforts needed to create simulation models. The developed approach has been implemented as a software prototype in the form of a modular Construction Simulation Toolkit (CST) based on the Discrete Event Simulation (DES) method and an online collaboration web portal 'ProSIM' for managing simulation models. The collaboration portal helps to overcome the problem of huge information and make simulation models accessible for non simulation experts. Simulation models created by CST toolkit facilitate the evaluation of design alternatives and construction methods with minimal changes in the simulation model. Both production and logistic operations can be simulated at the same time in a unified environment and take into account the shared resources and the interaction between production and logistic activities. It also takes into account the dynamic nature of construction projects and hence the changes in the construction site layout during the construction phase. The verification and validation of the proposed approach is carried out through various academic and real construction project case studies.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 Reference

공정 설계 및 최적화에 대한 위험성 기반 내재적 안전성 접근법

학위논문(박사)--서울대학교 대학원 :공과대학 화학생물공학부,2020. 2. 이종민.The role of process safety is to prevent potential disasters in the chemical process. While a variety of techniques are commonly used in the field, accurate risk assessment and analysis require quantitative methods to allow direct comparisons between different alternatives or designs, among other benefits. However, there are various processes with different characteristics and complexities, and not all methods can be equally applied. It is essential to consider safety according to the characteristic of each process and to establish a design method which considers safety from the initial design stage to the operation stage. However, most process safety approaches, such as Quantitative Risk Assessment (QRA) or Hazard and Operability (HAZOP) studies, are conducted at the end of the design process and often have expansive and time-consuming drawbacks due to their repetitive nature. Therefore this thesis proposed a risk-based design method and modeling for designing an inherently safe process to consider the economic feasibility and process safety simultaneously. The thesis deals with elements such as process knowledge management, process safety information, inherently safe design, process hazard analysis for the system configuration required to analyze, and understand the potential risk during the process design and operation. As for the process to apply this, natural gas-related processes, which are recently attracting attention due to the development of shale gas and small and medium-sized gas reservoirs were selected, to determine the optimal design of natural gas liquefaction process. In Chapter 2 of this thesis, the accident models used in the chemical process were analyzed, and the development and validation of the necessary indoor release model were addressed. Chapter 3 covered interactive simulation that uses process data during accident modeling. Finally, Chapter 4 presented a multi-objective optimization methodology to design a safer process by introducing risk modeling and inherent safety. The method is applied to the preliminary design stage of the natural gas liquefaction process and found the result that considers process safety as well as economic feasibility. The limitations of conventional designs using the concept of inherent safety were overcome by implementing the quantitative risk assessment procedure directly in the optimization sequence.화학 공정 안전은 공정의 위험을 평가하기 위해 수행된다. 여러 기법들 중 일반적으로 공정 관리 단계에서는 다양한 기법이 사용되지만, 특히 공정 안전성과 위험성을 정확하게 평가하고 분석하려면 서로 다른 설계나 대안 등과 직접적인 비교를 가능하게 하는 정량적 방법이 필요하게 된다. 하지만 특성과 복잡성이 다른 다양한 공정들이 존재하기 때문에 각 공정의 특성에 따라 안전을 고려해야 하고, 초기 설계 단계부터 운영 단계까지 안전을 고려한 화학 공정 설계 방법을 확립하는 것이 중요하다. 그러나 QRA (Quantitative Risk Assessment) 또는 HAZOP (Hazard and Operability study) 연구와 같은 대부분의 공정 안전 접근 방식은 설계 절차 마지막에 고려되고, 종종 반복적이거나 시간 소모적인 특성으로 인해 긴 시간과 많은 비용이 드는 단점이 존재한다. 따라서 본 연구는 공정의 경제적 타당성과 안전성을 동시에 고려하기 위해 본질적으로 안전한 공정을 설계하는 것을 목표로 하여 위험 기반 설계 방법과 설계에 필요한 모델링을 제안하였다. 따라서 본 논문에서는 공정 설계 및 운영 중에 발생할 수 있는 위험을 분석하고 이해하는 데 필요한 시스템 구성을 위해 공정 지식 관리, 공정 안전 정보, 내재적으로 안전한 설계, 공정 위험 분석, 프로젝트 경제성 검토 등의 요소들을 다루었다. 이를 적용할 공정으로는 최근 셰일 가스 및 중소규모 가스전 등의 개발로 주목 받고 있는 천연가스 관련 공정을 선정하여 최종적으로 다목적 최적화를 통한 LNG 액화 공정의 최적 설계를 결정하는 것을 목표로 하였다. 본 논문의 2장에서는 화학사고 결과 모델링에 대해 다루어 화학 공정에서 사용되는 모델들에 대한 분석이 행해졌으며 추가로 필요하다고 고려되는 실내 유출 모델에 대한 개발 및 검증이 제시되었다. 3장에서는 공정 정보를 사고 모델링에 사용하는 인터랙티브 시뮬레이션에 대해서 다루었다. 최종적으로 4장에서 이상의 결과물들을 적용하여 보다 안전한 공정을 설계하기 위한 목적으로 내재적 안전성의 개념을 도입한 다목적 최적화 방법론을 제시하였으며, 이를 천연가스 액화공정의 예비 설계단계에 적용하여 경제성과 안전성을 동시에 고려한 결과를 찾아냈다. 이 과정에서 기존 내재적 안전성을 고려한 설계들이 가지고 있던 한계를 정량적 위험성 평가 절차를 최적화 과정에 직접 구현하는 것을 통해 보완하였다.CHAPTER 1. Introduction 1 1.1. Research motivation 1 1.2. Research objective 5 1.3. Outline 6 CHAPTER 2. Accident models in Chemical Process Industries 7 2.1. Introduction 7 2.2. Analysis of conventional accident models for chemical processes 9 2.3. Development of indoor release model 12 2.4. Mitigation effect analysis 35 2.5. Concluding remarks 43 CHAPTER 3. Interactive Process-Accident Simulation 45 3.1. Introduction 45 3.2. Gas pressure regulation station case study 46 3.3. Concluding remarks 53 CHAPTER 4. Process Design with Inherent Safety 54 4.1. Introduction 54 4.2. Process description 61 4.3. Design optimization 68 4.4. Concluding remarks 86 CHAPTER 5. Conclusion 88 Nomenclature 89 References 92 Abstract in Korean (국문초록) 99Docto

On Modeling and Analyzing Cost Factors in Information Systems Engineering

Introducing enterprise information systems (EIS) is usually associated with high costs. It is therefore crucial to understand those factors that determine or influence these costs. Though software cost estimation has received considerable attention during the last decades, it is difficult to apply existing approaches to EIS. This difficulty particularly stems from the inability of these methods to deal with the dynamic interactions of the many technological, organizational and projectdriven cost factors which specifically arise in the context of EIS. Picking up this problem, we introduce the EcoPOST framework to investigate the complex cost structures of EIS engineering projects through qualitative cost evaluation models. This paper extends previously described concepts and introduces design rules and guidelines for cost evaluation models in order to enhance the development of meaningful and useful EcoPOST cost evaluation models. A case study illustrates the benefits of our approach. Most important, our EcoPOST framework is an important tool supporting EIS engineers in gaining a better understanding of the critical factors determining the costs of EIS engineering projects