MODELING AND ANALYSIS OF SPLIT AND MERGE PRODUCTION SYSTEMS

Many production systems have split and merge operations to increase production capac- ity and variety, improve product quality, and implement product control and scheduling policies. This thesis presents analytical methods to model and analyze split and merge production systems with Bernoulli and exponential reliability machines under circulate, priority and percentage policies. The recursive procedures for performance analysis are de- rived, and the convergence of the procedures and uniqueness of the solutions, along with the structural properties, are proved analytically, and the accuracy of the estimation is justi¯ed numerically with high precision. In addition, comparisons among the e®ects of di®erent policies in system performance are carried out

Analysis of methods

Information is one of an organization's most important assets. For this reason the development and maintenance of an integrated information system environment is one of the most important functions within a large organization. The Integrated Information Systems Evolution Environment (IISEE) project has as one of its primary goals a computerized solution to the difficulties involved in the development of integrated information systems. To develop such an environment a thorough understanding of the enterprise's information needs and requirements is of paramount importance. This document is the current release of the research performed by the Integrated Development Support Environment (IDSE) Research Team in support of the IISEE project. Research indicates that an integral part of any information system environment would be multiple modeling methods to support the management of the organization's information. Automated tool support for these methods is necessary to facilitate their use in an integrated environment. An integrated environment makes it necessary to maintain an integrated database which contains the different kinds of models developed under the various methodologies. In addition, to speed the process of development of models, a procedure or technique is needed to allow automatic translation from one methodology's representation to another while maintaining the integrity of both. The purpose for the analysis of the modeling methods included in this document is to examine these methods with the goal being to include them in an integrated development support environment. To accomplish this and to develop a method for allowing intra-methodology and inter-methodology model element reuse, a thorough understanding of multiple modeling methodologies is necessary. Currently the IDSE Research Team is investigating the family of Integrated Computer Aided Manufacturing (ICAM) DEFinition (IDEF) languages IDEF(0), IDEF(1), and IDEF(1x), as well as ENALIM, Entity Relationship, Data Flow Diagrams, and Structure Charts, for inclusion in an integrated development support environment

Modeling and Optimization of Disassembly Systems with a High Variety of End of Life States.

Remanufacturing is a promising product recovery method that brings new life to cores that otherwise would be discarded thus losing all value. Disassembly is a sub-process of remanufacturing where components and modules are removed from the core, sorted and graded, and directly reused, refurbished, recycled, or disposed of. Disassembly is the backbone of the remanufacturing process because this is where the reuse value of components and modules is realized. Disassembly is a process that is also very difficult in most instances because it is a mostly manual process creating stochastic removal times of components. There is a high variety of EOL states a core can be in when disassembled and an economic downside due to not all components having reuse potential. This thesis focuses on addressing these difficulties of disassembly in the areas of sequence generation, line balancing, and throughput modeling. In Chapter 2, we develop a series of sequence generation models that considers the material properties, partial disassembly, and sequence dependent task times to determine the optimal order of disassembly in the presence of a high variety of EOL states. In Chapter 3, we develop a joint precedence graph method for disassembly that models all possible EOL states a core can be in that can be used with a wide variety of line balancing algorithms. We also develop a stochastic joint precedence graph method in the situation where some removal times of components are normal random variables. In Chapter 4, we further advance the analytical modeling framework to analyze transfer lines that perform routing logics that result from a high variety of EOL states, such as a restrictive split routing logic and the possibility that disassembly and split operations can be performed at the same workstation.PhDIndustrial and Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111570/1/robriggs_1.pd

A tight bound on the throughput of queueing networks with blocking

In this paper, we present a bounding methodology that allows to compute a tight lower bound on the cycle time of fork--join queueing networks with blocking and with general service time distributions. The methodology relies on two ideas. First, probability masses fitting (PMF) discretizes the service time distributions so that the evolution of the modified network can be modelled by a Markov chain. The PMF discretization is simple: the probability masses on regular intervals are computed and aggregated on a single value in the orresponding interval. Second, we take advantage of the concept of critical path, i.e. the sequence of jobs that covers a sample run. We show that the critical path can be computed with the discretized distributions and that the same sequence of jobs offers a lower bound on the original cycle time. The tightness of the bound is shown on computational experiments. Finally, we discuss the extension to split--and--merge networks and approximate estimations of the cycle time.queueing networks, blocking, throughput, bound, probability masses fitting, critical path.

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

Optimal Topological Arrangement of Queues in Closed Finite Queueing Networks

Closed queueing networks are widely used in many different kinds of scientific and business applications. Since the demands of saving energy and reducing costs are becoming more and more significant with developing technologies, finding a systematic methodology for getting the best arrangement is very important. In this thesis, design rules are proposed for tandem and various other topologies, to help the designer find the best arrangements which maximize the throughput. Our topological arrangements problem (TAP) can be established as: the system has m-service stations in a network and each one may have different design parameters. To relax the queueing system, the original finite buffer queue is decomposed into a buffer and an infinite buffer server system. Mean Value Analysis (MVA) is used to measure the performance of each topology arrangement. Finally, mixed-integer sequential quadratic programming (MISQP) is used to solve the optimization problem and it is compared with enumeration and a simulation model of Arena (a discrete-event model)