A Review Of Design And Control Of Automated Guided Vehicle Systems

This paper presents a review on design and control of automated guided vehicle systems. We address most key related issues including guide-path design, estimating the number of vehicles, vehicle scheduling, idle-vehicle positioning, battery management, vehicle routing, and conflict resolution. We discuss and classify important models and results from key publications in literature on automated guided vehicle systems, including often-neglected areas, such as idle-vehicle positioning and battery management. In addition, we propose a decision framework for design and implementation of automated guided vehicle systems, and suggest some fruitful research directions

Dynamic Modeling, Sensor Placement Design, and Fault Diagnosis of Nuclear Desalination Systems

Fault diagnosis of sensors, devices, and equipment is an important topic in the nuclear industry for effective and continuous operation of nuclear power plants. All the fault diagnostic approaches depend critically on the sensors that measure important process variables. Whenever a process encounters a fault, the effect of the fault is propagated to some or all the process variables. The ability of the sensor network to detect and isolate failure modes and anomalous conditions is crucial for the effectiveness of a fault detection and isolation (FDI) system. However, the emphasis of most fault diagnostic approaches found in the literature is primarily on the procedures for performing FDI using a given set of sensors. Little attention has been given to actual sensor allocation for achieving the efficient FDI performance. This dissertation presents a graph-based approach that serves as a solution for the optimization of sensor placement to ensure the observability of faults, as well as the fault resolution to a maximum possible extent. This would potentially facilitate an automated sensor allocation procedure. Principal component analysis (PCA), a multivariate data-driven technique, is used to capture the relationships in the data, and to fit a hyper-plane to the data. The fault directions for different fault scenarios are obtained from the prediction errors, and fault isolation is then accomplished using new projections on these fault directions. The effectiveness of the use of an optimal sensor set versus a reduced set for fault detection and isolation is demonstrated using this technique. Among a variety of desalination technologies, the multi-stage flash (MSF) processes contribute substantially to the desalinating capacity in the world. In this dissertation, both steady-state and dynamic simulation models of a MSF desalination plant are developed. The dynamic MSF model is coupled with a previously developed International Reactor Innovative and Secure (IRIS) model in the SIMULINK environment. The developed sensor placement design and fault diagnostic methods are illustrated with application to the coupled nuclear desalination system. The results demonstrate the effectiveness of the newly developed integrated approach to performance monitoring and fault diagnosis with optimized sensor placement for large industrial systems

A framework for assessing robustness of water networks and computational evaluation of resilience.

Arid regions tend to take careful measures to ensure water supplies are secured to consumers, to help provide the basis for further development. Water distribution network is the most expensive part of the water supply infrastructure and it must maintain performance during unexpected incidents. Many aspects of performance have previously been discussed separately, including reliability, vulnerability, flexibility and resilience. This study aimed to develop a framework to bring together these aspects as found in the literature and industry practice, and bridge the gap between them. Semi-structured interviews with water industry experts were used to examine the presence and understanding of robustness factors. Thematic analysis was applied to investigate these and inform a conceptual framework including the component and topological levels. Robustness was described by incorporating network reliability and resiliency. The research focused on resiliency as a network-level concept derived from flexibility and vulnerability. To utilise this new framework, the study explored graph theory to formulate metrics for flexibility and vulnerability that combine network topology and hydraulics. The flexibility metric combines hydraulic edge betweenness centrality, representing hydraulic connectivity, and hydraulic edge load, measuring utilised capacity. Vulnerability captures the impact of failures on the ability of the network to supply consumers, and their sensitivity to disruptions, by utilising node characteristics, such as demand, population and alternative supplies. These measures together cover both edge (pipe) centric and node (demand) centric perspectives. The resiliency assessment was applied to several literature benchmark networks prior to using a real case network. The results show the benefits of combining hydraulics with topology in robustness analysis. The assessment helps to identify components or sections of importance for future expansion plans or maintenance purposes. The study provides a novel viewpoint overarching the gap between literature and practice, incorporating different critical factors for robust performance

A Polyhedral Study of Mixed 0-1 Set

We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set

Synthetic models of distribution gas networks in low-carbon energy systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Locating and Protecting Facilities Subject to Random Disruptions and Attacks

Recent events such as the 2011 Tohoku earthquake and tsunami in Japan have revealed the vulnerability of networks such as supply chains to disruptive events. In particular, it has become apparent that the failure of a few elements of an infrastructure system can cause a system-wide disruption. Thus, it is important to learn more about which elements of infrastructure systems are most critical and how to protect an infrastructure system from the effects of a disruption. This dissertation seeks to enhance the understanding of how to design and protect networked infrastructure systems from disruptions by developing new mathematical models and solution techniques and using them to help decision-makers by discovering new decision-making insights. Several gaps exist in the body of knowledge concerning how to design and protect networks that are subject to disruptions. First, there is a lack of insights on how to make equitable decisions related to designing networks subject to disruptions. This is important in public-sector decision-making where it is important to generate solutions that are equitable across multiple stakeholders. Second, there is a lack of models that integrate system design and system protection decisions. These models are needed so that we can understand the benefit of integrating design and protection decisions. Finally, most of the literature makes several key assumptions: 1) protection of infrastructure elements is perfect, 2) an element is either fully protected or fully unprotected, and 3) after a disruption facilities are either completely operational or completely failed. While these may be reasonable assumptions in some contexts, there may exist contexts in which these assumptions are limiting. There are several difficulties with filling these gaps in the literature. This dissertation describes the discovery of mathematical formulations needed to fill these gaps as well as the identification of appropriate solution strategies

Advanced decision support through real-time optimization in the process industry

En la industria de procesos se puede obtener un aumento de la eficiencia de las plantas de producción, bien mediante la sustitución de procesos o equipos antiguos por otros más modernos y eficientes, o bien operando de forma más eficiente las instalaciones actuales en lugar de realizar grandes inversiones con tiempos de amortización inciertos. Si nos centramos en esta segunda línea de acción, hoy en día la toma de decisiones es conceptualmente más compleja que en el pasado, debido al rápido crecimiento que ha tenido la tecnología últimamente y a que los sistemas de comunicación han generado un gran número de alternativas entre las que se ha de elegir. Además, una decisión incorrecta o subóptima, con la complejidad estructural de los problemas actuales, a menudo resulta en un aumento de los costes a lo largo de la cadena de producción. A pesar de ello, el uso de sistemas de apoyo a la toma de decisiones (DSS) sigue siendo atípico en las industrias de procesos debido a los esfuerzos que se requieren en términos de desarrollo y mantenimiento de modelos matemáticos y al desafío de formulaciones matemáticas complejas, los exigentes requisitos computacionales y/o la difícil integración con la infraestructura de control o planificación existente. Esta tesis contribuye en la reducción de estas barreras desarrollando formulaciones eficientes para la optimización en tiempo real (RTO) en una planta industrial. En particular, esta tesis busca mejorar la operación de tres secciones interconectadas de una fábrica de producción de fibra de viscosa: una red de evaporación, una de sistema de enfriamiento y una red de recuperación de calor.Departamento de Ingeniería de Sistemas y AutomáticaDoctorado en Ingeniería Industria

Unified modelling of aerospace systems: a bond graph approach

Systems Integration is widely accepted as the basis for improving the efficiency and performance of many engineering products. The aim is to build a unified optimised system not a collection of subsystems that are combined in some ad hoc manner. This moves traditional design boundaries and, in so doing, enables a structured evolution from an integrated system concept to an integrated system product. It is recognised that the inherent complexity cannot be handled effectively without mathematical modelling. The problem is not so much the large number of components but rather the very large number of functional interfaces that result. The costs involved are high and, if the claims of improved efficiency and performance are to be affordable (or even achievable), predictive modelling and analysis will play a major role in reducing risk. A modelling framework is required which can support integrated system development from concept through to certification. This means building a 'system' inside a computer and demonstrating the feasibility of an entire development cycle. The objective is to provide complete coverage of system functionality so as to gain confidence in the design before becoming locked into a full development programme with associated capital investment and contractual arrangements. With these points in mind the purpose of this thesis is threefold. First, to demonstrate the application of bond graphs as a unified modelling framework for aerospace systems. Second, to review the main principles involved with the modelling of engineering systems and to justify the selection of the bond graph notation as a suitable means of representing the power flow (i.e. the dynamics) of physical systems. Third, to present an exposition of the bond graph method and to evolve it into a versatile notation for integrated systems. The originality of the work is based on the recognition that systems integration is a relatively new field of interest without a mature body of academic literature or reported research. Apparently, there is no open literature on the modelling of complete air vehicles plus their embedded vehicle systems which deals with issues of integrated dynamics and control. To this end, bond graph concepts need to be developed and extended in new direction in order to facilitate an intuitive approach to the modelling of integrated systems

Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed