Criticality of infrastructure networks under consideration of resilience-based maintenance strategies using the example of inland waterways

Transportation infrastructures as backbone of modern, globalized, and networked societies ensure flows of people and goods and thus sustain social and economic prosperity. Concurrently, more and more infrastructure construction assets are facing the problem of systematic obsolescence due to deficient structural conditions, maintenance backlogs, and a lack of or misallocation of resources for the construction and maintenance of infrastructure buildings. This problem construct necessitates a resilience-based maintenance strategy for the asset portfolio. In particular, inland navigation as a mode of transport features large transport volumes and few redundancies. Combined with its increasing importance due to its comparatively high environmental friendliness, a predestined, yet in the literature underrepresented research subject results. This dissertation aims to investigate essential factors of infrastructure management and thereby identify the potential for improvement in the complex construct of maintenance management and related areas. The emphasis is on enhancing the resilience of inland waterways as a complex System-of-Systems with all its interdependencies. Thus, a holistic risk and resilience assessment is essential and is underlined with the aspects infrastructure availability and business decisions (Study A, B, C and D) and stakeholder communication and risk analysis (Study E, F, G) which are addressed by seven studies published as companion articles. Study A deals with assessing the reliability of transport infrastructure networks as part of supply chains, highlighting the importance of available and thus maintained infrastructure assets for functioning supply chains. Study B aims to identify critical warning times before closures of transport infrastructure networks and therefore suggests a mixed-methods approach, making it possible to derive and evaluate critical thresholds. Study C examines the corresponding company decisions, i.e., decisions as reaction towards neglected maintenance of public transport infrastructure, which comprises risk coping strategies, examined by empirical investigations. Study D extends this problem observation by showing that companies could see incentives for outsourcing if they face a lack of access to available transport infrastructure. Hence, the study analyzes facility relocation problems in dependence on infrastructure availability. Study E heads toward stakeholder communication and risk analysis and examines the processes across stakeholders, using an approach of collaborative serious gaming, which simultaneously enhances situation awareness and communication among stakeholders. Study F provides the implementation of a systemic approach and its visualization as a GIS-based risk dashboard, shedding light on interdependencies among critical infrastructures and cascading effects. Study G closes with an examination of the evaluation of the potential of infrastructure funds. For this purpose, the study conducts an online survey to determine investors’ willingness to pay for various fund mechanisms, integrating the option of private coverage. Despite the geographic focus of the case studies on Germany, valuable insights can be gained for infrastructure management that can also apply to other countries. In addition to the case study findings, general recommendations for infrastructure owners are derived. As a result, it can be stated that it is essential that maintenance strategies have to be more resilience-based than traditional strategies, which are mainly based on fixed time intervals for maintenance. Moreover, the application of both serious gaming and GIS visualization can help to enhance situation awareness and thus the resilience of infrastructure systems. An essential finding for which this dissertation provides methodological approaches is that considering the local area’s attractiveness for business locations should receive more attention regarding investment decisions. Thereby a focus should be set on the realistic threat of relocations as response to deteriorating infrastructure conditions. Eventually, public debates should strengthen the knowledge about infrastructure and its funding, while deficits in alongside mechanisms in infrastructure funding must be encountered. Consequently, this dissertation provides insights into the potential of infrastructure management. Mainly, it offers the potential to improve the resilience of the waterway transportation system and address stakeholders accordingly

Production Engineering and Management

It is our pleasure to introduce the 8th edition of the International Conference on Production Engineering and anagement (PEM), an event that is the result of the joint effort of the OWL University of Applied Sciences and the University of Trieste. The conference has been established as an annual meeting under the Double Degree Master Program “Production Engineering and Management” by the two partner universities. This year the conference is hosted at the university campus in Lemgo, Germany. The main goal of the conference is to offer students, researchers and professionals in Germany, Italy and abroad, an opportunity to meet and exchange information, discuss experiences, specific practices and technical solutions for planning, design, and management of manufacturing and service systems and processes. As always, the conference is a platform aimed at presenting research projects, introducing young academics to the tradition of symposiums and promoting the exchange of ideas between the industry and the academy. This year’s special focus is on Supply Chain Design and Management in the context of Industry 4.0, which are currently major topics of discussion among experts and professionals. In fact, the features and problems of Industry 4.0 have been widely discussed in the last editions of the PEM conference, in which sustainability and efficiency also emerged as key factors. With the further study and development of Direct Digital Manufacturing technologies in connection with new Management Practices and Supply Chain Designs, the 8th edition of the PEM conference aims to offer new and interesting scientific contributions. The conference program includes 25 speeches organized in seven sessions. Two are specifically dedicated to “Direct Digital Manufacturing in the context of Industry 4.0”. The other sessions are covering areas of great interest and importance to the participants of the conference, which are related to the main focus: “Supply Chai n Design and Management”, “Industrial Engineering and Lean Management”, “Wood Processing Technologies and Furniture Production”, and “Management Practices and Methodologies”. The proceedings of the conference include the articles submitted and accepted after a careful double-blind refereeing process

Intelligent Operation System for the Autonomous Vehicle Fleet

Modular vehicles are vehicles with interchangeable substantial components also known as modules. Fleet modularity provides extra operational flexibility through on-field actions, in terms of vehicle assembly, disassembly, and reconfiguration (ADR). The ease of assembly and disassembly of modular vehicles enables them to achieve real-time fleet reconfiguration, which is proven as beneficial in promoting fleet adaptability and in saving ownership costs. The objective of military fleet operation is to satisfy uncertain demands on time while providing vehicle maintenance. To quantify the benefits and burdens from modularity in military operation, a decision support system is required to yield autonomously operation strategies for comparing the (near) optimal fleet performance for different vehicle architectures under diverse scenarios. The problem is challenging because: 1) fleet operation strategies are numerous, especially when modularity is considered; 2) operation actions are time-delayed and time-varying; 3) vehicle damages and demands are highly uncertain; 4) available capacity for ADR actions and vehicle repair is constrained. Finally, to explore advanced tactics enabled by fleet modularity, the competition between human-like and adversarial forces is required, where each force is capable to autonomously perceive and analyze field information, learn enemy's behavior, forecast enemy's actions, and prepare an operation plan accordingly. Currently, methodologies developed specifically for fleet competition are only valid for single type of resources and simple operation rules, which are impossible to implement in modular fleet operation. This dissertation focuses on a new general methodology to yield decisions in operating a fleet of autonomous military vehicles/robots in both conventional and modular architectures. First, a stochastic state space model is created to represent the changes in fleet dynamics caused by operation actions. Then, a stochastic model predictive control is customized to manage the system dynamics, which is capable of real-time decision making. Including modularity increases the complexity of fleet operation problem, a novel intelligent agent based model is proposed to ensure the computational efficiency and also imitate the collaborative decisions making process of human-like commanders. Operation decisions are distributed to several agents with distinct responsibility. Agents are designed in a specific way to collaboratively make and adjust decisions through selectively sharing information, reasoning the causality between events, and learning the other's behavior, which are achieved by real-time optimization and artificial intelligence techniques. To evaluate the impacts from fleet modularity, three operation problems are formulated: (i) simplified logistic mission scenario: operate a fleet to guarantee the readiness of vehicles at battlefields considering the stochasticity in inventory stocks and mission requirements; (ii) tactical mission scenario: deliver resources to battlefields with stochastic requirements of vehicle repairs and maintenance; (iii) attacker-defender game: satisfy the mission requirements with minimized losses caused by uncertain assaults from an enemy. The model is also implemented for a civilian application, namely the real-time management of reconfigurable manufacturing systems (RMSs). As the number of RMS configurations increases exponentially with the size of the line and demand changes frequently, two challenges emerge: how to efficiently select the optimal configuration given limited resources, and how to allocate resources among lines. According to the ideas in modular fleet operation, a new mathematical approach is presented for distributing the stochastic demands and exchanging machines or modules among lines (which are groups of machines) as a bidding process, and for adaptively configuring these lines and machines for the resulting shared demand under a limited inventory of configurable components.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147588/1/lixingyu_2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147588/2/lixingyu_1.pd

Smart Sustainable Mobility: Analytics and Algorithms for Next-Generation Mobility Systems

To this date, mobility ecosystems around the world operate on an uncoordinated, inefficient and unsustainable basis. Yet, many technology-enabled solutions that have the potential to remedy these societal negatives are already at our disposal or just around the corner. Innovations in vehicle technology, IoT devices, mobile connectivity and AI-powered information systems are expected to bring about a mobility system that is connected, autonomous, shared and electric (CASE). In order to fully leverage the sustainability opportunities afforded by CASE, system-level coordination and management approaches are needed. This Thesis sets out an agenda for Information Systems research to shape the future of CASE mobility through data, analytics and algorithms (Chapter 1). Drawing on causal inference, (spatial) machine learning, mathematical programming and reinforcement learning, three concrete contributions toward this agenda are developed. Chapter 2 demonstrates the potential of pervasive and inexpensive sensor technology for policy analysis. Connected sensing devices have significantly reduced the cost and complexity of acquiring high-resolution, high-frequency data in the physical world. This affords researchers the opportunity to track temporal and spatial patterns of offline phenomena. Drawing on a case from the bikesharing sector, we demonstrate how geo-tagged IoT data streams can be used for tracing out highly localized causal effects of large-scale mobility policy interventions while offering actionable insights for policy makers and practitioners. Chapter 3 sets out a solution approach to a novel decision problem faced by operators of shared mobility fleets: allocating vehicle inventory optimally across a network when competition is present. The proposed three-stage model combines real-time data analytics, machine learning and mixed integer non-linear programming into an integrated framework. It provides operational decision support for fleet managers in contested shared mobility markets by generating optimal vehicle re-positioning schedules in real time. Chapter 4 proposes a method for leveraging data-driven digital twin (DT) frameworks for large multi-stage stochastic design problems. Such problem classes are notoriously difficult to solve with traditional stochastic optimization. Drawing on the case of Electric Vehicle Charging Hubs (EVCHs), we show how high-fidelity, data-driven DT simulation environments fused with reinforcement learning (DT-RL) can achieve (close-to) arbitrary scalability and high modeling flexibility. In benchmark experiments we demonstrate that DT-RL-derived designs result in superior cost and service-level performance under real-world operating conditions

Strategic technology decision-making in Swedish large-scale forestry

Technological development gives Swedish forest companies and forest owners’ associations opportunities to maintain competitiveness in the highly cost-sensitive market for forest products. Development efforts are typically performed through unstructured decision processes. However, an organization’s success is a product of its decisions, so the quality of these decisions is crucial. The main objectives of this thesis were therefore to describe and critically analyze strategic decision-making about forest technology. Study I investigated how and with what support forest companies and a forest owners’ association make decisions about forest technology. It was concluded that these organizations value collaborations with manufacturers and researchers, that economic criteria were most important in the decision-making process, and that large risks are preferably managed in a stepwise fashion. Study II reviewed the use of Multi-Criteria Decision Analysis (MCDA) methods in forest operations and it was shown that the methods were used at various temporal scales, most commonly when making strategic decisions. Study III developed and compared two modelling approaches for machine system analysis and concluded that they produced similar results despite having different levels of detail and demanding different competences. Study IV used the previously developed modelling approaches to compare the performance of established and new machine systems in Swedish final fellings, revealing an opportunity to reduce costs by adopting the new machine system. A conceptual flowchart for strategic decision making on forest technology development was created to improve the quality and efficiency of the decision-making process

New Fault Detection, Mitigation and Injection Strategies for Current and Forthcoming Challenges of HW Embedded Designs

Tesis por compendio[EN] Relevance of electronics towards safety of common devices has only been growing, as an ever growing stake of the functionality is assigned to them. But of course, this comes along the constant need for higher performances to fulfill such functionality requirements, while keeping power and budget low. In this scenario, industry is struggling to provide a technology which meets all the performance, power and price specifications, at the cost of an increased vulnerability to several types of known faults or the appearance of new ones. To provide a solution for the new and growing faults in the systems, designers have been using traditional techniques from safety-critical applications, which offer in general suboptimal results. In fact, modern embedded architectures offer the possibility of optimizing the dependability properties by enabling the interaction of hardware, firmware and software levels in the process. However, that point is not yet successfully achieved. Advances in every level towards that direction are much needed if flexible, robust, resilient and cost effective fault tolerance is desired. The work presented here focuses on the hardware level, with the background consideration of a potential integration into a holistic approach. The efforts in this thesis have focused several issues: (i) to introduce additional fault models as required for adequate representativity of physical effects blooming in modern manufacturing technologies, (ii) to provide tools and methods to efficiently inject both the proposed models and classical ones, (iii) to analyze the optimum method for assessing the robustness of the systems by using extensive fault injection and later correlation with higher level layers in an effort to cut development time and cost, (iv) to provide new detection methodologies to cope with challenges modeled by proposed fault models, (v) to propose mitigation strategies focused towards tackling such new threat scenarios and (vi) to devise an automated methodology for the deployment of many fault tolerance mechanisms in a systematic robust way. The outcomes of the thesis constitute a suite of tools and methods to help the designer of critical systems in his task to develop robust, validated, and on-time designs tailored to his application.[ES] La relevancia que la electrónica adquiere en la seguridad de los productos ha crecido inexorablemente, puesto que cada vez ésta copa una mayor influencia en la funcionalidad de los mismos. Pero, por supuesto, este hecho viene acompañado de una necesidad constante de mayores prestaciones para cumplir con los requerimientos funcionales, al tiempo que se mantienen los costes y el consumo en unos niveles reducidos. En este escenario, la industria está realizando esfuerzos para proveer una tecnología que cumpla con todas las especificaciones de potencia, consumo y precio, a costa de un incremento en la vulnerabilidad a múltiples tipos de fallos conocidos o la introducción de nuevos. Para ofrecer una solución a los fallos nuevos y crecientes en los sistemas, los diseñadores han recurrido a técnicas tradicionalmente asociadas a sistemas críticos para la seguridad, que ofrecen en general resultados sub-óptimos. De hecho, las arquitecturas empotradas modernas ofrecen la posibilidad de optimizar las propiedades de confiabilidad al habilitar la interacción de los niveles de hardware, firmware y software en el proceso. No obstante, ese punto no está resulto todavía. Se necesitan avances en todos los niveles en la mencionada dirección para poder alcanzar los objetivos de una tolerancia a fallos flexible, robusta, resiliente y a bajo coste. El trabajo presentado aquí se centra en el nivel de hardware, con la consideración de fondo de una potencial integración en una estrategia holística. Los esfuerzos de esta tesis se han centrado en los siguientes aspectos: (i) la introducción de modelos de fallo adicionales requeridos para la representación adecuada de efectos físicos surgentes en las tecnologías de manufactura actuales, (ii) la provisión de herramientas y métodos para la inyección eficiente de los modelos propuestos y de los clásicos, (iii) el análisis del método óptimo para estudiar la robustez de sistemas mediante el uso de inyección de fallos extensiva, y la posterior correlación con capas de más alto nivel en un esfuerzo por recortar el tiempo y coste de desarrollo, (iv) la provisión de nuevos métodos de detección para cubrir los retos planteados por los modelos de fallo propuestos, (v) la propuesta de estrategias de mitigación enfocadas hacia el tratamiento de dichos escenarios de amenaza y (vi) la introducción de una metodología automatizada de despliegue de diversos mecanismos de tolerancia a fallos de forma robusta y sistemática. Los resultados de la presente tesis constituyen un conjunto de herramientas y métodos para ayudar al diseñador de sistemas críticos en su tarea de desarrollo de diseños robustos, validados y en tiempo adaptados a su aplicación.[CA] La rellevància que l'electrònica adquireix en la seguretat dels productes ha crescut inexorablement, puix cada volta més aquesta abasta una major influència en la funcionalitat dels mateixos. Però, per descomptat, aquest fet ve acompanyat d'un constant necessitat de majors prestacions per acomplir els requeriments funcionals, mentre es mantenen els costos i consums en uns nivells reduïts. Donat aquest escenari, la indústria està fent esforços per proveir una tecnologia que complisca amb totes les especificacions de potència, consum i preu, tot a costa d'un increment en la vulnerabilitat a diversos tipus de fallades conegudes, i a la introducció de nous tipus. Per oferir una solució a les noves i creixents fallades als sistemes, els dissenyadors han recorregut a tècniques tradicionalment associades a sistemes crítics per a la seguretat, que en general oferixen resultats sub-òptims. De fet, les arquitectures empotrades modernes oferixen la possibilitat d'optimitzar les propietats de confiabilitat en habilitar la interacció dels nivells de hardware, firmware i software en el procés. Tot i això eixe punt no està resolt encara. Es necessiten avanços a tots els nivells en l'esmentada direcció per poder assolir els objectius d'una tolerància a fallades flexible, robusta, resilient i a baix cost. El treball ací presentat se centra en el nivell de hardware, amb la consideració de fons d'una potencial integració en una estratègia holística. Els esforços d'esta tesi s'han centrat en els següents aspectes: (i) la introducció de models de fallada addicionals requerits per a la representació adequada d'efectes físics que apareixen en les tecnologies de fabricació actuals, (ii) la provisió de ferramentes i mètodes per a la injecció eficient del models proposats i dels clàssics, (iii) l'anàlisi del mètode òptim per estudiar la robustesa de sistemes mitjançant l'ús d'injecció de fallades extensiva, i la posterior correlació amb capes de més alt nivell en un esforç per retallar el temps i cost de desenvolupament, (iv) la provisió de nous mètodes de detecció per cobrir els reptes plantejats pels models de fallades proposats, (v) la proposta d'estratègies de mitigació enfocades cap al tractament dels esmentats escenaris d'amenaça i (vi) la introducció d'una metodologia automatitzada de desplegament de diversos mecanismes de tolerància a fallades de forma robusta i sistemàtica. Els resultats de la present tesi constitueixen un conjunt de ferramentes i mètodes per ajudar el dissenyador de sistemes crítics en la seua tasca de desenvolupament de dissenys robustos, validats i a temps adaptats a la seua aplicació.Espinosa García, J. (2016). New Fault Detection, Mitigation and Injection Strategies for Current and Forthcoming Challenges of HW Embedded Designs [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/73146TESISCompendi