Dissertations / Theses on the topic 'A complex system approach'

This thesis develops a methodology for designing resilient system-of-systems (SoS) networks. This methodology includes a capability-based resilience assessment framework, used to quantify SoS resilience. A complex networks approach is used to generate potential SoS network designs, focusing on scale-free and random network topologies, degree-based and random rewiring adaptation, and targeted and random node removal threats. Statistical design methods, specifically response surface methodology, are used to evaluate SoS networks and provide an understanding of the advantages and disadvantages of potential designs. Linear regression is used to model a continuous representation of the network design space, and determine optimally resilient networks for particular threat types. The methodology is applied to an information exchange (IE) network model (i.e., a message passing network model) and military command and control (C2) model. Results show that optimally resilient IE network topologies are random for networks with adaptation, regardless of the threat type. However, the optimally resilient adaptation method sharply transitions from being fully random to fully degree-based as threat randomness increases. These findings suggest that intermediately defined networks should not be considered when designing for resilience. Cost-benefit analysis of C2 networks suggests that resilient C2 networks are more cost-effective than robust ones, as long as the cost of rewiring network links is less than three-fourths the cost of creating new links. This result identifies a threshold for which a resilient network design approach is more cost-effective than a robust one.This thesis develops a methodology for designing resilient system-of-systems (SoS) networks. This methodology includes a capability-based resilience assessment framework, used to quantify SoS resilience. A complex networks approach is used to generate potential SoS network designs, focusing on scale-free and random network topologies, degree-based and random rewiring adaptation, and targeted and random node removal threats. Statistical design methods, specifically response surface methodology, are used to evaluate SoS networks and provide an understanding of the advantages and disadvantages of potential designs. Linear regression is used to model a continuous representation of the network design space, and determine optimally resilient networks for particular threat types. The methodology is applied to an information exchange (IE) network model (i.e., a message passing network model) and military command and control (C2) model. Results show that optimally resilient IE network topologies are random for networks with adaptation, regardless of the threat type. However, the optimally resilient adaptation method sharply transitions from being fully random to fully degree-based as threat randomness increases. These findings suggest that intermediately defined networks should not be considered when designing for resilience. Cost-benefit analysis of C2 networks suggests that resilient C2 networks are more cost-effective than robust ones, as long as the cost of rewiring network links is less than three-fourths the cost of creating new links. This result identifies a threshold for which a resilient network design approach is more cost-effective than a robust one.

En français : Un des défis majeurs de la science de complexité se situe à l'investigation de l'émergence, où les interactions entre les composants microscopiques d'un système produisent la propriété globale, et réciproquement, la dynamique globale influence le bas niveau. Cette thèse a comme ambition de 1) élucider le mécanisme sous-jacent des systèmes complexes par la modélisation concrète des systèmes réels, et aussi 2) comparer entre les différents modèles proposés pour détecter la condition universelle de l'émergence. Pour cela, nous développons la nouvelle méthodologie basé sur l'interaction entre la théorie de système dynamique et la géométrie informationnelle, afin d'avoir la dialectique entre la modélisation constructive/déterministe et l'analyse des interactions sous la formalisation stochastique. La thèse se compose de 7 Parties, parmi lesquelles la Partie 2 à 6 correspondent au premier objectif, et la Partie 7 au seconde. Dans la Partie 1, nous allons réviser l'histoire de la science de la complexité et proposer la stratégie dialectique entre les méthodologies constructive et interactions-analytique, basé sur la théorie de système dynamique et la géométrie informationnelle. En Partie 2, nous traitons un modèle de réseau neuronal avec le comportement chaotique nommé ``l'itinérance chaotique" comme un candidat de la dynamique du cortex cérébral, et analysons l'effet de l'apprentissage autonome sans superviseur comme une source de créativité qui est la propriété émergente du système neuronal. La théorie de la mesure intérieure est étendue afin de interpréter l'émergence des nouveaux attracteurs par ``le chaos comme le catalyseur d'apprentissage. " En Partie 3, nous avons appliqué la dynamique du réseau neuronal chaotique aux robots qui manifestent la dynamique de recherche collective de manière émergente, au défi de la détection optimale des informations sporadiques. L'efficacité de la recherche collective est évaluée avec un simulateur virtuel. En Partie 4, nous développons les nouvelles mesures de la complexité du point de vue de la géométrie informationnelle, et analysons les données des réseaux sociaux. Les mesures de la complexité jouera un rôle principal dans la Partie 7. En Partie 5, nous appliquons la stratégie dialectique entre le système dynamique et la géométrie informationnelle vers la compréhension de la morphogenèse lors de l'embryogenèse chez le poisson zèbre. Quelques propositions théoriques sont établies et testées avec les données tentatives dérivées des projets européens Embryomics et BioEMERGENCES. En Partie 6, nous analysons les systèmes complexes liés au linguistique. Nous avons découvert les nouveaux invariants et la composition géométrique entre les voyelles japonaises, qui sont les propriétés émergentes au niveau du système. Nous développons aussi la modélisation écologique de l'environnement multilingue dans un contexte de la dialectique entre la théorie linguistique et la modélisation mathématique. En Partie 7, nous révisons les résultats obtenus dans les Parties précédentes sous une perspective comparative, en vue de détecter la structure universelle de l'émergence comme l'organisation des interactions qui ne dépende pas explicitement sur la propriété des composants. Surtout la comparaison entre les Parties 2 et 4, ainsi 5 et 6, nous indique la typologie et la stratégie de détection de la dynamique de l'émergence comme la relation et le contraint entre les foncteurs et méta-foncteurs. D'autre possibilité d'application de la stratégie établie est mise en discussion
En anglais : Recently emerging complex systems sciences tackle the systems where complex in- teractions between components lead to the manifestation of emergent property linking different levels of organization. This thesis aims to reveal the mechanism of emergent property in complex systems, both in concrete modeling as well as comparative analysis between different systems. We tackle various sub jects in complex systems science with newly proposed unified theoretical framework, based on the dialectic between dynam- ical system theory and information geometry. The thesis has therefore two levels of ob jectives: 1) Modeling and understanding of concrete complex systems with the use of constructive and interaction-analytical methodologies, and 2) comparison between different complex systems to characterize universal structure of emergence. The thesis consists of 7 Parts, in which Part 2 to 6 correspond to the first ob jective, and the Part 7 to the second one: In Part 1, we review the historical context of complex systems science and propose a dialectical strategy between the constructive and interaction-analytical methodology, based on the dynamical system theory and information geometry, respectively. In Part 2, we treat a candidate model of brain cortex dynamics known as “chaotic itinerancy”, and incorporate the effect of autonomous learning seeking for the creativity of intelligence as emergent property of neural system. The interpretation of emergence in terms of the internal measurement theory is extended to derive the concept of “chaotic itinerancy as catalyst of learning”. In Part 3, the dynamics of chaotic neural network is applied to emergent collective behavior of robots, so that to realize optimal intermittent search of sporadic informa- tion. The effectiveness of the collective infotaxis is analyzed on a simulator basis. In Part 4, we define novel complexity measures from information geometrical point of view and apply to the analysis of social network data. The established complexity measures play a key role in comparative analysis between different systems in Part 7. In Part 5, we apply the dialectical strategy between dynamical system and infor- mation geometry toward the understanding of morphogenesis during zebrafish embryo- genesis. Theoretical propositions are tested with tentative experimental data from two european pro jects, Embryomics and BioEMERGENCES. In Part 6, complex systems related to linguistics are investigated. We discovered novel invariants and geometrical relation between japanese vowels, as a system-level emergent property. Ecological modeling approach to multilingual environment is also proposed along the dialectical strategy between linguistic theory and mathematical modeling. In Part 7, we review the obtained results in previous Parts with comparative per- spective, seeking for a characterization of universal structure of emergence in terms of the organization of interactions that does not explicitly depend on the property of components. Comparison between Part 2 and 4, as well as 5 and 6, derived candi- date qualitative dynamics of emergence and its detection strategy as the dynamics and constraint between functors and meta-functors. Further possibility of the proposed strategy is discussed

Thesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 79-81).
Obsolescence mitigation is an increasingly important aspect of large systems development & maintenance that has often only been considered once obsolescence is imminent. For long lifecycle systems, this has become a major concern as the lifecycles of the components that are encompassed within these systems are often far shorter - up to ten times shorter - than the overall system lifecycle. Many defense systems can be characterized in this manner and therefore require obsolescence mitigation approaches to ensure the continuing ability for the system to perform and evolve. Current system-level obsolescence mitigation practices make recommendations for designing new systems to slow the onset of obsolescence and make the system more flexible when change for obsolescence is required. However, currently fielded systems were often not designed with this in mind. Other obsolescence mitigation techniques focus only on the approach to mitigating component-level obsolescence locally without examining the impact of the change on the system as a whole. This thesis combines the recommended approaches for obsolescence mitigation, the experience and lessons learned for obsolescence mitigation on a real-world case study system gained from interviews with key subject matter experts, along with systems engineering techniques for dealing with engineering change in systems to develop a robust systems engineering and management approach for obsolescence in large complex systems. The thesis provides the reader with a flow chart and a clustered DSM of the tasks along with a checklist that could be used with this obsolescence engineering and management approach.
by Jaime E. Devereaux.
S.M.in System Design and Management

Mainstream twentieth-century linguistics, a segregational approach, cannot explain the most obvious characteristics of language. The reasons for this are investigated. It is concluded that linguistics suffers from an incoherent conceptual framework which is the result of influences from three major sources: 1. The desire to establish linguistics as a proper science which led to the acceptance of a mechanistic and positivistic view of science and a pre-quantum conception of matter. 2. The language myth: there are many notions about language and related issues which we have inherited from our ancestors and tacitly accepted without scrutiny. Contemporary ideas about language are biased by this inherited stock of 'knowledge'. 3. Saussure's theory of language, later adopted and adapted by Chomsky, in which the 'true object of linguistic investigation' is abstracted away from what we ordinarily view as language. Together these three sources resulted in a peculiar view of language which cannot explain the most obvious things about it. The proposed alternative view, an integrational approach, redefines language in the holistic terms of a complex-systems approach. Language is the outcome of the dynamic interaction between social and physiological systems -- particular attention is paid to consciousness. Neither language, society or culture is an 'object', but is created through the interaction between individuals in communicative situations. Language is not 'being', but results from 'becoming'. Meaning is not given in advance, but created in each event of communication. Meaning is not a static closed system, but an open system which is dynamically constructed from moment to moment. Concepts of mathematical topology (fractal geometry and catastrophe theory), non-linear, dynamic, open and complex systems, and of chaology are used as conceptual tools to break away from the stronghold our inherited view of language has on our contemporary thinking about it.

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 65-67).
Incorporating flexibility into business processes can provide organizations with increased agility to respond to uncertainty within complex product development projects spanning across many years and many organizations. Current methods used for determining value in order to justify associated costs for implementing and maintaining process flexibility are not sufficient in capturing the full worth of flexibilities within processes. A framework is developed which builds upon on prior research to assess value of flexibility within product development processes, combining benefits of rigid constraints with flexible options. Valuation of a simple potential flexibility within an aircraft development project is used to demonstrate the use of the framework in practice and to evaluate strengths and weaknesses of the framework. The method of valuation provides benefit of capturing hidden value that would otherwise be ignored or left on the table and provides further insight into the behavior of the process flexibility in a manner which leads to optimization of that flexibility. However, adoption of the framework is hindered by the skillset required in practice along with the inherent inability to demonstrate its full value, as measured by actual performance.
by Robert W. McKellar.
S.M. in Engineering and Management

This research has developed several models and methodologies with the aim of improving the accuracy and applicability of reliability predictions for complex repairable systems. A repairable system is usually defined as one that will be repaired to recover its functions after each failure. Physical assets such as machines, buildings, vehicles are often repairable. Optimal maintenance strategies require the prediction of the reliability of complex repairable systems accurately. Numerous models and methods have been developed for predicting system reliability. After an extensive literature review, several limitations in the existing research and needs for future research have been identified. These include the follows: the need for an effective method to predict the reliability of an asset with multiple preventive maintenance intervals during its entire life span; the need for considering interactions among failures of components in a system; and the need for an effective method for predicting reliability with sparse or zero failure data. In this research, the Split System Approach (SSA), an Analytical Model for Interactive Failures (AMIF), the Extended SSA (ESSA) and the Proportional Covariate Model (PCM), were developed by the candidate to meet the needs identified previously, in an effective manner. These new methodologies/models are expected to rectify the identified limitations of current models and significantly improve the accuracy of the reliability prediction of existing models for repairable systems. The characteristics of the reliability of a system will alter after regular preventive maintenance. This alternation makes prediction of the reliability of complex repairable systems difficult, especially when the prediction covers a number of imperfect preventive maintenance actions over multiple intervals during the asset's lifetime. The SSA uses a new concept to address this issue effectively and splits a system into repaired and unrepaired parts virtually. SSA has been used to analyse system reliability at the component level and to address different states of a repairable system after single or multiple preventive maintenance activities over multiple intervals. The results obtained from this investigation demonstrate that SSA has an excellent ability to support the making of optimal asset preventive maintenance decisions over its whole life. It is noted that SSA, like most existing models, is based on the assumption that failures are independent of each other. This assumption is often unrealistic in industrial circumstances and may lead to unacceptable prediction errors. To ensure the accuracy of reliability prediction, interactive failures were considered. The concept of interactive failure presented in this thesis is a new variant of the definition of failure. The candidate has made several original contributions such as introducing and defining related concepts and terminologies, developing a model to analyse interactive failures quantitatively and revealing that interactive failure can be either stable or unstable. The research results effectively assist in avoiding unstable interactive relationship in machinery during its design phase. This research on interactive failures pioneers a new area of reliability prediction and enables the estimation of failure probabilities more precisely. ESSA was developed through an integration of SSA and AMIF. ESSA is the first effective method to address the reliability prediction of systems with interactive failures and with multiple preventive maintenance actions over multiple intervals. It enhances the capability of SSA and AMIF. PCM was developed to further enhance the capability of the above methodologies/models. It addresses the issue of reliability prediction using both failure data and condition data. The philosophy and procedure of PCM are different from existing models such as the Proportional Hazard Model (PHM). PCM has been used successfully to investigate the hazard of gearboxes and truck engines. The candidate demonstrated that PCM had several unique features: 1) it automatically tracks the changing characteristics of the hazard of a system using symptom indicators; 2) it estimates the hazard of a system using symptom indicators without historical failure data; 3) it reduces the influence of fluctuations in condition monitoring data on hazard estimation. These newly developed methodologies/models have been verified using simulations, industrial case studies and laboratory experiments. The research outcomes of this research are expected to enrich the body of knowledge in reliability prediction through effectively addressing some limitations of existing models and exploring the area of interactive failures.

This research has developed several models and methodologies with the aim of improving the accuracy and applicability of reliability predictions for complex repairable systems. A repairable system is usually defined as one that will be repaired to recover its functions after each failure. Physical assets such as machines, buildings, vehicles are often repairable. Optimal maintenance strategies require the prediction of the reliability of complex repairable systems accurately. Numerous models and methods have been developed for predicting system reliability. After an extensive literature review, several limitations in the existing research and needs for future research have been identified. These include the follows: the need for an effective method to predict the reliability of an asset with multiple preventive maintenance intervals during its entire life span; the need for considering interactions among failures of components in a system; and the need for an effective method for predicting reliability with sparse or zero failure data. In this research, the Split System Approach (SSA), an Analytical Model for Interactive Failures (AMIF), the Extended SSA (ESSA) and the Proportional Covariate Model (PCM), were developed by the candidate to meet the needs identified previously, in an effective manner. These new methodologies/models are expected to rectify the identified limitations of current models and significantly improve the accuracy of the reliability prediction of existing models for repairable systems. The characteristics of the reliability of a system will alter after regular preventive maintenance. This alternation makes prediction of the reliability of complex repairable systems difficult, especially when the prediction covers a number of imperfect preventive maintenance actions over multiple intervals during the asset's lifetime. The SSA uses a new concept to address this issue effectively and splits a system into repaired and unrepaired parts virtually. SSA has been used to analyse system reliability at the component level and to address different states of a repairable system after single or multiple preventive maintenance activities over multiple intervals. The results obtained from this investigation demonstrate that SSA has an excellent ability to support the making of optimal asset preventive maintenance decisions over its whole life. It is noted that SSA, like most existing models, is based on the assumption that failures are independent of each other. This assumption is often unrealistic in industrial circumstances and may lead to unacceptable prediction errors. To ensure the accuracy of reliability prediction, interactive failures were considered. The concept of interactive failure presented in this thesis is a new variant of the definition of failure. The candidate has made several original contributions such as introducing and defining related concepts and terminologies, developing a model to analyse interactive failures quantitatively and revealing that interactive failure can be either stable or unstable. The research results effectively assist in avoiding unstable interactive relationship in machinery during its design phase. This research on interactive failures pioneers a new area of reliability prediction and enables the estimation of failure probabilities more precisely. ESSA was developed through an integration of SSA and AMIF. ESSA is the first effective method to address the reliability prediction of systems with interactive failures and with multiple preventive maintenance actions over multiple intervals. It enhances the capability of SSA and AMIF. PCM was developed to further enhance the capability of the above methodologies/models. It addresses the issue of reliability prediction using both failure data and condition data. The philosophy and procedure of PCM are different from existing models such as the Proportional Hazard Model (PHM). PCM has been used successfully to investigate the hazard of gearboxes and truck engines. The candidate demonstrated that PCM had several unique features: 1) it automatically tracks the changing characteristics of the hazard of a system using symptom indicators; 2) it estimates the hazard of a system using symptom indicators without historical failure data; 3) it reduces the influence of fluctuations in condition monitoring data on hazard estimation. These newly developed methodologies/models have been verified using simulations, industrial case studies and laboratory experiments. The research outcomes of this research are expected to enrich the body of knowledge in reliability prediction through effectively addressing some limitations of existing models and exploring the area of interactive failures.

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 105-109).
Identifying the factors that could lead to the loss of quality is difficult for large, complex systems. Traditional design methods such as Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and Robust Design have been proven effective at the component level but are less effective for factors that involve interactions between components, software flaws and external noises. This thesis applies System Theoretic Process Analysis (STPA) to two case studies at Cummins, Inc. The first case study was a technology change to a subsystem in a new product development project. The intent of this case was to determine if STPA, applied broadly to safety and hazard analysis, would be effective in identifying causes of quality losses. The second case was a historical quality improvement project. The intent of this case was to determine if STPA would be effective for developing solutions to causes of quality losses. The results of the case studies were compared to the traditional design methods. Use of STPA allowed the design teams to identify more causal factors for quality losses than FMEA or FTA, including component interactions, software flaws, and omissions and external noises. STPA was also found to be complementary to Robust Design Methods. Finally, use of STPA was effective for analyzing the complete hierarchical structure of the system for solutions to potential causes of quality losses.
by Stephanie L. Goerges.
S.M.

Plus de 50% de la population mondiale vit dans des zones urbaines et cette proportion devrait augmenter dans les prochaines décennies. Comprendre ce qui régit l'évolution des systèmes urbains est donc devenu d'une importance fondamentale. Ce renouveau d'intérêt combiné avec la disponibilité de données à grande échelle, permet d'entrevoir l'avènement d'une nouvelle science des villes, interdisciplinaire et basée sur les données.Des études récentes ont montré l'existence de régularités statistiques et de lois d'échelle pour plusieurs indicateurs socio-économiques, tels que la consommation d'essence, la distance moyenne parcourue quotidiennement, le cout des infrastructures, etc. Malgré plusieurs tentatives récentes, la compréhension théorique de ces résultats observés empiriquement demeure très partielle.Le but de cette thèse est d'obtenir une modélisation simplifiée, hors-équilibre de la croissance urbaine, en s'appuyant sur un petit nombre de mécanismesimportants et qui fournit des prédictions quantitatives en accord avec lesdonnées empiriques. Pour cela, nous nous inspirerons des études en géographiequantitative et en économie spatiale et nous revisiterons certains de ces anciens modèles avec une nouvelle approche intégrant les outils et concepts de la physique
More than 50 % of the world population lives in urban areas and this proportion is expected to increase in the coming decades. Understanding what governs the evolution of urban systems has thus become of paramount importance.This renewed interest combined with the availability of large-scale data, allows a glimpse into the dawn of a new science of cities, interdisciplinary and based on data.Recent studies have shown the existence of statistical regularities and scaling laws for several socio-economic indicators such as fuel consumption, average commuting distance, cost of infrastructure, etc., and despite several recent attempts, the theoretical understanding of these results empirically observed remains very partial. The purpose of this thesis is to obtain a simplified, out of equilibrium model of urban growth, based on a small number of important mechanisms and which provides quantitative predictions in agreement with empirical data. For this, we will draw on studies in quantitative geography and spatial economy and we will revisit some of these old models with a new approach that integrates the tools and concepts of physics

The research presented in this thesis develops an improved design methodology for designing complex systems. While traditional methods have been able to create complex systems, their success is usually overshadowed by long delays and expensive overruns. The method developed within this research is known as Value Seeking System Design (VSSD) and builds upon the foundations of the System Engineering (SE) and Value Driven Design (VDD) approaches. Creation and implementation of the new design environment is provided, including a method on how to create the value model for any complex system. Key conclusions from this work include a need to redefine the process in which stakeholder needs are currently defined and captured as well as a need to create an improved value model. Defining all stakeholders’ needs as requirements constrains the designer to a rigid solution space, which may not include the “best” solution for the stakeholder. Similarly not including the social aspects within a value model causes the designer to make poor value trades. To overcome these problems the VSSD technique incorporates desirements and their associated design desirability functions within the design process to create a non-rigid solution space while the value model has been redeveloped to easily incorporate the performance, economic and social aspects of a design, to allow a more accurate and balanced value trade off analysis to occur. Benchmarking the VSSD approach against the current state of the art methods (SE and VDD) highlighted the advantages of adapting a value approach to complex system design compared to traditional requirement based techniques. Additionally while all three approaches were capable of designing complex systems the VSSD approach was demonstrated to be an improved design methodology as it possessed the benefits inherent within both the SE and VDD approaches without suffering from their limitations.

L'architecture système cherche à se distinguer de son domaine d'origine, l'ingénierie système, en devenant un domaine émergent. Loin d'être reconnue en tant que science ou discipline à proprement parler, sa pratique est de plus en plus répandue de nos jours. Cependant, cette pratique reste encore peu formalisée et peu enseignée, faute d'un corpus de connaissances, de techniques ou de démarches établi et accessible.Notre thèse contribue à combler ce manque en proposant un paradigme de la conception architecturale des systèmes artificiels complexes. Ce dernier est construit en se basant sur des paradigmes existants, en les combinant, puis en les complétant. Il vise à doter l'architecte de systèmes artificiels complexes d'un cadre opérant, voire performatif. Il se traduit par une structuration de la démarche de conception en quatre niveaux.Un niveau dit archétypal condense les grands principes de toute démarche de conception architecturale de systèmes artificiels complexes. Ces principes sont dérivés de diverses démarches déjà appliquées, principalement à la conception de systèmes ou de produits, mais également à la conception architecturale de bâtiments.Un niveau dit général repose sur le principe d'une partition présent-futur, se différenciant en cela des approches d'ingénierie qui s'appuient traditionnellement sur une dichotomie problème-solution. L'idée prépondérante tient dans l'assentiment que lorsqu'un architecte conçoit, il ne résout pas de problèmes, mais il imagine des futurs possibles et plausibles, nécessitant qu'il perçoive le présent. Cette vision impacte directement la nature des artéfacts sur lesquels il travaille. Nous proposons ensuite d'agréger ces artéfacts en des modèles, reflétant soit sa perception du présent, soit son élaboration des futurs, évoluant suivant des processus identifiés.Un niveau dit particulier a pour objectif de permettre la narration d'une conception particulière. Nous proposons pour cela une notation de la conception. Elle s'appuie sur un certain nombre de mécanismes élémentaires, dont celui de l'enchaînement divergence-convergence, que nous nommons mécanisme de respiration de la conception architecturale.Un niveau dit de boîte à outils n'est pas traité dans le cadre de cette thèse. Il comprendrait les différentes opérations cognitives nécessaires à l'architecte pour accomplir sa tâche de conception (abstraction, questionnement, jugement, comparaison, décision, etc.)L'approche proposée est illustrée par un exemple de conception architecturale d'un système complexe : « rendre une ville plus sûre » (connu dans la littérature anglo-saxonne comme Safe City)
Architecting seeks now to be distinct from its original domain, systems engineering, becoming an emergent domain. Far from being recognized as a science or a discipline, its practice is nowadays more and more widespread. However, this practice is still poorly formalized, and insufficiently being taught, lacking a well-established and accessible corpus of knowledge, techniques or approaches.This thesis contributes filling that gap by proposing a paradigm of the architectural design of artificial complex systems. The latter is built based on existing paradigms that are combined, then completed. It aims at providing architects with an effective, even performative framework. It results in an approach of the architectural design structured in four levels.A so-called archetypal level grasps the core principles of any approach of architectural design of artificial complex systems. These principles are derived from various approaches already applied, mainly in the field of system or product design, but also of architectural design of buildings.A so-called general level lies on the principle of a present-future division. In that sense, it differs from engineering approaches that usually rely on a problem-solution dichotomy. It is based on the following main idea: we should consent that when an architect designs, he does not solve problems, but he devises possible and plausible futures, requiring to perceive the present. This vision of the architect's way of working directly impacts the kind of artefacts he handles. We sho how to aggregate these artefacts into models, reflecting either his perception of the present, or his development of futures while progressing through some identified processes.A so-called particular level aims at allowing the storytelling of a given design. To achieve this goal, a notation of the design process is suggested. It lies on some basic mechanisms, one of them being the combination divergence-convergence, called the breathing of the architectural design.At last, a so-called toolbox level, not addressed in this thesis, would consist of various cognitive operations required for the architect in order to accomplish his task of designing (abstraction, questioning, judgement, comparison, decision, etc.)The whole approach is illustrated by an example of an architectural design of a complex system: a Safe City

Condition-based maintenance is an emerging paradigm of modern health monitoring, where maintenance operations are based upon diagnostics and prognostics. Prognostics promises to optimise maintenance scheduling, resources and supply chain management, leading to reductions in operational disruption, spares inventory, maintenance labour cost and hazardous conditions. The main objective of this research is to develop generic datadriven prognostic approaches to address several challenges associated with complex system prognostics, where in this particular work, the developed techniques are applied to the degradation data obtained from civil aerospace gas turbine engines. This thesis contains four key contributions. Firstly, deterministic Bayesian prognostics is used to deal with large uncertainty in degradation data. The novelty and value in the presented formulation lies in a fuller Bayesian treatment of observation error than prior art while retaining the closed-form solution desirable for real-time, deterministic computation. Secondly, the Bayesian hierarchical model (BHM) is introduced to optimise the use of fleet data from multiple assets. This formulation allows Bayesian updates of an individual predictive model to be made, based upon data received from a fleet of assets with different in-service lives. The results obtained demonstrate BHM capability in dealing with some extreme scenarios, occurring in complex system prognostics. The next contribution lies in developing variational inference for the existing BHM to overcome the computational and convergence concerns that are raised by sampling methods needed for the inference of the original formulation. This technique delivers an approximate but deterministic solution, where the quality of approximation is found to be satisfactory with respect to prediction performance, computational speed and ease of use. In the final contribution, an integration concept is proposed, combining the Bayesian data modelling technique with an information theoretic change-point detection algorithm to solve a wide class of prognostic problems, such as information arising from irregular events occurring during the life-cycle of an asset. This integration concept has a great potential to be implemented in complex system prognostics as it demonstrates several advantages of the deterministic BHM in combination with change-point detection to utilise, optimally, all available multiple unit data as well as data available at various levels of the system hierarchy.

Tooling is defined as the work performed by a tool. In the context of industrial production tooling takes many forms from a simple drill bar to highly complex assembly jigs. In all cases the tooling exists to assist in the accurate and precise performance of work on engineering products. The engineering product therefore defines and constrains the form and function of the associated tooling. The process of defining, fabricating, and verifying tooling is often subject to individual, business, or government perspectives and processes. Relying on individual experience and inadequate processes often results in frequent rework, product design interface issues, and a lack of historical perspective and traceability on the tooling design. The Systems Engineering process, which is already valued as a necessary component of complex system definition, will be beneficial when adapted and applied to the process of defining, fabricating, and verifying tooling. The methodical processes and tools associated with Systems Engineering will embed the tooling process in the product requirement and design process and encourage increased interaction and concurrent engineering practices. A tooling process, based on System Engineering principles combined with best industry practices, that is ingrained in the product life cycle and which thoroughly documents associated technical and producibility requirements will reduce the issues currently prevalent in complex tooling realization.

In recognition of the widespread deterioration of the natural environment, and the continual emergence of sudden catastrophic environmental changes resulting from complex interactions of theretofore apparently disparate phenomena, this research presents a complex systems approach to the modelling of such environmental catastrophes. Recognizing contemporary views of complexity and evolution, this research presents a dynamic complex systems model which displays emergent characteristics which can be directly related to the modelled phenomena - linking acid rain and eutrophication - and the study region, the Rutland Water catchment. This is achieved through the definition of a catastrophe indicator which indicates both the proximity and magnitude of catastrophe arising from the non-linear and discontinuous acid-phosphorus relationship within the soil domain which lies at the heart of this Chemical Time Bomb phenomenon. This facilitates assessment of the vulnerability of the Rutland Water catchment to potential propagation of this CTB given continued acidification and phosphate accumulation. The main contributions of this research may thus be found in the following areas: Development of a dynamic complex systems model - transferable to alternative catchments due to the minimal data requirements and its generic representation - which may be used to describe non-point sources of phosphates as part of assessments of potential eutrophication, overcoming such limitations found in existing models. * Definition of a catastrophe indicator( Re)- which highlights both the proximity and magnitude of catastrophe describing a specific Chemical Time Bomb phenomenon whereby the soil suddenly changes from being a sink to a source of phosphates; long-term accumulations of phosphate in the soil being released as a consequence of soil acidification in the short-term. Presentation of a complex systems approach - hinged upon this concept of a catastrophe indicator - to the representation of non-linearities and discontinuities between heretofore apparently disparate phenomena which are 'competing for a common resource.

Celem niniejszej pracy jest zbadanie możliwości efektywnego modelowania procesów transportu w złożonych systemach z zakresu dynamiki płynów za pomocą metody siatkowej Boltzmanna (LBM). Złożoność systemu została potraktowana wieloaspektowo i konkretne układy, które poddano analizie pokrywały szeroki zakres zagadnień fizycznych, m.in. przepływy wielofazowe, hemodynamikę oraz turbulencje. We wszystkich przypadkach szczególna uwaga została zwrócona na aspekty numeryczne — dokładność używanych modeli, jak również szybkość z jaką pozwalają one uzyskać zadowalające rozwiązanie. W ramach pracy rozwinięty został pakiet oprogramowania Sailfish, będący otwarta implementacja metody siatkowej Boltzmanna na procesory kart graficznych (GPU). Po analizie szybkości jego działania, walidacji oraz omówieniu założeń projektowych, pakiet ten został użyty do symulacji trzech typów przepływów. Pierwszym z nich były przepływy typu Brethertona/Taylora w dwu- i trójwymiarowych geometriach, do symulacji których zastosowano model energii swobodnej. Analiza otrzymanych wyników pokazała dobra zgodność z danymi dostępnymi w literaturze, zarówno eksperymentalnymi, jak i otrzymanymi za pomocą innych metod numerycznych. Drugim badanym problemem były przepływy krwi w realistycznych geometriach tętnic dostarczających krew do ludzkiego mózgu. Wyniki symulacji zostały dokładnie porównane z rozwiązaniem otrzymanym metoda objętości skończonych z wykorzystaniem pakietu OpenFOAM, przyspieszonego komercyjna biblioteka pozwalająca na wykonywanie obliczeń na GPU. Otrzymano dobra zgodność między badanymi metodami oraz pokazano, że metoda siatkowa Boltzmanna pozwala na wykonywanie symulacji do ok. 20 razy szybciej. Trzecim przeanalizowanym zagadnieniem były turbulentne przepływy w prostych geometriach. Po zwalidowaniu wszystkich zaimplementowanych modeli relaksacji na przypadku wiru Kidy, zbadano przepływy w pustym kanale oraz w obecności przeszkód. Do symulacji wykorzystano zarówno siatki zapewniające pełną rozdzielczość aż do skal Kolmogorova, jak i siatki o mniejszej rozdzielczości. Również w tym kontekście pokazano dobrą zgodność wyników otrzymanych metodą siatkową Boltzmanna z wynikami innych symulacji oraz badaniami eksperymentalnymi. Pokazano również, że implementacja LBM w pakiecie Sailfish zapewnia większą stabilność obliczeń niż ta opisana w literaturze dla tych samych przepływów i modeli relaksacji.

Many industries, such as healthcare, transportation, education, and other fields that involve large corporations and institutions, are complex systems composed of many diverse interacting components. Frequently, to improve performance within these industries, to move into new markets, or to expand capability or capacity, decision-makers face opportunities or mandates to implement innovations (new technology, processes, and services). Successful implementation of these innovations involves seamless integration with the policy, economic, social, and technological dynamics associated with the complex system. These dynamics are frequently difficult for decision-makers to observe and understand. Consequently, they take on risk from lack of insight into how best to implement the innovation and how their system-of-interest will ultimately perform. This research defines a framework for an integrated, multi-scale modeling and simulation systems approach that provides decision-makers with prospective insight into the likely performance to expect once an innovation of change is implemented in a complex system. The need for such a framework when modeling complex systems is described, and suitable simulation paradigms and the challenges related to implementing these simulations are discussed. A healthcare case study is used to demonstrate the framework’s application and utility in understanding how an innovation, once fielded, will actually affect the larger complex system to which it belongs.

At the start of the 21st century, the topic of complexity remains a formidable challenge in engineering, science and other aspects of our world. It seems that when disaster strikes it is because some complex and unforeseen interaction causes the unfortunate outcome. Why did the financial system of the world meltdown in 2008-2009? Why are global temperatures on the rise? These questions and other ones like them are difficult to answer because they pertain to contexts that require lengthy descriptions. In other words, these contexts are complex. But we as human beings are able to observe and recognize this thing we call 'complexity'. Furthermore, we recognize that there are certain elements of a context that form a system of complex interactions - i.e., a complex system. Many researchers have even noted similarities between seemingly disparate complex systems. Do sub-atomic systems bear resemblance to weather patterns? Or do human-based economic systems bear resemblance to macroscopic flows? Where do we draw the line in their resemblance? These are the kinds of questions that are asked in complex systems research. And the ability to recognize complexity is not only limited to analytic research. Rather, there are many known examples of humans who, not only observe and recognize but also, operate complex systems. How do they do it? Is there something superhuman about these people or is there something common to human anatomy that makes it possible to fly a plane? - Or to drive a bus? Or to operate a nuclear power plant? Or to play Chopin's etudes on the piano? In each of these examples, a human being operates a complex system of machinery, whether it is a plane, a bus, a nuclear power plant or a piano. What is the common thread running through these abilities? The study of situational awareness (SA) examines how people do these types of remarkable feats. It is not a bottom-up science though because it relies on finding general principles running through a host of varied human activities. Nevertheless, since it is not constrained by computational details, the study of situational awareness provides a unique opportunity to approach complex tasks of operation from an analytical perspective. In other words, with SA, we get to see how humans observe, recognize and react to complex systems on which they exert some control. Reconciling this perspective on complexity with complex systems research, it might be possible to further our understanding of complex phenomena if we can probe the anatomical mechanisms by which we, as humans, do it naturally. At this unique intersection of two disciplines, a hybrid approach is needed. So in this work, we propose just such an approach. In particular, this research proposes a computational approach to the situational awareness (SA) of complex systems. Here we propose to implement certain aspects of situational awareness via a biologically-inspired machine-learning technique called Hierarchical Temporal Memory (HTM). In doing so, we will use either simulated or actual data to create and to test computational implementations of situational awareness. This will be tested in two example contexts, one being more complex than the other. The ultimate goal of this research is to demonstrate a possible approach to analyzing and understanding complex systems. By using HTM and carefully developing techniques to analyze the SA formed from data, it is believed that this goal can be obtained.

Improving connectivity is increasingly a topic at the centre of the international trade and transport policy agendas. An examination on available documents and studies in both the policy-making and the academic fields shows that the concept of connectivity has often been defined in different ways, and thus has taken a variety of meanings. This poses the questions: what is freight connectivity?; what are its determinants in the context of international trade? The researcher is not aware of any study that has analysed, in a comprehensive and systematic way, the different perspectives, determinants and measures of connectivity to international markets. Using a mixed-methods approach that includes a systematic literature review encompassing literature in the fields of Transport Engineering and Economics, International Economics, Supply Chain Management, Physics and Transport Geography; a survey and in-depth interviews in three countries; comparative analysis of connectivity metrics in a variety of fields; and network analysis of over 100 networks, this Dissertation contributes to fill this gap by providing: (i) a complex systems approach to connectivity to international markets; (ii) a comprehensive definition of connectivity to international markets which encompasses the different factors that influence it; and (iii) a novel method to assess connectivity to international markets using network analysis. Further contributions of this research include insights on the multi-layered characteristics of both international trade flows and its support system; the perspective of emerging economies; and the study of a region – the Americas – mostly overlooked by the literature on complex systems applied to trade and transport networks. It is expected that a multi-disciplinary, comprehensive and more precise understanding and assessment of the determinants of connectivity will contribute to identify and design more effective policies to address barriers impeding the fast, smooth access to international markets, as well as guide future multi-disciplinary research and analysis in academia and policy-making.

O estudo econômico e financeiro vem se modificando e buscando novas metodologias. Desde a crise que se iniciou com os \"subprimes\" nos Estados Unidos em 2008 e se espalhou para as economias de todo o mundo, novas discussões de como ela poderia ter sido evitada e qual caminho deveriam os países seguir para sair da estagnação já surgem no mundo acadêmico em direção ao estudo da complexidade. Em termos econômicos, algumas críticas feitas ao estudo da economia tradicional, principalmente atribuídas ao excesso de restrições utilizados nos modelos, podem ser agora afrouxadas, uma a uma, através de modelagens baseadas em agentes. Já no entendimento e controle do risco financeiro, redes complexas prestam fundamental distinção. Os modelos até então utilizados para controle de riscos no mercado financeiro não levam em consideração o risco global, porém apenas o risco local. Muitas teorias sobre a diminuição do risco através da diversificação são aceitas e realmente produzem sistemas mais estáveis, porém com pouca resiliência, ou seja, o número de crises diminui, porém as que ocorrem são muito mais graves. Este trabalho sugeriu um modelo baseado em agentes, onde um sistema econômico simples foi construído, para ser capaz de gerar crises. Este modelo formado por firmas e demanda estocástica, utiliza bancos para simular o mercado financeiro. Tais bancos estão conectados entre si através de uma rede interbancária. Para testar os efeitos de risco sistêmico, foram realizados três testes. No primeiro aumentou-se a alavancagem máxima permitida e os bancos conseguiram obter mais lucro e maior crescimento, porém a partir de certo patamar o sistema entrou em colapso, com frequente crises. No segundo aumentou-se a conectividade média e os bancos também obtiveram maior lucro, porém com crises muito mais profundas. No aumento do índice de cluster da rede interbancária, assim como nos dois primeiros testes os bancos conseguiram maior crescimento, porém agora sem os mesmos efeitos indesejáveis causados pelo aumento do risco.
Economic and financial studies have been changing and searching new methodologies. Since the 2008 subprime crisis, which spread into economies around the globe, new discussions on how it could have been prevented, and paths which countries should follow to emerge from stagflation have been discussed by the academic world towards the complexity subject. In economic terms, some of the criticism of neoclassic economics, mainly due to excessive constrains used by its models, can now be eased, one by one, through agent based modeling. Regarding financial risk understanding and control, complex networks assume fundamental distinction. Models applied so far in financial market risk control dont consider global risk, but only the local one. Many theories on risk diversification are accepted and indeed produce more stable systems, although with little resilience, which means smaller number of crisis, but when it does occur, are more serious ones. This paper suggested an agent based model, using a simple economic system capable of generating crisis. This model was constituted by firms and stochastic demand, using banks to simulate the financial market. These banks were connected though a banking network. In order to test systemic risk, the model performed three tests. First, the maximum leverage allowed was increased and banks were able to achieve higher profits and growth, but from a certain level, the system collapsed with frequent crisis. Second, the average connectivity was increased and banks obtained higher profits, however with more severe crisis. Finally, increasing banking network cluster index, similarly to the first two tests, banks achieved higher growth, but without the undesirable effects caused by risk increase.

Financial crises can be devastating. They wreak economic havoc within the economies of the relevant countries. Despite being extremely unwelcome they continue to reoccur and, interestingly, their features and root causes seem to be very similar. While there are accepted frameworks that outline the sequential stages of financial crises, the range of potential actions to contain them appear to be rarely academically assessed, or even identified. Such containment actions are diverse and undertaken by a variety of institutions. Thus, the aim of the research presented in this thesis is to provide insights that emerge from an analysis and evaluation of relevant financial crisis containment actions. The analysis is undertaken applying a complex system approach to appropriate financial crisis variables-data. Complex systems theory argues that the effectiveness of actions cannot be assessed by an isolated analysis. Side-effects and interferences from other actions may, in fact, neutralise an intended effect. However, the consequences of actions can be identified by a range of analytical techniques associated with complex systems. Against that background, using models developed from extant theories of financial crises, financial markets and financial containment, such actions are inductively analysed in terms of their sustainability, strength and impact on key indicators. Then, a “mix” of appropriate containment actions is identified with their relative effectiveness. The results of this analysis suggest that there is not a single all-embracing action that alone can contain a financial crisis. However, with varying consequences and degrees of effectiveness, there appear to be several containment actions that can help. Countries facing an isolated domestic financial crisis may apply only few actions to reach three desired key goals (i.e. increased asset prices, reduced risk of bank runs and stable foreign exchange rates). An international financial crisis however, seems to call for attention on other fronts. In these cases, central banks should arrange a harmonisation of monetary policies causing no changes of the foreign exchange rate. More containment actions are also of merit and could be applied. An historical evaluation of the identified “mix” of appropriate containment actions conducted as part of the thesis, in part, supports and strengthens the results of the systemic analysis. Implications, derived from the research, point to a weighted combination of effective containment actions that can be taken by central banks, governments and regulators when attempting to contain financial crises.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.
Includes bibliographical references (leaves 133-135).
The research is based on observations made over a two-year period with the Closures Systems Integrators or CSIs (supervisory engineers who coordinate attribute balance and system decisions for conflicting door attributes) at a North American automobile manufacturer, focusing on organizational and technical improvements in product development. The product development (PD) process for vehicle side doors forms the case study. A Design Structure Matrix model was made of the process by which important closures attributes are managed through PD, Stamping, Manufacturing and Plant Teams. The attribute delivery process is very tightly coupled with many interactions and conflicts between the attributes, and careful system integration and interface management are essential. The study highlights the need for standardized designs and processes to create time for these system-level tasks, along with better knowledge and resource management. Critical inputs for system attributes are identified and it is shown that a lot of rework occurs if these inputs are changed. The Datum Flow Chain method is developed as a way to communicate data, help with assembly decisions and manage interfaces between component owners.
(cont.) An investigation of issues experienced at product launch shows that programs with CSIs have fewer design- related problems during launch, but that CSIs still spend too much time on Design and Release-type tasks for components (instead of a system focus) and fire-fighting. An extensive organizational study reveals the need for more leverage and clearer roles and responsibilities of CSIs. Conclusions on the process are supported by a simulation model and interviews with CSIs and many other engineers. Simulation results also show that adherence to official product development schedules timing is inherently difficult due to the structure of the as-is PD process. A brief comparison to Toyota's closures design process is also part of the thesis but was not part of the project itself. Recommendations for improvement include a set of design tasks that should be standardized, types of analytical tools that should be developed and managerial practices to be followed.
by M. Jehanzeb Noor.
S.M.

Rapid Application Development (RAD) is an iterative and incremental development approach that evolved to address problems associated with the more structured development approaches such as the Waterfall Model. Even though RAD is becoming an increasingly accepted development approach, much of the existing literature focuses on small to medium sized development projects. There is considerable debate about its application for large, complex IS development arenas. This research utilises a development project currently being implemented within UK Regional Government as a case study. It represents an atypical opportunity to examine the utility of RAD within a large, complex IS development, presenting the real-life context, experiences and commentary from individuals directly involved. An interpretive stance is adopted to gain a broad view of the organizational environment of the IS and the wider external context within which the information system is related. An ethnographic approach was selected enabling a richer and deeper interpretation, and a more comprehensive understanding of the issues under investigation. This methodology included non-participatory observation, indirect observation and informal semi-structured interviews. It also involved multiple strategies of data collection and analysis to facilitate cross-checking and to yield stronger substantiation of analysis. The thesis examines the cultural aspects inherent in the studied environment that impacted severely upon the project. It further explores a number of other issues held problematic for large and complex development arenas: managing user involvement and expectations, communications, requirements elicitation, decision-making and testing. Analysis of the case study material has aided the production of a model of critical success factors that could be applied to other such environments adopting a RAD-type approach. Thus it contributes to the field of IS knowledge by informing the debate surrounding applicability of RAD across large, complex development arenas.

Si presenta un approccio matematico formale ai complex networks tramite l'uso della Random Matrix Theory (RMT). La legge del semicerchio di Wigner viene presentata come una generalizzazione del Teorema del Limite Centrale per determinati ensemble di matrici random. Sono presentati inoltre i principali metodi per calcolare la distribuzione spettrale delle matrici random e se ne sottolineano le differenze. Si è poi studiato come la RMT sia collegata alla Free Probability. Si è studiato come due tipi di grafi random apparentemente uguali, posseggono proprietà spettrali differenti analizzando le loro matrici di adiacenza. Da questa analisi si deducono alcune proprietà geometriche e topologiche dei grafi e si può analizzare la correlazione statistica tra i vertici. Si è poi costruito sul grafo un passeggiata aleatoria tramite catene di Markov, definendo la matrice di transizione del processo tramite la matrice di adiacenza del network opportunamente normalizzata. Infine si è mostrato come il comportamento dinamico della passeggiata aleatoria sia profondamente connesso con gli autovalori della matrice di transizione, e le principali relazioni sono mostrate.

Doctor of Philosophy(PhD)
The aim of this thesis is to support the evaluation of sustainable development strategies for industrial networks in the context of industrial ecology (IE). Industrial networks are a group of units which carry out, or contribute to, industrial activity, and are connected by material and energy flows, but also capital and information exchanges. The components of an industrial network encompass resource extraction, processing and refining, forming and assembly, use, disposal, as well as recycling and reprocessing. The motivation behind this research is the realisation that much of the current environmental system analysis focus within IE lacks a structured approach to considering: • system environment • dynamic nature of the system and its environment • economic and social impacts • the effect of uncertainty on analysis outcomes. It is argued in this thesis that current environmental analysis approaches used in IE can be improved in their capacity to capture the complexity of industrial systems, with the objective of promoting sustainable development. While IE emphasises the benefit of a systems approach to identifying environmental strategies in industry, analysis tools have to date not engaged extensively with important aspects such as the influence of system environment and dynamics on the viability of an environmental strategy, or with the economic or social impacts of industrial system development, which are equally important for sustainable development. Nor is the assessment of the effect of uncertainty on analysis outcomes an integral part of environmental analysis tools in IE. This is particularly significant when, in fact, the degree of uncertainty in assumptions and data used increases with the scope, and therefore the abstraction, of the system under consideration. IE will have to engage with the network and contextual complexities to a greater degree if it is to evolve from a concept to the application of its principles in practice. The main contribution of this thesis is therefore the development of a structured approach to analysing industrial networks for the purpose of identifying strategies to encourage sustainable development, while accounting for the complexity of the underlying system as well as the problem context. This analysis is intended to allow the identification of preferred network development pathways and to test the effectiveness of sustainable development strategies. A top-down, prescriptive approach is adopted for this purpose. This approach is chosen as the industrial network analysis is intended to identify how a network should develop, rather than focusing on how it could develop. Industrial networks are systems which are complex in both their structure and behaviour. This thesis also delivers a characterisation of these networks, which serves two purposes – quantifying key elements of structure and behaviour; and using this information to build a foundation for subsequent industrial network analysis. The value of such an approach can be seen in the following example. With a detailed understanding of individual network characteristics, both separately and collectively, it is possible to determine the source of issues, the means available to address them, any barriers that might exist, and the consequences of implementing any strategic interventions. The analysis approach proposed in this thesis is based on multi-criteria decisions analysis (MCDA), which, as a process, combines initial problem structuring and subsequent quantitative analysis stages. The tools employed within MCDA have been employed variously around considerations of sustainable development. Their value in this thesis is their integration within a rigorous analytical framework. Rigorous problem structuring is attractive as it helps elucidate the complexities of the system and its environment and is, by definition, designed to deal with multiple environmental social and economic criteria that would have to be considered to promote sustainable development. For the quantitative analysis, the industrial network analysis draws from existing analysis tools in IE, but predominately from other systems research disciplines, such as process systems engineering (PSE) and supply chain management (SCM). These fields, due to their maturity and practical focus, have invested a lot of research into system design and strategic planning, capturing system dynamics and uncertainty to ensure, within selected system constraints, that a proposed system or changes to a system are viable, and that the system is capable of achieving the stated objectives. Both PSE and SCM rely heavily on optimisation for system design and planning, and achieve good results with it as an analytical tool. The similarity between industrial networks and process systems / supply chains, suggests that an optimisation platform, specifically multi-objective dynamic optimisation, could be employed fruitfully for the analysis of industrial networks. This is the approach taken in this thesis. It is consistent with the “top down” approach advocated previously, which is deemed preferable for the identification and implementation analysis of strategic interventions. This enables the determination of a structure (design) that is “best” able to operate under future conditions (planning) with respect to the chosen sustainable development objectives. However, an analysis is only ever as good as its underlying data and assumptions. The complexity and scope of the industrial network and the challenge of articulating sustainable development target(s) give rise to significant uncertainties. For this reason a framework is developed within this thesis that integrates uncertainty analysis into the overall approach, to obtain insight into the robustness of the analysis results. Quantifying all the uncertainties in an industrial network model can be a daunting task for a modeller, and a decision-maker can be confused by modelling results. Means are therefore suggested to reduce the set of uncertainties that have to be engaged with, by identifying those which impact critically on model outcomes. However, even if uncertainty cannot be reduced, and the implementation of any strategy retains a degree of risk, the uncertainty analysis has the benefit that it forces an analyst to engage in more detail with the network in question, and to be more critical of the underlying assumptions. The analysis approach is applied to two case studies in this thesis: one deals with waste avoidance in an existing wood-products network in a large urban metropolis; the other with the potential for renewable energy generation in a developing economy. Together, these case studies provide a rich tableau within which to demonstrate the full features of the industrial network analysis. These case studies highlight how the context within which the relevant industrial network functions influences greatly the evolution of the network over time; how uncertainty is managed; and what strategies are preferred in each case in order to enhance the contribution of each network to sustainable development. This thesis makes an intellectual contribution in the following areas: • the characterisation of industrial networks to highlight sources of environmental issues, role the characteristics (could) play in the identification of (preferred) sustainable development strategies, and the need to explicitly consider these in a systems analysis. • the synthesis, adaptation and application of existing tools to fulfil the need for analysis tools in IE that can handle both contextual and system complexity, and address the above mentioned issues of lacking consideration of o system environment o dynamic nature of the system and its environment o economic and social impacts o the effect of uncertainty on analysis outcomes. • the development and demonstration of an industrial network analysis approach that o is flexible enough to model any industrial network at the inter-firm level, regardless of form and configuration of materials and products circulated, and depending on the existing network and the proposed strategies. o is able to encompass a wide range of environmental strategies, either individually or in combination depending on what best suits the situation, rather than focusing on any strategy in particular. o ensures long term viability of strategies, rather than short term solutions delivering incremental improvement. • the development of a comprehensive approach to capturing and assessing the effect of uncertainty on solution robustness for industrial network analysis, including the screening to determine the most important parameters, considering valuation and technical uncertainties, including future uncertainty. The industrial network analysis approach presented in this thesis looks more to how a network should develop (according to a set of sustainable development objectives), rather than how it may in actual fact develop. Consequently, the influence of agent interests and behaviour is not considered explicitly. This may be construed as a limitation of the industrial analysis approach. However, it is argued that the “top down” modelling approach favoured here is useful at a policy-making level. Here, for example, government instrumentalities, trade organisations and industry groupings, non-government organisations and community-based organisations are likely to be interested more in the performance of the network as a whole, rather than (necessarily) following the behaviour of individual agents within the network. Future work could well entertain the prospect of a mixed approach, in which the top-down approach of this thesis is complemented by a “bottom-up”, agent-based analysis. In this manner, it would be possible to give an indication of how attainable the identified industrial network development pathways are. Furthermore, the use of government incentives can be explored to assess if network development could approach the preferred development pathway which is identified using the methodology and results articulated in this thesis.

I present an agent-based model of animal movements and scent-mediated interactions whereby territories emerge as dynamic entities, though moving on a time-scale much slower than that of the animals. Simulation analysis suggests that the territory border movement depends upon the ratio of two quantities: the so-called active scent time, measuring how long olfactory cues are recognised by conspecifics as fresh, and the time it takes for an animal to cover its territory. By examining the interplay of adjacent territory boundaries, I give analytic insights into this dependence. I also construct an approximate analytic model of animal movement within dynamic territories that enables quantification of the active scent time from the location distribution of animals. Fitting this to data on a red fox (Vulpes vulpes) population before and after an outbreak of sarcoptic mange, I show how foxes change their behaviour as a result of rapid declines in population. Finally, I examine an extension of my model to the case where animals have fidelity towards a central place, such as a den or nest site. In this case, stable home ranges emerge from the territorial dynamics, enabling insights to be given into the mechanisms behind allometric scaling laws of space use. This thesis represents the first example of territorial emergence from a mechanistic model of individual-level movement and interaction processes.

Thesis (Ph. D.)--University of California, San Diego, 2009.
Title from first page of PDF file (viewed January 12, 2010). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 92-104).

Cette thèse est consacrée à l'étude d’agents appelés prosumers parce qu’ils peuvent, à partir d’énergies renouvelables, à la fois produire et consommer de l’électricité. Si leurs productions excèdent leurs propres besoins, ceux-ci cherchent à vendre leur surplus sur des marchés de l’électricité. Nous proposons de modéliser ces prosumers à partir de données météorologiques, ce qui nous a permit de mettre en évidence des corrélations spatio-temporelles non triviales, d'une grande importance pour les agrégateurs qui forment des portefeuilles d’équipements afin de vendre des services à l'opérateur du réseau. Comme un agrégateur est lié par un contrat avec l'opérateur, il peut faire l'objet de sanctions s’il ne remplit pas son rôle. Nous montrons que ces corrélations impactent la stabilité des agrégats, et donc le risque encouru par les agrégateurs. Nous proposons un algorithme minimisant le risque d'un ensemble d’agrégations, tout en maximisant le gain attendu. La mise en place de dispositifs de stockage dans un réseau où les générateurs et les charges sont dynamiques et stochastiques est complexe. Nous proposons de répondre à cette question grâce à la théorie du contrôle. Nous modélisons le système électrique par un réseau d'oscillateurs couplés, dont la dynamique des angles de phase est une approximation de la dynamique réelle du système. Le but est de trouver le sous-ensemble des nœuds du graphe qui, lors d'une perturbation du système, permet le retour à l'équilibre si les bons signaux sont injectés, et ceci avec une énergie minimum. Nous proposons un algorithme pour trouver un placement proche de l'optimum permettant de minimiser l'énergie moyenne de contrôle
This thesis is devoted to the study of agents called prosumers because they can, from renewable, both produce and consume electricity. If their production exceeds their own needs, they are looking to sell their surplus on electricity markets. We propose to model these prosumers from meteorological data, which has allowed us to highlight non trivial spatial and temporal correlations. This is of great importance for aggregators that form portfolios of equipments to sell services to the network operator. As an aggregator is bound by a contract with the operator, it can be subject to penalties if it does not fulfill its role. We show that these correlations impact the stability of aggregates, and therefore the risk taken by the aggregators. We propose an algorithm minimizing the risk of the aggregations, while maximizing the expected gain. The placement of storage devices in a network where generators and loads are stochastic and not fixed is complex. We propose to answer this question with control theory. We model the electrical system as a network of coupled oscillators, whose phase angles dynamics is an approximation of the actual dynamics of the system. The goal is to find the subset of nodes in the graph that, during a disturbance of the system, allows returning to equilibrium if the right signals are injected and this with a minimum energy. We propose an algorithm to find a near optimal placement to minimize the average energy control

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2012.
"September 2012." Cataloged from PDF version of thesis.
Includes bibliographical references (p. 163-167).
The Compatibility Assessment Method (CAM), a new structured process for assessing compatibility between parent systems and child subsystems is proposed and applied to several cases where subsystems are being replaced in legacy systems. CAM is a screening process intended to be used by project managers who need to replace components of complex systems. The functional model-based process uses an extension of the Integrated Definition Modeling Language of IDEFO. The IDEFO method is used for defining compatibility measures based on each of the four constituent arrows that show inputs, controls, outputs, and mechanisms (ICOM). In this extension, the control constituents are replaced with constraints. Each of the ICOM constituents is expanded with parameters which include metrics and values. The ICOMs with their parameters and metrics are then used to characterize two or more subsystems in a matrix format. The differences between these matrices are entered into the sparse "Delta Matrix" which shows analysts the differences between the systems. These differences can be assigned to the appropriate levels of technical expertise to be analyzed and to determine feasibility of the child subsystem in the parent system. The process is compared to current practices in government unmanned aircraft system program offices to determine the usefulness of adopting this compatibility assessment process. This dissertation outlines the need for and development of the method for application by practitioners responsible for replacing subsystems on legacy systems. The development includes evaluations of the method and an experiment with cohorts of student system engineers to compare the output of the Compatibility Assessment Method to less-structured methods. This research contributes additional insight into system architecting theory and proposes a structured method for practitioners to use to improve the processes to perform part replacement in legacy systems. While others have offered methods to measure aspects of system architecture, this proposed method moves beyond the extant literature with tools for practitioners.
by David Scott Andrew Long.
Ph.D.

This diploma thesis focuses on the analysis of a particular soft complex system in the company. This system is a running car service with a determined problem situation. This system and its problem is then evaluated in terms of soft systems methodology, system dynamics and critical systems heuristics. The theoretical section provides concepts to understand the complexity and also individual system approaches. As beneficial of work I consider the practical part, which is aimed to the analysis of complex real-world system using the selected approaches as well as an evaluation of these approaches. Main purpose is to bring comparisons and suggestions for improvement and also a broader view to the system. All of this increases information value of approaches and we are able to deliver more relevant information. Thesis is therefore focused not only to deal with examples from practice but also to extend the selected theories within the system approaches.

This thesis suggests a new model of human-machine interaction in the domain of non-idiomatic musical improvisation. Musical results are viewed as emergent phenomena issuing from complex internal systems behaviour in relation to input from a single human performer. We investigate the prospect of rewarding interaction whereby a system modifies itself in coherent though non-trivial ways as a result of exposure to a human interactor. In addition, we explore whether such interactions can be sustained over extended time spans. These objectives translate into four criteria for evaluation; maximisation of human influence, blending of human and machine influence in the creation of machine responses, the maintenance of independent machine motivations in order to support machine autonomy and finally, a combination of global emergent behaviour and variable behaviour in the long run. Our implementation is heavily inspired by ideas and engineering approaches from the discipline of Artificial Life. However, we also address a collection of representative existing systems from the field of interactive composing, some of which are implemented using techniques of conventional Artificial Intelligence. All systems serve as a contextual background and comparative framework helping the assessment of the work reported here. This thesis advocates a networked model incorporating functionality for listening, playing and the synthesis of machine motivations. The latter incorporate dynamic relationships instructing the machine to either integrate with a musical context suggested by the human performer or, in contrast, perform as an individual musical character irrespective of context. Techniques of evolutionary computing are used to optimise system components over time. Evolution proceeds based on an implicit fitness measure; the melodic distance between consecutive musical statements made by human and machine in relation to the currently prevailing machine motivation. A substantial number of systematic experiments reveal complex emergent behaviour inside and between the various systems modules. Music scores document how global systems behaviour is rendered into actual musical output. The concluding chapter offers evidence of how the research criteria were accomplished and proposes recommendations for future research.

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 143-148).
Buildings account for over 40% of the energy consumption in the United States, nearly 40% of which is attributed to lighting. The selection of a fenestration system for a building is a critical decision as it offsets electric lighting use as well as impacts energy performance through heating and cooling systems. Further, the fenestration system contributes to both occupant comfort and ambiance of the space. Complex Fenestration Systems (CFS) address these factors with a variety of innovative technologies but the language to describe, discuss, and compare them does not exist. Existing traditional metrics for fenestration systems are unable to reveal the benefits that characterize complex fenestration systems because they are rigid, do not reflect annual performance, and were developed for a different purpose. The framework presented in this research offers a solution to this problem by using an annual climate-based methodology to provide a comprehensive evaluation of a system by incorporating three of the most relevant performance aspects: energy efficiency, occupant visual comfort, and ability to view through. Three metrics, the Relative Energy Impact (REI), the Extent of Comfortable Daylight (ECD), and the View Through Potential (VTP), were derived from these three criteria to express, in relative terms, a fagade's contribution to building energy use, comfortable daylight conditions, and the degree of transparency, respectively. Several practical matters were considered when developing a policy-relevant set of metrics, including both ease of calculation for manufacturers and usability for consumers. As such, the calculation methodology evolved from its initial proposal into a simplified approach, analytical where possible, and into a label-like concept for visual representation. These metrics are intended to exist as a mechanism by which manufacturers can evaluate and compare facade systems, provide high-level intuition of relative performance for designers and contractors, and enable the balance of performance objectives based on user preference. Ultimately, the creation of this comprehensive language is intended to stimulate innovation in fenestration systems and encourage their use in both new and retrofit building applications.
by Shreya H. Dave.
S.M.
S.M.in Technology and Policy

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada
This paper presents a method for the optimization of mixed networks that incorporates a mixed layer optimization of performance features. The expanded integrated Network Enhanced Telemetry (iNET) system envisioned telemetering for large and complex networks which will require core telemetry networks with ad hoc extensions for coverage. Organizing such a network has been successfully accomplished in simulations using a K-mean clustering algorithm. This paper shows how the features of these network elements will be captured and disseminated in a real system. This management of network elements across multiple layers is characterized as cross-layer optimization. This paper will also show how such cross layer features can be combined for a globally optimum solution. It shows by example how the iNET system comprising multiple ground stations, gateways, frequency, nodes, and three performance measures can be optimized to achieve overall optimal system performance.

The aim of this research is to identify and analyze the impact of design changes to a system in a concurrent engineering environment and the development project, and to make proposals how to minimize the impact on the development project performance. A further objective is also to determine the effect of design changes as a result of design influencing. In a concurrent engineering environment system components are being developed in parallel. Any change to one component of the system may impact on other system components under development. Design as part of the systems engineering process is an iterative and dynamic process. Although the systems engineering process has been very well structured and refined over the years, it still remains to a certain extent an unpredictable process. A consequence of this is that changes to a design of a subsystem or component comprising the system can occur at any stage of the process. The systems engineering process is a “static” process since there are no time constraints or management of consumption of resources on the different systems engineering processes and steps. As such system engineering cannot function in isolation. To bring a system into being, systems engineering must function within a project management environment to provide the management of schedule and the consumption of resources. The interaction between project management and system engineering processes can have a distinct influence on the systems engineering process and must be taken into account when studying the performance of system development projects. This research investigates the project management/systems engineering interface with specific focus on cost and schedule. Since project management is the encompassing process wherein a system is being developed, its influence on the system engineering process will also be investigated. This research has the following research objectives:

• Optimization of design influencing by dividing the design teams into two different complementary but opposing mindset groups.
• Evaluate the impact of design changes in terms of cost and schedule overruns in a concurrent engineering development environment.

A comprehensive development project was used as a case-study. A Narrative Inquiry comprising the main system development project players investigated the problems experienced on the project and found that management was the major cause for the project cost and schedule overruns. The principal finding of this research showed, that unplanned, unexpected and forced design changes was the primary area of conflict between systems engineering and project management, leading to development project cost and schedule overruns. The Narrative Inquiry findings were actually the symptoms of a deeper underlying problem. Root Cause analysis identified the fundamental mechanisms of design change and the influence of management on the process. This research identifies the fundamental mechanisms that result in design iterations and the influence that management has on this process. An improved “Effect-to-Cause” design influencing model is proposed to reduce the risk of design changes during system integration. A mathematical model has been developed to quantify the impact of a design change on a multi-layer, multi-component system. This model confirms that the system hierarchy design is very important to minimize the impact and consequential development project risk should a design change be required for one of the system components. By means of the mathematical model, a proposed system’s architecture can be modelled. The model quantifies the impact of a system component design change on the rest of the system development project. This model will facilitate the optimization of system architecture to reduce development project cost and schedule risks. The system architecture model will also enable design review boards to make informed decisions when considering options for a system component design change. This research also found that the Systems Engineering process must function harmoniously within the larger Project Management environment for the optimum performance of a development project. The road forward to achieve this goal is for the systems engineering and design processes to become more structured and the removal of the unpredictability in the processes so far as the number of design iterations is concerned. This will enable the systems engineering processes to be more easily accommodated within the structured project management processes to the benefit of the overall development project performance. A structured “Cause-to-Effect” design influencing methodology has been investigated. Indications are that this may be the road forward for systems engineering process development to even further reduce the risk of a design change during system integration and consequential detrimental impact on the development project performance.
Thesis (PhD)--University of Pretoria, 2012.
Graduate School of Technology Management (GSTM)
unrestricted

In today's global business scenarios, an organization can strengthen its com-petitiveness by offering a spectrum of industrial services that range from tra-ditional customer support to turnkey solutions. To achieve this service spec-trum, it is necessary to manage information consumption and production at right quality level in right time. When dealing with complex technical systems, e.g. military aircraft, with long life cycles, the management of maintenance-related information is crucial to fulfil stringent dependability, Life Support Cost (LSC) and safety requirements. Today, there is available Information & Communication Technology (ICT) to realize an eMaintenance solution for the necessary information logistics. However, there is a lack of appropriate frameworks, methodologies and tools that enable a service-oriented approach to eMaintenance. Hence, the purpose of this research is to explore and describe how an eMaintenance solution can be developed to provide information services that support the maintenance of complex technical systems. To fulfil the purpose, a major case study within military aviation has been performed, supported by two minor case studies within the healthcare sector and the process industry. Empirical data has been collected through interviews, observations, archival records and workshops. The analysis is based on developed theoretical frameworks, Design of Experiment (DoE) principles and available interna-tional standards. The results of this research are: I) an exploration and definition of eMaintenance; II) a description of eMaintenance as support to maintenance of complex technical systems; III) an eMaintenance Management Framework (eMMF) for establishment of an eMaintenance platform; and IV) a methodology with a supporting toolbox that facilitates the identification of maintenance support information.
Godkänd; 2008; 20081113 (ysko)

The objective of this thesis is to propose fundamental concepts, analytical and numerical tools, and approaches to characterize, understand, and better observe complex systems. The scientific contribution of this thesis can be separated in tree topics. In the first one, we show how to theoretically estimate the Mutual Information Rate (MIR), the amount of mutual information transmitted per unit of time between two time-series. We then show how a quantity derived from it can be successfully used to infer the network structure of a complex system. The proposed inference methodology shows to be robust in the presence of additive noise, different time-series lengths, and heterogeneous node dynamics and coupling strengths. It also shows to be superior in performance for networks formed by nodes possessing different time-scales, as compared to inference methods based on mutual information (MI). In the second topic, a deep analysis of causality from the space-time properties of the observed probabilistic space is performed. We show the existence of special regions in the state space which indicate variable ranges responsible for most of the information exchanged between two variables. We define a new causality measure named CaMI that explores a property we have understood: in order to detect if there is a flow of information from X to Y, one only needs to check the positiveness of the MI between trajectories in X and Y, however assuming that the observational resolution in Y is larger than in X. Moreover, we show how the assessment of causality can be done when we consider partitions with arbitrary, but equal rectangular cells in the probabilist space, what naturally facilitates the calculation of CaMI. In the third topic, we develop a symbolic coefficient of observability that allows us to understand what is the reduced set of accessible variables to observe a complex system, such that it can be fully reconstructed from the set of observed variables, regardless of its dimension. Using this symbolic coefficient, we explain how it is possible to compare different complex systems from the point of view of observability and how to construct systems of any dimensionality that can be fully observed by only one variable.