Tesis sobre el tema "Multi-criteria Design"

Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, March 2005.
Thesis Advisor(s): Fotis Papoulias, Roman B. Statnikov. Includes bibliographical references (p. 241). Also available online.

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Numerous optimization problems involve systems with multiple and often contradictory criteria. Such contradictory criteria have been an issue for marine/naval engineering design studies for many years. This problem becomes more important when one considers novel ship types with very limited or no operational record. A number of approaches have been proposed to overcome these multiple criteria design optimization problems. This Thesis follows the Parameter Space Investigation (PSI) technique to address these problems. The PSI method is implemented with a software package called MOVI (Multi-criteria Optimization and Vector Identification). Two marine/naval engineering design optimization models were investigated using the PSI technique along with the MOVI software. The first example was a bulk carrier design model which was previously studied with other optimization methods. This model, which was selected due to its relatively small dimensionality and the availability of existing studies, was utilized in order to demonstrate and validate the features of the proposed approach. A more realistic example was based on the "MIT Functional Ship Design Synthesis Model" with a greater number of parameters, criteria, and functional constraints. A series of optimization studies conducted for this model demonstrated that the proposed approach can be implemented in a naval ship design environment and can lead to a large design parameter space exploration with minimum computational effort.
Lieutenant Junior Grade, Turkish Navy

System architecture is defined as the description of a complex system in terms of its functional requirements, physical elements and their interrelationships. Designing a complex system architecture can be a difficult task involving multi-faceted trade-off decisions. The system architecture designs often have many project-specific goals involving mix of quantitative and qualitative criteria and a large design trade space. Several tools and methods have been developed to support the system architecture design process in the last few decades. However, many conventional problem solving techniques face difficulties in dealing with complex system design problems having many goals. In this research work, an interactive multi-criteria design optimization framework is proposed for solving many-objective system architecture design problems and generating a well distributed set of Pareto optimal solutions for these problems. System architecture design using multi-criteria optimization is demonstrated using a real-world application of an aero engine health management (EHM) system. A design process is presented for the optimal deployment of the EHM system functional operations over physical architecture subsystems. The EHM system architecture design problem is formulated as a multi-criteria optimization problem. The proposed methodology successfully generates a well distributed family of Pareto optimal architecture solutions for the EHM system, which provides valuable insights into the design trade-offs. Uncertainty analysis is implemented using an efficient polynomial chaos approach and robust architecture solutions are obtained for the EHM system architecture design. Performance assessment through evaluation of benchmark test metrics demonstrates the superior performance of the proposed methodology.

In recent years, the chemical and pharmaceutical industries have faced increased development times and costs with fewer novel chemicals being discovered. This has resulted in many companies focusing on innovative research and development as they consider this key to business success. In particular, a number of leading industrial organisations have adopted the principles of Whole Process Design (WPD). WPD considers the optimisation of the entire product development process, from raw materials to end product, rather than focusing on each individual unit operation. The complexity involved in the implementation of WPD requires rationalised decision-making, often with limited or uncertain information. This thesis assesses the most widely applied methods in Multi-Criteria Decision Analysis (MCDA) in conjunction with the results of two interviews and two questionnaires that identified the industrial requirements for decision-making during WPD. From the findings of this work, a novel decision-making methodology was proposed, the outcome of which allows a decision-maker to visually interpret their decision results with associated levels of uncertainty. To validate the proposed methodology, a software framework was developed that incorporates two other decision-making approaches, the Analytical Hierarchy Process (AHP) and ELimination Et Choix Traduisant la REalité trois (ELECTRE III). The framework was then applied to a number of industrial case studies to validate the application of the proposed methodology.

Mixing is a key process in microfluidic systems since that samples and reagents generally need to be mixed thoroughly before chemical or biological analysis or reactions. Micromixers are designed to fulfil this critical process. In general, the development of microdevices is a competitive field that requires from researchers shorter times and lower costs in prototyping. Computational Fluid Dynamics (CFD) helps in reducing the time from concept to device design. Intuition and experience of the designer is usually behind its application on design improvement, by analyzing some physical variables to determine the effect of design parameters and to adjust them accordingly to the pursued objectives. In this thesis, a design and optimization strategy is presented and used for the analysis and design of micromixers. The method systematically integrates CFD with an optimization strategy based on the use of Design of Experiments, Surrogate Modelling and Multi-Objective Genetic Algorithm techniques. The aim is to define optimum designs that give the trade-off of the performance parameters, which in this study are the mixing index, defined on the basis of mass concentration distribution, and the pressure drop in the microchannel. Three types of micromixers have been studied and their geometric parameters have been optimized. They are the Staggered Herringbone Mixer and two novel designs, a planar micromixer with baffles in the microchannel and a 3-D T-type micromixer. A completed fabrication method was implemented as part of this thesis work and it was used to fabricate some of the micromixers. Experimental measurements and published data have been used to validate the numerical results. The outcomes of this thesis demonstrate that using advanced optimisation techniques on the basis of CFD solutions and analyses allows the design of optimum micromixers for different operation conditions, which can be set by the designer, without being necessary to use a referential design to start the method.

Les modèles de conception des chaînes logistiques sont devenus de plus en plus complexes, à cause de l'environnement économique incertain et l'introduction de nouveaux critères de décision tels que : l'aspect environnemental, l'aspect social, l'aspect législatif, l'aspect économique, la satisfaction du client et la prise en compte des risques. Répondre aux changements qui touchent les chaînes logistiques exige de composer avec des incertitudes et des informations incomplètes. Configurer des chaînes logistiques multicritères avec prise en compte des incertitudes peut garantir la continuité des activités de l'entreprise.L'objectif principal de cette thèse est la conception de chaînes logistiques multicritères qui résistent aux changements et l'instabilité des marchés. Le manuscrit de cette thèse s'articule autour de sept principaux chapitres:1 - introduction.2 - Etat de l'art sur la conception des chaînes logistiques.3 -Conception des chaînes logistiques multicritères en mesure de répondre aux nouveauxcritères économiques, sociaux, environnementaux et législatifs.4 - Conception des chaînes logistiques multi-objectifs.5 - Développement d'une heuristique de résolution des problèmes de conception deschaînes logistiques de taille réelle.6 - Conception des chaînes logistiques avec prise en compte des incertitudes.7 - Conclusions et perspectives
This thesis contributes to the debate on how uncertainty and concepts of sustainable development can be put into modern supply chain network and focuses on issues associated with the design of multi-criteria supply chain network under uncertainty. First, we study the literature review , which is a review of the current state of the art of Supply Chain Network Design approaches and resolution methods. Second, we propose a new methodology for multi-criteria Supply Chain Network Design (SCND) as well as its application to real Supply Chain Network (SCN), in order to satisfy the customers demand and respect the environmental, social, legislative, and economical requirements. The methodology consists of two different steps. In the first step, we use Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) to buildthe model. Then, in the second step, we establish the optimal supply chain network using Mixed Integer Linear Programming model (MILP). Third, we extend the MILP to a multi-objective optimization model that captures a compromisebetween the total cost and the environment influence. We use Goal Programming approach seeking to reach the goals placed by Decision Maker. After that, we develop a novel heuristic solution method based on decomposition technique, to solve large scale supply chain network design problems that we failed to solve using exact methods. The heuristic method is tested on real case instances and numerical comparisons show that our heuristic yield high quality solutions in very limited CPU time. Finally, again, we extend the MILP model presented before where we assume that the costumer demands are uncertain. We use two-stage stochastic programming approach to model the supply chain network under demand uncertainty. Then, we address uncertainty in all SC parameters: opening costs, production costs, storage costs and customers demands. We use possibilistic linear programming approach to model the problem and we validate both approaches in a large application case

Hoy en día, los controladores proporcionales integrales y proporcionales integrales derivativos son los algoritmos de control más utilizado en la industria. Por otra parte, los controladores fraccionarios han recibido atención recientemente, por parte de la comunidad científica y desde el punto de vista industrial. Debido a esto, en esta tesis algunos de los escenarios implican la sintonización de estos controladores mediante el procedimiento de diseño mediante la optimización multi-objetivo. Este procedimiento se centra en proporcionar un equilibrio razonable entre los objetivos en conflicto y brinda al diseñador la posibilidad de apreciar la comparación de los objetivos de diseño. Esta tesis se divide en tres partes. La primera parte, presenta los fundamentos del sistema de control y discusión de los diferentes compromisos: entre los modos de operación servo / regulación y del rendimiento / robustez. Por otro lado, se ha proporcionado un marco conceptual acerca de la optimización multi-objetivo. La segunda parte, introduce la solución de Nash como una técnica de selección multi-criterio, para seleccionar un punto del frente de Pareto, que represente el mejor compromiso entre los objetivos de diseño. Esta solución es una selección semi-automática escogida en la aproximación del frente de Pareto y ofrece un buen compromiso entre los objetivos de diseño. Luego, se presenta el Multi-stage approach para el proceso de optimización multi-objetivo. Este enfoque implica dos algoritmos: un algoritmo determinista y algoritmo evolutivo. En el cual ambos algoritmos se complementen entre sí a pesar de sus desventajas y mejoran los resultados de la optimización en términos de convergencia y precisión. Además, se introduce el objetivo basado en la fiabilidad, en la descripción del problema multi-objetivo, este se utiliza para medir la degradación del rendimiento. Vale la pena mencionar que, debido a la existencia de incertidumbres en el diseño y fabricación, teniendo este objetivo de diseño le dará otra perspectiva al diseñador en el mundo real. Con el fin de validar el método, dos casos de estudios se ha considerado, el problema de control de la caldera (The Boiler Control Benchmark) para la sintonización de controladores y como segundo caso, una pila Peltier nolineal. Por último, la tercera parte de esta tesis, presentan las contribuciones a la sintonización de controladores. En primer lugar, se propone un conjunto de reglas de sintonía basado en la solución de Nash para un controlador proporcional-integral, en donde la robustez / rendimiento han sido considerados. Por otra parte, como un segundo caso se presenta las reglas de sintonía para un controlador proporcional-integral-derivativo, donde se han considerado el compromiso de robustez/rendimiento y los modos de operación servo / regulación. Además, se proponen reglas de sintonía para el controlador proporcional-integral-derivativo-fraccional-orden implementado el Multi-stage approach para la optimización multi-objetivo.
Nowadays, the proportional integral and proportional integral derivatives are the most used control algorithm in the industry. Moreover, the fractional controllers have received attention recently for both, the research community and from the industrial point of view. Owing to this, in this thesis some of the scenarios involve the tuning of these controllers by using the Multiobjective Optimization Design procedure. This procedure focuses on providing reasonable trade-off among the conflictive objectives and brings the designer the possibility to appreciate the comparison of the design objectives. This thesis is divided in three parts. The first part, presented the fundamentals of the control system showing and discussing the different trade-offs between performance/robustness and servo/regulation operation modes. On the other hand a background on multi-objective optimization has been provided. The second part, introduces the Nash solution as a multi-criteria decision making technique, to select a point from the Pareto front that represent the best compromise among the design objective. This solution provides a semi-automatic selection from the Pareto front approximation and offers a good trade-off between the goal objectives. Hereafter, a Multi-stage approach for the multi-objective optimization process is presented. This approach involves two algorithms: a deterministic and evolutionary algorithm. In which both algorithms complement each other in despite of their drawbacks and improve the results of the overall optimization in terms of convergence and accuracy. Further, the introduction of reliability based objective into the multi-objective problem is carried out, to measure the performance degradation. It is worthwhile to mention that, due to the existence of uncertainties in real-world designing and manufacturing having this design objective will give another perspective to the designer. In order to validate the approach, two different case studies has been considered, the Boiler control problem for controller tuning and as second case, a non-linear Peltier Cell. Finally, the third part of this thesis, the contributions on controller tuning have been presented. First, a set of tuning rules based on the NS for a proportional-integral (PI) controller have been devised, where the robustness/performance trade-off have been considered. Moreover, as a second case it is presented a tuning for proportional-integral-derivative controller where the trade-off of the performance/robustness and servo/regulation operation mode has been considered. Moreover, the fractional-order-proportional-integral-derivative controller is tuned by using the Multi-stage approach for the MOO process.

The background for this thesis is based on the assumption that the success of solar buildings relies on the assessment and integration of all the different design objectives, called criteria. These criteria are often quite complicated to deal with (e.g. environmental loading) and may be conflicting. The different design issues and the many different available energy technologies call for different areas of expertise to be involved in the design of solar buildings. This makes it difficult to evaluate the overall “goodness” of a proposed design solution. Also, the communication between design professionals and the client becomes complicated.

The goal of this work was therefore to produce a means for the design team and clients to be able to better understand and handle holistic solar design. A first hypothesis was that a structured approach for evaluating design alternatives might be a means to this end.

In order to specify an approach that would fit into the building design process, an analysis of design process theory and building design practice was carried out (chapter 2). Also, special solar design issues were investigated. This analysis resulted in the following conclusions:

· Most building design processes start out with no clearly defined goals or criteria of success. The design criteria are refined and discovered through evaluation and feedback on alternative design proposals.

· Design involves a lot of subjective value judgements, and decisions are often based on experience, “gut feeling”, or intuition. Design options are evaluated based on quantitative and qualitative performance measures. There exists no objective optimal design solution.

· It is possible to identify some main activities that are common to most design processes. These are categorized into 4 main tasks: problem formulation, generation of alternatives, performance prediction and evaluation. The activities are very much overlapping and dependent on each other.

· Decision-making in design happens mainly through evaluation of proposed design solutions.

The successful energy design of buildings requires that special attention be paid to the conceptual stage. However, it is a difficult task to find the most promising design alternatives satisfying several conflicting criteria. This thesis presents a simple multi-criteria decisions analysis method that could assist designers in green building design. Variables in the model include those alternatives that are common options when a residential building is to be constructed. The individual components that are considered are the building envelope, heating, ventilation and air conditioning (HVAC) system, service water heating, power and lighting. The key actors, objectives and methodology of multi-criteria decisions analysis are presented and finally a case study for a residential building in Athens is performed. The criteria by which to evaluate each building component of the newly built construction were identified by the decision-makers. Subsequently, decision frameworks for the selection of roof, walls, windows, heating system, energy source for heating system, power source, lighting and service water heating system were built. The method is followed step-by-step to conclude on the optimal building components based on their score. Due to the equal scoring of the windows and an inapplicable combination of electric underfloor heating with air-to-water heat pump, the method is characterized by low accuracy. The fact that the building components have been treated individually sets the method as a basic one and indicates that a more complex one should be preferred when more trustworthy results are needed.

In several types of embedded systems the applications are deployed both as software and as hardware components. For such systems, the partitioning decision is highly important since the implementation in software or hardware heavily influences the system properties. In the industry, it is rather common practice to take deployment decisions in an early stage of the design phase and based on a limited number of aspects. Often such decisions are taken based on hardware and software designers‟ expertise and do not account the requirements of the entire system and the project and business development constraints. This approach leads to several disadvantages such as redesign, interruption, etc. In this scenario, we see the need of approaching the partitioning process from a multiple decision perspective. As a consequence, we start by presenting an analysis of the most important and popular Multiple Criteria Decision Analysis (MCDA) methods and tools. We also identify the key requirements on the partitioning process. Subsequently, we evaluate all of the MCDA methods and tools with respect to the key partitioning requirements. By using the key partitioning requirements the methods and tools that the best suits the partitioning are selected. Finally, we propose two MCDA-based partitioning processes and validate their feasibility thorough an industrial case study.

Traffic signal systems serve as one of the most powerful control tools in improving the efficiency of surface transportation travel. Traffic operations on arterial roads are particularly complex because of traffic interruptions caused by signalized intersections along the corridor. This dissertation research presents a systematic framework of integrated traffic control in an attempt to break down the complexities into several simpler sub-problems such as pattern recognition, environment-mobility relationships and multi-objective optimization for multi-criterial signal timing design. The overall goal of this dissertation is to develop signal timing plans, including a day plan schedule, cycle length parameters, splits and offsets, which are suitable for real traffic conditions with consideration of multi-criterial performance of the surface transportation system. To this end, the specific objectives are to: (1) identify appropriate time-of-day breakpoints and intervals to accommodate traffic pattern variations for day plan schedule of signal timing; (2) explore the relationship between environmental outcomes (e.g., emissions) from emission estimators and mobility measures (e.g., delay and stops) for different types of intersections; (3) optimize signal timing parameters for multi-criteria objectives (e.g., minimizing vehicular delay, number of stops, marginal costs of emissions and total costs), with the comparison of performance metrics for different objectives, at the intersection level; (4) optimize arterial offsets for different objectives at the arterial level and compare the performance metrics of different objectives to recommend suitable objectives for integrated multi-criteria signal timing design in arterial traffic operations. An extensive review of the literature, which covers existing tools, traffic patterns, traffic control with environmental concerns, and related optimization methods, shows that both opportunities and challenges have emerged for multi-criteria traffic signal timing design. These opportunities include large quantities of traffic condition data collected by system detectors or non-intrusive data collection platforms as well as powerful tools for microscopic traffic modeling and instantaneous emission estimation. The challenge is how to effectively deal with these big data, either from field collection or detailed simulation, and provide useful information for decision makers in practice. Methodologically, there's a tradeoff between the accuracy of objective function values and the computational efficiency of simulation and optimization. To address this need, in this dissertation, traffic signal timing design that systematically enables the use of integrated data and models are investigated and analyzed in the four steps/studies. The technology of identifying time-of-day breakpoints in the first study shows a mathematical way to classify dynamic traffic patterns by understanding dynamic traffic features and instabilities at a macroscopic level on arterials. Given the limitations of using built-in emissions modules within current traffic simulation and signal optimization tools, the metamodeling-based approach presented in the second study makes a methodological contribution. The findings of the second study on environment-mobility relationships set up the base for extensive application of two-stage optimization in the third and fourth studies for sustainable traffic operations and management. The comparison of outputs from an advanced estimator with those from the current tool also addresses improving the emissions module for more accurate analysis (e.g., benefit-cost analysis) in practical signal retiming projects. The third study shows that there are tradeoffs between minimizing delay and minimizing marginal costs of emissions. When total cost (including cost of delay, fuel consumption and emissions) is set as a single objective function, that objective clears the way for relatively reliable results for all the aspects. In the fourth study, the improvements in marginal cost of emissions and total cost by dynamic programming procedure are obvious, which indicates the effectiveness of using total link cost as an objective at the corridor level. In summary, this dissertation advocates a sustainable traffic control system by simultaneously considering travel time, fuel consumption and emissions. The outcomes of this integrated multi-criteria signal timing design can be easily implemented by traffic operators in their daily life of retiming signal timing.

In the past decades, the world has noticed complex changes in its climate. The resources available now as well as in the future could be said to be analogous to the decreasing circumference of a funnel. The wealthy population with the means to elect what goods they wish to consume are becoming aware of their impact both on nature as well as on the less fortunate people of the planet. As a consequence environmental and human-centered factors are of higher priority than ever before in the decisions made by companies, which in turn will decide the future. This thesis aims to investigate what set of criteria can be seen as most relevant for sustainable material selection at a manufacturing company. To be relevant for the future these design criteria are decided with a base in modern research from the past decade in the field of material selection. The company chosen as a case to study and collaborate with was IKEA Components AB. The research was conducted on-site at the company’s facilities in Älmhult, Småland, as well as at the Blekinge Institute of Technology in Karlskrona, Blekinge. The company vision for the future which IKEA is striving towards is focused on lowering carbon dioxide equivalents, from which a lion share of the emissions is a result of the material they are selecting for their products. Experts within various fields of the chosen company were consulted to gain perspective and knowledge while designing and testing prototypes of a tool to facilitate a sustainable material selection. The metal alloys were analyzed for toxicity based on the percentages of all elements they contained and scored based on chosen sustainability criteria. The plastics were judged on recyclability, renewability, and degradability apart from available numbers for emission factors. After this, the materials were placed in the excel tool which was then tested by engineers and evaluated in semi-structured interviews. Updates were made to make the tool as user-friendly as was possible and new tests were conducted. Overall, the tool was appreciated by the users who tested it and more improvements were planned to finalize the prototype. Results are detailed in the latter part of the report, discussing designs the engineers preferred over others, the current scale of sustainability tools used in the company and how the testers scored the tool. In the discussion, criteria are evaluated based on their multi-criteria compliance with sustainability factors. Drawing conclusions about the subject of sustainability criteria was accomplished by conducting literature studies in material criticality, making use of the methods for sustainable product development taught in the master of science, investigating material toxicity, testing solutions for sustainable material selection at a typical furniture component manufacturing company, receiving feedback from constructors and exploring connections for the selected methods to the principles of sustainability.

Ces dernières décennies, l'industrie en microélectronique s'est astreinte à suivre la loi de Moore pour améliorer la performance des circuits intégrés (Integrated Circuit, IC). Cependant, il sera sans doute impossible de suivre cette loi dans le futur à cause de limitations physiques apparaissant avec la miniaturisation des transistors en-dessous d'un certain seuil si aucune innovatio n'a lieu. Afin de surmonter ce problème, de nouvelles technologies ont émergées, et parmi elles les circuits 3D (3D-Stacked Integrated Circuit, 3D-SIC) ont été proposés pour maintenir l'évolution de la loi de Moore. Les 3D-SIC peuvent apporter de nombreux avantages dans le design des futurs IC mais au coût d'une complexité de design accrue étant donné leur nature fortement combinatoire, et l'optimisation de plusieurs critères conflictuels. Dans cette thèse, nous présentons une première étude des outils qui pourraient aider dans le design de 3D-SIC, en utilisant l'optimisation multi-objectifs (multiobjective optimization, MOO) et l'aide multicritère à la décision (multi-criteria decision aid, MCDA). Notre étude vise l'une des problématiques principales dans le design de 3D-SIC: le partitionnement avec estimation du floorplanning en tenant compte de plusieurs objectifs. Cette thèse montre que l'utilisation d'un paradigme multicritère peut fournir une analyse pertinente et objective du problème. Cela peut permettre une exploration rapide de l'espace de design et une amélioration des flots de conception actuels étant donné qu'il est possible de fournir des informations qualitatives et quantitatives par rapport à l'espace de design qui ne seraient pas disponibles avec les outils actuels. De même, de par sa flexibilité, la MOO peut tenir compte des multiples degrés de liberté des 3D-SIC, ce qui permet plus de possibilités de design qui ne sont généralement pas prises en compte avec les outils actuels. De plus, les algorithmes développés peuvent montrer des propriétés de robustesse même si le problème est complexe. Enfin, appliquer l'aide multicritère à la décision pourrait permettre aux designers de faire des choix pertinents selon un processus transparent.
In the past decades, the microelectronic industry has been following the Moore's law to improve the performance of integrated circuits (IC). However, it will probably be impossible to follow this law in the future due to physical limitations appearing with the miniaturization of the transistors below a certain threshold without innovation. In order to overcome this problem, new technologies have emerged, and among them the 3D-Stacked Integrated Circuits (3D-SIC) have been proposed to keep the Moore's momentum alive. 3D-SICs can bring numerous advantages in the design of future ICs but at the cost of additional design complexity due to their highly combinatorial nature, and the optimization of several conflicting criteria. In this thesis, we present a first study of tools that can help the design of 3D-SICs, using mutiobjective optimization (MOO) and multi-criteria decision aid (MCDA). Our study has targeted one of the main issues in the design of 3D-SICs: the partitioning with floorplanning estimation under multiple objectives. This thesis shows that the use of a multi-criteria paradigm can provide relevant and objective analysis of the problem. This can allow a quick design space exploration and an improvement of the current design flows as it is possible to provide qualitative and quantitative information about a design space, that would not be available with current tools. Also, with its flexibility, MOO can cope with the multiple degrees of freedom of 3D-SICs, which enables more design possibilities that are usually not taken into account with current tools. In addition, the developed algorithms can show robustness properties even if the problem is complex. Finally, applying multi-criteria decision aid would allow designers to make relevant choices in a transparent process.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

The aim of this research is to test a decisional aid model - the Analytic Hierarchy Procedure (AHP) - in risk assessment for development of an urban area. The Port Authority of Venice commissioned the Regional Environmental Protection Agency (ARPAV) to carry out an estimation of major industrial hazards in Porto Marghera, an industrial estate near Venice (Italy), via Quantitative Risk Analysis (QRA). However, this model only provided a list of individual quantitative risk values, related to single locations. Therefore, there was both a need and an opportunity to introduce a decision aid model, which could take into account the geographic distribution of risk, the quantification of intangible factors and the analysis of possible future developments. The experimental model, through a series of trade -off comparisons, encouraged the use of expert opinions in conjunction with traditional quantitative analysis, enabling the decision maker to generate quantitative data on risk assessment from a series of subjective, qualitative assessments. It was also a major result to bring together complementary skills and expertise from different disciplines in a wide and clear collaborative research project.

The work presented in this thesis targets the analysis and implementation of multi-criteria performance prediction methods for System-on-Chips (SoC).

These new SoC architectures offer the opportunity to integrate complete heterogeneous systems into a single chip and can be used to design battery powered handhelds, security critical systems, consumer electronics devices, etc. However, this variety in terms of application usually comes with a lot of different performance objectives like power consumption, yield, design cost, production cost, silicon area and many others. These performance requirements are often very difficult to meet together so that SoC design usually relies on making the right design choices and finding the best performance compromises.

In parallel with this architectural paradigm shift, new Very Deep Submicron (VDSM) silicon processes have more and more impact on the performances and deeply modify the way a VLSI system is designed even at the first stages of a design flow.

In such a context where many new technological and system related variables enter the game, early exploration of the impact of design choices becomes crucial to estimate the performance of the system to design and reduce its time-to-market.

In this context, this thesis presents:

- A study of state-of-the-art tools and methods used to estimate the performances of VLSI systems and an original classification based on several features and concepts that they use. Based on this comparison, we highlight their weaknesses and lacks to identify new opportunities in performance prediction.

- The definition of new concepts to enable the automatic exploration of large design spaces based on flexible performance criteria and degrees of freedom representing design choices.

- The implementation of a couple of two new tools of our own:

- Nessie, a tool enabling hierarchical representation of an application along with its platform and automatically performs the mapping and the estimation of their performance.

-Yeti, a C++ library enabling the defintion and value estimation of closed-formed expressions and table-based relations. It provides the user with input and model sensitivity analysis capability, simulation scripting, run-time building and automatic plotting of the results. Additionally, Yeti can work in standalone mode to provide the user with an independent framework for model estimation and analysis.

To demonstrate the use and interest of these tools, we provide in this thesis several case studies whose results are discussed and compared with the literature.

Using Yeti, we successfully reproduced the results of a model estimating multi-core computation power and extended them thanks to the representation flexibility of our tool.

We also built several models from the ground up to help the dimensioning of interconnect links and clock frequency optimization.

Thanks to Nessie, we were able to reproduce the NoC power consumption results of an H.264/AVC decoding application running on a multicore platform. These results were then extended to the case of a 3D die stacked architecture and the performance benefits are then discussed.

We end up by highlighting the advantages of our technique and discuss future opportunities for performance prediction tools to explore.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

Multi-disciplinary ship synthesis models and multi-objective optimization techniques are increasingly being used in ship design. Multi-disciplinary models allow designers to break away from the traditional design spiral approach and focus on searching the design space for the best overall design instead of the best discipline-specific design. Complex design problems such as these often have high levels of uncertainty associated with them, and since most optimization algorithms tend to push solutions to constraint boundaries, the calculated "best" solution might be infeasible if there are minor uncertainties related to the model or problem definition. Consequently, there is a need to address uncertainty in optimization problems to produce effective and reliable results. This thesis focuses on adding a third objective, uncertainty, to the effectiveness and cost objectives already present in a multi-disciplinary ship synthesis model. Uncertainty is quantified using a "confidence of success" (CoS) calculation based on the mean value method. CoS is the probability that a design will satisfy all constraints and meet performance objectives. This work proves that the CoS concept can be applied to synthesis models to estimate uncertainty early in the design process. Multiple sources of uncertainty are realistically quantified and represented in the model in order to investigate their relative importance to the overall uncertainty. This work also presents methods to encourage a uniform distribution of points across the Pareto front. With a well defined front, designs can be selected and refined using a gradient based optimization algorithm to optimize a single objective while holding the others fixed.
Master of Science

Twintex®, a relatively new thermoplastic composite material system made of comingled polypropylene (PP) and glass fibers, has shown superior toughness in comparison with traditional glass-fiber epoxy composites. Along this improvement, this thesis aims at enhancing impact characterization of Twintex composites and developing a systematic approach for weave pattern selection and lay-up optimization of their laminates under impact. The research was conducted in experimental and numerical parts with a case study on potential application of Twintex in a highway guardrail. In the first part, a set of 180 drop-weight-impact and four-point-flexural experiments were performed for mechanical characterization of PP/glass laminates with different fiber architectures (balanced plain, balanced will, unbalanced plain, and unidirectional tape) before and after impact. Another set of the experiments was designed based on a Taguchi design of experiment (DOE) method and showed that this method has a good accuracy in predicting impact response of hybrid fiber reinforced plastic (FRP) composites such as Twintex. The X-ray microtomography and visual inspection techniques were also employed to investigate the interior and exterior damages induced to the specimens due to impact. These nondestructive evaluation techniques revealed that the impact damage mechanisms are highly dependent on the selected architecture of fibers. Also it is shown that, contrary to some previously published reports, impact resistance of FRP composites cannot be evaluated solely based on the extent of visible damages, and that inner damage along with associated damage modes must also be taken into account. Next, a case study was conducted to extract the criteria that may be used by engineers to assess impact-resistance of different Twintex FRP laminates for a potential guardrail application. Namely, a decision matrix with nine criteria was formed and three weighting techniques were developed under a multicriteria decision making environment to select the most appropriate fabric weave pattern for this specific application. The proposed multi-criteria approach is general and can assist designers to select optimum composite materials in other similar applications. The last part of this thesis deals with a simplified approach for numerical characterization (finite element analysis) of Twintex laminates under impact without a need for additional subroutine codes.

Integrated Project Delivery (IPD) combined with Target Value Design (TVD) is a better way to deliver value for the client than traditional guaranteed maximum price (GMP) methods. With traditional GMP delivery methods, the interests of the parties are often at odds. The goal of IPD is to align all party interests in order to achieve a win-win scenario. Due to the aligning nature of IPD and the fact that each party’s success is dependent on achieving the project objectives as a whole; a non-biased, transparent, decision-making process is necessary in order to deliver the project objectives within the constraints of the TVD. Thus delivering the expected value for the client and ensuring that all parties achieve project success. The need for this transparent decision-making process is compounded by the fact that a “target” based system rapidly declines to a less than optimal state if there is no unbiased decision-making process in place. If we treat the entire lifespan of a project as the complex system that it is, we can begin to take advantage of the hierarchical nature of complex systems. The goal of this paper is to show that by modeling the life span of a project through a multi-criteria decision making model, built on a hierarchical framework will allow you to find a non-inferior solution to your TVD. I’m proposing to use Hierarchical Holographic Modeling (HHM) as the framework for an Analytical Hierarchical Process (AHP) multi-criteria decision-making model complete with post-optimality analysis as the preferred project management method.

Power Generation Systems (PGSs) based on Hybrid Renewable Energy (HRE) are one of the promising solutions for future distributed generation systems. Among different configurations, Hybrid Photovoltaic - Wind turbine (PV-WT) grid connected PGSs are the most adopted for their good performance. However, due to the complexity of the system caused by wind power variability and solar radiation intermittency, the optimal balance between these two energy sources requires particular attention to achieve a good engineering solution. This thesis deals with the optimal sharing and sizing of PV-WT by adopting different Multi Criteria Decision Making (MCDM) optimization approaches. Different approaches have been developed using Multi attribute decision Making (MADM) and Multi Objective Decision Making (MODM). Moreover, sensitivity and uncertainty of MCDM algorithms have been analyzed, by considering different weighting criteria techniques with different fluctuation scenarios of wind speed and solar radiation profiles, and by considering stochastic analysis to solar radiation, wind speed, and load demand input data , thus highlighting advantages and drawbacks of the proposed optimal sizing approaches. The developed approaches could be assumed as a powerful roadmap for decision makers, analysts, and policy makers.

Eco-urban electric cars (EC) are superior to conventional cars in terms of the operation cost and carbon footprint. However, the performance of EC in terms of their maximum speed and power, initial and maintenance cost and reliability in the available power is lower than conventional cars. The reliability in available energy can be viewed as the main concerns when comparing EC to conventional cars. Reliability in available energy is highly dependent upon the efficiency of the power system as well as the type and size of batteries. Type and size of batteries have a significant effect on the maintenance cost as well as the initial cost. This thesis is focused on two aspects of the research in electric cars, namely, (i) selection and size optimisation of components, and (ii) improving the reliability of the available energy. Traditionally, a robust design approach is adopted in design of the power system of cars. This is mainly aimed at providing the user with the luxury of using the car wherever there is a suitable road and whenever they want to use the car. This flexibility, however, comes with the price of heavier and more expensive power systems. By incorporating data on the dominant usage of an EC and adopting a deterministic design and optimisation method more cost-effective power systems, more compatible with the usage can be obtained. In this study, a power system simulation tool is developed. Using the simulation tool, the performance of the power system components can be analysed for different usage scenarios. Case studies are conducted. Each case is based on a dominant usage defined for a two-person EC driven in Kayseri city in Turkey. For each case, the best power system configuration is obtained. Another original contribution of this thesis is in the context of the reliability of the available energy, by providing a decision support system - a route planning advisor - that helps the user to select the most suitable route in terms of a variety of criteria both conventional, such as travelling time and travelling distance, as well as EC-related such as, available power, vicinity to a charging station. The optimiser of the developed multi criteria route planning advisor (MCRPA) tool is based on a robust hybrid Dijkstra - A* - NSGA-II algorithm. MCRPA incorporates information on EC characteristics (such as power system, aerodynamic shape, weight), city characteristics (current traffic flows, road types, speed limits, altitude, whether conditions), and city charging stations characteristics (capacity, charging level, crowding density). Carrying out case studies, the efficiency and performance of the MCRPA is evaluated.

[EN] Bridges, as an important component of infrastructure, are expected to meet all the requirements for a modern society. Traditionally, the primary aim in bridge design has been to achieve the lowest cost while guaranteeing the structural efficiency. However, concerns regarding building a more sustainable future have change the priorities of society. Ecological and durable structures are increasingly demanded. Under these premises, heuristic optimization methods provide an effective alternative to structural designs based on experience. The emergence of new materials, structural designs and sustainable criteria motivate the need to create a methodology for the automatic and accurate design of a real post-tensioned concrete bridge that considers all these aspects. For the first time, this thesis studies the efficient design of post-tensioned concrete box-girder road bridges from a sustainable point of view. This research integrates environmental, safety and durability criteria into the optimum design of the bridge. The methodology proposed provides multiple trade-off solutions that hardly increase the cost and achieve improved safety and durability. Likewise, this approach quantifies the sustainable criteria in economic terms, and evaluates the effect of these criteria on the best values of the variables. In this context, a multi-objective optimization is formulated to provide multiple trade-off and high-performing solutions that balance economic, ecologic and societal goals. An optimization design program selects the best geometry, concrete type, reinforcement and post-tensioning steel that meet the objectives selected. A three-span continuous box-girder road bridge located in a coastal region is selected for a case study. This approach provides vital knowledge about this type of bridge in the sustainable context. The life-cycle perspective has been included through a lifetime performance evaluation that models the bridge deterioration process due to chloride-induced corrosion. The economic, environmental and societal impacts of maintenance actions required to extend the service life are examined. Therefore, the proposed goals for an efficient design have been switch from initial stage to life-cycle consideration. Faced with the large computational time of multi-objective optimization and finite-element analysis, artificial neural networks (ANNs) are integrated in the proposed methodology. ANNs are trained to predict the structural response based on the design variables, without the need to analyze the bridge response. The multi-objective optimization problem results in a set of trade-off solutions characterized by the presence of conflicting objectives. The final selection of preferred solutions is simplified by a decision-making technique. A rational technique converts a verbal pairwise comparison between criteria with a degree of uncertainty into numerical values that guarantee the consistency of judgments. This thesis gives a guide for the sustainable design of concrete structures. The use of the proposed approach leads to designs with lower life-cycle cost and emissions compared to general design approaches. Both bridge safety and durability can be improved with a little cost increment by choosing the correct design variables. In addition, this methodology is applicable to any type of structure and material.
[ES] Los puentes, como parte importante de una infraestructura, se espera que reúnan todos los requisitos de una sociedad moderna. Tradicionalmente, el objetivo principal en el diseño de puentes ha sido lograr el menor coste mientras se garantiza la eficiencia estructural. Sin embargo, la preocupación por construir un futuro más sostenible ha provocado un cambio en las prioridades de la sociedad. Estructuras más ecológicas y duraderas son cada vez más demandadas. Bajo estas premisas, los métodos de optimización heurística proporcionan una alternativa eficaz a los diseños estructurales basados en la experiencia. La aparición de nuevos materiales, diseños estructurales y criterios sostenibles motivan la necesidad de crear una metodología para el diseño automático y preciso de un puente real de hormigón postesado que considere todos estos aspectos. Por primera vez, esta tesis estudia el diseño eficiente de puentes de hormigón postesado con sección en cajón desde un punto de vista sostenible. Esta investigación integra criterios ambientales, de seguridad estructural y durabilidad en el diseño óptimo del puente. La metodología propuesta proporciona múltiples soluciones que apenas encarecen el coste y mejoran la seguridad y durabilidad. Al mismo tiempo, se cuantifica el enfoque sostenible en términos económicos, y se evalúa el efecto que tienen dichos criterios en el valor óptimo de las variables. En este contexto, se formula una optimización multiobjetivo que proporciona soluciones eficientes y de compromiso entre los criterios económicos, ecológicos y sociales. Un programa de optimización del diseño selecciona la mejor combinación de geometría, tipo de hormigón, armadura y postesado que cumpla con los objetivos seleccionados. Se ha escogido como caso de estudio un puente continuo en cajón de tres vanos situado en la costa. Este método proporciona un mayor conocimiento sobre esta tipología de puentes desde un punto de vista sostenible. Se ha estudiado el ciclo de vida a través de la evaluación del deterioro estructural del puente debido al ataque por cloruros. Se examina el impacto económico, ambiental y social que produce el mantenimiento necesario para extender la vida útil del puente. Por lo tanto, los objetivos propuestos para un diseño eficiente han sido trasladados desde la etapa inicial hasta la consideración del ciclo de vida. Para solucionar el problema del elevado tiempo de cálculo debido a la optimización multiobjetivo y el análisis por elementos finitos, se han integrado redes neuronales en la metodología propuesta. Las redes neuronales son entrenadas para predecir la respuesta estructural a partir de las variables de diseño, sin la necesidad de analizar el puente. El problema de optimización multiobjetivo se traduce en un conjunto de soluciones de compromiso que representan objetivos contrapuestos. La selección final de las soluciones preferidas se simplifica mediante una técnica de toma de decisiones. Una técnica estructurada convierte los juicios basados en comparaciones por pares de elementos con un grado de incertidumbre en valores numéricos que garantizan la consistencia de dichos juicios. Esta tesis proporciona una guía que extiende y mejora las recomendaciones sobre el diseño de estructuras de hormigón dentro del contexto de desarrollo sostenible. El uso de la metodología propuesta lleva a diseños con menor coste y emisiones del ciclo de vida, comparado con diseños que siguen metodologías generales. Los resultados demuestran que mediante una correcta elección del valor de las variables se puede mejorar la seguridad y durabilidad del puente con un pequeño incremento del coste. Además, esta metodología es aplicable a cualquier tipo de estructura y material.
[CAT] Els ponts, com a part important d'una infraestructura, s'espera que reunisquen tots els requisits d'una societat moderna. Tradicionalment, l'objectiu principal en el disseny de ponts ha sigut aconseguir el menor cost mentres es garantix l'eficiència estructural. No obstant això, la preocupació per construir un futur més sostenible ha provocat un canvi en les prioritats de la societat. Estructures més ecològiques i durables són cada vegada més demandades. Davall estes premisses, els mètodes d'optimització heurística proporcionen una alternativa eficaç als dissenys estructurals basats en l'experiència. L'aparició de nous materials, dissenys estructurals i criteris sostenibles motiven la necessitat de crear una metodologia per al disseny automàtic i precís d'un pont real de formigó posttesat que considere tots estos aspectos. Per primera vegada, esta tesi estudia el disseny eficient de ponts de formigó posttesat amb secció en calaix des d'un punt de vista sostenible. Esta investigació integra criteris ambientals, de seguretat estructural i durabilitat en el disseny òptim del pont. La metodologia proposada proporciona múltiples solucions que a penes encarixen el cost i milloren la seguretat i durabilitat. Al mateix temps, es quantifica l'enfocament sostenible en termes econòmics, i s'avalua l'efecte que tenen els dits criteris en el valor òptim de les variables. En este context, es formula una optimització multiobjetivo que proporciona solucions eficients i de compromís entre els criteris econòmics, ecològics i socials. Un programa d'optimització del disseny selecciona la millor geometria, tipus de formigó, armadura i posttesat que complisquen amb els objectius seleccionats. S'ha triat com a cas d'estudi un pont continu en calaix de tres vans situat en la costa. Este mètode proporciona un major coneixement sobre esta tipologia de ponts des d'un punt de vista sostenible. S'ha estudiat el cicle de vida a través de l'avaluació del deteriorament estructural del pont a causa de l'atac per clorurs. S'examina l'impacte econòmic, ambiental i social que produïx el manteniment necessari per a estendre la vida útil del pont. Per tant, els objectius proposats per a un disseny eficient han sigut traslladats des de l'etapa inicial fins a la consideració del cicle de vida. Per a solucionar el problema de l'elevat temps de càlcul degut a l'optimització multiobjetivo i l'anàlisi per elements finits, s'han integrat xarxes neuronals en la metodologia proposada. Les xarxes neuronals són entrenades per a predir la resposta estructural a partir de les variables de disseny, sense la necessitat d'analitzar el pont. El problema d'optimització multiobjetivo es traduïx en un conjunt de solucions de compromís que representen objectius contraposats. La selecció final de les solucions preferides se simplifica per mitjà d'una tècnica de presa de decisions. Una tècnica estructurada convertix els juís basats en comparacions per parells d'elements amb un grau d'incertesa en valors numèrics que garantixen la consistència dels dits juís. Esta tesi proporciona una guia que estén i millora les recomanacions sobre el disseny d'estructures de formigó dins del context de desenrotllament sostenible. L'ús de la metodologia proposada porta a dissenys amb menor cost i emissions del cicle de vida, comparat amb dissenys que seguixen metodologies generals. Els resultats demostren que per mitjà d'una correcta elecció del valor de les variables es pot millorar la seguretat i durabilitat del pont amb un xicotet increment del cost. A més, esta metodologia és aplicable a qualsevol tipus d'estructura i material.
García Segura, T. (2016). Efficient design of post-tensioned concrete box-girder road bridges based on sustainable multi-objective criteria [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/73147
TESIS

The realism of virtual surgery through a surgical simulator depends largely on the precision and reliability of the haptic device. The quality of perception depends on the design of the haptic device, which presents a complex design task due to the multi-criteria and conflicting character of the functional and performance requirements. In the model-based evaluation of the performance criteria of a haptic device, the required computational resources increase with the complexity of the device structure as well as with the increased level of detail that is created in the detail design phases. Due to uncertain requirements and a significant knowledge gap, the design task is fuzzy and more complex in the early design phases. The goal of this thesis is to propose a situated, i.e., flexible, scalable and efficient, methodology for multi-objective and multi-disciplinary design optimization of high-performing 6-DOF haptic devices. The main contributions of this thesis are: 1. A model-based and simulation-driven engineering design methodology and a flexible pilot framework are proposed for design optimization of high-performing haptic devices. The multi-disciplinary design optimization method was utilized to balance the conflicting criteria/requirements of a multi-domain design case and to solve the design optimization problems concurrently. 2. A multi-tool framework is proposed. The framework integrates metamodel-based design optimization with complementary engineering tools from different software vendors, which was shown to significantly reduce the total computationally effort. 3. The metamodeling methods and sampling sizes for specific performance indices found from case studies were shown to be applicable and usable for several kinds of 6-degrees-of-freedom haptic devices. 4. The multi-tool framework and the assisting methodology were further developed to enable computationally efficient and situated design multi-objective optimization of high-performing haptic devices. The design-of-experiment (DOE) and metamodeling techniques are integrated with the optimization process in the framework as an option to solve the design optimization case with a process that depends on the present system complexity.

QC 20171108

The work presented in this thesis aims at validating an original multicriteria performances estimation tool, NESSIE, dedicated to the prediction of performances to accelerate the design of electronic embedded systems.

This tool has been developed in a previous thesis to cope with the limitations of existing design tools and offers a new solution to face the growing complexity of the current applications and electronic platforms and the multiple constraints they are subjected to.

More precisely, the goal of the tool is to propose a flexible framework targeting embedded systems in a generic way and enable a fast exploration of the design space based on the estimation of user-defined criteria and a joint hierarchical representation of the application and the platform.

In this context, the purpose of the thesis is to put the original framework NESSIE to the test to analyze if it is indeed useful and able to solve current design problems. Hence, the dissertation presents :

- A study of the State-of-the-Art related to the existing design tools. I propose a classification of these tools and compare them based on typical criteria. This substantial survey completes the State-of-the-Art done in the previous work. This study shows that the NESSIE framework offers solutions to the limitations of these tools.

- The framework of our original mapping tool and its calculation engine. Through this presentation, I highlight the main ingredients of the tool and explain the implemented methodology.

- Two external case studies that have been chosen to validate NESSIE and that are the core of the thesis. These case studies propose two different design problems (a reconfigurable processor, ADRES, applied to a matrix multiplication kernel and a 3D stacking MPSoC problem applied to a video decoder) and show the ability of our tool to target different applications and platforms.

The validation is performed based on the comparison of a multi-criteria estimation of the performances for a significant amount of solutions, between NESSIE and the external design flow. In particular, I discuss the prediction capability of NESSIE and the accuracy of the estimation.

-The study is completed, for each case study, by a quantification of the modeling time and the design time in both flows, in order to analyze the gain achieved by our tool used upstream from the classical tool chain compared to the existing design flow alone.

The results showed that NESSIE is able to predict with a high degree of accuracy the solutions that are the best candidates for the design in the lower design flows. Moreover, in both case studies, modeled respectively at a low and higher abstraction level, I obtained a significant gain in the design time.

However, I also identified limitations that impact the modeling time and could prevent an efficient use of the tool for more complex problems.

To cope with these issues, I end up by proposing several improvements of the framework and give perspectives to further develop the tool.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

Pressure Swing Adsorption (PSA) is the most efficient option for middle scale separation processes. PSA is a cyclic process whose main steps are adsorption, at high pressure, and regeneration of the adsorbent, at low pressure. The design of PSA cycles is still mainly approached experimentally due to the computational challenges posed by the complexity of the simulation and by the need to detect the performance at cyclic steady state (CSS). Automated tools for the design of PSA processes are desirable to allow a better understanding of the the complex relationship between the performance and the design variables. Furthermore, the operation is characterised by trade-offs between conflicting criteria. A multi-objective flowsheet design framework for complex PSA cycles is presented. A suite of evolutionary procedures, for the generation of alternative PSA configurations has been developed, including simple evolution, simulated annealing as well as a population based procedure. Within this evolutionary procedure the evaluation of each cycle configuration generated requires the solution of a multi-objective optimisation problem which considers the conflicting objectives of recovery and purity. For this embedded optimisation problem a multi-objective genetic algorithm (MOGA), with a targeted fitness function, is used to generate the approximation to the Pareto front. The evaluation of each alternative design makes use of a number of techniques to reduce the computational burden. The case studies considered include the separation of air for N2 production, a fast cycle operation which requires a detailed diffusion model, and the separation of CO2 from flue gases, where complex cycles are needed to achieve a high purity product. The novel design framework is able to determine optimal configurations and operating conditions for PSA for these industrially relevant case studies. The results presented by the design framework can help an engineer to make informed design decisions.

The purpose of this thesis is to develop an integrated model which involves creative and analytical features for designing a cost effective logistics centre layout on operational level, with respect to time and space utilization. Engineering methods, creative skills, simulation and multi-criteria decision making methods were integreted in the  developed model. The model has been implemented and validated in Oskarshamn Intralog, which is a sister company of Scania. After applying the model in the case company, three different layout concepts were generated based on engineering and simulation techniques. These concepts were evaluated from utilization of space, time and flexibility aspects. Furthermore, multi criteria decision making method was used to select the most cost effective layout concept among these concepts. Different aspects helped to see various effects of warehouse operations on layout design. Simulation was used as a powerful tool to test cycle time within designed concepts. Clearly it was concluded that a combination of two concepts led to reach the expected results as an optimum point among space, time utilization and flexibility which fullfilled the answer to both academical and practical problem

 

Syftet med den här uppsatsen är att utveckla en integrerad modell som inbegriper kreativa och analytiska egenskaper. Modellen ska användas till att designa en kostnadseffektiv planering av anläggningen för ett logistikcentrum på en operationell nivå, med avseende på tid- och lagerplatsutnyttjande. Tekniska metoder, kreativitet, simulering, samt “multi-criteria decision making” är integrerade i modellen. Validering och implementering av modellen skedde på Oskarshamn Intralog, ett systerföretag till Scania. Efter tillämpning av modellen på fallföretaget, genererades tre olika koncept för planering av anläggningen. Koncepten utvärderades utifrån utnyttjande av plats, tid, samt flexibilitet. Dessutom har metoden “multi-criteria decision making” använts för att selektera det mest kostnadseffektiva av de tre koncepten. Olika aspekter på tid- och lagerplatsutnyttjande, samt flexibilitet bidrog till att se olika effekter på lagerhantering. Simuleringar genomfördes för att testa cykeltiden i de utvecklade koncepten. Slutsatsen är att en kombination av två koncept ledde till det förväntade resultatet; en optimal punkt för tid- och lagerplatsutnyttjande, samt flexibilitet, vilket uppfyller svar till de akademiska och praktiska problemen

In today’s world there are 2.6 billion people that lack basic sanitation (37% of world inhabitants). In August of 2012, Cranfield University was awarded by the Bill & Melinda Gates Foundation with $810,000 to produce a prototype of the Cranfield’s innovative Nano-membrane Toilet (NMT). Finally, the prototype is going to be exhibited at the “Reinvent the Toilet Fair” during 21st and 22nd of March 2014 in the Taj Palace Hotel, New Delhi (India). Cranfield’s NMT demands electricity for its daily performance. Nevertheless, it is targeted to off-grid communities. Consequently, a human-powered generator (HPG) was selected as a backup solution. The current MSc by Research aimed to design and test of a prototype of the aforesaid HPG. Moreover, to promote its usage, a portable power supply unit is designed to store energy and power small-loads like charging mobile phones and electric lighting. To select the most suitable design for our case study, a methodology using the Technique for Order of Preference by Similarity to the Ideal Solution has been developed. As a result the plugged-in bike HPG alternative was selected. Next, prototypes of this generator and the portable power supply unit were developed, tested and shipped for display. While testing of the plugged-in generator and portable power supply unit, 26 Watt-hours (Wh) were harvested over 15 minutes, with its corresponding average charging power of 105 Watts. Nevertheless, the present study concludes 96 Wh as a more accurate energy level to be harvested during one hour of pedalling. Considering 96 Wh of energy, a round-trip battery efficiency of 70% (lead-acid), and a NMT’s demand of 283 Wh; a 10 people household needs to pedal the HPG over 4 hours and 20 minutes. Nevertheless, if considering an 85% inverter efficiency, 57.12 Wh are available to fully charge one mobile phone (5.6 Wh) and provide 4.5 hours of room and desk lighting (11 Watts bulb).

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Choi, Seung-Kyum; Committee Member: Allen, Janet K.; Committee Member: Paredis, Chris. Part of the SMARTech Electronic Thesis and Dissertation Collection.

In traditional planning process, energy analysts work on finalized architectural designs and have limited capability to amend inefficient energy features such as high aspect ratio. Energy efficiency being a major part of sustainable design, the need for performance-oriented design tools has become imminent. There is a wide range of energy simulation tools across the world. Crawley et al. (2005) proposes a plain comparison of the most common ones based on vendor-supplied information. The present report aims to identify simulation tools that can help architects making energy-efficient design decisions in early stage of building process and the most suitable programs will be tested on a standard case in Stockholm area with respect to their architecture, functionalities, usability and limitations.

The literature suggests that organisations which have adopted Six Sigma have realised that upon achieving a Five Sigma level the only way to surpass this is to redesign the process(es) by means of Design for Six Sigma (DFSS). For others, the selection of Six Sigma over the DFSS approach is not a definitive question and just a guideline can be provided. A major objective of this research was to extend the selection of the requisite Six Sigma approach beyond the sigma level case and the general guidelines, towards a multi-criteria decision using established techniques. Thus, two research questions were defined: what influences the selection of the requisite Six Sigma approach, i. e. Six Sigma versus DFSS? and, how effective is the use of Multi-Criteria Decision Analysis (MCDA) techniques in the selection of the requisite Six Sigma approach? An action research methodology was applied where one Six Sigma project, one DFSS project and one Six Sigma project applied in a non-manufacturing process were implemented and analysed in collaboration with 3M Corporation, General Domestic Appliances (GDA) and Land Rover. From the action research spiral it was concluded that the sigma level has a positive association with the selection of redesign or improvement efforts within Six Sigma, however the Five Sigma level cannot necessarily dictate the use of one approach over the other. Besides the sigma level the selection of the requisite Six Sigma approach is influenced by multiple and conflicting criteria. In addition, the selection can occur at different stages of the methodologies. To assist decision-makers in organising, synthesising and optimising the criteria affecting this decision, the Stochastic Analytic Hierarchy Process (SAHP) was developed and applied to the problem at hand. The SAHP was developed on the basis of Analytic Hierarchy Process (AHP) and disparate sources of relevant literature. SAHP provides a mechanism for achieving a more effective selection of the requisite Six Sigma approach in the form of considering multiple and conflicting criteria using quantitative and qualitative information under uncertainty. In contrast to the traditional AHP, SAHP incorporates probabilistic distributions to incorporate uncertainty that people have in converging into a Likert scale their judgments of preferences. The vector of priorities is calculated using Monte Carlo simulation and the final rankings analysed for rank reversal using statistical analysis with managerial aspects introduced systematically. The concept and implementation of SAHP is new to the selection of the requisite Six Sigma approach and as such it constitutes the main innovation to result from this research. It extends the selection of the requisite Six Sigma approach towards a systematic multi-criteria decision considering multiple and conflicting criteria under uncertainty. Furthermore, while SAHP was originally conceived as a specific aid to the improve or redesign issue within Six Sigma, this research indicates that it is potentially much more widely applicable. This research also provides evidence of how different factors affecting the selection of requisite Six Sigma approach were considered. Further areas of research include the use of a positivist method in order to increase the sample size of the research and identify different factors affecting the decision improve or redesign. The development of SAHP software and extending the SAHP practice to different multi-criteria decisions are also potential areas for further research.

The awareness on raw material scarcity and environmental issues has globally stimulated interest into the re-design of products, processes or services, maximizing prevention, reuse and recycling rates. Within this context, plastic represents a key material. In particular, plastic packaging is a priority issue, accounting for the 40% of the European converters demand and about 60% of post-consumer plastic waste. Nowadays, less than 30% of collected plastic waste is recycled, while landfilling and incineration rates of plastic waste remain high, approximately 27% and 41% respectively. The EU Commission is currently hardly working on this issue: the recent EU Plastic Strategy sets very ambitious goals for plastics sustainability. This background topic is the key point of the master thesis. The study starts with mapping the best practices on plastic recycling and prevention, following the entire plastic packaging value chain. Adopting a multi-criteria perspective, legislative, economic and technical, technological and environmental framework of good practices and criticalities is outlined, in order to assess the current state of innovation on circular economy for plastics. The overview on levers and barriers for plastic circularity allows to design a new set of circular economy indicators suitable to be applied on plastic packaging sector. As good practices, eco-design principles are adopted in order to delineate an assessment tool able to identify plastic packaging sustainability and circularity. Moreover, the compliance with the regulatory framework and possible economic advantages are verified. Therefore, the final goal of the study is to identify practical suggestions which can be converted into a set of indicators for measuring plastic packaging circularity, delineating criticalities and possible improvements for boosting the sustainable transition of the entire sector.

Principais investimentos no Design para Adaptabilidade do mobiliário contemporâneo têm envolvido características como multiplicidade de funções, capacidade de atualização, personalização e compartilhamento de componentes. Tais características vêm permitindo a adaptação do mobiliário às rápidas transformações comportamentais e tecnológicas surgidas nos espaços domésticos e de trabalho. As conexões entre componentes do projeto do mobiliário são fortemente responsáveis por sua adaptabilidade tanto na fase criativa como na fase de uso. Esta dissertação parte da hipótese de que o processo de escolha das conexões, hoje pouco estruturado, pode ser feito a partir de métodos que não só estimulem a fase criativa do projeto como também contribuam para ampliar o desempenho adaptativo do mobiliário. Para avaliar diferentes tipos de conexão foram elaborados critérios para identificar o potencial compositivo de arranjos entre componentes (flexibilidade) relacionando-o à gama de funções emergentes (versatilidade). O resultado desta identificação foi testado por especialistas e validado através de ferramenta multicritério (Método Analítico Hierárquico). O teste com especialistas demonstrou que metodologias adotadas para seleção de conexões, quando estruturadas a partir de objetivos de projeto, podem aumentar o potencial de adaptabilidade e, ao mesmo tempo converterem-se em valioso apoio ao Design do mobiliário contemporâneo.
Manufacturers of contemporary furniture have made significant investments in the Design for Adaptability, particularly in the development of characteristics such as the multiplicity of functions, updating, customization and the share of components. These investments increased the potential of contemporary furniture to adapt to the observed transformations of behavior in domestic and working spaces. The adaptation has been made possible thanks to role played by the development of different types of connections between furniture components. This dissertation departs from the Idea that today’s processes involving the choice of connections are poorly structured and can be improved with a support decision’s methodology. This upgrade may well lead to the increment of creative attitudes during design process and to the development of higher levels of response to adaptability requests in furniture design. In order to evaluate and to select amidst the different types of connections a set of criteria were designed as to identify number of potential arrays of components (flexibility) and correlating this potential to the possible number of emergent functions (versatility). The result of this identification has been tested by specialists and then validated by a multicriteria method (AHP). The test with specialists confirmed that structured methodologies can be successfully used to improve the Design for Adaptability and, at the same time, constitute a valuable tool for the contemporary furniture’s Design.

Infrastructures are the most fundamental facilities and systems serving the society. Due to the existence of infrastructures in economic, social, and environmental contexts, all lifecycle phases of such fundamental facilities should maximize utility for the designers, occupants, and the society. With respect to the nature of the decision problem, two main types of uncertainties may exist: 1) the aleatory uncertainty associated with the nature of the built environment (i.e., the economic, social, and environmental impacts of infrastructures must be described as probabilistic); and 2) the epistemic uncertainty associated with the lack of knowledge of decision maker utilities. Although a number of decision analysis models exist that consider the uncertainty associated with the nature of the built environment, they do not provide a systematic framework for including aleatory and epistemic uncertainties, and decision maker utilities in the decision analysis process. In order to address the identified knowledge gap, a three-phase modular decision analysis methodology is proposed. Module one uses a formal preference assessment methodology (i.e., utility function/indifference curve) for assessing decision maker utility functions with respect to a range of alternative design configurations. Module two utilizes the First Order Reliability Method (FORM) in a systems reliability approach for assessing the reliability of alternative infrastructure design configurations with respect to the probabilistic decision criteria and decision maker defined utility functions (indifference curves), and provides a meaningful feedback loop for improving the reliability of the alternative design configurations. Module three provides a systematic framework to incorporate both aleatory and epistemic uncertainties in the decision analysis methodology (i.e., uncertain utility functions and group decision making). The multi-criteria, probabilistic decision analysis framework is tested on a nine-story office building in a seismic zone with the probabilistic decision criteria of: building damage and business interruption costs, casualty costs, and CO2 emission costs. Twelve alternative design configurations and four decision maker utility functions under aleatory and epistemic uncertainties are utilized. The results of the decision analysis methodology revealed that the high-performing design configurations with an initial cost of up to $3.2M (in a cost range between $1.7M and $3.2M), a building damage and business interruption cost as low as $303K (in a cost range between $303K and $6.2M), a casualty cost as low as $43K (in a cost range between $43K and $1.2M), and a CO2 emission as low as $146K (in a cost range between $133K to $150K) can be identified by having a higher probability (i.e., up to 80%) of meeting the decision makers' preferences. The modular, holistic, decision analysis framework allows decision makers to make more informed performance-based design decisions—and allows designers to better incorporate the preferences of the decision makers—during the early design process.
PHD

The research objective of this dissertation is to create and demonstrate methods for parameterizing the Pareto frontiers of continuous multi-attribute design problems using barycentric coordinates, and in doing so, to enable intuitive exploration of optimal trade spaces. This work is enabled by two observations about Pareto frontiers that have not been previously addressed in the engineering design literature. First, the observation that the mapping between non-dominated designs and Pareto efficient response vectors is a bijection almost everywhere suggests that points on the Pareto frontier can be inverted to find their corresponding design variable vectors. Second, the observation that certain common classes of Pareto frontiers are topologically equivalent to simplices suggests that a barycentric coordinate system will be more useful for parameterizing the frontier than the Cartesian coordinate systems typically used to parameterize the design and objective spaces. By defining such a coordinate system, the design problem may be reformulated from y = f(x) to (y,x) = g(p) where x is a vector of design variables, y is a vector of attributes and p is a vector of barycentric coordinates. Exploration of the design problem using p as the independent variables has the following desirable properties: 1) Every vector p corresponds to a particular Pareto efficient design, and every Pareto efficient design corresponds to a particular vector p. 2) The number of p-coordinates is equal to the number of attributes regardless of the number of design variables. 3) Each attribute y_i has a corresponding coordinate p_i such that increasing the value of p_i corresponds to a motion along the Pareto frontier that improves y_i monotonically. The primary contribution of this work is the development of three methods for forming a barycentric coordinate system on the Pareto frontier, two of which are entirely original. The first method, named "non-domination level coordinates," constructs a coordinate system based on the (k-1)-attribute non-domination levels of a discretely sampled Pareto frontier. The second method is based on a modification to an existing "normal boundary intersection" multi-objective optimizer that adaptively redistributes its search basepoints in order to sample from the entire frontier uniformly. The weights associated with each basepoint can then serve as a coordinate system on the frontier. The third method, named "Pareto simplex self-organizing maps" uses a modified a self-organizing map training algorithm with a barycentric-grid node topology to iteratively conform a coordinate grid to the sampled Pareto frontier.

Les réseaux de chauffage urbain (DHN) sont un moyen efficace de fournir de l'énergie thermique aux consommateurs. L'état actuel de la technique montre que les DHN évoluent vers des réseaux thermiques intelligents dans des systèmes énergétiques intégrés alors que leur conception est basée sur les principes de durabilité. Sur cette base, cette thèse couvre deux domaines de recherche principaux : Fonctionnement et conception des systèmes de chauffage urbain. Dans la partie A de cette thèse, des méthodes avancées pour le fonctionnement de la DHN sont développées à l'aide d'analyses exergétiques et thermoéconomiques. Cela inclut la formulation de bilans de coûts exergétiques pour les modèles de réseau basés sur des graphiques. La partie intrinsèque est le déploiement d'une matrice algébrique, qui détermine les coûts exergétiques pour la modélisation dynamique du système. Une étude de cas d'un réseau réel prouve que la méthodologie proposée offre de nouvelles perspectives sur l'allocation individuelle des coûts, ce qui aide à évaluer la faisabilité de l'intégration par des tiers et l'intégration des sources d'énergie distribuées. Dans la partie B de cette thèse, un nouvel indicateur appelé «load deviation index (LDI)» est proposé pour lier les mesures de la demande (DSM) à la conception durable des systèmes DHN. Pour cela, un cadre de conception axé sur les affaires est proposé, qui prend en compte les influences critiques dans le DHN tout en évitant un trop grand détail. Le comportement du DSM est analysé du point de vue du système et son impact sur la conception du DHN est étudié dans deux études de cas. Alors que l'un se concentre sur les benchmarks pour différentes options de conception en utilisant une métrique de durabilité multicritères, un autre donne des indications détaillées sur l'utilité du cadre proposé pour la conception en évaluant l'impact de DSM sur les améliorations de conception possibles
District heating networks (DHN) arean efficient way of providing thermal energy to consumers. Current state of the art shows that DHNs are developing towards smart thermal networks in integrated energy systems while their design is based upon the principles of sustainability. Based on that, this thesis covers two main research areas: Operation and design of district heating systems. In part A of this thesis, advanced methods for DHN operation are developed with the help of exergetic and thermoeconomic analysis. This includes the formulation of exergetic cost balances for graph-based network models. Intrinsic part is the deployment of an algebraic matrix, which determines the exergetic costs for dynamic system modeling. A case study of areal-existing network provides evidence that the proposed methodology offers new insights into individual allocation of costs which helps to assess the feasibility of third-party integration and the integration of distributed energy sources. In part B of this thesis, a new indicator called “load deviation index (LDI)” is proposed to link demand side measures (DSM) with the sustainable design of DHN systems. For that, abusiness-focused design frameworks proposed which takes the critical influences of DHN into account while avoiding a too high detail. DSM behavior is analyzed from a system perspective and its impact on DHN design is studied in two case studies. While one focuses on benchmarks for different design options using a multi-criteria sustainability metric, another gives detailed insights into the usefulness of the proposed framework for design purposes through assessing the impact of DSM on possible design improvements using a multi-objective optimization approach

Europe experienced the destruction of numerous infrastructures during World War II, followed by a reflation and a strong economic growth during the next two decades allowing a more perennial and durable situation. A classical bridge lasting in general around 80 years, one should observe that these constructions built after the war will have to be either replaced either seriously strengthened in a few years. Besides, since the needs also vary over time, transportation infrastructures built during those years might not be adapted to the actual needs anymore – some bridges might thus have to be widened. A case study has been chosen in order to simulate under which conditions the widening of such a bridge can be performed. This road bridge, located in Vierzon in France, is rather simple since it is made of simply supported prestressed concrete beams and of reinforced concrete piers. It has been chosen in particular for its reduced size – three spans of 30 m each and two road lanes – that corresponded well to this project. Based on some data provided when the bridge was initially built and on a visual inspection, this project suggests six technical solutions to double the actual amount of lanes. An evaluation of the performance of the solutions according to three criteria – durations of works, cost of the works, and environmental impact – is made in order to give recommendations regarding the optimal solution. The results show that in spite of being installed quickly, adding steel beams is more expensive and has a greater impact on the environment than adding prestressed concrete beams. Regarding the modification of piers, the solution suggesting widening the existing piers is preferable than adding new extra piers according to all the criteria. Consequently, among all the solutions analysed, the optimal one is also the simplest one. Finally, the limits of the study and some suggestions for improvements are indicated.

Thesis (M.S. in Information Technology Management) Naval Postgraduate School, Sept. 1997.
Thesis advisors, Tung X. Bui, Geoffrey Xie. Includes bibliographical references (p. 91-93). Also available online.

The objective of the study is to propose a new learning medium, which takes advantage of the latest developments in computer based training (CBT) and the World Wide Web as an innovative mode for delivering education. The key research focus of this thesis is the design of the framework to best combine hypertext technology, computer based training functionality's and interactive multimedia to enhance learning effectiveness. This research also focuses on the interactive multimedia to enhance learning effectiveness. Additionally, this research incorporates the migration and enhancement of a multiple criteria decision support textbook from print media to electronic media. Lessons learned from this development effort will be used to derive a general framework for developing integrated web based CBT tools. A multimedia training module prototype developed during this research can be viewed at HTTP://WWW.CIMNET.NPS.NAVY.COM/COOP

Supply chain and operations management has matured from a field that addressed only operational and economic concerns to one that comprehensively considers the broader environmental and social issues that face industrial organizations of today. Adding the term “green” to supply chain activities seeks to incorporate environmentally conscious thinking in all processes in the supply chain. The aim of this work is to develop a Green Supply Chain (GrSC) framework based on a multi-objective optimization approach, with specific emphasis on agrofood supply chain design, planning and operations through the implementation of appropriate green supply chain management and logistics principles. The case study is the orange juice cluster. The research objective is the minimization of the environmental burden and the maximization of economic profitability of the selected product categories. This work focuses on the application of GrSCM to two fundamental strategic issues targeting agro food supply chains. The former is related to the Green Supplier Selection (GSS) problem devoted to the farming production systems and the way they are integrated into the global supply chain network. The latter focuses on the global Green Supply Chain Network Design (GSCND) as a whole. These two complementary and ultimately integrated strategic topics are framed in order to evaluate and exploit the unique characteristics of agro food supply chains in relation to eco-labeling. The methodology is based on the use of Life Cycle Assessment, Multi-objective Optimization via Genetic Algorithms and Multiple-criteria Decision Making tools (TOPSIS type). The approach is illustrated and validated through the development and analysis of an Orange Juice Supply Chain case study modelled as a three echelon GrSC composed of the supplier, manufacturing and market levels that in turn are decomposed into more detailed subcomponents. Methodologically, the work has shown the development of the modelling and optimization GrSCM framework is useful in the context of eco-labeled agro food supply chain and feasible in particular for the orange juice cluster. The proposed framework can help decision makers handle the complexity that characterizes agro food supply chain design decision and that is brought on by the multi-objective and multi-period nature of the problem as well as by the multiple stakeholders, thus preventing to make the decision in a segmented empirical manner. Experimentally, under the assumptions used in the case study, the work highlights that by focusing only on the “organic” eco-label to improve the agricultural aspect, low to no improvement on overall supply chain environmental performance is reached in relative terms. In contrast, the environmental criteria resulting from a full lifecycle approach is a better option for future public and private policies to reach more sustainable agro food supply chains.

Les systèmes photovoltaïques de pompage d'eau (PVWPS) sont une solution intéressante pour améliorer l’accès à l’eau dans les communautés rurales des pays en voie de développement. Cette thèse développe une méthodologie de conception optimale des PVWPS pour l’accès à l’eau domestique basée sur une approche interdisciplinaire. L’objectif est de déterminer les dimensionnements du PVWPS et ses positions géographiques dans le village qui maximisent l’impact positif du système sur le développement socio-économique et minimisent son coût sur cycle de vie. Cette méthodologie est appliquée au cas d’un village rural du Burkina Faso, où nous avons collecté des données techniques et sociaux-économiques depuis 2 ans. La première originalité principale de ce travail est la modélisation du lien entre la conception du PVWPS et son impact socio-économique, ce qui permet d’inclure l’impact socio-économique comme fonction objectif de l’optimisation. La seconde originalité principale est l’intégration de la position géographique du PVWPS dans le village comme variable d’optimisation, en plus du dimensionnement du système. Cette méthodologie pourrait également être appliquée à la mise en place d'autres types de systèmes, tels que les moulins communaux alimentés par énergie photovoltaïque dans les zones isolées ou les bornes de recharges publiques pour les véhicules électriques dans les villes
Photovoltaic water pumping systems (PVWPS) are an interesting solution to improve access to water in rural communities of developing countries. This thesis develops a methodology for the optimal design of PVWPS for domestic consumption based on an interdisciplinary approach. The objective is to determine the sizings of the PVWPS and its geographical positions in the village that maximize the positive impact of the system on socio-economic development and minimize its life-cycle cost. This methodology is applied to the case of a rural village in Burkina Faso, where we have been collecting technical and socio-economic data for 2 years. The first main originality of this work is the modelling of the link between the design of a PVWPS and its socio-economic impact, which allows to include the socio-economic impact to be included as an objective function of the optimisation. The second main originality is the inclusion of the geographical position of the PVWPS in the village as an optimisation variable, in addition to the sizing of the system. There is potential for applying the proposed methodology for the set-up of other types of systems such as community mills powered by photovoltaic energy in isolated areas and public charging points for electrical vehicles in cities

The thesis deals with the design and arrangement of a new paint line at company Automotive Ligting s.r.o in Jihlava. It deals with design of several possible options of arrangement of machines that are required for the processing of polycarbonate granules and their conversion into acrylic glass using two-component injection molding. The glass is then coated with the coating line which is part of the arrangement included in this project. Design of the individual sites and their organization is based on both the company's requirements and the principles of technological design. The best of the three options is analyzed in detail and evaluated from the economic point of view.

The increased demand for biofuels is expected to put additional strain on the available agricultural resources while at the same time causing environmental degradation. Hence, new energy policies need to be formulated and implemented in order to meet global energy needs while reducing the impact of biofuels farming and production. This research focuses on proving a decision support system which can aid the formulation of policies for the sustainable biofuel production. The system seeks to address policy formulation that requires reconciliation of the qualitative aspects of decision making (such as stakeholder’s viewpoints) with quantitative data, which often may be imprecise. To allow this, based on: Fuzzy logic and Multi Criteria Decision Making (MCDM) in the form of Analytical Hierarchy Process (AHP). Using these concepts, three software functionalities, “Options vs. Fuzzy Criteria Matrix”, “Analytical Hierarchy Process” and “Fuzzy AHP” were developed. These were added within the framework of pre-existing base software, Compendium (developed by the Open University, UK). A number of case study based models have been investigated using the software. These models made use of data from the Philippines and India in order to pinpoint suitable land and crop options for these countries. The models based on AHP and Fuzzy AHP were very successful in identifying suitable crop options for India by capturing both the stakeholder viewpoints and quantitative data. The software functionalities are very effective in scenario planning and selection of policies that would be beneficial in achieving a desired future scenario. The models further revealed that the newly developed software correctly identified many of the important issues in a consistent manner.

U radu je razvijen složeni model vrednovanja i rangiranja varijanti rešenja koridora infrastrukturnih linijskih objekata. Model karakteriše višeakterski i višekriterijumski pristup. Model je baziran na kriterijumima vrednovanja koji su razvrstani u pravilnu hijerarhiju i čija je relevantnost verifikovana naučnim metodama. Metoda vrednovanja odabrana je inteligentnim pristupom uz pomoć drveta odlučivanja. Model predviđa i analizu osetljivosti odabranog optimalnog rešenja na promenu težina pojedinih (ili svih) kriterijuma vrednovanja. Naučni doprinos istraživanja ogleda se u primeni AHP metode koja je u Srbiji po prvi put primenjena kao podrška odabiru optimalnog rešenja koridora infrastrukturnih objekata kao i prikazanoj integraciji sa drugim metodama (stakeholder analiza, anketa, deskriptivna statistika, faktorska analiza).
In this paper a complex model evaluation and ranking of alternative solutions of linear infrastructure corridor structure characterized multi-actor and multi-criteria approach, which is based on the evaluation criteria whose relevance was verified by scientific methods and are sorted in the correct hierarchy. Valuation method chosen is an intelligent approach using the tree decision. The model predicts, and a sensitivity analysis of the selected optimal solution to weight change some (or all) of evaluation criteria. The scientific contribution of the research is the application of AHP method that is in Serbia for the first time applied to support the selection of the optimal solutions corridor infrastructure as shown integration with other methods (stakeholder analysis, survey, descriptive statistics, factor analysis)

The first part of this thesis describes the current technologies of mechanical spin-ning. This is a ring, rotor and air-jet spinning. The product of spinning machines is yarn, the basic material for production textile. The next section describes in detail the current state of the node manipulator lifter tube on spinning machine TORNADO J20, by concern RIETER. It describes the structure, kinematics, duty cycle and requirements for the manipulator. The following optimization options which are described more options for solutions of individual functions of the manipulator, on the end is selected by multi-criteria analysis. The best solution that is elaborate in the next section. The author has created 3-D model optimized lifter tube. Positioning mechanism maintains the current kinematics, it is very similar. But gripper was designed as a passive, thus reduce the load positioning mechanism. Optimization was performed primarily to reduce overall production costs and to reduce weight manipulator. The conclusion is a comparison of current and new solutions. There are also eco-nomic recovery to.