Concerns about energy supply and climate change have been driving companies towards more sustainable manufacturing while they are looking on the economic side as well. One practicable task to achieve sustainability in manufacturing is choosing more sustainable technologies among available technologies. Combination of two functions of ‘Technology Selection’ and ‘Capacity Planning’ is not usually addressed in the research literature. The importance of integrated decisions on technology selection and capacity planning at such strategic level is therefore essentially important. This is supported by justifications in some selected manufacturing areas particularly concerning economies of the scale and accumulated knowledge. Furthermore, manufacturing firms are working in a global competitive environment that is changing in a continuous way. Strategic design of systems under such circumstances requires a carefully modelled approach to deal with the complexity of uncertainties. The overall project aims are to develop an integrated methodological approach to solving the combined ‘technology selection’ and ‘capacity planning’ problems in manufacturing sector. The approach will also incorporate the multi-perspective concept of sustainability, while taking uncertainties into account. A framework consisting of four modules is proposed. Problem structuring module adopts an Ontology method to map the technology mix combinations and to capture input data. ‘Optimisation for Sustainable Manufacturing’ module addresses the optimisation of technology selection and capacity planning decisions in an integrated way using Goal, Mixed Integer Programming method. The model developed takes the multi-criteria aspect of sustainability development into account. Three criteria, namely a) Environmental (e.g. Energy consumption and Emissions), b) Economics, and c) Technical (e.g. Quality) are involved. ‘Normalisation algorithm by comparison with the best value’ method is adopted in this research in order to facilitate a systematic comparison among various criteria. The economic evaluation is based on ‘Life-Cycle Analysis’ approach. The ‘Present Value (PV)’ method is adopted to address ‘Time Value of Money’, while taking both ‘Inflation’ and ‘Market Return’ into account in order to make the proposed model more realistic. A mathematical model to represent the total PV of each technology investment, including both capital and running costs, is developed. ‘Sensitivity Analysis’ module addresses the uncertainty element of the problem. A controlled set of re-optimisation runs, which is guided by a tool coded in Visual Basic for Applications (VBA), is developed to perform intensive sensitivity analyses. It is aimed to deal with the uncertainty element of the problem. Within ‘Solution Structuring’ module, two knowledge structuring schemes, namely Decision Tree and Interactive Slider Diagram, are proposed to deal with the large size of solution sets generated by the “Sensitivity Analysis” module. An innovative, hybrid, Supervised and Unsupervised Machine Learning algorithm is developed to generate a decision tree that aims to structure the solution set. The unsupervised learning stage is implemented using DBSCAN algorithm, while the supervised learning element adopts C4.5 algorithm. The methodological approach is tested and validated using an exemplar case study on coating processes in an automotive company. The case is characterised by three operations, twelve possible technology mix states, both capital budget and environmental limits, and 243 different sensitivity analysis experiments. The painting systems are evaluated and compared based on their quality, technology life-cycle costs, and their potential VOC (Volatile Organic Compounds) emissions into the air.

Les méthodes actuelles d’optimisation de formes permettent des gains importants vis-à-vis des fonctions à optimiser. Elles sont largement utilisées par les industriels, notamment dans l’automobile comme chez Renault. Parmi ces approches, l’optimisation de formes paramétriques permet d’obtenir rapidement une géométrie optimale sous réserve que l’espace de conception soit assez restreint pour pouvoir être parcouru en un temps de simulation raisonnable. Ce manuscrit présente deux méthodes d’optimisation de formes paramétriques en grande dimension pour des applications nécessitant des coûts de calculs importants, par exemple en mécanique des fluides. Une manière originale de reconstruire un modèle CAO paramétré à partir d’une surface morte est présentée au préalable. Nous proposons une approche pour identifier les zones interdites de l’espace de conception ainsi que leurs gestions dans une boucle d’optimisation par plans d’expériences. La première méthode s’appuie sur des techniques statistiques pour lever le verrou du nombre de degrés de liberté et utilise une optimisation à deux niveaux de fidélité pour minimiser les temps de calcul. Cette méthode en rupture avec le processus industriel habituel a été appliquée pour optimiser le coefficient de trainée aérodynamique d’un véhicule. La seconde méthode se base sur l’exploitation des gradients fournis par les solveurs adjoints, c’est-à-dire sur les sensibilités du critère (comme l’uniformité d’un écoulement par exemple) par rapport aux degrés de liberté de l’optimisation. Cette méthode innovante et en rupture avec les approches classiques permet de lever très naturellement le verrou du nombre de paramètres. Cependant, les gradients fournis par les logiciels ne sont pas donnés par rapport aux paramètres CAO mais par rapport aux nœuds du maillage. Nous proposons donc une façon d’étendre ces gradients jusqu’aux paramètres CAO. Des exemples académiques ont permis de montrer la pertinence et la validité de notre approche. / Current design loops for shape optimizations allow significant improvements in relation to the functions that need to be optimized. They are widely used in industry, particularly in the car industry like Renault. Among these approaches, parametric shape optimization allows rapid enhancement of the shape, on the condition that the design space is confined enough in order to be explored within a reasonable computational time. This Thesis introduces two CAD-based large-scale shape optimization methods for products requiring significant computational cost, for example in fluid mechanics. An original way to create a parameterized CAD model developed from a dead geometry is presented first. We propose an approach to identify the restricted areas of the design space and their managements in an optimization loop that uses a design of experiments. The first method is based on statistical techniques to circumvent the difficulties of large-scale optimizations and uses a two-level multi-fidelity modelling approach to minimize the computational time. This method, breaking away from the usual industrial process, was applied to optimize the aerodynamic drag coefficient of a car body. The second method is based on the gradients provided by adjoint solvers, that is to say on the sensitivity of the cost function (such as the uniformity deviation for example) with respect to the design points or displacement boundaries. This innovative method breaking away from classical approaches naturally gets over the number of degrees of freedom. However, the sensitivities provided by softwares are not computed with respect to CAD parameters but with respect to the coordinates of the vertices of the surface mesh. Thus, we propose a way to extend these gradients to CAD parameters. Academic test cases have proved the efficiency and accuracy of our method.

L’industrie aérospatiale doit faire face à de nouvelles exigences environnementales, tout particulièrement concernant la réduction des coûts de lancement. L’utilisation de matériaux sandwichs composites plus légers permet de répondre à ces besoins. Cependant, l’allégement des matériaux sandwichs favorise une transmission importante du bruit, d’où la nécessité de prendre en compte des critères vibroacoustiques dès la phase de préconception. Dans cette optique, le travail présenté dans ce mémoire a pour objectif de proposer une démarche d’optimisation vibroacoustique des panneaux sandwichs composites légers, sous contraintes de masse et rigidité. Une étude spécifique est consacrée à l’optimisation des variables géométriques de solides cellulaires à périodicité de type nid d’abeille. L’objectif principal est de minimiser la densité modale en s’appuyant sur des modèles homogénéisés fiables. Afin de calculer les propriétés mécaniques macroscopiques des panneaux sandwichs, une méthode numérique d’homogénéisation tridimensionnelle est développée. Cette méthode permet de calculer les propriétés mécaniques équivalentes en utilisant les déformations et contraintes moyennes sur le volume représentatif. Les résultats obtenus sont conformes à ceux calculés par des méthodes classiques basées sur des modèles analytiques. Dans le but d’identifier une fonction objectif riche en informations sur le comportement vibroacoustique de panneau sandwich, on choisit d’étudier la densité modale du panneau. Par la suite, la fréquence de transition, qui sépare la zone de comportement de flexion pure du panneau sandwich du comportement en cisaillement pur de l’âme, est utilisée pour définir la fonction objectif. Après une étude d’analyse de sensibilité sur les paramètres mécaniques et géométriques de la structure sandwich, une démarche globale d’optimisation mono-objectif est mise en oeuvre pour maximiser la fréquence de transition de la structure sandwich composite constituée d’une âme en nid d’abeille hexagonale. Enfin, cette démarche est étendue pour estimer les propriétés géométriques optimales de nouvelles âmes. / The aerospace industry has to adapt to new environmental requirements, especially concerning the reduction of the launch costs. The use of lighter composite sandwich materials can meet part of these requirements. However, their high stiffness-toweight ratio implies that they tend to increase noise transmission, which may be damageable to the payload. Vibroacoustic criterai should hence be taken into account from the early design stages. In this context, the work presented in this thesis aims to provide a vibroacoustic optimization approach of lightweight composite sandwich panels, under mass and stiffness constraints. A specific study is devoted to the optimization of geometric variables of periodic cellular solids such as honeycombs. The main objective is to minimize the modal density based on reliable homogenized models. In order to calculate the macroscopic mechanical properties of the sandwich panel, a numerical method of three-dimensional homogenization is developed. This method allows to calculate the equivalent mechanical properties by applying the average strains and stresses on a unit cell. The results obtained are consistent with those calculated by conventional methods based on analytical approaches. The modal density is chosen as an objective function for optimization, as it is closely related to the vibroacoustic behavior of the structure. The transition frequency, which separates the region of pure panel bending from the pure core shear zone, is further studied and considered as an alternative objective function. After a sensitivity analysis of the mechanical and geometric parameters of the sandwich structure, a mono-objective optimization approach is implemented to maximize the transition frequency of a composite sandwich structure with a hexagonal core. This approach is then extended to estimate the optimal geometric properties of new core shapes.

Le domaine général de la thèse est l’analyse de sensibilité de fonctions boîte noire. L’analyse de sensibilité étudie comment la variation d’une sortie peut être reliée à la variation des entrées. C’est un outil important dans la construction, l’analyse et l’optimisation des expériences numériques (computer experiments).Nous présentons tout d’abord l’indice d’interaction total, qui est utile pour le criblage d’interactions. Plusieurs méthodes d’estimation sont proposées. Leurs propriétés sont étudiées au plan théorique et par des simulations.Le chapitre suivant concerne l’analyse de sensibilité pour des modèles avec des entrées fonctionnelles et une sortie scalaire. Une approche séquentielle très économique est présentée, qui permet non seulement de retrouver la sensibilité de entrées fonctionnelles globalement, mais aussi d’identifier les régions d’intérêt dans leur domaine de définition.Un troisième concept est proposé, les support index functions, mesurant la sensibilité d’une entrée sur tout le support de sa loi de probabilité.Finalement les trois méthodes sont appliquées avec succès à l’analyse de sensibilité de modèles d’emboutissage. / The general field of the thesis is the sensitivity analysis of black-box functions. Sensitivity analysis studies how the variation of the output can be apportioned to the variation of input sources. It is an important tool in the construction, analysis, and optimization of computer experiments.The total interaction index is presented, which can be used for the screening of interactions. Several variance-based estimation methods are suggested. Their properties are analyzed theoretically as well as on simulations.A further chapter concerns the sensitivity analysis for models that can take functions as input variables and return a scalar value as output. A very economical sequential approach is presented, which not only discovers the sensitivity of those functional variables as a whole but identifies relevant regions in the functional domain.As a third concept, support index functions, functions of sensitivity indices over the input distribution support, are suggested.Finally, all three methods are successfully applied in the sensitivity analysis of sheet metal forming models.

When provided with spatial niches by growth in static nutrient medium, Pseudomonas fluorescens diversifies through adaptive radiation into several well-defined phenotype classes. One of these classes, named wrinkly spreader (WS) for its morphology on agar medium, forms a biofilm at the air-liquid interface through mutations in one of several loci including the genes wspF and awsX. These genes code for negative regulators of di-guanylate cyclases (DGCs). These DGCs catalyse synthesis of cyclic-di-GMP, a second messenger, overproduction of which effects physiological changes leading to overproduction of a cellulose polymer and the WS phenotype. Intriguingly, a diverse range of wspF mutations leads to diversity both in colony morphology and strain fitness.In this study, I investigate genetic and fitness diversity in wrinkly spreaders with the aim of identifying the causal factors that link genetic diversity and physiological factors with diversity in fitness. I approach the subject from several directions, examining the historical context of genetic diversity in wspF and awsX, distribution of control over output in the Wsp pathway and overall fitness effects of different causal factors. I investigate the genetic basis of wrinkly spreader evolution through generation of a large number of novel WS strains and exploration of the distribution of mutations in the wspF and awsX genes. In combination with this I calculate estimates of the past rates of mutation in these genes, derived from a phylogenetic investigation of a group of orthologues. I examine the response of the Wsp pathway to change in WspF function through a novel computational analysis that is capable of revealing valuable information on control in a biological system based purely on model structure. In addition I show how this analysis can be refined through specification of broad estimates of system parameters, thereby avoiding issues related to over-reliance on specific parameter values. Finally, I investigate the fitness implications of these factors, as well as a variety of others, through assays of fitness in a group of WS strains combined with machine learning analyses of predictive relationships between protein and mutation characteristics and experimentally measured strain fitness, and consider the implications of this analysis in the context of intermediate physiological effects.I find that mutations in the WspF protein that lead to the WS phenotype tend to be located in regions of historically strong conservation, the first time that any such pattern to WS mutations has been identified. Mutations in AwsX, on the other hand, do not fit such a pattern. Computational analysis of the Wsp pathway shows that, regardless of model parameters, pathway output is always more sensitive to changes in methylesterase activity by WspF than to changes in phosphorylation of WspF, which may explain the greater frequency of mutations fixed in vivo seen in the methylesterase domain. Despite these patterns, none of a wide range of mutation and sequence-based biochemical characteristics, including local rates of past evolution and size and position of mutations, exhibited any predictive power over WS fitness. Overall, the findings in this study point towards an essential role for complex pleiotropic effects in strongly modulating the fitness effect of different mutations in wspF.

L'analyse de sensibilité pour la simulation numérique des écoulements compressibles en aérodynamique externe par rapport à la discrétisation de maillage et aux incertitudes liées à des paramètres d'entrées du modèle a été traitée 1- par le moyen des méthodes adjointes pour le calcul de gradient et 2- par approximations stochastiques non-intrusives basées sur des grilles creuses. 1- Une méthode d'adaptation de maillages goal-oriented basée sur les dérivées totales des fonctions aérodynamiques d'intérêt par rapport aux nœuds du maillage a été introduite sous une forme améliorée. La méthode s'applique au cadre de volumes finis pour des écoulements RANS pour des maillages mono-bloc et multi-bloc structurés. Des applications 2D pour des écoulements transsoniques ainsi que subsonique détaché atour d'un profil pour l'estimation du coefficient de traînée sont présentées. L'apport de la méthode proposée est vérifié. 2- Les méthodes du polynôme de chaos généralisé sous forme pseudospectrale creuse et de la collocation stochastique construite sur des grilles creuses isotropes et anisotropes sont examinées. Les maillages anisotropes sont obtenus par le biais d'une méthode adaptive basée sur l'analyse de sensibilité globale. L'efficacité des ces approximations est testée avec des fonctions test et des écoulements aérodynamiques visqueux autour d'un profil en présence d'incertitudes géométriques et opérationnelles. L'intégration des méthodes et aboutissements 1- et 2- dans une approche couplée permettrait de contrôler de façon équilibrée l'erreur déterministe/stochastique goal-oriented. / Sensitivity analysis for the numerical simulation of external aerodynamics compressible flows with respect to the mesh discretization and to the model input parametric uncertainty has been addressed respectively 1- through adjoint-based gradient computation techniques and 2- through non-intrusive stochastic approximation methods based on sparse grids. 1- An enhanced goal-oriented mesh adaptation method based on aerodynamic functional total derivatives with respect to mesh coordinates in a RANS finite-volume mono-block and non-matching multi-block structured grid framework is introduced. Applications to 2D RANS flow about an airfoil in transonic and detached subsonic conditions for the drag coefficient estimation are presented. The asset of the proposed method is patent. 2- The generalized Polynomial Chaos in its sparse pseudospectral form and stochastic collocation methods based on both isotropic and dimension-adapted sparse grids obtained through an improved dimension-adaptivity method driven by global sensitivity analysis are considered. The stochastic approximations efficiency is assessed on multi-variate test functions and airfoil viscous aerodynamics simulation in the presence of geometrical and operational uncertainties. Integration of achievements 1- and 2- into a coupled approach in future work will pave the way for a well-balanced goal-oriented deterministic/stochastic error control.

Motivés par des besoins en industrie microélectronique, ces travaux apportent des contributions en modélisation probabiliste de données spatiales, et en maîtrise statistique de procédés.Le problème spatial a pour spécificité d’être posé sur un domaine circulaire. Il se représente par un modèle de krigeage dont la partie déterministe est constituée de polynômes orthogonaux et la partie stochastique de processus gaussiens. Traditionnellement définis avec la norme euclidienne et la mesure uniforme sur le disque, ces choix n’exploitent pas les informations a priori sur les procédés d’usinage.Pour tenir compte des mécanismes de rotation ou de diffusion à partir du centre, nous formalisons les processus gaussiens polaires sur le disque. Ces processus intègrent les corrélations radiales et angulaires dans le modèle de krigeage, et en améliorent les performances dans les situations considérées. Ils sont ensuite interprétés par décomposition de Sobol et généralisés en dimension supérieure. Des plans d’expériences sont proposés dans le cadre de leur utilisation. Au premier rang figurent les cylindres latins qui reproduisent en coordonnées polaires les caractéristiques des hypercubes latins.Pour intégrer à la fois les aspects spatiaux et temporels du problème industriel, la maîtrise statistique de procédé est abordée en termes d’application de cartes de contrôle aux paramètres des modèles spatiaux. Les séries temporelles suivies ont aussi la particularité de comporter des données atypiques et des changements structurels, sources de biais en prévision, et de fausses alarmes en suivi de risque. Ce problème est traité par lissage robuste et adaptatif. / Driven by industrial needs in microelectronics, this thesis is focused on probabilistic models for spatial data and Statistical Process Control. The spatial problem has the specificity of being defined on circular domains. It is addressed through a Kriging model where the deterministic part is made of orthogonal polynomials and the stochastic term represented by a Gaussian process. Defined with the Euclidean distance and the uniform measure over the disk, traditional Kriging models do not exploit knowledge on manufacturing processes. To take rotations or diffusions from the center into account, we introduce polar Gaussian processes over the disk. They embed radial and angular correlations in Kriging predictions, leading to significant improvements in the considered situations. Polar Gaussian processes are then interpreted via Sobol decomposition and generalized in higher dimensions. Different designs of experiments are developed for the proposed models. Among them, Latin cylinders reproduce in the space of polar coordinates the properties of Latin hypercubes. To model spatial and temporal data, Statistical Process Control is addressed by monitoring Kriging parameters, based on standard control charts. Furthermore, the monitored time – series contain outliers and structural changes, which cause bias in prediction and false alarms in risk management. These issues are simultaneously tackled with a robust and adaptive smoothing.

This research project was based on the Design, Implementation and Evaluation of a Photovoltaic Water heating system in South Africa, Eastern Cape Province. The purpose of the study was to design and investigate the scientific and economic contribution of direct water cooling on the photovoltaic module. The method involved performance comparison of two photovoltaic modules, one naturally cooled (M1) and the other, direct water cooled module (M2). Module M2 was used to produce warm water and electricity, hence, a hybrid system. The study focused on comparing the modules’ efficiency, power output and their performance. The temperatures attained by water through cooling the module were monitored as well as the electrical energy generated. A data logger and a low cost I/V characteristic system were used for data collection for a full year. The data were then used for performance analysis of the modules. The results of the study revealed that the directly water cooled module could operate at a higher electrical efficiency for 87% of the day and initially produced 3.63% more electrical energy each day. This was found to be true for the first three months after installation. In the remaining months to the end of the year M2 was found to have more losses as compared to M1 as evidenced by the modules’ performance ratios. The directly water cooled module also showed an energy saving efficiency of 61%. A solar utilization of 47.93% was found for M2 while 8.77% was found for M1. Economically, the project was found to be viable and the payback period of the directly cooled module (M2) system was found to be 9.8 years. Energy economics showed that the system was more sensitive to the price changes and to the energy output as compared to other inputs such as operation and maintenance and years of operation. A generation cost of R0.84/kWh from the system was found and when compared to the potential revenue of R1.18 per kWh, the system was found to enable households to make a profit of 40.5 %. Use of such a system was also found to be able to contribute 9.55% towards carbon emission reduction each year. From these results, it was concluded that a directly cooled photovoltaic/thermal heating (PV/T) system is possible and that it can be of much help in terms of warm water and electricity provision.

Real-world systems usually contain some degree of natural uncertainty, their parameters are more or less variable. When seeking optimal solution, optimization models often disregard this variability and consider parameters of the model to be constant. This thesis focuses on methods of post-optimization analysis. Thorough post-optimization analysis should be a part of every optimization process of systems with variable parameters. Post-optimization analysis can identify parameters whose variability poses the greatest threat to the systems performance. This thesis describes some of the basic post-optimization methods and then a new method based on interval arithmetics is formulated.

Les phénomènes vibratoires à haute fréquence dans les amortisseurs sont défavorables du point de vue de la qualité sonore du véhicule. Les efforts transmis de l’amortisseur à la caisse, situés dans une bande de fréquences entre 200 Hz et 800 Hz, sont responsables du bruit que l’on appelle « gloglottement ». Ce bruit nait dans l’amortisseur lorsque la voiture roule sur une route dégradée et se transmet à la caisse par voie solidienne. La compréhension du phénomène de gloglottement et sa prédiction nécessitent l’identification des mécanismes physiques qui vont générer des pics d’efforts et des vibrations hautes fréquences. Ceux-ci sont liés aux comportements de l’huile de l’amortisseur, des composants mécaniques internes et des interactions entre ces éléments. Les moyens mis en oeuvre pour cette étude sont d’une part le développement d’un modèle d’amortisseur qui prend en compte la modélisation de la dynamique des clapets, des effets de « stiction » des clapets, du frottement et des relations entre les pertes de charges et les débits. D’autre part, une campagne d’essais a permis de construire le modèle et de le valider. La simulation permet de reproduire les phénomènes physiques observés à la mesure et ainsi d’identifier les mécanismes à l’origine du bruit, comme l’ouverture du clapet à ressort et la « stiction » à l’ouverture du clapet anti-retour. La sensibilité de la réponse vibratoire haute fréquence du modèle vis-à-vis de ses paramètres est évaluée avec la méthode de Morris. De plus, des orientations sont données sur la valeur des paramètres de conception dans le but de minimiser les pics d’efforts générés par l’amortisseur. / High-frequency vibratory phenomena in shock absorbers are not suitable for the car sound quality. Forces (in the frequency range [200-800] Hz) transmitted from the shock absorber to the car body are responsible for the so-called "rattling noise". This structure-borne noise is starting from the shock absorber when the car drives over a rough road and is transmitted to the car body by structural transfer path. In order to understand and predict the phenomena, physical mechanisms generating high-frequency vibrations and peaks in the shock absorber response must be identified. These mechanisms are closely related to oil behaviour, internal mechanical components and interactions between all these elements. The present work consists on the one hand in modelling the shock absorber taking into account valve dynamics, valve stiction, friction and loss of pressure relations in the orifices. On the other hand, experimental shock absorber testing was conducted in order to build the model and to validate it. Model simulations reproduce observed phenomena in the experiments and helped us to identify the mechanisms leading to structure-borne noise, like spring valve opening and check-valve stiction. Sensitivity of the model response due to its input parameters was evaluated with Morris method. Moreover, some guidances are given in order to reduce the level of structure-borne noise generated by the shock absorber.