L'Organisation des Nations Unies vise à moderniser les industries afin de les rendre durables et plus respectueuse de l'environnement d'ici 2030. Afin de répondre à ces attentes, il faut mettre en place des voies d'améliorations des procédés de fabrication d'un point de vue environnemental. Cette démarche nécessite une connaissance fine des flux entrants et sortants lors de la fabrication d'un produit. Néanmoins, ce n'est pas le cas pour les procédés de fabrication additives ou les impacts environnementaux générés lors de la fabrication d'un produit sont encore méconnus. Par conséquent, il est primordial de bien "compter" les différentes sources de consommations et de rejets. Pour cela, une évaluation quantitative des flux intervenants pendant la fabrication de pièces est nécessaire pour améliorer la connaissance de la performance environnementale d'un procédé. Les travaux de cette thèse portent sur la proposition d'une méthodologie d'évaluation multicritère pour les procédés de fabrication additive afin de pouvoir prédire, dès l'étape de conception d'un produit, des informations sur les aspects techniques, économiques et environnementaux du couple pièce/procédé. Afin de proposer aux concepteurs la possibilité d'évaluer un produit dès son étape de conception, des modèles de consommation fins traduisant le comportement du procédé ont été mis en place. La méthodologie développée s’intéresse à l'ensemble des sources de consommation et de rejets ainsi qu'à l'ensemble des étapes nécessaires à la fabrication d'une pièce mécanique.Ce manuscrit est divisé en six chapitres qui permettent de présenter le contexte général de l'étude, l'état de l'art, la méthodologie d'évaluation multicritère, l'application sur les procédés de fabrication additive et l'exploitation sur un cas industriel. Le dernier chapitre se consacre à la conclusion sur les apports de ces travaux et propose des perspectives de recherche. / The United Nations aims to modernize industries in order to make them sustainable and more environmentally friendly by 2030. In order to meet these expectation, it is necessary to put in place ways of improving production processes from an environmental point of view. This approach requires a detailed knowledge of the incoming and outgoing flows during the manufacturing of a product. However, this is not the case for additive manufacturing processes where the environmental impacts generated during this stage are still unknown. For that, a quantitative evaluation of the flows involved during the manufaturing of parts is necessary in order to improve the knowledge of the environmental performance of a process. The work of this thesis focuses on the development of methodology for additive manufacturing processes in order to predict information on the technical, economic, and environmental aspects of a product during the design stage of a part. The methodology developped is increasingly interested in all the sources of consumption as well as all the stages necessary for the manufacturing of a mechanical part.This manuscript is divided into six chapters that can present the general context of the study, the state of the art, the methodology developped, a application of the methodology to additive manufacturing processes and the computer tool developed during this thesis. The last chapter is devoted to the conclusion on the contributions of this work and provides research perspectives.

Research has validated the contribution of information sharing to performance improvement. It has also suggested that flexibility is a highly important competitive priority for those companies where demand is volatile. Several studies argue that flexibility has been recognized as a key enabler for supply chain responsiveness. However, the impact of information sharing on supplier flexibility is still unexplored, especially for the companies that operate in agile business environments such as in the automotive industry where flexibility is a strategic requirement to manage demand uncertainty. In agile supply chains, such as in the automotive industry, information sharing can play an important role in responding to demand variability. In such settings, the demand volumes generally fluctuate, and hence create production-scheduling problems for the upstream suppliers such as first-tier suppliers. Interestingly, the impact of demand fluctuations on suppliers is higher than that of Original Equipment Manufacturers (OEMs). The aim of this doctoral thesis is to investigate the role of information sharing between OEMs and first-tier suppliers, in enhancing supplier flexibility. Particularly, the research focuses on exploring the relationship between sharing demand schedules and inventory data, and volume and delivery flexibility. The questions on whether information sharing between OEMs and first-tier suppliers affect supplier flexibility remain unanswered. The following research questions have emerged:  RQ1: How does information sharing between OEMs and first-tier suppliers affect the latter's responsiveness to fluctuating demand? RQ2: What is the relationship between information sharing of OEMsʼ demand forecasts and inventory data, and suppliers’ volume and delivery flexibility? RQ3: What factors should OEMs consider to improve the sharing of demand forecasts with suppliers? The empirical part of this thesis comprises three individual studies that constitute the empirical foundations of the research problem. Each study analyzes one research question using its own methodological approach. Hence, different research methods for collecting and analyzing data were used to address the research questions. Applying different research methods is deemed advantageous because it allows for methodological rigorousness in this doctoral thesis. This thesis contributes to the body of knowledge in three dimensions—theory, method, and context. First, it contributes to the academic field of operations and supply chain management by developing a model to explain how information sharing could affect suppliers’ delivery performance. The model provides a measurement scale to measure the level of information sharing between OEMs and suppliers, and its impact on suppliers’ delivery flexibility. Second, this thesis contributes to the methods by using state-of-the-art techniques, which is partial least squares structural equation modeling (PLS-SEM) including consistent PLS, and applying advanced concepts to empirically test the proposed model. Third, this thesis has a managerial contribution to examine the concept of information sharing and flexibility at the supplier level. Investigating the problem at the supplier level may enable managers to improve short-term decisions, such as production scheduling decisions, internal production, and inventory processes, and evaluate collaboration practices with OEMs. This doctoral thesis is organized in a monograph format comprising five chapters: Introduction, Literature review, Methodology, Empirics, and Conclusion. As an outcome, several scientific articles have emerged from this thesis and have been submitted for consideration for publication in peer-reviewed journals and international conferences in the field of operations and supply chain management. These articles are listed and appended at the end of this dissertation. / <p>QC 20160302</p>

Numerous studies have evaluated the relationship between biodiversity and productivity, with general trends suggesting a positive relationship. While most studies only use species richness, this study also analyzed how productivity changes with functional diversity and Shannon’s diversity index. Functional diversity gives important context to the examination of biodiversity-productivity relationships due to the direct link between organisms’ functional traits and their role in a given ecosystem. This study used data from the USDA Forest Service Forest Inventory and Analysis (FIA) database collected in Alabama, Louisiana, and Mississippi to estimate plot-level productivity and diversity. Structural equation modeling was used to determine the strength of the relationship between measures of diversity and forest productivity. This study found that species richness had the greatest influence on forest productivity, but it was largely an indirect effect mediated by stand density. This study could be expanded spatially to include more forest types for comparison of trends.