Pour améliorer l’analyse des risques dans les projets et renforcer son efficacité, les gestionnaires de projet devraient réutiliser les expériences et les bonnes pratiques acquises au cours de projets antérieurs. Le retour d’expérience constitue une source de connaissances importante pour réduire les niveaux d’incertitude et donc les risques dans les projets. Les méthodologies de retour d’expériences sont ainsi devenues réellement reconnues dans de nombreuses entreprises. Toutefois, ces entreprises se sont souvent contentées de recueillir des informations en fin de projet en pensant que cela suffirait à générer les connaissances nécessaires pour améliorer leur performance. Malheureusement, la capitalisation de ces expériences est traditionnellement une étape statique à la clôture du projet qui permet simplement la capture de quelques événements mémorisés par les experts impliqués. En outre, l’information capitalisée est difficile à réutiliser directement dans une nouvelle analyse des risques. Nos efforts se sont concentrés sur l’élaboration d’une méthode ayant pour but d’améliorer le processus de gestion des risques dans les projets en utilisant un système de retour d’expérience et, ainsi, de contribuer à une logique d’amélioration continue. La méthode envisagée est basée sur un système d’exploitation des connaissances qui permet de développer des compétences clés comme : la résolution des problèmes, la capacité à prendre des décisions collectivement, la réflexion, l’apprentissage et la capacité prospective (envisager). Le modèle proposé est défini sur la base de l’étude de la contribution de trois domaines centraux : le Management de Projets, le Management des Risques et le retour d’expérience. La singularité de nos travaux réside dans le fait d’intégrer explicitement un mécanisme de retour d’expérience en continu afin d’améliorer la performance des processus de gestion des risques dans les projets. Nous proposons de mettre en oeuvre une démarche de modélisation des connaissances orientée retour d’expérience. Nous définissons un modèle permettant de caractériser les projets, les risques et les expériences en vue du repérage, de la capitalisation et de l’exploitation des connaissances. La modélisation de ces éléments permet également de disposer d’une structuration facilitant une lecture plus rapide du projet ou de ses processus. Nous avons donc développé un modèle qui permet de représenter les éléments clé utilisés lors du processus de management des risques et ainsi de faciliter la capitalisation les expériences et la recherche des expériences antérieures similaires. Cela permet ensuite de standardiser et d’améliorer la démarche de management des risques. Du point de vue de la recherche des expériences antérieures, nous définissons : D’une part, un algorithme de recherche des expériences similaires fondé sur les comparaisons entre des graphes étiquetés orientés. Cela consiste en l’établissement d’une correspondance entre deux graphes (le graphe 1 étant le contexte du projet actuel et le graphe 2 le contexte d’un projet passé enregistré sous forme d’expérience) par une factorisation par paire de la matrice d’affinité qui découple la structure des noeuds et des arcs similaires (Zhou et De la Torre, 2012). D’autre part, un algorithme pour trouver la correspondance optimale entre ces graphes, de sorte que la somme de la compatibilité des noeuds et des arcs soit maximisée. Pour ce faire, nous avons utilisé un algorithme génétique. Enfin, nous proposons une démarche d’exploitation des expériences passées similaires. De cette manière nous pouvons obtenir un ensemble de risques associés à ces objets similaires afin d’alimenter le système d’aide à la décision dans la gestion du projet. / In order to improve Project Risk Management and to reinforce its effectiveness, the managers of the project should reuse the experiences and the good practices acquired in previous projects. The Experience Management constitutes an important source of knowledge to reduce the levels of uncertainty and thus the risks in the projects. The methodologies for Experience Management have thus become truly recognized in many companies. However, these companies were often satisfied to collect information at the end of the project by thinking that would be enough to generate knowledge necessary to improve their performance. Unfortunately, the capitalization of these experiments is traditionally a static stage at the close of the project, which simply allows the capture of some events memorized by the implied experts. Moreover, capitalized information is difficult to reuse directly in a new-risk analysis. Our efforts focused on developing a methodology to improve the Risk Management Process in Projects using an Experience Management System and thus contribute to the logic of continuous improvement. The proposed approach is based on a knowledge-based system that enables the development of key competencies such as problem solving, collective decision-making, reflection, learning and prospective capacity. The proposed model is based on the study of the contribution of three central fields: Projects Management, Risks Management and the Experience Management. The singularity of our work lies in the fact of integrating a mechanism back from experiment explicitly uninterrupted in order to improve the performance of the processes of risk management in the projects. We propose to implement a knowledge-based modeling approach based on Experience management. We define a model to characterize projects, risks and experiences for the identification, capitalization and exploitation of knowledge. The modeling of these elements also makes it possible to have a structuring facilitating a faster reading of the project or its processes. Therefore, we have developed a model which allows us to represent the key elements used during the risk management process and thus to facilitate the capitalization of the experiments and the research of previous similar experiences. That then makes it possible to standardize and improve the risk management approach. From the point of view of the search for previous experiences, we define: On the one hand, an algorithm of research of similar experiments founded on the comparisons between directed labeled graphs. That consists of the establishment of a correspondence between two graphs (graph 1 being context of the current project and graph 2 context of the last project recorded in the form of experiment) by a pairwise factorization of the affinity matrix, which decouples the structure of nodes and similar arcs (Zhou and Of Torre, 2012). On the other hand, an algorithm to find the optimal correspondence between these graphs, so that the sum of the compatibility of the nodes and the arcs is maximized. With this intention, we used a genetic algorithm. Lastly, we propose an approach of exploitation of similar last experiences. In this manner, we can obtain a set of risks associated with these similar objects in order to feed the assistance system with the decision in the management of the project.

Made available in DSpace on 2015-04-11T14:03:00Z (GMT). No. of bitstreams: 1 Jacilane de Holanda Rabelo.pdf: 4788725 bytes, checksum: 199f5b959e361201af68d3afa0ac710f (MD5) Previous issue date: 2013-02-19 / CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico / The knowledge acquired by the members of a software organization is one of its most important assets. Therefore, the proper management of this knowledge has become a real need in the software development industry. The capture of lessons learned has become a practice developed by some of these organizations in order to manage and transfer knowledge. One of the most common approaches to encourage knowledge transfer is codification. Knowledge codification can facilitate the storage of lessons learned for a future usage. This MA research aims at elaborating a strategy to facilitate the codification of lessons learned in software organizations, consequently promoting this practice. The strategy was denominated PABC-Pattern, and three studies were developed: the first compared the approach initially called ABC-Pattern with another visual approach the Mind Map; the second compared the ABC-Pattern with the codification structure supported by the ACKNOWLEDGE tool. Results from the first study indicated that the participants had a preference in using the ABC-Pattern approach due to its usage and utility. For this preference, it follows some of the reasons identified: a) more codification details; b) a more detailed description of the knowledge s scenario which is more clarifying; c) the possibility of acquiring more information with less effort; and d) the possibility of describing both the problem and solution. The main contribution for the second study were the improvement suggestions for the ABC-Pattern, in which enabled an evolution of the strategy. The second version of the strategy was denominated PABC-Pattern and was experimentally evaluated by a third study, in an observational study, with the help of the Technology Information professionals. The results showed that PABC-Pattern found good acceptance as an approach to codify and share knowledge, and also that industry professionals would recommend its usage where they work / O conhecimento adquirido pelos membros de uma organização de software é um dos seus ativos mais importantes. A gestão adequada deste conhecimento tornou-se uma necessidade real na indústria de desenvolvimento de software. A coleta de lições aprendidas é uma das práticas utilizadas por parte dessas organizações para gerenciar e transferir o conhecimento. Uma das abordagens para incentivar a transferência de conhecimento é a codificação. A codificação do conhecimento pode facilitar o registro das lições aprendidas para sua consulta posterior. O objetivo desta pesquisa de mestrado é elaborar uma estratégia para facilitar a codificação das lições aprendidas em organizações de software, de modo a incentivar esta prática. A estratégia foi nomeada PABC-Pattern. Foram realizados três estudos: o primeiro comparou a abordagem inicialmente chamada ABC-Pattern com outra abordagem visual, o Mapa Mental; o segundo comparou a abordagem ABC-Pattern com a estrutura de codificação apoiada pela ferramenta ACKNOWLEDGE. Os resultados do primeiro estudo indicaram que os participantes tinham uma preferência em utilizar a abordagem ABC-Pattern, devido à sua facilidade de uso e utilidade. Foram identificadas algumas das razões para essa preferência: a) mais detalhes de codificação; b) uma descrição mais detalhada do cenário do conhecimento, que é mais esclarecedora, c) a possibilidade de adquirir mais informações com menos esforço, e d) a possibilidade de descrever tanto o problema e a solução. A principal contribuição do segundo estudo foram as sugestões de melhoria para ABC-Pattern que possibilitaram uma evolução da estratégia. A segunda versão da estratégia foi chamada de PABC-Pattern e foi avaliada experimentalmente através de um terceiro estudo, dessa vez de observação, com profissionais da área de Tecnologia da Informação. Os resultados possibilitaram apontar que PABC-Pattern teve uma boa aceitação como abordagem para codificar e compartilhar o conhecimento e que os profissionais da indústria recomendariam sua utilização na empresa em que trabalham.

Inom byggindustrin är det svårt att skapa standardiserade logistikprocesser eftersom det vid varje nytt bygge även skapas en ny organisation. Förutsättningarna skiljer sig även mellan olika byggen, vilket försvårar ett förbättringsarbete. Skanska Väg och Anläggning Norr fick under 2017 uppdraget att bygga om Vasaplan i centrala Umeå, och i september 2018 stod projektet klart. Ombyggnationen var i det stora hela ett mycket lyckat projekt, men efter färdigställandet av projektet har problem angående materialtillgång identifierats. Syftet med arbetet är att undersöka hur leveranser till en byggarbetsplats kan optimeras samt hurvida ett mellanlager kan underlätta hanteringen av leveranserna till byggarbetsplatsen. En jämförelse har gjorts där det har undersökts ifall det är mer lönsamt att använda sig av lagerhållning, eller endast av JIT-leveranser. Förhoppningen är att arbetet kan bidra till att Skanska i framtiden får ett mer standardiserat tillvägagångssätt vid planering av leveranser till byggarbetsplats av material som kräver liknande lagerhållning och transport som granithällar. För att lösa detta har två matematiska modeller använts; Anläggningslokaliseringsproblemet (ALP) samt en matematisk modell som optimerar placering av material på en lageryta. Två stycken produktionsflödesmodeller, JIT och EOQ, har även använts i beräkningarna. Resultatet från produktionsflödesmodellerna, JIT och EOQ, visar att JIT-leveranser med hjälp av en omlastningscentral alltid är den mest kostnadseffektiva lösningen då lageryta är en direkt kostnad för Skanska. I de fall lager inte är en direkt utgift för Skanska så rekommenderar den matematiska modellen för ALP en optimal användning av de lager som är tillgängliga. / For every new construction project, a new organisation is created. It is therefore a challenge for the construction industry to create standardized logistic processes. In addition, different construction projects have different traits, which results in further challenges for improvement efforts for the construction logistic processes. In 2017 Skanska Väg och Anläggning Norr did the reconstruction of Vasaplan in the central of Umeå, and in September 2018 the reconstruction project was done. The reconstruction was in its entirety a very successful project, however when the project was finished problems regarding material supply were identified. The aim of this paper is to analyze how deliveries to a construction site can be optimized and whether storage spaces can aid in the handling of deliveries to the construction site. A comparison has been made between storing material and using JIT-deliveries. The hope is to help Skanska in developing a more standardized approach when it comes to planning the deliveries of materials that has similar storage and transport conditions as the slabs of granite used. To solve this two mathematical models have been used; Facility location problem and a mathematical model that optimizes the placement of materials in a storage space. Two production flow models, JIT and EOQ, were also used when performing the calculations. The result from the production flow models, JIT and EOQ, show that JIT deliveries are always the most cost effective solution when storage space is a direct cost for Skanska, when used together with a logistics center. However, when storing is no extra expense for Skanska, the mathematical model for the Facility location problem suggests a optimal use of the storage spaces that are available.