The concepts of continuous improvement (CI) and learning are advocated in project management (PM) literature and standards, as suitable concepts to adopt when managing projects. CI can be described as philosophy in which all members of an organization work together to achieve sustained and incremental improvements.Learning can in turn be divided into the learning organization, focusing oncharacteristics that allow an organization to learn, and organizational learning,focusing on how learning is achieved in an organizational context. How big of a part projects play in organizations can differ, from scarce occurrence to being the dominant way of working. Organizations that solely carry out projects can bedescribed as project-based organizations (PBOs). This study explores the concepts of CI and learning in the context of a project-based organization. The reason for doing this is that little information has been found on how CI and learning should be achieved and sustained in a PM context, although being described as important concepts in PM.A longitudinal exploratory case study was performed, at the Projects department at Luossavaara-Kiirunavaara AB, in order to understand how the concepts of CI and learning could be applied in a PBO. Several data collection methods have been applied in order to achieve triangulation. A qualitative approach was used in order to understand the specific characteristics associated with operating as a PBO, and thus affecting if and how CI and learning could be applied. The research process, whichdescribes the case study in chronological order, and display findings as they emerged, is given a fair amount of room in the thesis, in order to allow the reader to both scrutinize the study, and reach conclusions of her own.The findings indicate that no aspects of operating as a PBO counteract the potential of achieving CI and learning, but that awareness has to be raised regarding the challenges that come with it. CI is described as attractive due to a low-cost approach, and low entry barriers. This description is however based on applying CI in repetitive task environments (e.g. manufacturing industry), not the non-repetitive task environment that characterizes operating as a PBO. If CI is to be achieved in a PBO it is likely that both the PBO and the concept of CI has to be adjusted to one another, to a much greater extent than is described in the CI literature. The current approaches to learning in PBOs seem to be based on a hard approach, trying to capture and disseminate learning throughout the organization. However, this study indicates that this way of working falls short, and suggests that a softer approach might be needed in order to achieve organizational learning in PBOs

The existence of variation has been a major problem in industry since the industrial revolution. Hence, many organizations try to find strategies to master and reduce the variation. Statistical analysis, such as process capability analysis and Design of Experiments (DoE), often plays an important role in such a strategy. Process capability analysis can determine how the process performs relative to its requirements or specifications, where an important part is the use of process capability indices. DoE includes powerful methods, such as factorial designs, which helps experimenters to maximize the information output from conducted experiments and minimize the experimental work required to reach statistically significant results.Continuous processes, frequently found in the process industry, highlight special issues that are typically not addressed in the DoE literature, for example, autocorrelation and dynamics. The overall purpose of this research is to contribute to an increased knowledge of analyzing DoE and capability in process industry, which is achieved through simulations and case studies of real industrial processes. This research focus on developing analysis procedures adapted for experiments and comparing decision methods for capability analysis in process industry.The results of this research are presented in three appended papers. Paper A shows how the use of a two-level factorial experiment can be used to identifying factors that affect the depth and variation of the oscillation mark that arises from the steel casting process. Four factors were studied; stroke length of the mold, oscillation frequency, motion pattern of the mold (sinus factor), and casting speed. The ANOVA analysis turned out to be problematic because of a non- orthogonal experimental design due to loss of experimental runs. Nevertheless, no earlier studies where found that shows how the sinus factor is changed in combination with the oscillation frequency so that the interaction effect could be studied. Paper B develops a method to analyze factorial experiments, affected by process interruptions and loss of experimental runs, by using time series analysis. Paper C compares four different methods for capability analysis, when data are autocorrelated, through simulations and case study of a real industrial process. In summary, it is hard to recommend one single method that works well in all situations. However, two methods appeared to be better than the others. Keywords: Process industry, Continuous processes, Autocorrelation, Design of Experiments, Process capability, Time series analysis. / Förekomsten av variation i tillverkningsprocesser har varit ett problem redan sedan den industriella revolutionen. Därför har många organisationer försökt hitta en strategi för att hantera och reducera variationen. Statistiska metoder som duglighetsanalys och försöksplanering spelar ofta en viktig roll i dessa sammanhang. Duglighetsanalys bedömer hur processen presterar i relation till dess krav eller specifikationer, där en viktig del är användningen av duglighetsindex. Försöksplanering omfattar kraftfulla metoder, exempelvis faktorförsök, för att hjälpa den som utför experiment att maximera informationsutbytet vid experiment och samtidigt minimera de resurser som krävs för att nå statistiskt säkerställda resultat.Kontinuerliga processer, vilka är frekvent förekommande i processindustrin, ger upphov till speciella problem vid experiment som normalt inte behandlas i litteraturen, exempelvis autokorrelation och dynamik. Det övergripande syftet med forskningen i denna avhandling är att bidra till en ökad kunskap om analysen av försöksplanering och duglighet i process industri, vilket uppnås genom simuleringar och fallstudier av verkliga industriella processer.Denna forskning fokuserar på att föreslå och utveckla analysmetoder anpassade för experiment samt att jämföra olika beslutsmetoder för duglighetsanalys i industriella processer.Resultaten av forskningen presenteras i tre bifogade artiklar. Artikel A visar hur ett två-nivåers faktorförsök kan användas för att identifiera de faktorer som påverkar oscillationsmärkesdjupet som uppstår från stålstränggjutnings¬processen. Fyra faktorer studerades; slaglängden av gjutform, svängnings¬frekvensen, rörelsemönstret av gjutform (sinusfaktor) och gjuthastigheten. ANOVA analys visade sig vara problematiskt eftersom försöksdesignen inte var ortogonala på grund av förlorade försöksomgångar. Trots det har inga tidigare studier hittats som visar hur sinusfaktorn ändras i kombination med svängnings¬frekvensen så att samspelseffekten kan studeras. Artikel B utvecklar en metod för att analysera faktorförsök, påverkat av processavbrott och förlust av experimentomgångar, baserat på tidsserieanalys. Artikel C jämför fyra olika metoder för duglighetsanalys, när data är autokorrelerad, genom simuleringar och fallstudie av en faktisk industriell process. Sammanfattningsvis är det svårt att rekommendera en metod som fungerar bra i alla situationer. Resultaten pekar på att två metoder är bättre än de andra.

The dissertation studies two aspects of international hierarchy. The world of international politics is not one of completely sovereign states competing in anarchy. Patterns of hierarchy, where a dominant state has legitimate control over some actions of a subordinate state, color the globe. First, I look at shared norms and hierarchy. Most studies concerning hierarchy focus on material maximization as an explanation for hierarchy--if hierarchy increases the wealth and security of two states, then hierarchy is more likely. I argue that shared norms held by two states facilitate hierarchy. Shared norms produce a common in-group community, generate common interests, create common ways of doing business, and give rise to common values that increase subordinate states' ability to persuade the dominant state. These factors ease the creation and maintenance of international hierarchical relationships. Second, I study interstate behaviors that can be explained as actions of maintenance by dominant states over subordinates to preserve or increase a level of hierarchy. I theorize that sticks and carrots from a dominant state (like economic sanctions, military interventions, and foreign aid) help sustain a dominant state's rule by convincing subordinate states to follow the dominant state's commands and expectations. Using data on U.S. hierarchies from 1950 to 2010, I utilize multivariate regressions to test hypotheses drawn from these theories. I find that shared norms associate with hierarchy, and maintenance actions uncommonly associate with compliance.

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This thesis is about implementing Design of Experiments in enterprises manufacturing high performance ceramics. The manufacturing of ceramics is a complex process which involves problems with variation in product properties and in process performance. Every system in operation generates information that can be used to improve it. To be able to improve, measurements must be made and recorded data must be transformed into information. Design of Experiments is about performing tests using a minimum of resources to receive a maximum of information about a process or a system. Today most of the development of processes and products is done supported by expensive, and often misleading, one-factor-at-a-time experiments. To examine the possibilities of facilitating implementation of Design of Experiments, case-studies of two Swedish manufacturers of high performance ceramics were carried out. A model of implementing Design of Experiments is presented based on theory and the case-studies. The proposed model consists of three major phases: 1.Planning and education. 2.Pilot project with new ways of working. 3.Assessment, maintenance and improvement. Design of Experiments appears to be a well suited technique for structuring the development of manufacturing high performance ceramics. The implementation of Design of Experiments could be facilitated by long-term planning for process improvement. To make assessment and evaluation possible, process performance should be documented not only after but also before an implementation takes place. Both knowledge about statistics and knowledge about the studied processes should be present in the teams carrying out experiments. / <p>Godkänd; 1998; 20070404 (ysko)</p>

Railway switches and crossings (S&amp;Cs) are among the most important high-value components in a railway network and a single failure of such an asset could result in severe network disturbance, huge economical loss, and even severe accidents. Therefore, potential defects need to be detected at an early stage and the status of the S&amp;C must be monitored to prevent such consequences. One type of defect that can occur is called a squat. A squat is a local defect like a dent or an open pit in the rail surface. In this thesis, a testbed including a full-scale S&amp;C and a bogie wagon was studied. Vibrations were measured for different squat sizes by an accelerometer mounted at the point machine, while a boggy was travelling along the S&amp;C. A method of processing the vibration data and the speed data is proposed to investigate the feasibility of detecting and quantifying the severity of a squat. A group of features were extracted to apply isolation forest to generate anomaly scores to estimate the health status of the S&amp;C. One key technology applied is wavelet denoising. The study shows that it is possible to monitor the development of the squat size introduced in the test bed by measuring point machine vibrations. The relationships between the normalised peak-to-peak amplitude of the vibration signal and the squat depth were estimated. The results also show that the proposed method is effective and can produce anomaly scores that can indicate the general health status of an S&amp;C regarding squat defects.

This master thesis presents, suggests, and discusses a novel approach to enhance the mission dependability of Autonomous Underwater Vehicles (AUVs) through Adaptive Dynamic Redundancy (ADR). The AUVs demand improved dependability not only because they operate in harsh and unpredictable waters, but also because mission failures occur, leading to mission aborts and potential loss of valuable data and equipment. The ADR was carefully implemented for AUV thrusters using curated methods. The ADR stands out as it maintains high dependability while utilizing less power consumption, basing this on necessity, needs, environmental data and conditions, thruster health, and mission criticality. By leveraging a switching feature between Dual Modular Redundancy (DMR) and 1-out-of-3 redundancy, ADR aims to minimize the risk of failures while optimizing the power consumption and reducing wear and tear on the thrusters both for their operational and futuristic state. Through the comparative analysis, the ADR has demonstrated its capability to enhance dependability by improving reliability, safety, and operational efficiency of AUVs compared to other standardized redundancy concepts. The findings suggest that ADR not only prevents failures more effectively than TMR and DMR, but also significantly extends the mission’s lifespan and increases overall mission success rates.

Face aux nouveaux cadres législatifs ou environnementaux dans lesquels ils doivent évoluer, les systèmes industriels actuels sont, en plus d'être contraints par des exigences classiques de productivité et de cout, sujets au respect de nouvelles exigences relatives à la sûreté, la sécurité ou au développement durable notamment. Pour répondre à ces exigences et améliorer la maitrise des performances de ses systèmes, EDF souhaite faire évoluer sa démarche d'Optimisation de la Maintenance Basée sur la Fiabilité vers une nouvelle méthode. Cette méthode nécessite en autre la proposition d'une approche outillée permettant de quantifier a priori les programmes de maintenance (CMPQ) sur ses systèmes par rapport aux indicateurs de performance attendus (KPIs). Cet outillage fait l'objet de cette thèse financée dans le cadre du GIS 3SGS - projet DEPRADEM 2. Après avoir généralisé les besoins d'EDF en regard de la CMPQ, nous proposons une identification de la connaissance générique nécessaire pour évaluer les KPI. Afin d'aboutir à un outil permettant l'automatisation de ces études de CMPQ, cette connaissance générique est ensuite modélisée sur la base de deux langages : le langage semi-formel SysML capitalisant, par l'intermédiaire de différents diagrammes, la connaissance statique, interactionnelle et comportementale ; et le langage AltaRicaDF, supportant un modèle dynamique permettant d'évaluer les KPIs par simulation stochastique. La création de ce modèle dynamique à partir des différents diagrammes est basée sur un mapping entre les concepts d'intérêt des deux langages. La démarche dans sa globalité est validée à la CMPQ d'un cas d'étude fourni par EDF : le système ARE / To face with new legislatives and environmental contexts in which they have to operate, it is needed now that the industrials systems have to satisfy to many different requirements and constraints. Thus, these requirements are not only conventional ones such as availability and costs, but also emergent ones such as safety and sustainability. This report implies for the specific French company EDF (energy power supplier) to evolve from its usual approach of reliability centered maintenance (RCM) to a new approach. It is consisting mainly in developing a tool able to support the Complex Maintenance Programs Quantification (CMPQ). This Ph.D. is dealing with this the engineering and deployment of this tool in the frame of the GIS 3SGS - DEPRADEM 2 project. The first step of the work is to generalize EDF needs, then to propose a framework enabling to identify required generic knowledge needed to assess the Key Performances Indicators (KPIs) for supporting quantification. The next step is to model the generic knowledge in two complementary ways: a formalization of the static, interactional and behavioral knowledge based on different SysML diagrams; and a formalization of the dynamic and executable knowledge formalized by AltaRicaDF (ADF) language, allowing to perform stochastic simulation and to assess required KPIs. The path to elaborate dynamic executable vision from SysML diagrams is released by means of rules between each element of interest of both languages. All this approach/tool is applied to a specific EDF case study: the ARE system

Effective maintenance planning is essential and important in any organisation that is responsible for procuring and managing complex assets. In the marine shipping industry maintenance planning is very significant due to its complexity and the obligations on shipping organisations to comply with certain regulations and requirements. Moreover, improper planning can reduce the ship's availability, which may in turn, be reflected in the revenue of the company. Another issue that requires attention in this field is the cost of maintenance, since improper or inadequate planning could result in breakdowns that could increase the cost of maintenance.This research aims to identify the key factors that affect ship maintenance planning and to provide a framework that can help the decision maker to identify and choose optimum decisions regarding ship maintenance. The research is divided into four stages in order to achieve its objectives and to address the research problem.The first stage is the review of the literature to identify the need for maintenance and to select the key factors that affect maintenance planning. The findings indicate that: maintenance scheduling, selection of maintenance strategy, ship construction, crew compensation, and shipyard selection are the most important factors.The second stage is to evaluate maintenance performance measurements for the marine shipping industry by conducting case study and interviews with professionals involved in the mercantile industry. Semi-structured interviews were conducted with six senior staff experts from three different organisations. The results show that: dry docking scheduling, maintenance costs and budgets, customer satisfaction, employees' satisfaction, classification requirements, and the ship's maintenance requirements are the main factors that have great influence on maintenance planning.The third stage is to develop new methodology to measure the maintenance performance in the marine shipping organisation which is the ship maintenance performance measurement (SMPM) framework. The developed method was validated to assist managers in making the right decisions in ship maintenance planning. The framework was developed based on ten thematic criteria that can be used as indicators for potential organisation growth, i.e., maintenance strategy; dry docking scheduling; budget and costs; the ship's equipment; customer satisfaction; employees; health, safety and environment; learning and growth; classification requirements; and the ship's operation and demands requirements. Interviews were conducted with key personnel from the Kuwait Oil Tanker Company (KOTC) to validate the framework.The fourth stage demonstrates that an optimised schedule for the dry docking of ships for routine maintenance has been constructed. This is accomplished on the basis of one measured criterion, dry docking scheduling, by using an integer programming model to maximise the ship's availability within the company fleet. The model is defined by three constraints: the maintenance window, maintenance completion, and the ship's limit. The model was validated using data from KOTC, and the results depict an optimum solution for maintenance scheduling, maximising the ship's availability to 100% and not less than 92%.

Call number: LD2668 .T4 1978 W44 / Master of Science