Modelos de risk based inspection e risk based inspection and maintenance aplicados a sistemas de produção de energias renováveis

A utilização de recursos energéticos renováveis apresenta-se como um caminho vital para a humanidade alcançar um desenvolvimento sustentável. Nesta campanha, a energia eólica surge como um dos principais vectores de orientação tendo evoluído de forma quase exponencial nos últimos anos. No entanto, apesar da sua relativa maturidade, esta tecnologia enfrenta ainda alguns problemas e desafios. Não obstante a experiência empírica da indústria eólica, adquirida nos últimos trinta anos e dos esforços para melhorar a fiabilidade operacional das turbinas, as taxas de falha ainda se apresentam elevadas. Face às correntes práticas de Manutenção das turbinas e parques eólicos e às características de falha, (por vezes catastróficas), existe a necessidade de optimizar as estratégias de manutenção das turbinas eólicas e reduzir os custos durante o ciclo de vida, de modo a maximizar o retorno do investimento. Descreve-se neste trabalho o estado do conhecimento actual face ao objectivo pretendido, a recolha de dados reais da operação e Manutenção, a aplicabilidade dos modelos escolhidos para obtenção da probabilidade de falha, e as consequências e avaliação do risco. Assim, desenvolveu-se uma ferramenta de apoio à decisão, baseada em Modelos de RBI (Risk Based Inspection) e RBIM (Risk Based Inspection and Maintenance) aplicados a turbinas eólicas.

Tarkastusten turvallinen ja taloudellinen optimointi kattilalaitoksessa

Vuoden 1999 muutos kansallisessa painelaitelainsäädännössä mahdollistaa perinteisten määräaikaistarkastusten korvaamisen aiempaa joustavimmilla tavoilla. Tarkastusresurssit voidaan uuden mallin mukaisesti kohdentaa laitteisiin olemassa olevan, todellisen riskin perusteella, joka osoitetaan asianmukaisin arviointimenettelyin. Nykyiset riskianalyysit ovat osoittautuneet tähän tarkoitukseen liian raskaiksi ja työläiksi. Tässä työssä on kehitetty nykyisten arviointimenetelmien pohjalta näitä kevyempi, riskiperusteinen analyysimalli, jota on testattu kattilalaitoksen riskikohteiden arvioinnissa. Arviointimenettely on rakennettu ensisijaisesti palvelemaan painelaitteiden kunnonvalvontajärjestelmään sisältyvien tarkastusten määrittelyä, mutta se soveltuu yhtälailla perinteisen tarkastustoiminnan rinnalle. Tällöin vältytään päällekkäisiltä tarkastuksilta ja voidaan hyödyntää lainsäädännön suomaa mahdollisuutta tarkastus-aikavälien pidentämiseen sekä säästetään kustannuksissa. Aiempaan nähden, kohteen potentiaaliset riskit voidaan esittää kehitetyllä riskianalyysimallilla yhteismitallisina, jolloin niiden keskinäinen vertailu ja päätöksenteko ovat helpompia.

A risk-based model for inspection and maintenance of cross-country petroleum pipeline

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

On the Regulation of Small Actors: Three Experimental Essays about Policies based on Voluntary Compliance and Decentralized Monitoring

Monitoring and enforcement are perhaps the biggest challenges in the design and implementation of environmental policies in developing countries where the actions of many small informal actors cause significant impacts on the ecosystem services and where the transaction costs for the state to regulate them could be enormous. This dissertation studies the potential of innovative institutions based on decentralized coordination and enforcement to induce better environmental outcomes. Such policies have in common that the state plays the role of providing the incentives for organization but the process of compliance happens through decentralized agreements, trust building, signaling and monitoring. I draw from the literatures in collective action, common-pool resources, game-theory and non-point source pollution to develop the instruments proposed here. To test the different conditions in which such policies could be implemented I designed two field-experiments that I conducted with small-scale gold miners in the Colombian Pacific and with users and providers of ecosystem services in the states of Veracruz, Quintana Roo and Yucatan in Mexico. This dissertation is organized in three essays.

The first essay, “Collective Incentives for Cleaner Small-Scale Gold Mining on the Frontier: Experimental Tests of Compliance with Group Incentives given Limited State Monitoring”, examines whether collective incentives, i.e. incentives provided to a group conditional on collective compliance, could “outsource” the required local monitoring, i.e. induce group interactions that extend the reach of the state that can observe only aggregate consequences in the context of small-scale gold mining. I employed a framed field-lab experiment in which the miners make decisions regarding mining intensity. The state sets a collective target for an environmental outcome, verifies compliance and provides a group reward for compliance which is split equally among members. Since the target set by the state transforms the situation into a coordination game, outcomes depend on expectations of what others will do. I conducted this experiment with 640 participants in a mining region of the Colombian Pacific and I examine different levels of policy severity and their ordering. The findings of the experiment suggest that such instruments can induce compliance but this regulation involves tradeoffs. For most severe targets – with rewards just above costs – raise gains if successful but can collapse rapidly and completely. In terms of group interactions, better outcomes are found when severity initially is lower suggesting learning.

The second essay, “Collective Compliance can be Efficient and Inequitable: Impacts of Leaders among Small-Scale Gold Miners in Colombia”, explores the channels through which communication help groups to coordinate in presence of collective incentives and whether the reached solutions are equitable or not. Also in the context of small-scale gold mining in the Colombian Pacific, I test the effect of communication in compliance with a collective environmental target. The results suggest that communication, as expected, helps to solve coordination challenges but still some groups reach agreements involving unequal outcomes. By examining the agreements that took place in each group, I observe that the main coordination mechanism was the presence of leaders that help other group members to clarify the situation. Interestingly, leaders not only helped groups to reach efficiency but also played a key role in equity by defining how the costs of compliance would be distributed among group members.

The third essay, “Creating Local PES Institutions and Increasing Impacts of PES in Mexico: A real-Time Watershed-Level Framed Field Experiment on Coordination and Conditionality”, considers the creation of a local payments for ecosystem services (PES) mechanism as an assurance game that requires the coordination between two groups of participants: upstream and downstream. Based on this assurance interaction, I explore the effect of allowing peer-sanctions on upstream behavior in the functioning of the mechanism. This field-lab experiment was implemented in three real cases of the Mexican Fondos Concurrentes (matching funds) program in the states of Veracruz, Quintana Roo and Yucatan, where 240 real users and 240 real providers of hydrological services were recruited and interacted with each other in real time. The experimental results suggest that initial trust-game behaviors align with participants’ perceptions and predicts baseline giving in assurance game. For upstream providers, i.e. those who get sanctioned, the threat and the use of sanctions increase contributions. Downstream users contribute less when offered the option to sanction – as if that option signal an uncooperative upstream – then the contributions rise in line with the complementarity in payments of the assurance game.

Computer vision in aseptic pharmaceutical manufacturing: a deep learning-based approach to vial inspection and pack formation during a lyophilizer loading cycle

Vision systems are powerful tools playing an increasingly important role in modern industry, to detect errors and maintain product standards. With the enlarged availability of affordable industrial cameras, computer vision algorithms have been increasingly applied in industrial manufacturing processes monitoring. Until a few years ago, industrial computer vision applications relied only on ad-hoc algorithms designed for the specific object and acquisition setup being monitored, with a strong focus on co-designing the acquisition and processing pipeline. Deep learning has overcome these limits providing greater flexibility and faster re-configuration. In this work, the process to be inspected consists in vials’ pack formation entering a freeze-dryer, which is a common scenario in pharmaceutical active ingredient packaging lines. To ensure that the machine produces proper packs, a vision system is installed at the entrance of the freeze-dryer to detect eventual anomalies with execution times compatible with the production specifications. Other constraints come from sterility and safety standards required in pharmaceutical manufacturing. This work presents an overview about the production line, with particular focus on the vision system designed, and about all trials conducted to obtain the final performance. Transfer learning, alleviating the requirement for a large number of training data, combined with data augmentation methods, consisting in the generation of synthetic images, were used to effectively increase the performances while reducing the cost of data acquisition and annotation. The proposed vision algorithm is composed by two main subtasks, designed respectively to vials counting and discrepancy detection. The first one was trained on more than 23k vials (about 300 images) and tested on 5k more (about 75 images), whereas 60 training images and 52 testing images were used for the second one.

Architecture for machining process and production monitoring based in open computer numerical control

This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.

Static and hydrodynamic monitoring of citalopram based on its electro-oxidation behavior at a glassy-carbon surface

The electrooxidative behavior of citalopram (CTL) in aqueous media was studied by cyclic voltammetry (CV) and square-wave voltammetry (SWV) at a glassy-carbon electrode. The electrochemical behaviour of CTL involves two electrons and two protons in the irreversible and diffusion controlled oxidation of the tertiary amine group. The maximum analytical signal was obtained in a phosphate buffer (pH ¼ 8.2). For analytical purposes, an SWV method and a flow-injection analysis (FIA) system with amperometric detection were developed. The optimised SWV method showed a linear range between 1.10 10 5–1.20 10 4 molL 1, with a limit of detection (LOD) of 9.5 10 6 molL 1. Using the FIA method, a linear range between 2.00 10 6–9.00 10 5 molL 1 and an LODof 1.9 10 6 molL 1 were obtained. The validation of both methods revealed good performance characteristics confirming applicability for the quantification of CTL in several pharmaceutical products.

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Suivi de l'adhésion thérapeutique des patients hypertendus ou dyslipi- démiques par les cercles de qualité médecins-pharmaciens [Monitoring drug adherence for hypertensive and dyslipidemic patients in networks of community-based pharmacists and physicians].

Patient adherence is often poor for hypertension and dyslipidaemia. A monitoring of drug adherence might improve these risk factors control, but little is known in ambulatory care. We conducted a randomised controlled study in networks of community-based pharmacists and physicians in the canton of Fribourg to examine whether monitoring drug adherence with an electronic monitor (MEMS) would improve risk factor control among treated, but uncontrolled hypertensive and dyslipidemic patients. The results indicate that MEMS achieve a better blood pressure control and lipid profile, although its implementation requires considerable resources. The study also shows the value of collaboration between physicians and pharmacists in the field of patient adherence to improve ambulatory care of patients with cardiovascular risk factors.

Perfluoroalkylated substances in food matrices: development of mass spectrometry based analytical methods and preliminary monitoring

Perfluoroalkylated substances are a group of chemicals that have been largely employed during the last 60 years in several applications, widely spreading and accumulating in the environment due to their extreme resistance to degradation. As a consequence, they have been found also in various types of food as well as in drinking water, proving that they can easily reach humans through the diet. The available information concerning their adverse effects on health has recently increased the interest towards these contaminants and highlighted the importance of investigating all the potential sources of human exposure, among which diet was proved to be the most relevant. This need has been underlined by the European Union through Recommendation 2010/161/EU: in this document, Member States were called to monitor their presence of in food, producing accurate estimations of human exposure. The purpose of the research presented in this thesis, which is the result of a partnership between an Italian and a French laboratory, was to develop reliable tools for the analysis of these pollutants in food, to be used for generating data on potentially contaminated matrices. An efficient method based on liquid chromatography-mass spectrometry for the detection of 16 different perfluorinated compounds in milk has been validated in accordance with current European regulation guidelines (2002/657/EC) and is currently under evaluation for ISO 17025 accreditation. The proposed technique was applied to cow, powder and human breast milk samples from Italy and France to produce a preliminary monitoring on the presence of these contaminants. In accordance with the above mentioned European Recommendation, this project led also to the development of a promising technique for the quantification of some precursors of these substances in fish. This method showed extremely satisfying performances in terms of linearity and limits of detection, and will be useful for future surveys.

Research on vehicle-based driver status/performance monitoring; development, validation, and refinement of algorithms for detection of driver drowsiness.

National Highway Traffic Safety Administration, Washington, D.C.

Decision support system for inspection and maintenance:a case of oil pipelines

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is unproductive. A risk-based decision support system (DSS) that reduces the amount of time spent on inspection has been presented. The risk-based DSS uses the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of occurrence of these risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost and the cumulative effect of failure is determined through probability analysis. The model optimizes the cost of pipeline operations by reducing subjectivity in selecting a specific inspection method, identifying and prioritizing the right pipeline segment for inspection and maintenance, deriving budget allocation, providing guidance to deploy the right mix labor for inspection and maintenance, planning emergency preparation, and deriving logical insurance plan. The proposed methodology also helps derive inspection and maintenance policy for the entire pipeline system, suggest design, operational philosophy, and construction methodology for new pipelines.

Risk-based maintenance model for offshore oil and gas pipelines:a case study

Offshore oil and gas pipelines are vulnerable to environment as any leak and burst in pipelines cause oil/gas spill resulting in huge negative Impacts on marine lives. Breakdown maintenance of these pipelines is also cost-intensive and time-consuming resulting in huge tangible and intangible loss to the pipeline operators. Pipelines health monitoring and integrity analysis have been researched a lot for successful pipeline operations and risk-based maintenance model is one of the outcomes of those researches. This study develops a risk-based maintenance model using a combined multiple-criteria decision-making and weight method for offshore oil and gas pipelines in Thailand with the active participation of experienced executives. The model's effectiveness has been demonstrated through real life application on oil and gas pipelines in the Gulf of Thailand. Practical implications. Risk-based inspection and maintenance methodology is particularly important for oil pipelines system, as any failure in the system will not only affect productivity negatively but also has tremendous negative environmental impact. The proposed model helps the pipelines operators to analyze the health of pipelines dynamically, to select specific inspection and maintenance method for specific section in line with its probability and severity of failure.

Responsive fixture design using dynamic product inspection and monitoring technologies for the precision machining of large-scale aerospace parts

When machining a large-scale aerospace part, the part is normally located and clamped firmly until a set of features are machined. When the part is released, its size and shape may deform beyond the tolerance limits due to stress release. This paper presents the design of a new fixing method and flexible fixtures that would automatically respond to workpiece deformation during machining. Deformation is inspected and monitored on-line, and part location and orientation can be adjusted timely to ensure follow-up operations are carried out under low stress and with respect to the related datum defined in the design models.

Comparative analysis of the relationship between phenological phenomena and meteorological indicators based on insect and plant monitoring

Climate change is one of the biggest environmental problems of the 21st century. The most sensitive indicators of the effects of the climatic changes are phenological processes of the biota. The effects of climate change which were observed the earliest are the remarkable changes in the phenology (i.e. the timing of the phenophases) of the plants and animals, which have been systematically monitored later. In our research we searched for the answer: which meteorological factors show the strongest statistical relationships with phenological phenomena based on some chosen plant and insect species (in case of which large phenological databases are available). Our study was based on two large databases: one of them is the Lepidoptera database of the Hungarian Plant Protection and Forestry Light Trap Network, the other one is the Geophytes Phenology Database of the Botanical Garden of Eötvös Loránd University. In the case of butterflies, statistically defined phenological dates were determined based on the daily collection data, while in the case of plants, observation data on blooming were available. The same meteorological indicators were applied for both groups in our study. On the basis of the data series, analyses of correlation were carried out and a new indicator, the so-called G index was introduced, summing up the number of correlations which were found to be significant on the different levels of significance. In our present study we compare the significant meteorological factors and analyse the differences based on the correlation data on plants and butterflies. Data on butterflies are much more varied regarding the effectiveness of the meteorological factors.