The objective of this study is to propose an approach that assists facility managers in obtaining the needed information to establish a proactive roof maintenance plan. Two main methodologies are used in this research. The first approach, Historical Maintenance Data Analysis (HMDA), investigates and pinpoints the root cause of roof leaks by thoroughly collecting and analyzing roof maintenance records. HMDA hypothesizes that a mathematical model can be developed to reveal relationships between potential roof leak causes and leak incidences. The second approach, Roof Service Life Prediction (RSLP), investigates the applicability of the Factor Method in roof maintenance. The use of RSLP for leak predictions is based on the assumption that the first-time leak has a linear relationship with the estimated service life (ESL) of the roof. This research demonstrates that roof maintenance records can be used to predict and identify major factors that are likely causes of roof leaks in a mathematical causal model. Roof leaks are not totally random events and can be predicted. In this study, three parameters (Age, Workmanship, and Roof Repair) have a significant impact on the roof leaks probability within the first three years of a roof life. A unit change of workmanship and roofs age increases the odds of a roof leak. On the other hand, changes in roof repair decrease the odds of a roof leak. The Factor Method performed in the RSLP confirms the existence of a relationship between the ESL and the first-time leak. The correlations discovered are positive and significant to highly significant. The extents of correlation are found to be low to medium. The finding also illustrates a relatively simple and useful factor method technique that can be applied to the roof maintenance decision-making process. The estimated service life of a roof provides a reasonable estimation of a maintenance-free period. When ESL information is used in conjunction with knowledge obtained from HMDA, the new synthesis of knowledge will expand the facility maintenance professionals ability to develop and schedule a proactive roof maintenance plan.

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This thesis describes an investigation of the possibility to apply a maintenance concept originally developed for the industry, on software maintenance. Today a large amount of software development models exist but not many of them treat maintenance as a part of the software life cycle. In most cases maintenance is depicted as an activity towards the end of the software life cycle. The high cost ascribed to software maintenance motivates for improvements. The maintenance concept TQMain proposed in this thesis distinguishes from other maintenance concepts by its use of preventive, predictive and proactive maintenance strategies. TQMain uses a common database to store real-time data from various departments and uses it for analyse and assessment to track the development of deviations in the condition of the production process and product quality at an early stage. A continuous cyclic improvement of the maintenance strategy is reached by comparing the data from the real-time measurements with data from the database. The ISO/IEC Software engineering – Product qualities is used as a source of empiric data to conclude that the correct quality characteristics are used for identifying software product quality and its characteristics and compare them with the characteristics of industrial product quality. The results presented are that in the conceptual outline of TQMain measures are obviously not the same as in software maintenance, but the aspect of product quality is common for both. The continuous cyclic improvement of the product quality that TQMain features together with the aspect of detecting potential failures before they occur would, judging from the conceptual outline of TQMain be applicable on software maintenance.

A MCC (Manutenção Centrada em Confiabilidade) é uma metodologia criada na década de 50, que visa a melhoria no gerenciamento e planejamento da manutenção, focando nos componentes críticos, e com adoção de elementos de confiabilidade. A bibliografia utilizada neste estudo aponta inúmeros benefícios, comprovando a sua eficácia, como: o aumento da disponibilidade operacional, redução do tempo de intervenção, redução dos custos operacionais de manutenção, maior previsibilidade nas tarefas, e por fim, maior confiabilidade dos equipamentos. A indústria da construção civil, possuindo equipamentos de grande porte e de custos operacionais relativamente altos, e ainda com o agravante de serem móveis, necessita de um modelo de manutenção de alto nível, visando maior confiabilidade operacional para assegurar disponibilidade. Com isso, a adoção de uma metodologia que visa a preservação do ativo, como a MCC, passa a ser uma grande aliada de uma produção de alto valor e lucratividade. O presente trabalho apresenta uma análise da viabilidade da implementação da metodologia MCC no gerenciamento da manutenção de equipamentos móveis, de uma empresa de construção civil. A nova metodologia trouxe à manutenção da empresa um novo panorama para com planejamento de suas atividades de manutenção, e por reflexo a produção. A implantação desta contou com a sistemática de implantação tradicional, porém utilizando o SIGM para elencar os dados de manutenção, sob seu histórico, e em conjunto com brainstorming, para priorização e apuração das falhas e modos de falhas. A MCC possibilitou a reformulação de planos de manutenção já existentes, a elaboração de novos planos preditivos e preventivos, e a alteração de periodicidades de planos preventivos sendo para estes, reduzidos em 1000 l consumidos, o intervalo entre estas intervenções. / The RCM (Reliability Centered Maintenance) is a methodology created in the 50s, to improve the management and maintenance planning, focusing on critical components, and adoption of reliability elements. The bibliography indicates numerous benefits, proving its effectiveness, as increased operational availability, reduced intervention time, reduce operating costs of maintenance, greater predictability in the tasks, and finally, reliability. The construction industry, having operating large equipment and costs relatively high, and with the aggravation of being mobile, you need a high-level maintenance model, seeking greater operational reliability. The adoption of a methodology aimed at the preservation of assets, with a focus on reliability. This paper analysis of the viability of implementation the RCM method in managing the maintenance of mobile equipment, in a construction company. The new methodology brought to the company maintaining a new outlook towards planning their maintenance activities, and reflective production. The implementation of this included the systematic traditional deployment, but using CMMS to list the maintenance data, in its history, and in conjunction with brainstorming, prioritization and for investigation of failures and failure modes. The RCM enabled the redesign of existing maintenance plans, the development of new predictive and preventive plans, and changing periodicities preventive plans -For these being , reduced in 1000 l consumed , the interval between these operations.

This work examines possible safety risks associated with the operation of IIoT technologies in industrial production. The content of this document is an analysis of used IIoT technologies, their purpose and method of implementation into production processes and the company's technology strategy. The outcome of this analysis will serve to develop possible risk scenarios and their associated impacts. Finally, I recommend possible changes that either eliminate these risks completely or at least minimize them.

Intresset för elkvalitet har ökat då elektrisk utrustning, såsom omriktare, numera ger upphov till mer störningar. Elektrisk utrustning har också blivit mer känslig mot störningar samtidigt som industrier har blivit mindre toleranta mot produktionsstörningar. Traditionellt har felhantering i elnät skett när problemet redan uppstått och utgått från historiska data. Metrum har dock genom sin applikation PQ4Cast introducerat mönsterigenkänning för att prognosticera elkvalitetsparametrar samt aktiv effekt och i och med det bidra till ett proaktivt underhåll. Applikationen skapar en prognos för kommande vecka utifrån data för de senaste veckorna, under utveckling är även en funktion för trendanalys av bland annat effektförbrukning och spänningsnivå. Syftet med implementeringen av PQ4Cast är att få en högre tillgänglighet och minimera kostnader för underhåll och oplanerade avbrott. Ett andra syfte är att skapa ökad kontroll över variationer i effektuttag. Målet med detta examensarbete är att avgöra vilka avvikelser som är viktiga för Sandvik att ha kontroll över, ta fram metoder för att utvärdera applikationens funktionalitet samt ge underlag till hur prognoser från applikationen bör hanteras. Utöver det ska även nyttan med funktionen för trendanalys avgöras. Sandvik ser störst nytta med att få kontroll över framtida värden för aktiv effekt, reaktiv effekt samt variationer i spänningens effektivvärde. Av dessa borde variationer i aktiv samt reaktiv effekt vara mest lämpad för PQ4Cast att identifiera. För undersökning av överensstämmelse mellan prognos och verkligt utfall rekommenderas användning av korrelationskoefficient, determinationskoefficient samt signifikansnivå på fem procent. Användning av MAPE, Mean Absolute Percentage Error, rekommenderas också att användas för att kvantifiera prognosfelet. Vid god överensstämmelse rekommenderas prognoserna för aktiv effekt från PQ4Cast användas för veckoprognos till elhandelsbolaget Statkraft i kombination med temperaturprognos samt prognos över produktion kommande veckan. Trendanalysfunktionen visar ett medelfel med några procent för den aktiva effekten. Ytterligare undersökningar av funktionen rekommenderas och vid god överensstämmelse rekommenderas denna användas som grund för prognoser som ges till Statkraft samt används som grund för nytt effektavtal med Vattenfall i kombination med produktionsprognos. För analys av trend för spänningens effektivvärde är avvikelsen från prognosvärdet endast några tiondels procent och här rekommenderas fortsatta undersökningar och då specifikt vid del i nätet där installation av solcellsanläggning planeras. Applikationen PQ4Cast samt trendanalysfunktionen förväntas kunna leda till ekonomiska fördelar i form av minskade kostnader för inköp av el samt minskade elnätsavgifter och även betydande besparingar om störningar som kan leda till avbrott kan upptäckas i tid och avstyras. Kortvariga störningar, såsom spänningsdippar, är dock svåra för PQ4Cast att upptäcka i dagsläget. / Interest in power quality has increased as electrical equipment, such as inverters, nowadays emits more disturbances. Electrical equipment has also become less tolerant to disturbances, while industries have become less tolerant to disturbances in the production. Traditionally, fault diagnosis and handling have been performed when the fault has already arisen and has been based on historical data. Through its application PQ4Cast, Metrum have introduced pattern recognition to forecast power quality parameters and active power, and thereby contribute to proactive maintenance. The application creates a forecast for the coming week based on data for the last few weeks. Under development is also a function for trend analysis of, among other things, power consumption and voltage level. The objective with the implementation of PQ4Cast is to achieve higher availability and minimize costs for maintenance and unplanned interruptions. A second objective is to increase the control over variations in power consumption. The aim of this thesis is to determine which deviations are important for Sandvik, develop methods for evaluating the application’s functionality and provide a basis for how forecasts from the application should be managed. The aim is also to determine the usefulness of the trend analysis function. For Sandvik, the greatest benefit is seen in gaining control over future values for active power, reactive power and variations in the RMS value of the voltage. Of these, variations in active and reactive power should be most suitable for PQ4Cast to identify. For examination of the conformity between prognosis and actual outcome, the use of correlation coefficient, determination coefficient and significance level of five percent is recommended. Use of MAPE, Mean Absolute Percentage Error, is also recommended to quantify the forecast error. In the event of good conformity, the forecasts for active power from PQ4Cast are recommended for weekly forecasts to the electricity trading company, Statkraft, in combination with temperature forecasts and forecasts of production following week. The trend analysis function shows MAPE at a few percent for the active effect. Further investigations of the function are recommended and in case of good conformity, the prognosis is recommended as the basis for forecasts given to Statkraft and as the basis for new power agreements with Vattenfall in combination with production forecast. For analysis of the trend for the voltage's RMS value, the deviation from the forecasted value is only a few tenths of a percentage. Here further studies are recommended and then specifically at area in the grid where installation of solar power is planned. The application PQ4Cast and the trend analysis function are expected to lead to economic benefits, such as reduced costs for purchase of electricity, reduced electricity grid charges and significant savings if disturbances that may lead to interruptions can be detected and prevented. Disturbances of short duration, such as voltage dips, are however hard to detect with the current setup of the application.

This master thesis deals with position of the maintenance in the company structure and with modern management approaches. One of the highest levels of maintenance is the proactive maintenance, which is using the technical diagnostics to find out the causes of failures. The most inportant in case of machines are vibrodiagnostics and thermodiagnostics, which are going to be applied on the motors in company Bosch Diesel s.r.o.

Master‘s thesis deals with maintenance and related technical diagnostics of machine tools. Diagnostics methods on which is the thesis focused are vibrodiagnostics, tribodiagnostics and electrodiagnostics. Work includes design of diagnostic system and measurement of vibration and electrical parameters of the machining center. Based on given results from data evaluation, further steps in predictive maintenance and usage of technical diagnostics for machine tools are recommended. Within tribotechnical diagnostics, the thesis is based on evaluation of long-term monitoring of process liquid status, which was used in several machining machines. A procedure for the measurement of selected parameters is proposed and periodical liquid status checks are established.

This diploma thesis deals with the maintenance and diagnostic failure conditions for machine tools. It is focused on the selection of appropriate methods of technical diagnostic state for machine tools in company SMC Vyškov. As part of the system design and proactive maintenance measurement methodology machine tools.

The railway system is an important part of the sociotechnical society, as it enables efficient, reliable, and sustainable transportation of both people and goods. Despite increasing investments, the Swedish railway has encountered structural and technical problems due to worn-out infrastructure as a result of insufficient maintenance. Two important technical aspects of the rail are the stability and robustness. To prevent transversal and longitudinal deviations, the rail is attached to sleepers by fasteners. The fasteners’ conditions are therefore crucial for the stability of the track and the safeness of the railway. Automatic fastener inspections enable efficient and objective inspections which are a prerequisite for a more adequate maintenance of the railway. This master thesis aims to investigate how machine learning can be applied to the problem of automatic fastener fault detection. The master thesis includes the complete process of applying and evaluating machine learning algorithms to the given problem, including data gathering, data preprocessing, model training, and model evaluation. The chosen model was the state-of-the-art object detector YOLOv5s. To assess the model’s performance and robustness to the given problem, different settings regarding both the dataset and the model’s architecture in terms of transfer learning and hyperparameters were tested.  The results indicate that YOLOv5s is an appropriate machine learning algorithm for fastener fault detection. The models that achieved the highest performance reached an mAP[0.5:0.95] above 0.744 during training and 0.692 during testing. Furthermore, several combinations of different settings had a positive effect on the different models’ performances.  In conclusion, YOLOv5s is in general a suitable model for detecting fasteners. By closer analysis of the result, the models failed when both fasteners and missing fasteners were partly visible in the lower and upper parts of the image. These cases were not annotated in the dataset and therefore resulted in misclassification. In production, the cropped fasteners can be reduced by accurately synchronizing the frequency of capturing data with the distance between the sleepers, in such a way that only one sleeper and corresponding fasteners are visible per image leading to more accurate results. To conclude, machine learning can be applied as an effective and robust technique to the problem of automatic fastener fault detection.