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41	Robot Condition Monitoring and Production Simulation Karlsson, Martin, Hörnqvist, Fredrik January 2018 (has links) The automated industry is in a growing phase and the human tasks is increasingly replaced by robots and other automation solutions. The increasing industry entails that the automations must be reliable and condition monitoring plays an important role in achieving that ambition. By utilizing condition monitoring of a machine it is possible to detect a wear before it turns into a critical damage that could result in complete failure. A useful tool when monitoring the condition of a machine is by sampling and analyzing vibrations. Vibrations are generated by the moving parts of the machinery and high amplitude vibrations can often be seen as an indication of the developed faults. The frequency of these vibrations can be calculated and then detected in the sampled data. Today there is no condition monitoring system that monitor industrial robots by analyzing vibrations. The problem with analyzing robots, is that they operate with a varying speed. Since the running conditions are changing rapidly all the time, this means that the vibration frequencies also changes constantly. This is due to the fact that the vibration frequencies are dependent and affected of the operation speed. This research is a sequel and continuation of a research from previous year. The purpose of the research is to investigate the possibility to monitor the condition of a gearbox in a industrial robot, by utilizing vibration analysis. The robot that has been tested under tuff conditions in order to reach a failure, is an ABB IRB 6600. To sample data in a stationary way even tough the speed is changing during the sample time, the method order tracking has been utilized. This makes it possible to sample data with numbers of measurement per rotation instead of sampling according to time. This is processed by SKF:s condition monitoring system multilog IMx and the signal is then presented as a time waveform in the software @ptitude Observer. In Observer, it is also possible to show the signal in a spectrum by using Fast Fourier Transform. By utilizing MATLAB, the research has also resulted in a new analyzing method. This method is called Spectral Auto-Correlation. The methodology of this practice is to correlated the time waveform with itself in order to see which frequencies that are reappearing. The correlated result is then calculated with a Fast Fourier Transform to illustrate the signal in a spectrum for further analysis. During the analysis of the parts in the gearbox, critical defects were found on both the cycloidal disks. The fault frequency for the defects were calculated and analyzed from the data. This resulted in trends where the amplitude from the fault frequency had more than doubled over the time the robot has been operating in the project. This report also include a production simulation where a robot cell from SKF is simulated. The robot cell is simulated with and without a condition monitoring system. A comparison was then made to see what advantages there were with utilizing a condition monitoring system. The result of the simulation was an increased productivity with two to three percent. Other Mechanical Engineering Annan maskinteknik
42	Dopamine Receptor Supersensitivity Kostrzewa, Richard M. 01 January 1995 (has links) Dopamine (DA) receptor supersensitivity refers to the phenomenon of an enhanced physiological, behavioral or biochemical response to a DA agonist. Literature related to ontogenetic aspects of this process was reviewed. Neonatal 6-hydroxydopamine (6-OHDA) destruction of rat brain DA neurons produces overt sensitization to D1 agonist-induced oral activity, overt sensitization of some D2 agonist-induced stereotyped behaviors and latent sensitization of D1 agonist-induced locomotor and some stereotyped behaviors. This last process is unmasked by repeated treatments with D1 (homologous "priming") or D2 (heterologous "priming") agonists. A serotonin (5-HT) neurotoxin (5,7-dihydroxytryptamine) and 5-HT2C receptor antagonist (mianserin) attenuate some enhanced behavioral effects of D1 agonists, indicating that 5-HT neurochemical systems influence D1 receptor sensitization. Unlike the relative absence of change in brain D1 receptor number, DA D2 receptor proliferation accompanies D2 sensitization in neonatal 6-OHDA-lesioned rats. Robust D2 receptor supersensitization can also be induced in intact rats by repeated treatments in ontogeny with the D2 agonist quinpirole. In these rats quinpirole treatments produce vertical jumping at 3-5 wk after birth and subsequent enhanced quinpirole-induced antinociception and yawning. The latter is thought to represent D3 receptor sensitization. Except for enhanced D1 agonist-induced expression of c-fos, there are no changes in the receptor or receptor-mediated processes which account for receptor sensitization. Adaptive mechanisms by multiple "in series" neurons with different neurotransmitters may account for the phenomenon known as receptor supersensitivity. 6-Hydroxydopamine adenylyl cyclase Dopamine D receptor 1 Dopamine D receptor 2 Dopamine D receptor 3 locomotion muscarinic receptors ontogeny oral activity priming quinpirole serotonin 5-HT receptor 2C SKF 38393 stereotypies supersensitization yawning Biomedical Sciences
43	Unmasking the Invisible Hand : German perspectives and processes of foreign trade Aryanisation in Sweden, 1936-1945 Lecuit, Tom January 2024 (has links) This paper explores the mechanisms and processes within the German foreign trade Aryanisation project in Sweden from the mid-1930s to 1945. Aryanisation as a concept has, similarly to the Holocaust and National Socialism before it, for the longest time been seen as a uniquely German affair. While that situation has greatly changed when it comes to the Holocaust, Fascism and National Socialism, Aryanisation is still defined as a German affair affecting only Jews in Germany even by the US Holocaust museum’s Holocaust encyclopaedia.1 As a result, research into Aryanisation efforts in Nazi Germany’s foreign trade sector has been relatively sparse. Drawing on the small existing body of research that was sparked by Swedish historian Sven Nordlund, this paper seeks to complete the picture of the German trade Aryanisation campaign in Sweden by examining its inner workings on the German side of affairs. The study is framed within an elastic interpretation of the rationality v ideology binary and further tied to Holocaust research by highlighting characteristic elements of modernity, bureaucracy and artificiality in how NS ideology crept its way into every aspect of life, even trade with a neutral country. Through a thorough analysis of a large body of associated correspondence and official documents, this study uncovers the complex and evolving picture of German perspectives and processes within its project to shape its trade relations to Sweden according to Nazi ideas. Aryanisation Foreign trade Holocaust Nazi Germany Sweden World War II international relations ideology economic rationality intelligence networks discrimination screening SKF ball bearing trade History Historia Economic History Ekonomisk historia
44	Fallstudie om Prediktivt och Tillståndsbaserat Underhåll inom Läkemedelsindustrin / Case study regarding Predictive and Condition-based Maintenance in the Pharmaceutical Industry Redzovic, Numan, Malki, Anton January 2022 (has links) Underhåll är en aktivitet som varje produktion vill undvika så mycket som möjligt på grund av kostnaderna och tiden som anknyts till den. Trots detta så är en väl fungerande underhållsverksamhet väsentlig för att främja produktionens funktionssäkerhet och tillgänglighet att tillverka. En effektiv underhållsorganisation går däremot inte ut på att genomföra mer underhåll än vad som egentligen är nödvändigt utan att genomföra underhåll i rätt tid. På traditionellt sätt så genomförs detta genom att ersätta slitage delar och serva utrustningen med fastställda mellanrum för att förebygga att haveri, vilket kallas för förebyggande underhåll. De tidsintervaller som angivits för service bestäms av leverantörerna och grundar sig i en generell uppskattning av slitagedelarnas livslängd utifrån tester och analys. Till skillnad från att köra utrustningen till den går sönder som kallas för Avhjälpande underhåll så kan underhåll genomföras vid lämpliga tider så att det inte påverkar produktion och tillgänglighet. Men de tidsintervall som leverantörerna rekommenderar till företagen garanterar inte att slitage delen håller sig till det intervallet, delarna kan exempelvis rasa tidigare än angivet eller till och med hålla längre. Av denna anledning är det naturliga steget i underhållets utveckling att kunna övervaka utrustningens hälsa i hopp om att kunna förutspå när och varför ett haveri ska uppstå. Den här typen av underhåll kallas för tillståndsbaserat och prediktivt underhåll och medför ultimat tillgänglighet av utrustning och den mest kostnadseffektiva underhållsorganisationen, då god framförhållning och översikt uppnås för att enbart genomföra underhåll när det behövs. Det som gör tillståndsbaserat och prediktivt underhåll möjligt är den fjärde industriella revolutionen “Industri 4.0” och teknologierna som associeras med den som går ut på absolut digitalisering av produktionen och smarta fabriker. Teknologier som IoT, Big Dataanalys och Artificiell Intelligens används för att koppla upp utrustning till nätet med hjälp av givare för att samla in och lagra data som ska användas i analyser för att prognosera dess livslängd. Uppdragsgivaren AstraZeneca i Södertälje tillverkar olika typer av läkemedel som många är livsviktiga för de patienter som tar dessa mediciner. Om AstraZenecas produktion står still på grund av fel i utrustningen kommer det inte enbart medföra stora ekonomiska konsekvenser utan även påverka de människor som med livet förlitar sig på den medicin som levereras. För att försäkra produktionens tillgänglighet har AstraZeneca gjort försök att tillämpa tillståndsbaserat och prediktivt underhåll men det är fortfarande enbart i startgroparna. Eftersom ventilation är kritisk del av AstraZeneca produktion då ett fel i ventilationssystemet resulterar i totalt produktionsstopp i byggnaden förens problemet åtgärdas och anläggningen sanerats blev det även rapportens fokusområde. Arbetets uppgift går därför ut på att undersöka möjligheter för AstraZeneca att utveckla deras prediktiva och tillståndsbaserat underhåll på deras ventilationssystem, för att sedan kunna identifiera och presentera förslag på åtgärder. Dessa förslag analyserades sedan med hjälp av verktygen QFD-Matris och Pugh-Matris för att kunna uppskatta vilket förslag som är mest kostnadseffektivt, funktions effektivt samt vilket förslag som kommer tillföra mest nytta för underhållet på AstraZeneca. / Maintenance is an activity that every production wants to avoid as much as possible due to the costs and the time associated with it. Despite this, a well-functioning maintenance operation is essential to promote the production's availability to manufacture and operational reliability. Running an efficient maintenance operation is not about carrying out more maintenance than is necessary but carrying out the right amount of maintenance at the right time. Traditionally speaking this is done by replacing worn parts and servicing the equipment at set intervals to prevent breakdowns, this method is called preventive maintenance. The intervals specified for service are determined by the suppliers and are based on general estimates of the service life for the spare parts from test and analytics. Preventive maintenance allows for maintenance to be carried out at appropriate time to not affect production and availability unlike running the equipment until breakdown, which is called reactive maintenance. However, these intervals that the suppliers recommend do not guarantee that the parts adhere to the given interval, the part can for example break down earlier than expected or even outlast its prescribed lifetime. Because of this, the natural step in the development of maintenance is giving companies the ability to monitor the health of the equipment in hope of being able to predict potential breakdowns. This is what Condition-Based and predictive maintenance is and it provides the ultimate availability of equipment and the most cost-effective maintenance organization, because the good foresight and overview allows maintenance to be carried out only when needed. The fourth industrial revolution “Industry 4.0”, absolute digitalization of production, smart factories and all the technologies associated with this is what makes this type of maintenance possible. Technologies such as IoT, Big Data Analytics and Artificial Intelligence are used to connect equipment to the network using sensors so that data can be stored and collected to be analyzed to forecast the lifespan of parts and equipment. AstraZeneca in Södertälje manufactures different types of medicine, many of which are vital for the patients who take them. If their production comes to a standstill due to equipment failure, it will not only have major financial consequences but also greatly affect the people who rely on the medicine offered with their lives. To ensure the availability of production, AstraZeneca has made attempts to apply condition-based and predictive maintenance, but it is still only in its infancy. Since ventilation is a critical part of AstraZeneca's production, as a failure here will result in a total production stoppage for the building affected and will not resume before the problem is remedied and the plant is decontaminated, it also became the report's focus area. The task at hand is therefore to investigate the opportunities AstraZeneca must develop their predictive and condition-based maintenance for their ventilation systems, in order to be able to present proposals for measures. The proposals will then be analyzed using tools like the QFD-Matrix and the Pugh-Matrix in order to estimate which is more cost effective, function effective and which one will bring the most benefit to AstraZeneca. Reactive Maintenance Preventive Maintenance Condition-based Maintenance Predictive Maintenance Industry 4.0 Internet of Things Simulation Big Data Big Data Analytics Digital Twin Artificial Intelligence Cloud Storage Maintenance systems CMMS ERP systems EAM systems SAP IBM Maximo SKF SPM Instruments Sensors Analytics Ventilations Systems Shock pulse sensor Vibration sensor. Avhjälpande Underhåll Förebyggande Underhåll Tillståndsbaserat underhåll Prediktiv underhåll Industri 4.0 Internet of Things Simulation Big Data Big Data Analys Digital Tvilling Artificiell Intelligens Molnlagring Cybersäkerhet Underhållssystem CMMS ERP system EAM system SAP IBM Maximo SKF SPM Instruments Sensorer Analys Ventilationssystem Stöt Pulsgivare Vibrationsgivare. Engineering and Technology Teknik och teknologier
45	Railway curve squeal: Statistical analysis of train speed impact on squeal noise Asplund, Ruben January 2024 (has links) No description available. ml operation maintenance railway maintenance railway curve machine learning statistics railway train passenger train x60 squeal noise curve squeal squealing noise squeal wheel squeal squealing programming system development computer engineering data visualization data preprocessing industrial computer systems matlab python vibration vibrations vibration signals signals and systems filtering signal processing computer systems communication system infrastructure technology infrastructure track t-test z-test random forest xgboost feature importance speed detection band-pass filter script yaw angle angle of attack decision tree gbdt filter temperature humidity dew point curve radius cloud accelerometers sensors track rail statistical analysis acoustics sound ai artificial intelligence gradient boosting decision trees curve software development drift underhåll järnvägsunderhåll järnvägskurva maskininlärning statistik järnväg tåg x60 skrikljud snäva kurvor kurvradie kurvskrik hjulskrik programmering systemutveckling datateknik data industriella datorsystem matlab python vibration signaler vibrations signaler signaler och system filtrering signalbehandling datorsystem kommunikationssystem infrastrukturteknik infrastruktur spår t-test z-test random forest Södertälje band-pass filter hastighets detektion attackvinkeln anfallsvinkel IMx SKF temperatur fuktighet daggpunkt accelerometer järnvägskurvskrik tåg hastighetens statistisk analys akustik ljud ai kurva kurvor mjukvaruutveckling artificiell intelligens Infrastructure Engineering Infrastrukturteknik Signal Processing Signalbehandling Communication Systems Kommunikationssystem Computer Systems Datorsystem

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