Cette thèse présente un couplage thermodynamique pour une modélisation approfondie du processus de soudure par ultrasons, surtout la soudure des thermoplastiques. Il s’agit de bien connaître le mode de fonctionnement des ensembles acoustiques réalisant la soudure ainsi que le comportement des matériaux à souder. En conséquence, les propriétés de ces matériaux, surtout celles nécessaires pour la modélisation par éléments finis, sont identifiées. Les paramètres mécaniques et thermiques sont mesurés en statique et ils sont comparés avec les résultats calcules par homogénéisation. Certains sont déterminés en dynamique, selon la fréquence et aussi en fonction de la température. Ceci est très utile parce que les matériaux travaillent à haute fréquence ultrasonique et que la température lors de la soudure change fortement. La machine de soudage par ultrasons (l’ensemble acoustique) a déjà été conçue et fabriquée. La modélisation EF en 3D avec Abaqus nous montre bien ses comportements modaux et vibratoires. Ensuite, les matériaux à souder sont introduits en modélisants le contact dynamique entre l’ensemble acoustique et la bande à souder. Ce modèle nous permet de déterminer le temps de contact et la compression dans les matériaux en fonction de la force de maintien. La dissipation d’énergie qui est engendrée par viscosité des matériaux à souder est calculée et introduite dans le modèle couplé thermomécanique. Le transfert de chaleur dans tout l’ensemble lors de la soudure est modélisé et il montre le champ de température, surtout la température à l’interface entre deux couches de matériaux. Cette modélisation est complétée en utilisant la méthode ALE (Arbitrary Lagrangian Eulerian) afin de tenir compte du mouvement d’avancement des bandes à souder / This thesis presents a thermomechanical coupling for advanced modeling of welding processes, especially the ultrasonic welding for thermoplastic materials. The mode of operation of welding machines and the behaviour of welding materials must be well known. Consequently, the properties of these materials, especially those required for finite element modelling, are identified. The mechanical and thermal parameters are measured in static mode and are compared with results calculated by homogenization. Some parameters are also measured dynamically and show a dependency on frequency and temperature. This is very useful because the materials are solicited at high ultrasonic frequency and the temperature during the welding changes significantly. The welding ultrasonic machine (the acoustic ensemble) has already been designed and manufactured. The modelling by finite element in 3D with ABAQUS shows good modal and vibration behaviours. Then, the welding materials are introduced by modelling the dynamic contact between the acoustic ensemble and welding band. This model allows us to determine the contact duration and the compression in the materials depending on the applied load. The dissipation of energy that is generated by viscosity of welding materials is calculated and included in the thermomechanical coupled model. The heat transfer in the whole system is modeled and enable to compute the temperature field, especially the temperature at the interface between two layers of welding materials. This model is completed using the ALE (Arbitrary Lagrangian Eulerian) method to take into account the displacement of the welding bands

Simulations of particle systems at constant temperature may be used to estimate several of the system’s physical properties, and some require integration over very long time to be accurate. To achieve sufficient accuracy in finite time the choice of numerical scheme is important and we suggest to use the symplectic Euler method combined with a step in an Ornstein-Uhlenbeck process. This scheme is computationally very cheap and is often used in applications of molecular dynamics. This thesis strives to motivate the usage of the scheme due to the lack of theoretical results and comparisons to alternative methods. We conduct three numerical experiments to evaluate the scheme. The design of each experiment aims to expose weaknesses or strengths of the method. For both model problems and more realistic experiments are the results positive in favor of the method; the symplectic Euler method combined with an Ornstein- Uhlenbeck step does perform well over long times. / Simuleringar av partikelsystem vid konstant temperatur kan användas för att uppskatta flera av systemets fysiska egenskaper. Vissa klasser av egenskaper kräver integration över väldigt lång tid för att uppnå hög noggrannhet och för att uppnå detta i ändlig tid är valet av numerisk metod viktigt. Vi föreslår att använda den symplektiska Euler-metoden i kombination med ett implicit steg i en Ornstein-Uhlenbeck-process. Detta stegschema kräver låg beräkning jämfört med andra scheman och används redan i olika applikationer av molekyldynamik. Detta examensarbete eftersträvar att än mer motivera användandet av schemat, eftersom teoretiska resultat som stödjer metoder är få, och avsaknaden av tidigare liknande studier är betydlig. Vi genomför tre numeriska experiment för att pröva schemat. Under utformningen av experimenten har vi försökt att inkorporera olika fenomen som kan orsaka svårigheter för metoden för att exponera svagheter eller styrkor hos den. För båda modellproblem och för ett mer realistiskt experiment är resultaten positiva till schemats fördel; metoden att kombinera ett symplektisk Euler-steg med ett steg i Ornstein-Uhlenbeck-processen presterar bra över lång tid.

[ES] La revolución estética que ha visto el siglo XX, donde surgieron multitud de propuestas, llegó de forma dispar a las distintas formaciones instrumentales. Mientras la música sinfónica y de cámara vivió un renacer auspiciado por las nuevas técnicas compositivas, la orquesta de vientos quedó estancada en un aparente contexto de tonalidad y modalidad que, lejos de evolucionar a la par que las otras formaciones, ha experimentado un aparente retroceso hacia posturas estéticas más conservadoras. El presente trabajo surge de la necesidad de evolucionar el repertorio actual para orquesta de vientos, profundizando en sus posibilidades tímbricas y desarrollando un repertorio que aborda la composición para orquesta de vientos, desde una perspectiva actual que desarrolle algunas de las corrientes estéticas principales de la vanguardia musical de los siglos XX y XXI. A continuación, se elabora un análisis detallado de los procesos compositivos abordados en cada una de las obras a estudio, sin perder la perspectiva del objetivo fundamental; la composición de dos obras que desarrollen el potencial sonoro de la formación orquestal de vientos y percusión dentro de un estilo contemporáneo. Previamente, se exponen algunas de las aportaciones más importantes al género realizadas por distintos compositores, que han supuesto una vinculación real y significativa de las nuevas propuestas compositivas de los siglos XX y XXI con la formación de vientos en su concreción orquestal o de gran ensemble. Se destacan especialmente aquellas propuestas de autores relacionados estrechamente con el repertorio de vientos, especialmente en su vertiente bandística. Paralelamente se referencian otros trabajos de autores significativos dentro del repertorio orquestal y camerístico, que han realizado contribuciones esporádicas a la orquesta/ensemble de vientos. Contribuciones que por su originalidad o estilo enmarcado en las corrientes estéticas compositivas de los siglos XX y XXI, implican un hecho destacado para el género de vientos y percusión. / [EN] The aesthetic revolution that the twentieth century has seen, where a multitude of proposals arose, reached the different instrumental groups in a disparate way. While symphonic and chamber music lived a rebirth sponsored by new compositional techniques, the wind orchestra was stuck in an apparent context of tonality and modality that, far from evolving at the same time as the other formations, has experienced an apparent retreat towards postures more conservative aesthetics. The present work arises from the need to evolve the current repertoire for wind orchestra, deepening its timbral possibilities and developing a repertoire that addresses composition for wind orchestra, from a current perspective that develops some of the main aesthetic currents of the avant-garde musical of the twentieth and twenty-first centuries. Next, a detailed analysis of the compositional processes addressed in each of the works under study is elaborated, without losing the perspective of the fundamental objective; the composition of two works that develop the sound potential of the orchestral wind and percussion formation within a contemporary style. Previously, some of the most important contributions to the genre made by different composers are exposed, which have meant a real and significant connection of the new compositional proposals of the 20th and 21st centuries with the formation of winds in their orchestral or large ensemble concretion. Especially noteworthy are those proposals by authors closely related to the wind repertoire, especially in its band aspect. At the same time, other works by significant authors within the orchestral and chamber repertoire are referenced, who have made sporadic contributions to the wind orchestra / ensemble. Contributions that for their originality or style framed in the aesthetic compositional currents of the XX and XXI, imply an outstanding fact for the wind and percussion genre. / [CA] La revolució estetica que ha vist el segle XX, on van sorgir multitud de propostes, va arribar de manera dispar a les diferents formacions instrumentals. Mentre la música simfonica i de cambra va viure un renaixement afavorit per les noves tecniques compositives, l'orquestra de vents va quedar estancada en un aparent context de tonalitat i modalitat que, lluny d'evolucionar al mateix temps que les altres formacions, ha experimentat un aparent retrocés cap a postures estetiques més conservadores. El present treball sorgeix de la necessitat d'evolucionar el repertori actual per a orquestra de vents, aprofundint en les seves possibilitats tímbriques i desenvolupant un repertori que aborda la composició per a orquestra de vents, des d'una perspectiva actual que desenvolupi alguns dels corrents estetiques principals de l'avantguarda musical dels segles XX i XXI. A continuació, s'elabora una analisi detallada dels processos compositius abordats en cadascuna de les obres a estudi, sense perdre la perspectiva de l'objectiu fonamental; la composició de dues obres que desenvolupin el potencial sonor de la formació orquestral de vents i percussió dins d'un estil contemporani. Previament, s'exposen algunes de les aportacions més importants al genere realitzades per diferents compositors, que han suposat una vinculació real i significativa de les noves propostes compositives dels segles XX i XXI amb la formació de vents en la seva concreció orquestral o de gran ensemble. Es destaquen especialment aquelles propostes d'autors relacionats estretament amb el repertori de vents, especialment en la seva vessant bandística. Paral · lelament es referencien altres treballs d'autors significatius dins del repertori orquestral i de cambra, que han realitzat contribucions esporadiques a l'orquestra / ensemble de vents. Contribucions que per la seva originalitat o estil emmarcat en els corrents estetics compositives dels XX i XXI, impliquen un fet destacat per al genere de vents i percussió. / Fayos Jordán, JM. (2022). La orquesta de vientos como medio de aplicación y desarrollo de las técnicas compositivas actuales. Una propuesta performativa [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/183185 / TESIS

Durch den Wandel von herkömmlichen industriellen Produktionsprozessen hin zur Industrie 4.0 sowie die höhere Dynamik der Märkte werden auch Arbeitsprozesse dynamischer. Dies erzeugt hohe Anforderungen an die Mitarbeiter, die in diesem anspruchsvollen Umfeld arbeiten, und an das Management der beteiligten Workflows und Softwarewerkzeuge. Apps, also Programme mit engem Funktionsumfang, die auf die Lösung einer bestimmten Aufgabe spezialisiert sind, eignen sich als Grundbaustein für interaktive Systeme, die an die neuen Flexibilitätsanforderungen in Produktionsprozessen angepasst sind. In dieser Arbeit wird eine Methode vorgestellt, die es ermöglicht, spezialisierte Apps so zu kombinieren, dass nicht nur bestimmte isolierte Aufgaben, sondern auch komplexe Geschäftsprozesse damit bearbeitet werden können. Diese Methode, App-Orchestrierung genannt, ist ein Beitrag zum Forschungsgebiet der formalen Methoden der Mensch-Computer Interaktion und zur Bewältigung der Dynamisierung von komplexen Arbeitsprozessen im Zuge von Industrie 4.0. Die formale Modellierungssprache AOF-L, die auf BPMN und dem Semantic Web Stack aufbaut, wird entwickelt, und ein Software-Framework zur Modellierung und Ausführung von App-Ensembles mittels der AOF-L wird implementiert. In einer Nutzerstudie wird ein darauf aufbauendes industrielles Wartungsszenario evaluiert. / The transformation of industrial processes towards Industry 4.0 and the increasing dynamics of the markets are strong drivers for more dynamic industrial workflows. This development creates vast challenges to the staff that works in these ever changing environments and to the management of workflows and software tools. Apps — programs with a restricted set of functionality, tailored to a specific problem and its solution — are becoming more and more ubiquitous, especially on mobile devices. They are suitable as a building block for interactive systems ready to cope with the new requirements of flexible production processes. This work presents a method for combining specialized apps so that they can be used to fulfill complex business processes. The App-Orchestration approach is a contribution to the field of formal methods for human-computer interaction and to dealing with the new requirements of complex work environments in Industry 4.0 scenarios. The formal modeling language AOF-L which is based on BPMN and the semantic web stack, is presented. It can be employed to model interactive systems comprised of self-contained apps that are connected in a purposeful manner. Additionally, a software framework to model and execute App-Ensembles is implemented. In a user study an industrial maintenance scenario that was built using the developed method is evaluated.

Thermostated time evolutions are on a firm ground and widely used in classical molecular dynamics (MD) simulations. Hamilton´s equations of motion are supplemented by time-dependent pseudofriction terms that convert the microcanonical isoenergetic time evolution into a canonical isothermal time evolution, thus permitting the calculation of canonical ensemble averages by time averaging. However, similar methods for quantum MD schemes are still lacking. Given the rich dynamical behavior of ultracold trapped quantum gases depending on the value of the s-wave scattering length, it is timely to investigate how classical thermostating methods can be combined with powerful approximate quantum dynamics schemes to deal with interacting quantum systems at finite temperature. In this work, the popular method of Nose and Hoover to create canonically distributed positions and momenta in classical MD simulations is generalized to a genuine quantum system of infinite dimensionality. We show that for the quantum harmonic oscillator, the equations of motion in terms of coherent states may be modified in a Nose-Hoover manner to mimic the coupling of the system to a thermal bath and create a quantum canonical ensemble. The method is developed initially for a single particle and then generalized to the case of an arbitrary number of identical quantum particles, involving entangled distribution functions. The resulting isothermal equations of motion for bosons and fermions contain additional terms leading to Bose-attraction and Pauli-blocking, respectively. Questions of ergodicity are discussed for different coupling schemes. In the many-particle case, the superiority of the Nose-Hoover technique to a Langevin approach is demonstrated. In addition, the work contains an investigation of the Grilli-Tosatti thermostating method applied to the harmonic oscillator, and calculations for quantum wavefunctions moving with a time-invariant shape in a harmonic potential.

La physique moderne repose sur deux théories fondamentales distinctes, la relativité générale et la mécanique quantique. Toutes les deux décrivent d’une part les phénomènes macroscopiques et cosmologiques tels que les ondes gravitationnelles et les trous noirs et d’autre part les phénomènes microscopiques comme la superfluidité ou le spin des particules. L’unification de ces deux théories reste, jusqu’à présent, un problème non résolu. Il est intéressant de noter que les différentes théories de gravité quantique prédisent une violation des principes de la relativité générale à différents niveaux.Il est donc hautement intéressant de détecter les violations de ces principes et de déterminer à quel niveau elles se produisent.De récentes propositions pour effectuer des tests du principe d’ équivalence d’Einstein suggèrent une amélioration spectaculaire des performances en utilisant des capteurs atomiques `a ondes de matière.Dans ce contexte, il est nécessaire de concevoir des états d’entrée de l’interferomètre avec des conditions initiales bien définies. Un test de pointe de l’universalité de la chute libre (Universality of FreeFall en anglais (UFF) ) nécessiterait, par exemple,un contrôle des positions et des vitesses avec une précision de l’ordre de 1 μm et 1 μm.s⁻¹ , respectivement.De plus, les systématiques liées à la taille du paquet d’ondes limitent le taux d’expansion maximum possible à 100 μm.s⁻¹. La création initiale des états d’entrée de l’interféromètre doit être assez rapide,de l’ordre de quelques centaines de ms au maximum,pour que le temps de cycle de l’expérience soit pertinent d’un point de vue métrologique. Dans cette thèse j’ai développé des séquences optimisées s’appuyant sur l’excitation du centre de masse et de la taille d’un ou plusieurs ensembles d’atomes refroidis ainsi que dégénérés. Certaines séquences proposé dans cette thèse ont déjà été implémenté dans des expériences augmentant de manière significative le contrôle des ensembles atomiques. / Modern physics relies on two distinct fundamental theories, General Relativity and Quantum Mechanics. Both describe on one hand macroscopic and cosmological phenomena such as gravitational waves and black holes and on the other hand microscopic phenomena as superfluidity or the spin of particles. The unification of these two theories remains, so far, an unsolved problem. Interestingly, candidate Quantum Gravity theories predict a violation of the principles of General Relativity at different levels. It is, therefore, of a timely interest to detect violations of these principles and determine at which level they occur. Recent proposals to perform Einstein Equivalence Principle tests suggest a dramatic performance improvement using matter-wave atomic sensors. In this context, the design of the input states with well defined initial conditions is required. A state-of-the-art test of the universality of free fall (UFF) would, for example, require a control of positions and velocities at the level of 1 µm and 1 µm.s⁻¹, respectively. Moreover, sizerelated systematics constrain the maximum expansion rate possible to the 100 µm.s⁻¹level. This initial engineering of the input states has to be quite fast, of the order of few hundred ms at maximum, for the experiment’s duty cycle to be metrologically-relevant. In this thesis I developed optimized sequences based on the excitation of the center of mass and the size excitation of one or two cooled atomic sample as well as degenerated gases. Some sequences proposed in this thesis have already been implemented in experiments and significantly increase the control of atomic ensembles.

No description available.

[pt] Este trabalho busca usar o comitê de algoritmos de aprendizado por reforço profundo (deep reinforcement learning) sob uma nova perspectiva. Na literatura, a técnica de comitê é utilizada para melhorar o desempenho, mas, pela primeira vez, esta pesquisa visa utilizar comitê para minimizar a dependência do desempenho de aprendizagem por reforço profundo no ajuste fino de hiperparâmetros, além de tornar o aprendizado mais preciso e robusto. Duas abordagens são pesquisadas; uma considera puramente a agregação de ação, enquanto que a outra também leva em consideração as funções de valor. Na primeira abordagem, é criada uma estrutura de aprendizado online com base no histórico de escolha de ação contínua do comitê com o objetivo de integrar de forma flexível diferentes métodos de ponderação e agregação para as ações dos agentes. Em essência, a estrutura usa o desempenho passado para combinar apenas as ações das melhores políticas. Na segunda abordagem, as políticas são avaliadas usando seu desempenho esperado conforme estimado por suas funções de valor. Especificamente, ponderamos as funções de valor do comitê por sua acurácia esperada, calculada pelo erro da diferença temporal. As funções de valor com menor erro têm maior peso. Para medir a influência do esforço de ajuste do hiperparâmetro, grupos que consistem em uma mistura de diferentes quantidades de algoritmos bem e mal parametrizados foram criados. Para avaliar os métodos, ambientes clássicos como o pêndulo invertido, cart pole e cart pole duplo são usados como benchmarks. Na validação, os ambientes de simulação Half Cheetah v2, um robô bípede, e o Swimmer v2 apresentaram resultados superiores e consistentes demonstrando a capacidade da técnica de comitê em minimizar o esforço necessário para ajustar os hiperparâmetros dos algoritmos. / [en] This work seeks to use ensembles of deep reinforcement learning algorithms from a new perspective. In the literature, the ensemble technique is used to improve performance, but, for the first time, this research aims to use ensembles to minimize the dependence of deep reinforcement learning performance on hyperparameter fine-tuning, in addition to making it more precise and robust. Two approaches are researched; one considers pure action aggregation, while the other also takes the value functions into account. In the first approach, an online learning framework based on the ensemble s continuous action choice history is created, aiming to flexibly integrate different scoring and aggregation methods for the agents actions. In essence, the framework uses past performance to only combine the best policies actions. In the second approach, the policies are evaluated using their expected performance as estimated by their value functions. Specifically, we weigh the ensemble s value functions by their expected accuracy as calculated by the temporal difference error. Value functions with lower error have higher weight. To measure the influence on the hyperparameter tuning effort, groups consisting of a mix of different amounts of well and poorly parameterized algorithms were created. To evaluate the methods, classic environments such as the inverted pendulum, cart pole and double cart pole are used as benchmarks. In validation, the Half Cheetah v2, a biped robot, and Swimmer v2 simulation environments showed superior and consistent results demonstrating the ability of the ensemble technique to minimize the effort needed to tune the the algorithms.

Online shopping offers numerous benefits, but large product catalogs make it difficult for shoppers to understand the existence and characteristics of every item for sale. To simplify the decision-making process, online retailers use ranking models to recommend products relevant to each individual user. Contextual user data, such as location, time, or local weather conditions, can serve as valuable features for ranking models, enabling personalized real-time recommendations. Little research has been published on the usefulness of weather-based features for ranking models in online clothing retailing, which makes additional research into this topic worthwhile. Using Swedish sales and customer data from Babyshop, an online retailer of children’s fashion, this study examined possible correlations between local weather data and sales. This was done by comparing differences in daily weather and differences in daily shares of sold items per clothing category for two cities: Stockholm and Göteborg. With Malmö as an additional city, historical observational weather data from one location each in the three cities Stockholm, Göteborg, and Malmö was then featurized and used along with the customers’ postal towns, sales features, and sales trend features to train and evaluate the ranking relevancy of a gradient boosted decision trees learning to rank LightGBM ranking model with weather features. The ranking relevancy was compared against a LightGBM baseline that omitted the weather features and a naive baseline: a popularity-based ranker. Several possible correlations between a clothing category such as shorts, rainwear, shell jackets, winter wear, and a weather variable such as feels-like temperature, solar energy, wind speed, precipitation, snow, and snow depth were found. Evaluation of the ranking relevancy was done using the mean reciprocal rank and the mean average precision @ 10 on a small dataset consisting only of customer data from the postal towns Stockholm, Göteborg, and Malmö and also on a larger dataset where customers in postal towns from larger geographical areas had their home locations approximated as Stockholm, Göteborg or Malmö. The LightGBM rankers beat the naive baseline in three out of four configurations, and the ranker with weather features outperformed the LightGBM baseline by 1.1 to 2.2 percent across all configurations. The findings can potentially help online clothing retailers create more relevant product recommendations. / Internethandel erbjuder flera fördelar, men stora produktsortiment gör det svårt för konsumenter att känna till existensen av och egenskaperna hos alla produkter som saluförs. För att förenkla beslutsprocessen så använder internethandlare rankningsmodeller för att rekommendera relevanta produkter till varje enskild användare. Kontextuell användardata såsom tid på dygnet, användarens plats eller lokalt väder kan vara värdefulla variabler för rankningsmodeller då det möjliggör personaliserade realtidsrekommendationer. Det finns inte mycket publicerad forskning inom nyttan av väderbaserade variabler för produktrekommendationssystem inom internethandel av kläder, vilket gör ytterligare studier inom detta område intressant. Med hjälp av svensk försäljnings- och kunddata från Babyshop, en internethandel för barnkläder så undersökte denna studie möjliga korrelationer mellan lokal väderdata och försäljning. Detta gjordes genom att jämföra skillnaderna i dagligt väder och skillnaderna i dagliga andelar av sålda artiklar per klädeskategori för två städer: Stockholm och Göteborg. Med Malmö som ytterligare en stad så gjordes historiska metereologiska observationer från en plats var i Stockholm, Göteborg och Malmö till variabler och användes tillsammans med kundernas postorter, försäljningsvariabler och variabler för försäljningstrender för att träna och utvärdera rankningsrelevansen hos en gradient-boosted decision trees learning to rank LightGBM rankningsmodell med vädervariabler. Rankningsrelevansen jämfördes mot en LightGBM baslinjesmodel som saknade vädervariabler samt en naiv baslinje: en popularitetsbaserad rankningsmodell. Flera möjliga korrelationer mellan en klädeskategori som shorts, regnkläder, skaljackor, vinterkläder och och en daglig vädervariabel som känns-som-temperatur, solenergi, vindhastighet, nederbörd, snö och snödjup upptäcktes. Utvärderingen av rankingsrelevansen utfördes med mean reciprocal rank och mean average precision @ 10 på ett mindre dataset som bestod endast av kunddata från postorterna Stockholm, Göteborg och Malmö och även på ett större dataset där kunder med postorter från större geografiska områden fick sina hemorter approximerade som Stockholm, Göteborg eller Malmö. LigthGBM-rankningsmodellerna slog den naiva baslinjen i tre av fyra konfigurationer och rankningsmodellen med vädervariabler slog LightGBM baslinjen med 1.1 till 2.2 procent i alla konfigurationer. Resultaten kan potentiellt hjälpa internethandlare inom mode att skapa bättre produktrekommendationssystem.

Automatic Root Cause Analysis (RCA) systems aim to streamline the process of identifying the underlying cause of software failures in complex cloud-native environments. These systems employ graph-like structures to represent causal relationships between different components of a software application. These relationships are typically learned through performance and resource utilization metrics of the microservices in the system. To accomplish this objective, numerous RCA systems utilize statistical algorithms, specifically those falling under the category of causal discovery. These algorithms have demonstrated their utility not only in RCA systems but also in a wide range of other domains and applications. Nonetheless, there exists a research gap in the exploration of the feasibility and efficacy of multivariate time series causal discovery algorithms for deriving causal graphs within a microservice framework. By harnessing metric time series data from Prometheus and applying these algorithms, we aim to shed light on their performance in a cloudnative environment. Furthermore, we have introduced an adaptation in the form of an ensemble causal discovery algorithm. Our experimentation with this ensemble approach, conducted on datasets with known causal relationships, unequivocally demonstrates its potential in enhancing the precision of detected causal connections. Notably, our ultimate objective was to ascertain reliable causal relationships within Ericsson’s cloud-native system ’X,’ where the ground truth is unavailable. The ensemble causal discovery approach triumphs over the limitations of employing individual causal discovery algorithms, significantly augmenting confidence in the unveiled causal relationships. As a practical illustration of the utility of the ensemble causal discovery techniques, we have delved into the domain of anomaly detection. By leveraging causal graphs within our study, we have successfully applied this technique to anomaly detection within the Ericsson system. / System för automatisk rotorsaksanalys (RCA) syftar till att effektivisera process för att identifiera den underliggande orsaken till programvarufel i komplexa molnbaserade miljöer. Dessa system använder grafliknande strukturer att representera orsakssamband mellan olika komponenter i en mjukvaruapplikation. Dessa relationer lär man sig vanligtvis genom prestanda och resursutnyttjande mätvärden för mikrotjänsterna i systemet. För att uppnå detta mål använder många RCAsystem statistiska algoritmer, särskilt de som faller under kategorin orsaksupptäckt. Dessa algoritmer har visat att de inte är användbara endast i RCA-system men även inom en lång rad andra domäner och applikationer. Icke desto mindre finns det en forskningslucka i utforskningen av genomförbarhet och effektivitet av orsaksupptäckt av multivariat tidsserie algoritmer för att härleda kausala grafer inom ett mikrotjänstramverk. Genom att utnyttja metriska tidsseriedata från Prometheus och tillämpa Dessa algoritmer strävar vi efter att belysa deras prestanda i ett moln- inhemsk miljö. Dessutom har vi infört en anpassning i formen av en ensemble kausal upptäcktsalgoritm. Vårt experiment med denna ensemblemetod, utförd på datauppsättningar med kända orsakssamband relationer, visar otvetydigt sin potential för att förbättra precisionen hos upptäckta orsakssamband. Särskilt vår ultimata Målet var att fastställa tillförlitliga orsakssamband inom Ericssons molnbaserade systemet ’X’, där grundsanningen inte är tillgänglig. De ensemble kausal discovery approach segrar över begränsningarna av att använda individuella kausala upptäcktsalgoritmer, avsevärt öka förtroendet för de avslöjade orsakssambanden. Som en praktisk illustration av nyttan av ensemblens kausal upptäcktstekniker har vi fördjupat oss i anomalidomänen upptäckt. Genom att utnyttja kausala grafer inom vår studie har vi framgångsrikt tillämpat denna teknik för att detektera anomali inom Ericsson system