The diploma thesis deals with the assessment of the reliability of processes at the packaging center in the company CommScope Czech Republic s.r.o. The first part of the work is research about options for quality management using ISO 9000 standards, but also TQM approaches. At the same time, methods and analytical techniques are discussed, which will be further used in the practical part of this thesis. The following section introduces CommScope Inc. and its main product - optical fiber. The practical part contains an introduction to the packaging center and its processes, it also describes the analysis of the reliability of the original state and proposals for corrective measures that were designed within the Kaizen event. The rest of the work is then devoted to the implementation of the proposed changes and their economic assessment. Finally, an evaluation of the methods used, the results achieved and other recommendations are given.

The thesis is focused on the production management company XY. In the first part, there is the theoretical knowledge required for the understanding of this problem and diploma thesis. In the second part there is the analysis of company processes. Based on the identified problems the methodology of improvement is designed in this section.

The aim of this diploma thesis is to create and apply a methodology to improve the manufacturing process. Processes for the passage of a contract through the company and activities of the foreman were analyzed. According to this analysis, a methodology was created for continuous improvement of the manufacturing process. This methodology was applied to the data obtained in the analysis. Based on the application of the methodology, actions have been proposed to improve the production process.

The thesis is focused on reducing number of nonconformities using quality tools in the company engaged in dyeing and finishing of textile materials. The aim is a proposal of nonconformities management system. Based on analysis of the current method solving nonconformities are designed registration processes of internal nonconformities and complaints, which are followed by evaluation of nonconformities. The proposal will result in a systematic approach in solving of nonconformities.

This diploma thesis deals with a Six Sigma method, about especially analysis defects of forms for tire production company Barum Continental. In the first, theoretic part, there is the Six Sigma method, improvement method and implementation into practice defined, and at last I attended to the tools of Six Sigma method, e. g. Control Charts, Regression analysis, Pareto analysis. In the second, practical part, there is the industrial process analyzed. Then I was introduced Barum Continental spol. s.r.o. concern, which data extended. Up to data processing I was used tools of Six Sigma method and also histogram.

Theme of the Master’s thesis is analysis of process for production of small plates. Main parts of the thesis are analysis of the production process, process mapping, data capture, analysis of the data by Pareto analysis and find causes of nonconformities. Causes analysis is based on data analysis and process observation. It is divided to chapters by factors which are influencing the process. Optimization measures are designed with regard to their simplicity of realization and system in organization.

Diplomová práce se zaměřuje na zefektivnění podnikových procesů ve společnosti Grow3. Obsahuje analýzu procesů, zjištění příčin současných problémů za použití teoretických modelů a návrhovou část vedoucí k zefektivnění těchto procesů. Součástí je také vytvoření standardizovaných modelů pro nejdůležitější procesy. Poslední část obsahuje výsledky a porovnání provedených analýz s přihlédnutím na vytvořená doporučení.

The thesis is focused on extreme value theory and its applications. Initially, extreme value distribution is introduced and its properties are discussed. At this basis are described two models mostly used for an extreme value analysis, i.e. the block maxima model and the Pareto-distribution threshold model. The first one takes advantage in its robustness, however recently the threshold model is mostly preferred. Although the threshold choice strongly affects estimation quality of the model, an optimal threshold selection still belongs to unsolved issues of this approach. Therefore, the thesis is focused on techniques for proper threshold identification, mainly on adaptive methods suitable for the use in practice. For this purpose a simulation study was performed and acquired knowledge was applied for analysis of precipitation records from South-Moravian region. Further on, the thesis also deals with extreme value estimation within a stationary series framework. Usually, an observed time series needs to be separated to obtain approximately independent observations. The use of the advanced theory for stationary series allows to avoid the entire separation procedure. In this context the commonly applied separation techniques turn out to be quite inappropriate in most cases and the estimates based on theory of stationary series are obtained with better precision.

Calculate the Pareto frontier with minimum arm energy ripple and conduction loss of an MMC when the second and fourth harmonic of the circulating current is used as free parameters. ParetoMMC attempts to solve min F(X, lambda), X where F(X, lambda) = E_ripple(X)*lambda + P_loss*(1 - lambda). X denotes the amplitudes and phases of the second and fourth harmonic of the circulating current. lambda is the weighting scalar in the range 0 <= lamda <= 1. The MMC dc side is connected to a dc voltage source, while the ac side is a symmetric three phase voltage with isolated star point. A third harmonic in the common mode voltage is assumed.:ParetoMMC.m F_eval.m LICENSE.GNU_AGPLv3

With the breakthrough of machine learning techniques, the research concerning music emotion classification has been getting notable progress combining various audio features and state-of-the-art machine learning models. Still, it is known that the way to preprocess music samples and to choose which machine classification algorithm to use depends on data sets and the objective of each project work. The collaborating company of this thesis, Ichigoichie AB, is currently developing a system to categorize music data into positive/negative classes. To enhance the accuracy of the existing system, this project aims to figure out the best model through experiments with six audio features (Mel spectrogram, MFCC, HPSS, Onset, CENS, Tonnetz) and several machine learning models including deep neural network models for the classification task. For each model, hyperparameter tuning is performed and the model evaluation is carried out according to pareto optimality with regard to accuracy and execution time. The results show that the most promising model accomplished 95% correct classification with an execution time of less than 15 seconds. / I och med genombrottet av maskininlärningstekniker har forskning kring känsloklassificering i musik sett betydande framsteg genom att kombinera olikamusikanalysverktyg med nya maskinlärningsmodeller. Trots detta är hur man förbehandlar ljuddatat och valet av vilken maskinklassificeringsalgoritm som ska tillämpas beroende på vilken typ av data man arbetar med samt målet med projektet. Denna uppsats samarbetspartner, Ichigoichie AB, utvecklar för närvarande ett system för att kategorisera musikdata enligt positiva och negativa känslor. För att höja systemets noggrannhet är målet med denna uppsats att experimentellt hitta bästa modellen baserat på sex musik-egenskaper (Mel-spektrogram, MFCC, HPSS, Onset, CENS samt Tonnetz) och ett antal olika maskininlärningsmodeller, inklusive Deep Learning-modeller. Varje modell hyperparameteroptimeras och utvärderas enligt paretooptimalitet med hänsyn till noggrannhet och beräkningstid. Resultaten visar att den mest lovande modellen uppnådde 95% korrekt klassificering med en beräkningstid på mindre än 15 sekunder.