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Automatic detection of tool fracture in metal sheet punching
Kluz, Jan ; Rajchl, Matej (referee) ; Brablc, Martin (advisor)
This Bachelor thesis deals with the design and subsequent implementation of the realtime fault detection system during the sheet metal punching process with a tool of small dimensions (0.5 × 12 mm). The proposed system is important for significant ease of the operator's work, acceleration of the process of production, as well as saving of the company finance budget. The first part of this thesis deals with the theoretical background of the studied issue. The following part is a brief theoretical introduction to the field of digital signal processing. The next chapter presents methods developed for fault signals detection including speed enhancing and data flow reducing algorithms. The main examined methods were: frequency peaks, frequency bands, autocorrelation, frequency correlation methods and machine learning including deep machine learning. Deep machine learning of the neural network achieved the best results overall. Features from time and frequency domain were used for purposes of creating the classification model using machine learning. The possibility of developing the predictive maintenance system is also described, including research of this area in a modern industry. Subsequently, the achieved results and their evaluation are presented. The end of this thesis is dedicated to the description of the implementation of classification system into realtime form and connecting this system to the punching press computer using Arduino Uno microcontroller and basic signal control electronics. The proposed system has been successfully assembled, tested and put into on-site testing.
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Automatic detection of tool fracture in metal sheet punching
Kluz, Jan ; Rajchl, Matej (referee) ; Brablc, Martin (advisor)
This Bachelor thesis deals with the design and subsequent implementation of the realtime fault detection system during the sheet metal punching process with a tool of small dimensions (0.5 × 12 mm). The proposed system is important for significant ease of the operator's work, acceleration of the process of production, as well as saving of the company finance budget. The first part of this thesis deals with the theoretical background of the studied issue. The following part is a brief theoretical introduction to the field of digital signal processing. The next chapter presents methods developed for fault signals detection including speed enhancing and data flow reducing algorithms. The main examined methods were: frequency peaks, frequency bands, autocorrelation, frequency correlation methods and machine learning including deep machine learning. Deep machine learning of the neural network achieved the best results overall. Features from time and frequency domain were used for purposes of creating the classification model using machine learning. The possibility of developing the predictive maintenance system is also described, including research of this area in a modern industry. Subsequently, the achieved results and their evaluation are presented. The end of this thesis is dedicated to the description of the implementation of classification system into realtime form and connecting this system to the punching press computer using Arduino Uno microcontroller and basic signal control electronics. The proposed system has been successfully assembled, tested and put into on-site testing.
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Decision-Making Processes in a particular Firm or an Institution
Šímová, Klára ; Černý, Jan (advisor) ; Váchová, Lucie (referee)
The topic of the thesis are decision-making processes in a particular firm or an institution. The chosen company, located in Tábor, is engaged in design, production and subsequent servicing of telecommunications and security systems. The work is divided into three parts. The first will describe the company, the second part is theoretical containing the characteristics of managerial decision and all the information necessary for the third practical part. The practical section provides flowcharts for installation and servicing of equipment and subsequently describes the decision-making processes occurring upon receipt of customer requirements, making quotations up to installation of a particular solution. It concerns the selection of suppliers, responsible employee, determining payment terms and considering the possibility of cooperation with other legal entities. In conclusion, there are recommendations for the management of the company.
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Process modeling notations and their utilization
Bartošová, Kateřina ; Svatá, Vlasta (advisor) ; Juříček, Jan (referee)
The companies can choose from a wide range of tools and methodologies for mapping their processes. The key point is to select the right ones to ensure they will match with the purpose of process mapping and the process models will be clear and easy to understand for the entire stakeholder spectrum. For process modeling we often use diagrams. We have notations that are very advanced, they can be very detailed and accurate. On the other hand we have those which are very simple and with only a few symbols they can capture basic ideas and attributes of the process. The aim of this thesis is to compare representatives from each group of notations and answer the question which notation is more suitable for different types of utilization of business process models. The representative of the advanced instruments is BPMN 2.0, which is compared with the basic flowcharts. The research is based on Delphi method.
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