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Impact of IIoT security on proactive maintenance of company's assets
Chomyšyn, Maxim ; Vladimír,, Türkon (referee) ; Sedlák, Petr (advisor)
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.
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Implementation of IoT Communication Protocols Utilizing UniPi Module for Raspberry Pi
Krejčí, Jan ; Štůsek, Martin (referee) ; Mašek, Pavel (advisor)
Presented diploma thesis is focused on the implementation of Wireless M-Bus protocol to embedded device RaspberryPi with expansion board UniPi. The protocol is implemented in Python with Wireless M-Bus devices communicating via IQRF transceiver connected to the UART bus. The theoretical part is focused on an overview of embedded devices for the IoT, the possibility of their expansion. Further, the UniPi expansion board and Wireless M-Bus transceiver are detailed. First part of the thesis focuses on the Wireless M-bus layers, which provides a basic knowledge for understanding the practical part. The theoretical part concludes overview of captured devices including a description of their data units. In the practical part is the implementation of the sample application for receriving data from a Wireless M-Bus sensors. The application is able to read data from devices transmitting encrypted communication.
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Big Data Processing in Industry 4.0
Stredánsky, Dávid ; Fajčík, Martin (referee) ; Smrž, Pavel (advisor)
Main goal of this thesis is to create application for industrial big data processing. Final application uses bearing vibration data. The application's design is inspired by Lambda architecture for big data processing. The application monitors data recieved from sensors in real time and enables periodic batch processing. Known methods from bearing condition monitoring, such as root mean square, deviation or skewness extraction are used in batch processing. Data prediction method Prophet is tested out in this thesis. Final web appli- cation is written in the Python language with the use of Dash framework and results are stored in MySQL database.
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Remote Monitoring and Diagnostics of Production Processes
Liška, Jakub ; Rychlý, Marek (referee) ; Burget, Radek (advisor)
The goal of this bachelor thesis is to explore the possibilities of remote monitoring of production processes in industry and the further implementation of these possibilities into a functional application. The application can be divided into two main parts. The first part is the acquisition of raw data from the production process (production line, industrial equipment) using communication modules and send them to a remote server. In the second part, the data is processed on servers, stored in a database and displayed to the end user using an interface in a web browser. The application supports the display of important indicators in real time (with a certain limitation of the refresh rate of the used communication modules) as well as the display of historical data
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Data Analysis for Predictive Maintenance of a Robotic Arm
Žitný, Roland ; Rozman, Jaroslav (referee) ; Janoušek, Vladimír (advisor)
The Mitsubishi MELFA robotic arms used in modern factories work almost without interruption and produce sensory data about their operation. Various analysis techniques can be applied to such data for predictive maintenance, which provide information on the condition and maintenance needs of such robotic arms. The proposed predictive maintenance process consists of a sensory data acquisition system using the slmpclient and mitsubishi-monitor libraries, an analysis method system with anomaly detection using a convolutional autoencoder, anomaly classification using convolutional neural networks, and data segmentation into segments of individual robot actions using hidden Markov models. Such analysis techniques provide information on the severity, type, and location of emerging faults and abnormalities in behavior, which then determine the time required to perform the required maintenance. This work presents a created chain of predictive maintenance processes, where the obtained findings provide valuable insights into the application of predictive maintenance of Mitsubishi MELFA robotic arms in an industrial environment.
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Impact of IIoT security on proactive maintenance of company's assets
Chomyšyn, Maxim ; Vladimír,, Türkon (referee) ; Sedlák, Petr (advisor)
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.
|
|
|
Remote Monitoring and Diagnostics of Production Processes
Liška, Jakub ; Rychlý, Marek (referee) ; Burget, Radek (advisor)
The goal of this bachelor thesis is to explore the possibilities of remote monitoring of production processes in industry and the further implementation of these possibilities into a functional application. The application can be divided into two main parts. The first part is the acquisition of raw data from the production process (production line, industrial equipment) using communication modules and send them to a remote server. In the second part, the data is processed on servers, stored in a database and displayed to the end user using an interface in a web browser. The application supports the display of important indicators in real time (with a certain limitation of the refresh rate of the used communication modules) as well as the display of historical data
|
|
|
Big Data Processing in Industry 4.0
Stredánsky, Dávid ; Fajčík, Martin (referee) ; Smrž, Pavel (advisor)
Main goal of this thesis is to create application for industrial big data processing. Final application uses bearing vibration data. The application's design is inspired by Lambda architecture for big data processing. The application monitors data recieved from sensors in real time and enables periodic batch processing. Known methods from bearing condition monitoring, such as root mean square, deviation or skewness extraction are used in batch processing. Data prediction method Prophet is tested out in this thesis. Final web appli- cation is written in the Python language with the use of Dash framework and results are stored in MySQL database.
|
|
|
Implementation of IoT Communication Protocols Utilizing UniPi Module for Raspberry Pi
Krejčí, Jan ; Štůsek, Martin (referee) ; Mašek, Pavel (advisor)
Presented diploma thesis is focused on the implementation of Wireless M-Bus protocol to embedded device RaspberryPi with expansion board UniPi. The protocol is implemented in Python with Wireless M-Bus devices communicating via IQRF transceiver connected to the UART bus. The theoretical part is focused on an overview of embedded devices for the IoT, the possibility of their expansion. Further, the UniPi expansion board and Wireless M-Bus transceiver are detailed. First part of the thesis focuses on the Wireless M-bus layers, which provides a basic knowledge for understanding the practical part. The theoretical part concludes overview of captured devices including a description of their data units. In the practical part is the implementation of the sample application for receriving data from a Wireless M-Bus sensors. The application is able to read data from devices transmitting encrypted communication.
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