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study programme
Original title in Czech: Konstrukční a procesní inženýrstvíFaculty: FMEAbbreviation: D-KPI-KAcad. year: 2023/2024
Type of study programme: Doctoral
Study programme code: P0715D270017
Degree awarded: Ph.D.
Language of instruction: Czech
Accreditation: 18.2.2020 - 18.2.2030
Mode of study
Combined study
Standard study length
4 years
Programme supervisor
prof. Ing. Martin Hartl, Ph.D.
Doctoral Board
Chairman :prof. Ing. Martin Hartl, Ph.D.Councillor internal :doc. Ing. Jaroslav Katolický, Ph.D.prof. Ing. Jiří Pospíšil, Ph.D.doc. Ing. Jaroslav Juračka, Ph.D.prof. Ing. Radomil Matoušek, Ph.D.prof. Ing. Josef Štětina, Ph.D.prof. Ing. Pavel Hutař, Ph.D.doc. Ing. Petr Blecha, Ph.D., FEng.prof. Ing. Petr Stehlík, CSc., dr. h. c.Councillor external :Ing. Jan Čermák, Ph.D., MBA
Fields of education
Study aims
The main goal of the doctoral study programme is, in accordance with the Higher Education Act, to train highly qualified and educated professionals who are capable of independent scientific, research and creative activities in the field of design and process engineering. The graduates are equipped with knowledge and skills that enable them to work at Czech or international academic institutions or research institutes. The programme focuses on theoretical knowledge as well as practical experience in the field of doctoral studies. Cooperation with international research institutes is highly supported. The study programme is designed to fulfil demands and meet societal and industry requirements for highly educated and qualified professionals in the fields of design and process engineering. Doctoral study programme is primarily based on research and creative activities of doctoral students. These activities are intensively supported by student participation in national and international research projects. Research areas include design (analysis, conception, design of machinery, vehicles, machine production and energy) and process engineering (analysis, design and projection of processes in the engineering, transport, energy and petrochemical industries).
Graduate profile
A graduate of the doctoral study programme is a highly qualified expert with broad theoretical knowledge and practical skills, which enables him/her to carry out creative and research activities both independently and/or in a scientific team. The graduate is acquainted with current findings in the field of design and process engineering and is able to apply the knowledge in his/her research or creative activities. The graduate is also able to prepare a research project proposal and to oversee a project. At the same time, the graduate is able to make use of theoretical knowledge and transfer it in practice. Moreover, the graduate can adapt findings from related disciplines, cooperate on interdisciplinary tasks and increase their professional qualifications. The graduate participation on national and international researches and cooperation with international research institutions contributes to higher level of their professional competences. This experience allows graduates not only to carry out their own scientific activities, but also to professionally present their results, and to take part in international discussions. The graduate can demonstrate knowledge and skills in three main areas and the synergy produces great outcomes. 1. Broad theoretical knowledge and practical skills closely related to the topic of the dissertation (see below). 2. Professional knowledge and skills necessary to carry out scientific work, research, and creative activities. 3. Interpersonal and soft skills and competencies - the graduate is able to present their ideas and opinions professionally, is able to present and defend the results of their work and to discuss them and work effectively in a scientific team or to lead a team. According to the topic of the dissertation, the graduate will acquire highly professional knowledge and skills in mechanical engineering, in particular in design and operation of machines, machinery, engineering processes and vehicles and transport vehicles. Thanks to the broad knowledge and skills, graduates can pursue a career in research institutes in the Czech Republic and abroad, as well as in commercial companies and applied research.
Profession characteristics
A graduate of the doctoral study programme is a highly qualified expert with broad theoretical knowledge and practical skills, which enables him/her to carry out creative and research activities both independently and/or in a scientific team. The graduate is acquainted with state-of-the-art findings in the field of design and process engineering and is able to apply the knowledge in his/her research or creative activities. The graduate is also able to prepare a research project proposal and to oversee a project. At the same time, the graduate can make use of theoretical knowledge and transfer it in practice. Moreover, the graduate can adapt findings from related disciplines, cooperate on interdisciplinary tasks and increase their professional qualifications. The graduate typically finds a job as a researcher, academic personnel, computer scientist or designer. The graduate is also well equipped with skills and competences to perform well in managerial positions.
Fulfilment criteria
See applicable regulations, DEAN’S GUIDELINE Rules for the organization of studies at FME (supplement to BUT Study and Examination Rules)
Study plan creation
The rules and conditions of study programmes are determined by: BUT STUDY AND EXAMINATION RULES BUT STUDY PROGRAMME STANDARDS, STUDY AND EXAMINATION RULES of Brno University of Technology (USING "ECTS"), DEAN’S GUIDELINE Rules for the organization of studies at FME (supplement to BUT Study and Examination Rules) DEAN´S GUIDELINE Rules of Procedure of Doctoral Board of FME Study Programmes Students in doctoral programmes do not follow the credit system. The grades “Passed” and “Failed” are used to grade examinations, doctoral state examination is graded “Passed” or “Failed”.
Availability for the disabled
Brno University of Technology acknowledges the need for equal access to higher education. There is no direct or indirect discrimination during the admission procedure or the study period. Students with specific educational needs (learning disabilities, physical and sensory handicap, chronic somatic diseases, autism spectrum disorders, impaired communication abilities, mental illness) can find help and counselling at Lifelong Learning Institute of Brno University of Technology. This issue is dealt with in detail in Rector's Guideline No. 11/2017 "Applicants and Students with Specific Needs at BUT". Furthermore, in Rector's Guideline No 71/2017 "Accommodation and Social Scholarship“ students can find information on a system of social scholarships.
Issued topics of Doctoral Study Program
The topic is focused on the analysis of the possibilities of using modern methods of management and quality assurance in the development and production of plastic parts in engineering production. Emphasis will be placed on the implementation of current trends of digitalization and green transformation of industry. The aim will be to develop a methodology for reducing CO2 emissions and increasing production efficiency for a selected product type. The topic is suitable for combined studies and requires the support of a collaborating company.
Tutor: Jankových Róbert, doc. Ing., CSc.
The topic of the dissertation is focused on dealing with advanced proactive multiparametric on-line and off-line diagnostics of electric drives of machinery, authoritative evaluation of obtained data, storing the Internet of Things and subsequent active data processing with feedback influence on electric drive and machinery. The obtained results will be verified in selected engineering companies.
Tutor: Hammer Miloš, doc. Ing., CSc.
The purpose of this work will be to design artificial neural network models for automatic diagnosis so that the classifier automatically recognizes anomalous states of a defined machine component. For example, AI algorithms can be trained to automatically recognize gearbox fault conditions without the supervision of a vibrodiagnostic engineer, both from acceleration time signals and from FFT spectra, spectrograms and orbits of shaft vibrations in plain bearings.
Tutor: Matoušek Radomil, prof. Ing., Ph.D.
This dissertation will aim to develop analytical tools in the field of circular economy, with a specific focus on waste transportation including the algorithmization of efficient search of large networks. The student will expand his knowledge of programming and statistical methods to apply them to monitored data. In developing a novel analytical approach for evaluating extensive studies, the student will utilize existing complex tools such as NERUDA, TIRAMISO, REVEDATO, and POPELKA developed at the Institute of Process Engineering (ÚPI). The student will further develop these tools using newly designed algorithms and thus expand their functionality. The programming activities will focus on appropriate software implementation and utilizing available computational resources. The motivation for this work stems from the need to implement advanced mathematical models into computational tools used in industrial practice. The following issues will be tackled: • Introduction to circular economy and waste management issues and related mechanisms from the operation. • Understanding the principles of existing computational tools at the Institute of Process Engineering (NERUDA, TIRAMISO, REVEDATO, POPELKA, etc.). • Extending knowledge of modern programming techniques and necessary mathematical apparatus. • Development and implementation of algorithms into existing or newly emerging software with a focus on industrially oriented applications.
Tutor: Pavlas Martin, doc. Ing., Ph.D.
The draft theme responds to the need to improve the level of safety in workplaces where workers are exposed to particles < 2.5 μm (dust/aerosol) which have an impact on human health, including occupational diseases and stress loads on workers. The research activity will build on the results of the completed project TL02000240 - Improving the level of OSH management in operations with fine and ultrafine particles. The topic is suitable for students of the combined form of study working in enterprises with powder coating, electroplating or welding plants. Employer support in carrying out the necessary experiments in these workplaces is essential. The topic focuses on risk management, workplace condition monitoring, worker workload prediction and smart workplace design. Translated with www.DeepL.com/Translator (free version)
Tutor: Blecha Petr, doc. Ing., Ph.D., FEng.
Machine vision systems based on some of the machine learning methods are used to solve non-trivial computer vision tasks such as object recognition and image segmentation. Deep convolutional networks (ConvNets) proved to be the ideal tool for such tasks. Systems based on deep ConvNets, trained on a sufficiently large and sufficiently representative datasets, show high accuracy and precision. In practice, however, the datasets are often too small, do not sufficiently capture the variability of the problem being solved, or the distribution of object classes in the datasets are imbalanced. A system trained on such a dataset can show inconsistent results in real conditions. The main aim of the work will be analysis of the influence of the composition of training data on the robustness of computer vision systems, and design of methods and methodologies for increasing the robustness of computer vision systems in relation to this phenomenon.
Tutor: Šeda Miloš, prof. RNDr. Ing., Ph.D.
The support system of CNC machine tools must withstand the effects of external influences so that the machine maintains production accuracy in the long term. The support system is one of the main parts of the CNC machine tool, which plays a significant role not only in production, but also in geometric accuracy. Among the influences that have a negative effect on the machine, we count the change in temperature around the machine, the technology and the chip machining strategy. The geometric shape of the supporting bodies of the machines, the topology and the chosen material from which the body is made can significantly affect the negative consequences arising from temperature changes and the machining strategy. The goal of the work is to use a system approach to find the optimal solution of the support system for this type and type of CNC machine tools.
Tutor: Marek Jiří, prof. Dr. Ing., Ph.D., DBA, FEng.
The aim of the manufacturers of CNC machine tools is to satisfy the customer's needs to the maximum. One of the ways to achieve this is to have a consistent modular system, which will allow the machine tool to be efficiently manufactured according to the customer's wishes from individual building modules. In addition, it is desirable to think about the principles of the circular economy. The aim of the thesis is to select representatives of the type and type of CNC machine tool, on which the principles of modularity and the principles of the circular economy will be applied. All this must be preceded by a thorough analysis of the essential quantities that influence this proposal. The design of the modular system will be consistently solved with a system approach.
The mathematical description of complex technical systems is usually in the form of non-linear differential equations, whose analytical solution imposes high computational demands, which in practice is not suitable for real-time control. Therefore, in this dissertation, the aim will be to apply artificial intelligence methods using evolutionary strategies and to determine the optimal parameter settings of the methods for a nonlinear multicriteria helicopter model and to verify safe in-flight control in real time.
Thesis will be focused on minimization of influence of distorsion of flow at radial compressor intake. Distorsion negatively influences performance of compressor. Advanced shape multidisciplinary optimization applied on radial compressor blades geometry will be studied. The goal is to increase robustness of compressor related to efficiency and stabililty degradation due to inflow distorsion.
Tutor: Juračka Jaroslav, doc. Ing., Ph.D.