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Directorate for Development and Projects
Thematic Excellence Programme 2020 (TKP2020-NKA-10)
Thematic Excellence Programme 2020 - National Challanges sub-programme
Project ID: TKP2020-NKA-10
Type of contract: Sponsorship agreement
Project description:
Thematic area III.: Industry 4.0+: Researches for Sustainable Regional Industrial Development (in the field of Industry and Digitalization)
The ongoing fourth industrial revolution aims to enhance competitiveness, and the basis is the optimization of manufacturing methods and the integration of production and logistic processes. Consequently, expectations against workers have also changed, as the state of the art technological solutions replacing mechanical actions demands increasingly complex tasks and more creative thinking.
Our project completed the Industry 4.0 readiness level measurement of the involved companies and the development of Industry 4.0-based brownfield solutions, guaranteeing the market applicability of research activities and the development of supply chains. We also analyzed the effect of the difference in Industry 4.0 development levels to the relationship of regions, their trade level, mobility and knowledge transfer. We developed a method to analyze dynamic complex systems and their networks using the methods of graph theory, differential equations, and operation research.
Besides these, a highly innovative measurement method has also been developed.
We have been researching and developing methods for the optical detection of objects and their anomalies. In one research direction we worked on such deep-learning models, which are capable of semi-supervised learning and detection, or can classify the defect classes by examples. These techniques can be applied in visual inspection systems for productions or the monitoring of states of outdoor objects. The other main research direction was the delineation of curvilinear objects for the generation of graph structures. Such objects are the road networks on aerial images, the stems and branches of trees of plants, or the blood vessels of organs. If the graph model is generated successfully, then their analysis is possible with conventional graph methods.
We focus on the management and human aspects of Industry 4.0. There are several positive impacts of using the digital technologies, however the real challenge is to collect data concerning human knowledge, competences, attitudes concerning the demands of Industry 4.0. The current research identifies essential features and characteristics that have the potential to increase the acceptance of digital technologies and to overcome fears and prejudices of the employees. The outcome is a Digital Identity (Competence and Attitude) Development Program focusing on how to prepare employers and employees to work with I4.0 technologies. The final program is a postgraduate program, which we will sell to business partners, companies and organizations. Moreover, second part of the research analyzes supply chain coordination issues. The aim is to develop a novel business model for automation-based product and service delivery (self-driving platooning). To do this, we reviewed the expected future solutions, examine the related decisions, and takes into account the expectations of the stakeholders. Based on the analysis of the I4.0 readiness models, we determine the external success factors of the implementation of I4.0 solutions and develop a specific indicator system (I4.0+ model) to specify leagues of development subregions. The analysis of leagues offers the decision-makers to perform development strategies to improve the league position of a subregion.
In our research on Brownfield Industry 4.0, we have developed monitoring and intervention algorithms that take into account the uncertainty of the human workforce in manufacturing systems, in an environment of existing systems and systems with mixed digital maturity. The algorithms and methodologies explored cover the modelling of systems (ontology-based), the integrability of available and applicable systems for observations and their interconnectivity in the digital twin concept. In our study, we have placed the latest industrial digitalisation systems within the traditional Lean methodologies and in the course of our work we have highlighted how these brownfield developments can lead companies into the latest fifth industrial revolution. We have published our harness industry examples and case studies in open access journals and published the data and a short summary.
Thematic area IV.: Research and Development Related to Traditional and Autonomous Vehicles, Involving the Zalaegerszeg Test Track
1. The project involved the design and construction of a vehicle-mountable road quality measurement system. The device processes signal from several sensors and save the results on SD card and in the cloud. We have also started testing the device on the test track in Zalaegerszeg and on public roads. We are investigating how additional information about the road sections can be obtained by processing sensor signals based on sensor fusion principles. We started the development of a device for measuring the rolling friction coefficient, which will be implemented by processing signals from 3-axis force and torque sensors to derive the factors characterizing the interaction between the tire and the road surface. We also intend to determine the rolling friction coefficient based on information, that can be downloaded from the CAN bus (power consumption, speed... ) of our test car.
2. Within the TKP project, the following measurement technology developments were carried out:
a) Device for measuring and monitoring road quality - including various sensors.
b) Towing device for measuring the rolling resistance between tyre and road surface.
c) Laboratory rotating drum device for measuring the coefficient of friction between model surfaces.
d) Development of a pedestrian dummy model equipped with acceleration sensors for dynamic testing of vehicle/pedestrian collisions.
e) Development of a device for interfacing with the CAN bus of vehicles.
f) Development of a test environment and software for the study and the measuring of IMU sensors. The above devices were tested on different road sections (Zala County road sections, ZalaZONE test track) and under laboratory conditions. Our research and measurement results have been published in conferences and international journals. We use and exploit the tools (test vehicle, data collection equipment and software) acquired in the framework of the TKP both in undergraduate education and PhD training. The acquisitions and research results will clearly be used in our project-based test engineering training, which has been launched in autumn 2022. The research results have contributed significantly to enhancing the scientific and publication activities of the Institute of Mechatronics Engineering and Research.
3. In the first phase of the project the appropriate mechanical plans for the commissioning and installation of the cold test bench and the preparatory works for transport and on-site installation have been completed. As a result the condition of the cold test bench components was examined, the problematic elements from the point of view of assembly were identified, and the list of parts was compiled. Based on the floor plan of the final location of the test bench, placement variations that can be adapted to local conditions were designed in the CAD system. Installation is likely to take place in the following phase due to delays in site preparatory works. A state-of-the-art NI PXI-based central measurement and control system was designed, which complements the existing Siemens-based control system and enables the testing of electric drives instead of/alongside the testing of internal combustion engines, which require highest sampling times. The resulting system will also run MCSA-ESA (Motor Current Signature Analyses and Electric Signature Analyses) diagnostic applications. The validation of the mechanical and electrical systems of a mobile platform (soft car) for testing the control algorithms and actuator functions (ADAS) of self-driving vehicles was carried out, including the optimal choice and layout of the platform's drive system, sensors and electrical interfaces.
4. The Higher Education Industry by tradition exists as a network of prestigious institutions for the creation and distribution of advanced knowledge. The industry’s basic products are the various academic degree programs they offer. The birth of new technologies spawned a movement which is set to disrupt the entire industry and it’s looking to make all traditional business models defunct. This is because, in short, the new technologies will facilitate the decentralization of the creation and distribution of knowledge. The project focuses on optimizing educational activities over networked knowledge centers and their collaborating industry partners, where the resources are distributed in space and time, by developing a secure knowledge transfer system that takes into account the individual progress of its users, the students. With the help of this system, we can bring trainings to our partners as they ordered it and conduct it in the most optimal way.
Steps we have taken:
- Formed interlocking pools of majors and embedded them into a network of industry and university partners in order to ease the growing pressure exerted by the rapidly changing requirements of the job market and by the increasingly diverse background of the students entering the education system.
- In order to remain competitive domestically and internationally universities must connect their training programs and research projects to the industry and to each other while providing personalized and self-paced learning to their students. A solution to this problem was achieved by introducing a project-based collaborative learning environment, that was fitted into the framework of the current Hungarian higher education system. To ensure the proper evolution of the pools of majors we initiated a constant review of the defining projects of the project-based collaborative learning environment.
- Changing the manufacturing technology of education and the physical environment in which it operates.
- We integrated existing knowledge into a cloud-based distribution system, however not in a static and linear way, but in the form of “mind maps”.
- We formed the mind map clouds, a “learning path” that is individually defined for each student.
- We continuously validate the curriculum, perform eye-camera measurements. We use artificial intelligence and eyetracking to track online knowledge consumption and to continuously optimize the “learning path” of the individual student through the knowledge cloud.
- We analyze the data generated during the educational process and provide a deep learning-based service to our partners to shape their human resources in an optimal way.
Project duration: 01.09.2020.-30.11.2022.
Total project cost: 1 400 000 000 Ft
Support rate: 100 %
Professional leader: Dr. István Szalai
Professional leader ’s email address:
Project manager: Szabolcs Fehérvölgyi
Project manager's email address: