Seznam abstraktů 2024: SEKCE F - EKONOMIKA A ŘÍZENÍ VÝROBY V HUTNÍM, OCELÁŘSKÉM A NAVAZUJÍCÍM PRŮMYSLU

In 2023, the subsidiary transport company Doprava TŽ, s.r.o. was merged with the parent company Třinecké železárny, a.s. The digitization of the transport process was integral part of the merger. Before the merger, there was a low level of digitalisation and a high administrative burden in subsidiary company. Data was written by hand in a paper, then repeatedly re-typed into a computer and several times checked. A SQL-based program called EDL (electronical delivery list) was developed by our programmers. Transportation begins with an electronic reservation created by the client, which has a unique ID. Then the dispatcher assigns the reservation to the driver. During the shift, driver fulfils the assigned reservations, which he selects, starts and ends using a hand reader. The progress of the transport is recorded using barcodes and QR codes. All data of the entire transport process from the moment of the reservation to the end of the transport are shared online in program EDL on PC or hand reader. Benefits of implementing the EDL program are reduction of administrative burden for all process participants, significant acceleration of the entire process, continuous control over the entire process, reducing the error rate, increase in productivity, data unification and on-line overview of the entire process. All paper documents were abolished.

Operational constrains of Hot Dip Galvanizing Line - HDGL - management are more and more challenging: competitiveness (quality/yield improvement - productivity increase - OPEX reduction), flexibility (complex product-mix) and environment footprint reduction (lower energy consumption, raw material savings). These challenges can be addressed with the usage of digital tools enhancing the process optimization and automatic control of production lines.
For that purpose, physical-based models have been built and industrially implemented in order to predict microstructural evolutions during annealing and related mechanical properties of flat-C steels at the line exit.
These models rely on the description of the main metallurgical phenomena, i.e. recrystallisation, phase transformation and precipitation during heating, soaking and cooling.
The accurate design of each individual metallurgical brick and sequencing of the models enables the precise description of final microstructural characteristics: phases sizes, fractions and composition. These features are then used for the prediction of mechanical properties thanks to mean-field dislocation-based model.
Finally, these models are implemented in an optimizer (so-called MasterModel in the proposed solution) and coupled with a thermal process control model to manage in the most efficient way HDGL, enabling fine control of coil to coil properties and chemical composition heterogeneities.
The proposed approach and model’s combination cover large chemical composition and steel grades spectrum from conventional ferrite-based alloys to Advanced High Strength Steels.

Installation of Fives’ digital solution Eyeron® was successfully completed within about one-year time in a stainless steel manufacturer plant, allowing significant process improvements and savings. Immediate coils quality grading helped to immediately improve cut management. Depending on the importance of parameter deviation, powerful rules system allowed to decrease cases of product out of the tolerances, schedule accurate slitting works in real time and propose the most advantageous upgrade in real time thanks to smart communication with orders database in real-time. Outstanding process improvements were made while covering different bottleneck topics along the whole process streamline: a flatness grading index after hot strip mill helped to increase speed during cold processing and minimize breakages. Correlating process parameters and coil defectology made efficient due to the on-line data collection of surface inspection systems, statistical analysis of bright-annealed stainless steels helped to target the root cause of generalized “black dots” defect at the reheating furnace, and combined preventive work reassign earlier potential defective coils to other adequate surface finishes, making subsequent gas savings and minimizing carbon footprint. A predictive model using artificial intelligence can compute defect occurrence probability and suggest new more acceptable process parameter ranges to improve process stability.

Simple material and mass balance were efficiently drawn in high carbon ferromanganese production processes based on simple calculations. However the prediction on different products in different reactive zones using a mathematical model using artificial intelligence neural network has not been well exploited. The current project has investigated means to use AI to predict products. The establishment of a mathematical model to predict each product in each zone is not a trivial exercise. To ease the prediction of every product quantitatively, MATLAB was used as an efficient tool to generate the mathematical programming model for each product. Theoretical assumptions were used to generate the mathematical programming model which was developed per reactive zone.

Electric Current Assisted Sintering (ECAS) systems offer an efficient method for creating sintered materials. ECAS systems are complex systems that need both thermal and electrical models coupled with each other. It is crucial to monitor and document electrical variables such as temperature, current, voltage, power, and energy consumption with respect to time in an ECAS system throughout the sample production process. It is also important to model or obtain the electrical container model of the system, which has a significant determining effect on all operating characteristics. The electrical parameters of the container can be utilized to design autonomous ECAS systems that provide precise and higher-quality operation characteristics. The Internet of Things (IoT) and Industry 4.0 are contemporary solutions in the context of autonomous material production. They enable seamless connectivity and real-time data exchange and allow machines to work autonomously. This integration of IoT collectively with ECAS systems can enhance production efficiency, reduce downtime, and minimize production errors. IoT integration create smarter, and more responsive ECAS systems ensuring the reliability and consistency of material production processes. In this study, an IoT-based ECAS system design approach that systematically measures electrical and thermal quantities during the sintering process and can be used to produce the correct container characteristics and to analyze the sintering regime is proposed. An algorithm that enables the determination of equivalent circuit parameters by directly measuring and processing experimental data has been presented. The proposed design can be used to produce high-quality ECAS systems.

Currently, the 7th edition of the "Implementation Doctorate" program is being implemented in Poland. This is a unique program on a global scale, the idea of which is that the program: will contribute to improving the effectiveness of cooperation between science and the economic environment, will provide support for innovation processes and the commercialization of the results of scientific research and development work, as well as the know-how associated with these results, including the promotion of good practices in innovation, will contribute to the dissemination of knowledge on the relationship between science and innovation and the economy. This program is dedicated to all scientific disciplines. This paper focuses on: detailed assumptions of the program, the functioning of this program in the context of changes in the implementation of the third degree (doctoral studies) and entrusting them in scientific units to the so-called doctoral schools, the problem of defining and dividing the activity of doctoral students into scientific and implementation, the problem of defining the so-called implementation, defining the principles of evaluation of industrial entities whose employee is to implement the program, defining the principles of evaluation of the doctoral promoter and the scientific unit in which the doctoral program is carried out, the issues of assessing the progress of a doctoral student and how to verify it, the problem of maintaining the secrecy of sensitive information of entities in the context of reporting the progress of the implementation of the doctorate and the defense of the doctorate. The above problems were defined on the basis of qualitative analysis of the effects of the program. This paper focuses on the analysis of doctorates in the field of engineering and technical sciences, which seem to have the greatest potential for the implementation of doctorates under this program. In particular, the focus was on the analysis of issues related to metallic materials. The results of the above-mentioned analyses indicate the legitimacy of the Implementation Doctorate program and the possibility of its further development. Qualitative analysis indicates that the idea of the "Implementation Doctorate" program has proven itself in the field of metallic materials topics.

Additive manufacturing and 3D printing is one of the most rapidly evolving industry branches nowadays. This technology brings possibility of creating new designs and materials which military industry could adopt with its benefits. 3D printing based on stereolithography method was invented in 1980s. In recent times it became more and more popular and affordable what powered up a development of these technologies and spread them into public environment. Making these technologies affordable contributed to creation of a large base of informed and experienced worker’s. Additive technologies are also widely studied in many educational and scientific institutions. In this paper the impact and possibilities of use additive manufacturing in military industry mainly in terms of application of 3D printing in production of weapons and ammunition will be described. Technologies of 3D printing were listed according to normalization. Technological advancements in terms of printing methods and materials were studied. Prediction of possible usage was researched based on material studies and previous scientific papers aiming for different types of materials used in military industry like metals, composites, plastics, and explosives. Requirements on additive manufacturing technologies were defined for different types of production. Operational benefits for armed forces were also studied and finally challenges for future development of additive manufacturing in military industry were set.