Table of contents

In this volume of IOP Conference Series: Materials Science and Engineering contains papers contributed to the conference of "Modern Materials and Manufacturing" – MMM 2021 held on April 27 – 29, 2021 in Tallinn, Estonia. The conference was organized by Tallinn University of Technology (TalTech). Selected papers of conference are published in special issue of Proceedings of the Estonian Academy of Sciences and journal Mechanics of Composite Materials, prepared with participation of PhD students.

The conference on Modern Materials and Manufacturing is an international forum focused on Industry 4.0 and Manufacturing Engineering, Materials Engineering and Tribology, and brings together materials and manufacturing experts from the universities and industry. It encourages new collaborations between different partners not only from academia, but also from national competence centers, industry and funding bodies.

Due to the high quality of presentations and subsequent networking opportunities, this event, hosting combined 13th International DAAAM Baltic Conference and 29th International Baltic Conference BALTMATTRIB 2021, has achieved worldwide interest and active participation from researchers from national and global technical communities.

The technical program contained presentations results of the scientific and engineering researches in important areas of materials engineering as well as materials processing technologies with particular emphasis on the current trends in the development and application of advanced materials.

The organizing committee believe this issue will be a valuable resource, not only for the participants of MMM 2021 Conference, but also for the whole research community in the field of materials and manufacturing engineering.

Scientific Committee of DAAAM Baltic 2021, Scientific Committee of BALTMATTRIB 2021, Editors are available in the pdf

All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

Detailed information about peer review process:

• Type of peer review: Single-blind

• Reviewers rated the following criteria in a three-point system: Quality of Content, Significance for theory or practice, Originality and level of innovativeness, Thematic Relevance and Overall recommendation.

Reviewers also gave comments for the authors, pointed out strengths and weaknesses of the submitted contribution and provided suggestions for improvements. Authors must resubmit articles after the revision and then final decision about acceptance/rejections was made.

• Conference submission management system: Conference SoftwareX-Conf Tool Pro

• Number of submissions received: 65

• Number of submissions sent for review: 65

• Number of submissions accepted: 58

• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 89, 2

• Average number of reviews per paper: 2

• Total number of reviewers involved: 65

• Contact persons for queries:

○ Aigar Hermaste aigar.hermaste@taltech.ee

○ Andrei Surženkov andrei.surzenkov@taltech.ee

The standard specimens have been made by anisotropic carbon fiber plastic with an epoxy matrix. The specimens were subject to static load after its shock impact. During static compression loading, the parameters of acoustic emission (AE) signals were synchronously recorded: AE impulse amplitudes, its energy and the number of oscillations. According to the analysis of the acoustic emission signals the following events were observed: matrix cracking, fiber delamination and fiber destruction. The character of the AE signals change made it possible to determine the energy of the acoustic emission signals as a diagnostic witness of the onset of two moments of the specimen destruction. The first = near 70% of ultimate load's (the destruction of matrix) and total destruction under ultimate static load.

In this paper, a new type of fibreless, bulk, sound absorber is studied. The acoustic material is an additive manufactured lattice structure constituted by a mesh of pins generated by uniform spatial translation of a regular hexagonal prismatic open cell. The material presents remarkable advantages of metal foams: it is "green", since no deteriorating, air polluting fibres are used; it is thermally and mechanically resistant, thus fire retardant, self-supporting and impact resistant. Compared to fibrous acoustic materials, it has low moisture absorption although the weight is higher. In addition to these properties, this additive manufactured material is provided with regular open cells whose geometry can be precisely controlled according to the desired performance. Moreover, the acoustical behaviour can be well modelled by simulating the air-solid thermo-viscous interaction within one single cell. The high, broad band sound absorption is a major result of the large viscous losses occurring in the flow which oscillates within the small hexagonal apertures. This lattice, referred to as honeycomb skeleton absorber (HAS), is a multifunctional material which can be used in a variety of structural applications where the sound levels must be controlled and/or a certain thermal resistance/insulation is required (for instance car floors).

Near full dense C40 hexagonal structured Mo(Si_1-xAl_x)₂-based composite coupons with 7 mm diameter by 7 mm height were prepared by selective laser melting (SLM) of MoSi₂-30 wt.% AlSi10Mg powder mixture and subjected to isothermal oxidation. As a reference, MoSi₂ bulk sample was prepared by spark plasma sintering (SPS) technique. The quantitative oxidation tests were conducted in dry air atmosphere at 500 °C for 72 and 120 hours with three specimens for each dwell time. The estimated weight change after 120 h oxidation accompanied with the SEM analysis revealed the slow oxidation of the SPS prepared MoSi₂ bulk sample without evidence of pesting, however, the formed oxide layer was not protective and contained large cracks and multiple microcracks. The SLM produced sample showed remarkably slower oxidation rate as well as the formation of only a nanoscale oxide layer, highlighting the significant influence on Al additive to enhance MoSi₂ oxidation resistance, thus making the developed material promising to be used as heating element.

Functionally gradient materials (FGM) are progressive materials, where the final characteristics are sequentially changing with dimensions. Direct fabrication of functionally gradient Ti6Al4V-TiB composite was performed by spark plasma sintering (SPS) technique. Powder mixtures of six different ratios of Ti-alloy and TiB2 were subjected to sintering at a temperature of 1350 °C and a pressure of 50 MPa with a dwelling time of 15 min to obtain a six-layer specimen. Scanning electron microscope images demonstrate smooth transition between layers. Vikers hardness (HV5) is 350 on the top side and 1038 on the bottom side, and a corresponding coefficient of friction (CoF) is 0.99 and 0.76, respectively, which demonstrates their different performance under sliding wear.

Nowadays, manufacturers face the problems to adjust their production according to the fast-changing global competition. Car manufacturers, for example, are in front of a new era of individual mobility. They need to switch from combustion engines to electric drives. In general, manufacturers have to develop production strategies to lower set up time and meet requirements faster. The classical production line is most effective if the product variety is low and the lot size is high but facing the rapid growing demand for individualized products and fast-changing requirements, manufacturers must discover new ways of manufacturing. One possibility is the flexible shopfloor. In this work, we will present our concept of a flexible shopfloor IT for controlling a robotic demonstrator. We use OPC UA over TSN as a platform for communication and CODESYS as Soft SPS for the control of sensors and actuators. In order to create valid data for ongoing discussions we use function point analysis and counting lines of sourcecode to measure software size. Our expectation is that the initial effort for implementing a flexible shopfloor IT is higher compared to the classic approach, but for all the following implementation it will take less time, because of the possibility of reuse already developed systems.

In recent years, with the advancement in sensor technologies, computing technologies and artificial intelligence, the long-sought autonomous vehicles (AVs) have become a reality. Many AVs today are already driving on the roads. Still, we have not reached full autonomy. Sensors which allow AVs to perceive the surroundings are keys to the success of AVs to reach full autonomy. However, this requires an understanding of sensor configurations, performance and sensor placements. In this paper, we present our experience on sensors obtained from AV shuttle ise Auto. An AV shuttle ise Auto designed and developed in Tallinn University of Technology is used as an experimental platform for sensor configuration and set-up.

Industrial robot systems offer a flexible, adaptable basis due to their kinematics and their mobility An influencing variable, which is particularly relevant for processes with long process times, is the thermal heating and the associated thermal drift of the tool center point. The maximum deviation from the actual nominal position can reach up to ΔAP_t = 1.5 mm. Currently, there are no procedures and methods established in practice which compensate the effects of thermal drift without expensive calibration measures and system downtime. In these investigations a system was developed which allows the reduction of thermally induced displacement by using controlled heating elements. The aim is to keep the entire robot system at a permanent, balanced temperature level. The heating elements are adapted to the geometry of the respective axis and heat the material to a temperature θ close to the steady state. A comparison of the drift through the heating system with the error occurring in normal operation shows that the drift of the heating system is comparable with the drift of normal heating. With the heating mats, a thermally induced error of ΔAP_t = 0.234 mm can be generated within t = 20 min. While normal heating requires up to t = 600 min. The achieved error deviation of the drift of the self-heating to the heated variants is with ΔAP = 0.04 mm only minimal. The results can help to reduce the influence of thermal heating and the associated thermal drift of the TCP without using cost-intensive measures with additional hardware and software on external computers for compensating the errors.

As autonomous vehicle development continues at growing speeds, so does the need for optimization, diagnosis, and testing of various autonomous systems elements, under different conditions. However, since such processes should be carried out in parallel, it may result in bottlenecks in development and increased complexity. The trend for Digital Twins brings a promising option for the diagnosis and testing to be carried out separately from the physical devices, incl. Autonomous vehicles, in the virtual world. The idea of intercommunication between virtual and physical twins provides possibilities to estimate risks, drawbacks, physical damages to the vehicle's drive systems, and the physical one's critical conditions. Although the problem of providing communications between these systems arises, at the speed that will be adequate to represent the physical vehicle in the virtual world correctly, it is still a trending topic. The paper aims to demonstrate a way to solve this problem-by using ROS as a middleware interface between two twining systems on the autonomous vehicle propulsion drive example. Data gathered from the physical and virtual world can be exchanged in the middle to allow continuous training and optimization of the propulsion drive model, leading to more efficient path planning and energy-efficient drive of the autonomous vehicle itself.

Green soundproofing acoustic porous materials are a valid alternative to traditional synthetic materials. Green eco-friendly acoustic panels and other soundproofing solutions are made at least in part recycled or natural materials that are safer for the environment. They do not contribute to the environmental and toxic waste problem since at the end of their useful life, green materials can be disposed of without polluting the environment. They are increasingly being used in the automotive industries and also in construction improving the acoustic comfort inside buildings as well as mitigate reverberation effects and reduce the transmission of noise between rooms. In this paper, the acoustic properties of different but typical green acoustic materials are analysed and their acoustic characteristics experimentally determined. The problems of designing of green acoustic materials have been analyzed and the main solutions to the design and use in acoustics have been proposed. The effect of the structure and arrangement of materials on the acoustic properties of materials has been analyzed.

The aim of the work was to investigate the adhesion of AlCrN coating deposited by PVD method on TiB₂/Ti composites manufactured by Spark Plasma Sintering (SPS). The composites were produced from three kinds of mixtures of powders: (1) Ti and TiB₂, (2) Ti6Al4V and TiB₂ and (3) Ti and B. Each of the mixtures was prepared at 50/50 wt. % ratio of components. Before the coating deposition the specimens were polished to obtain the surface roughness typically required for machine parts. For each set of specimens an individual surface preparation procedure was developed. The coating adhesion was measured using a scratch tester. The process of scratching was carried out to observe the characteristic moments of adhesive and cohesive failures. The highest critical loads were obtained for the coating deposited on composites produced from the mixture of two powders containing pure Ti and TiB₂.

Autonomous robotic systems are one of the pillars of Industry 4.0, together with Digital Twin (DT) simulations and advanced Human Machine Interfaces (HMI). Customization requirements in modern manufacturing demand a closer collaboration between operators and automated technologies, leading to a novel Human-Robot Collaboration (HRC) and interaction paradigm aimed at the augmentation of human capabilities in the workplace. This scenario calls for a new definition of HRC standards and design for safety, programming, and an overall assessment of modern cyber-physical systems. A comprehensive design process aiming to formulate a common framework of requirements based on human, organizational and production needs is missing. A user-centered design approach described may be a solution to address the open challenges of future HRC. DT and Augmented and Virtual reality technologies (AR/VR) are implemented in elaborated model as the necessary tools to assign the operator a central position in the design, control, and assessment of modern industrial collaborative scenarios.

The rotary tube piercing (RTP) is the first process of making seamless tube after producing the desired alloy ingot. There are several ways to make a seamless tube, one of the most common being RTP. This approach covers a wide range of processes that are categorized according to the number and shape of the rollers. On the other hand, each of these types has designed guides in the output and input of the piercing process. In this article, a new design of input and output guide for all types of rollers have been examined and simulated. Thus, three specimens including Diescher and Conical rollers were considered with 3 and 2 numbers, respectively. Results including torque, total force, temperature distribution and strain were extracted using FEM simulation. The results obtained through simulation are more in line with the experimental results obtained from previous research. While showing the successful performance of the output and input guides of the RTP process, the results indicate that the 3-roller Diescher type RTP has the most suitable arrangement for seamless tube production.

The study is focused on development of an accurate and cost effective function approximation techniques for modelling functionally graded materials. Different grading functions (exponential, power law) are expanded into Haar wavelet series based on higher order Haar wavelet approach. The proposed techniques can be utilized also for modelling load cases, complex boundary conditions, grading functions etc.

Robotic grasping and manipulation is a highly active research field. Typical solutions are usually composed of several modules, e.g. object detection, grasp selection and motion planning. However, from an industrial point of view, it is not clear which solutions can be readily used and how individual components affect each other. Benchmarks used in research are often designed with simplified settings in a very specific scenario, disregarding the peculiarities of the industrial environment. Performance in real-world applications is therefore likely to differ from benchmark results. In this paper, we present a concept for the design of general Pick&Place benchmarks, which help practitioners to evaluate the system and its components for an industrial scenario. The user specifies the workspace (obstacles, movable objects), the robot (kinematics, etc.) and chooses from a set of methods to realize a desired task. Our proposed framework executes the workflow in a physics simulation to determine a range of system-level performance measures. Furthermore, it provides introspective insights for the performance of individual components.

Recently fibreless solutions have become a trend in the design of sustainable and environmentally friendly duct silencers. Hereby microperforated panels have been proven to provide adequate performance for the substitution of unfavourable fibrous material layers commonly used in mass-produced silencers. This paper presents an acoustic study of microperforated elements aimed for an effective and eco-friendly heating, ventilation, and air conditioning (HVAC) duct silencer. Several microperforated sheet metal panels have been experimentally tested in a variety of layered configurations in order to maximize the sound absorption coefficient in operational frequency range. The optimal solution is implemented in the design concept of a novel fibreless HVAC silencer presented in this research. The results of the study demonstrate the appropriateness of the double-layered microperforates for a duct silencer as well as for a variety of Noise, vibration and harshness (NVH) implementations were potent noise absorption is aimed.

Underpotential deposition, i.e. the cathodic deposition above reversible potential E(Meⁿ⁺/Me), produces an atomic layer of a metal on a semiconductor electrode, such as e.g. bismuth telluride. This phenomenon allows electrodeposition of superlattices formed of building blocks of a layered semiconductor structure joined by biatomic metal interlayer. This work outlines the optimized pulse potential controlled electrodeposition of (Bi₂)m(Bi₂Te₃)_n films produced under mentioned above technique. The influence on the morphology of the electrodeposited films of key-parameters as applied pulse frequency, duty cycle, a routine of sodium dodecyl sulfate introduction in the electrolyte is discussed. The optimized procedure comprises a short (about 10 s) cathodic pre-treatment at high overpotential of the cathodic reaction, the subsequent periodic switching for 120 min between potentials of electrodeposition and refinement at 0.1 Hz and 5% duty cycle with addition of surfactant 60 min after the start of the electrodeposition.

To train convolutional neural networks (CNN) it is common practise to collect a huge amount of data. This is cost intensive and often not applicable. Up to date several studies have investigated the concept of few shoot learning, e.g. 1-3 samples per class. Suboptimal is still the over fitting resulting from the gap between training data and representative test data in the application. Since this is still a field of intensive research, an alternative and common approach is transfer learning with data- and image augmented pictures. However, collecting and labelling data for fine-tuning can still take an enormous amount of time, when it comes to multiclass pictures in industrial applications like assembly kit verification. The kits often contain stock lists with a small interclass and a high intraclass-distance. A specific characteristic of stock lists is that parts are easily adaptable and exchangeable. To bring object detection closer to the industry, we successfully show a dataset driven approach that combines a single class collection of pictures, which we call single class (SC) dataset and adapt with a few samples the specific multiclass use case. In result, we use a model trained on a huge SC dataset that can easily and fast be adapted to specific industrial use cases.

Machine learning (ML) offers a lot of potential for applications in Industry 4.0. By applying ML many processes can be improved. Possible benefits in production are a higher accuracy, an early detection of failures, a better resource efficiency or improvements in quantity control. The use of ML in industrial production systems is currently not widespread. There are several reasons for this, among others the different expertise of data scientists and automation engineers. There are no specific tools to apply ML to industrial facilities neither guidelines for setting up, tuning and validating ML implementations. In this paper we present a taxonomy structure and according method which assist the design of ML architectures and the tuning of involved parameters. As this is a very huge and complex field, we concentrate on a ML algorithm for time series forecast, as this can be used in many industrial applications. There are multiple possibilities to approach this problem ranging from basic feed-forward neural networks to recurrent networks and (temporal) convolutional networks. These different approaches will be discussed and basic guidelines regarding the model selection will be presented. The introduced assistance method will be validated on a industrial dataset.

The aim of the research is to provide a sample data and analysis to present the state of digitalization in the Baltic sea region. A matrix contains seven operation fields and ten services and technologies mapped available digital services in six countries like Denmark, Estonia, Finland, Latvia, Lithuania, and Poland. A comparison analysis describes the level of digitalization strength and weakness areas by country in Baltic sea region. Support structure analysis is a reference to select the suitable partner to enhance the level of digitalization in countries. The results show that there are differences in the strength and weakness areas in Baltic sea region. Further the strength areas of each country are compared to weakness areas of digitalization to develop a roadmap to improve the readiness to implement and use Industry 4.0 functionality and tools.

Absence from work caused by overloading the musculoskeletal system lowers the life quality of the worker and gains unnecessary costs for both the employer and the health system. Exoskeletons can present a solution. Typically, such systems struggle with stiffness and discomfort and primarily a lack of battery lifetime. Soft-robotic exoskeletons offer a possibility to overcome these problems by increasing the system flexibility, not limiting the supported DoF and being actuator and joint together. Since soft-robotic exoskeletons can be designed only using power when supporting the wearer, it is possible to increase the battery lifetime by only acting on those actions for which the wearer needs support. Dealing with controls for soft-robotic exoskeleton one major difficulty is to find a compromise between saving energy and supporting the wearer. Having an action-depending control can reduce the supported actions to cover only relevant ones and increase the lifetime of the battery. The system conditions are to detect the user actions in real-time and distinguish between actions which require support and those which do not. We contribute an analysis and modification of human action recognition (HAR) benchmark algorithms from activities of the daily living, transferred them onto industrial use cases containing short and mid-term action and reduce the models to be compatible using embedded computers for real-time recognition on soft exoskeletons. We identified the most common challenges for inertial measurement units based HAR and compare the best-performing algorithms using a newly recorded data set overhead car assembly for industrial relevance. As a benchmark data set we focused on the "Opportunity" data set. By introducing orientation estimation, we were able to increase the F1 scores by up to 0.04. With an overall F1 score without a Null-class of up to 0.883, we were able to lay the foundation to use HAR for action dependent force support.

In this paper a laboratory stand is presented that was developed for a multi-axis machine stepper drive control system. Each stepper drive utilizes an EtherCAT communication module based on a development board with software developed by the authors. The modules are used to exchange process data with a higher level controller. The EtherCAT communication standard is described including it's utilization for stepper drive control. A functional description of the developed communication module is also presented. The aim of the Laboratory stand is to conduct research of cyclic communication (1 milisecond or less) and synchronization between multiple drive slave devices and a supervisory controller. The main focus of the presented results was to determine EtherCAT communication cycle jitter on the developed modules. The main aim of the research was to verify whether the data exchange via EtherCAT bus has an impact on the synchronous operation of the multi-axis system.

Life data analysis is an effective statistical process to gain information on the reliability of technical facilities. The Weibull analysis is a widely-used method for modeling the probabilities of different functional failures. For its application in modern manufacturing and maintenance processes, an automation of this analysis is expedient. An exemplary process of data collection and fitting of a parametric model with continuous time scale is analyzed in this article. Its automation with different statistic software tools is described and comparatively evaluated. With the ambition of minimizing manual effort in the process, a highly automated solution was developed in this research. We describe this self-implemented solution in "R" and justify that this procedure automatizes the process more than the examined commercial implementations. The here presented work proves to be a practical real-time assistance, right now applied in aircraft maintenance.

Rapid prototyping as well as retrofitting and digitization of legacy manufacturing equipment often needs design and application of closed loop controllers. The analysis and modeling for such systems like energy-conversion or material transport devices is labor-intensive and needs process understanding. This paper presents a universal approach of identification and closed loop control of arbitrary linear systems delivered through web services using OPC UA as a standardized industrial communication interface. The identification service was used to model the dynamics of a 6-DOF industrial robot and a laboratory-scale water plant containing two separately controllable pumps. The control service successfully controlled the robot's linearizable axes and the water plant's pumps by using their respective identified state-space models. To evaluate the performance of the controllers in terms of stability, accuracy, and time response, target trajectories and disturbances like signal noise and latency in communication were introduced. Simulation and laboratory experiments show promising results for control of diverse systems with varying time-constants and imply broad applicability. So, this paper brings a guideline to efficiently implement model predictive control in manufacturing.

The development of new types of coatings is realised by many scientific and technological centres in numerous countries. To evaluate new material solutions, researchers use various methods with wide range of tribotesters. Consequently, the obtained results are incomparable. The barrier of new technologies development, especially surface modifications dedicated to work at high temperatures, is a lack of worldwide recognised tribological test methods. This paper presents the method for tribological evaluation of tribosystems with PVD/CVD coated elements, in oscillatory motion and at high temperature (up to 900 °C). The method is realised by using SRV Optimol Instruments Prüftechnik GmbH (Germany) device. The realised verification tests proved the correctness of the elaborated methodology.

In a high-mix low volume production environment, time to market is a key factor. However, one bottleneck lies in the often times manual parametrization of machines for new or modified designs. A truly flexible manufacturing environment therefore requires a continuous data flow from the design stages to the shop floor. This paper presents a concept for the automated parameterization of machines at a large automotive plant. Therefore, this paper initially discusses the results of a stakeholder analysis. The stakeholders comprise of different departments related to the product design and manufacturing processes. The requirements resulting from the interviews conducted with the stakeholders are grouped and ordered by priority. Secondly a general architecture for the control interface is presented. It includes multiple submodules, which model the continuous data flow between the departments and the production systems. The first main step of the data flow is the transformation of the information which is presented in various styles depending on the source departments to structured and standardized data. Thereafter machine parameters are generated automatically by a submodule using the structured input data and inference rules. Finally, the architecture supports the automatic transfer of the machine readable output data to the assembly line. To test the architecture a prototype comprising of more than 100 robots in a live production environment is implemented. It allows for a continuous data flow from the design and productions planning department to the robots. This enables a flexible process control, which up to today has supported the fast roll out of more than 100 new product variants. In contrast to the conventional manual setup of the machines for operation, the prototype was able to show that the monetary and time expenditure could be reduced by 95 percent.

Production planning and scheduling rely heavily on the efficient operations of production logistics and material handling equipment. Industry 4.0 technologies such as Internet of Things (IoT), Digital Twins, and Artificial Intelligence (AI) can be applied to production logistics in terms of autonomous mobile robots that facilitate to increase the flexibility and productivity of the whole production site. However, before the implementation of an automated production logistics systems, its feasibility must be analysed. This paper describes a simulation-based approach, including the definition of and comparative analysis of Key Performance Indicators (KPIs), to analyse the performance of production intralogistics applied to a selected use case. The presented approach offers a proof of concept on the basis of which decision-makers can implement mobile robots for intralogistics in their own production environments.

Hard and highly wear resistant chilled cast irons are of high interest in heavy industries like mining and steel production to achieve durable and sustainable wear protection. In this work a comprehensive view on abrasion mechanisms and the change in microstructure of these materials at elevated temperatures is targeted. Therefore, two different types of commercially available chilled high-chromium white cast irons were chosen. Detailed material characterization and hot hardness tests up to 1000°C were performed to get a first indication of temperature stability. For analysis of abrasive behaviour dry sand/steel wheel testing up to 700°C was conducted. A major part of the work was a thorough examination of the wear tracks and the influence on the microstructure. In the investigated materials chromium carbides Cr(Fe)₇C₃ and Mo-rich precipitations are present; the size and stoichiometry depend on the chemical composition. According to the differences in carbide size and type and the respective matrix composition, the hardness and abrasive behaviour changes, especially at higher temperatures. Incorporation of SiC abrasive in the wear zone leads to an in-situ wear protection, which was especially effective at 300°C increasing material's wear resistance compared to room temperature (RT). At higher temperatures up to 700°C it was possible to compensate the hardness loss of the cast iron materials.

Good cementing properties, fast setting and strong thermal performance make calcium-aluminate a valuable raw material for use in the production of different types of new refractory materials, e.g., heat conductive/storage materials. The main aim of the study was to determine thermal properties of novel Nb-slag based materials with different fillers, and to clarify optimal composition and technology. Process of preparation of studied materials was following: mixing of components, casting to moulds and hardening of materials. To estimate potential application areas, we studied the following thermal properties of CA-based materials: thermal behaviour, coefficient of thermal expansion (CTE) and conductivity. For this small cylindrical specimens were cut out from produced materials, and plates sized 300 × 300 mm were used for conductivity studies. Different compositions of CA-based materials, the hardening process, and the influence of mechanical activation on the strength were analyzed. Best thermal properties similar to the analogous reference material were obtained by quartz sand and granite sand as filler materials. The thermal conductivity of the novel CA-based material is 1.5 times higher and the bending strength is about 3 times higher compared to commercial thermoplates.

The performance of cutting tool materials (CTMs) influences the quality and lifetime of parts produced with their help. Unexpected fracturing or other failures of the tools lead to defects of parts that exaggerate materials fatigue and fracture processes. For the purpose of Industry 4 and future generations of factories it is important to enable in-situ monitoring of cutting processes while hyperspectral imaging can serve as a powerful tool. Cubic boron nitride (cBN) has extreme hardness and can provide improved wear resistance if mixed with other CTMs. Besides, such materials can be used without cooling liquids that helps to mitigate workplace health risks. The aim of the current work was to understand how well current hyperspectral imaging technologies can track the changes in performance of CTMs with addition of cBN. The paper presents the results of multiple in-situ (obtained during cutting with real lathe) and static (before or after cutting) tests performed with hyperspectral camera. The wear rate of CTMs and roughness of workpieces were measured with the help of scanning electron microscope and 3D optical profiler respectively. The effect of cBN content and effect of TiN or ZrO2 additives on performance of alumina-based CTMs produced by spark plasma sintering technique is presented.

The development of multi-material hybrids by injection molding has been studied very intensively at the IPF in the past. For that, a material bonding between the different substrates was achieved by using a newly developed two-step curing powder coating material as latent reactive adhesive. The aim of the project "Hybrid Pultrusion" was to perform a novel approach for the fabrication of material bonded metal-plastic joints (profiles) in a modified pultrusion process. Therefore, powder pre-coated steel coil is combined with a glass-fiber reinforced epoxy resin matrix. For initial basic studies, the impregnated fiber material has been applied on the pre-coated steel sheets using the Resin Transfer Molding process (RTM-process). It was proved via lap shear tests, that this procedure resulted in very high adhesive strengths up to 35 MPa resulting from the formation of a covalent matrix-steel bonding as well. In addition, the failure mechanism was subsequently studied. Furthermore, by adapting the successful material combination to the pultrusion process it was demonstrated that material bonded hybrids can be achieved even under these continuous processing conditions.

In this paper a novel approach to solving the feedrate optimization problem in Computerized Numerically Controlled (CNC) machines for Non-Uniform Rational B-Spline (NURBS) toolpaths is presented. Particle Swarm Optimization (PSO) gradient-free algorithm is used to determine the optimal shape of the feedrate profile. The shape of the profile is optimized to achieve shortest travel time within the constraints imposed by the machine's axes. Compared to more common approaches the profile is initialized with a quasi-optimal shape determined by a feedrate limit curve and then optimized to the final shape. Simulation results are presented that show the performance and computational effectiveness of the proposed method.

The Autonomous Vehicle (AV) industry aims to design strategic plans to ensure the safety of the developed systems before their mass deployment. Real-road testing is shown to be impractical for validating these systems as it requires many years if not decades of testing in different environmental conditions. Therefore, this method must be complemented with simulation for a feasible solution. The primary goal of this research is to develop advanced techniques in the safety validation area by using immersive simulation technologies. This study led to a simulation approach for safety evaluation of an AV shuttle, ise Auto, currently operating at the TalTech campus. First, we create a virtual environment based on the specified path on the university campus including all relevant features. The environment is created by using geospatial data which is collected by a drone, then they are converted to a 3D map applicable for the LGSVL simulator. Next, the developed shuttle 3D model is imported to the simulation environment and with the aim of the LGSVL, sensor data are provided for the Autoware perception algorithms, which is the control software of the shuttle. This system enables us to evaluate AV's decision-making performance and safety in different situations.

To evaluate the effects of surface topography, ice and ambient conditions on the sliding behaviour of steel samples on ice, in the present study friction and velocity measurements were performed with steel samples having different surface roughness values and distinct surface structures. It was shown that the influence of surface roughness on friction and sliding velocity is strongly dependant on ice conditions and the applied experimental parameters due to the formation of different friction regimes.

The continuous need to develop Industry 4.0 branches has led to a position, where highly sophisticated and multi-layer smart robotic systems are conducting the way in future manufacturing. This study aims to build a connectivity and system intelligent layer on top of a Co-bot integrated CNC-based Manufacturing cell. The connectivity layer is used to bypass all the data from machines to the upper intelligent layer vice versa. When raw data is arriving in the intelligent layer it is converted to information and again to knowledge for reflection back to the cell. Machine to Machine Communication and Digital Twin process for optimization is used for data conversions. This study is a down-scale example of the CPS for further development of existing robot cells.

The profitability of companies, especially in Germany, is affected by rising energy prices and increasingly stringent energy legislation. Certification according to ISO 50.001, an international standard for energy management systems, can help to meet legal requirements and increase energy efficiency. This article offers assistance in the form of a methodology that provides a structure for the selection process of an energy management system (EnMS). Considering properties of the individual company, it helps to identify an appropriate software solution. It is applied to a globally operating metalworking company in an example study. Furthermore, the measurement infrastructure in particular is a basic requirement that should not be overlooked in addition to the process of choosing an appropriate software solution. In this context, suitable metering points or criteria must be defined as well as sufficient attention paid to the anticipated costs for acquiring and integrating new measuring transducer and energy meters. The type and number of relevant measuring points must be considered in particular. Discussing these aspects, this article facilitates the process of planning and implementing an energy monitoring.

Small defects in the grain or major damage to a moulded part or tool can bring production to a standstill. SMEs in particular have neither the personnel nor the equipment to repair such damage on their own, so they send it to specialised contractors. The repair process is carried out manually, depending on the accuracy requirements, and is usually completed by a finishing process. This work requires qualified personnel and, at the same time, requires a lot of time in case of larger damages. In this paper we present a way to map the Maintenance, Repair and Operations (MRO) process chain in a partially automated manner.

The symbiosis of individual technologies results in a significantly increased efficiency of the MRO process chain, which continues to focus on people and their process knowledge.

While Directed Energy Deposition (DED) for the MRO of moulded parts is used widely, usually a high manual effort in measuring the component geometries and teaching of the machine tool paths is necessary. However, there are clear advantages compared to the manufacture of new parts or manual laser welding repair. At the same time, the resource and energy requirements can often be significantly reduced compared to new part production. Promo focuses on automating the time-consuming machine programming by reducing the number of necessary work steps in CAD/CAM-based program creation.

Based on a subsequent robot-guided scan, a digital actual 3D model is generated. Due to intelligent path planning algorithms, no manual programming of the robot is necessary and at the same time it is possible to detect components of different sizes, shapes and covers in this system with a minimum of effort. In addition, the operator passes on elementary information, such as the approach path of the milling head, to the subsequent processes by means of finger gestures and can thus significantly reduce tedious CAM programming steps. Now, the scanned component is transferred to a 3D-CAD model and a target/actual comparison is created for the damaged areas. Those are milled out in a defined manner and then restored using DED.

Dynamic alloying in the mode of super-deep penetration (SDP) allows us to evaluate the effects that occur in the materials of the spacecraft when interacting with high-speed streams of cosmic dust. The results of the experiments are presented, confirming that dynamic alloying in the SDP mode creates anisotropy in a solid body and leads to a change in physical properties (electrical resistance, electron work function). The dynamic alloying increased the anisotropy of electrical resistance in technical aluminum 99.7% Al in 2.05 times (105%), led to a decrease of the electrical resistance in the longitudinal direction by 16% and increase in the transverse direction by 41%.

Metallic cellular structures with triply periodic minimal surfaces (TPMS) is a great approach to enhance multifunctionality for several engineering disciplines. In the present study, we aimed to generate metal-based Neovious, Schoen I-WP and Schwarz Primitive structures, leveraging on TPMS based design methods. Neovious, Schoen I-WP and Schwarz Primitive structures are mathematically formulated. Geometric factors like wall thickness, number of cells and the length of unit cell can affect the mechanical response namely elastic modulus and compressive strength. Herein, Neovious, I-WP and Primitive based materials are fabricated through Selective Laser Melting (SLM) to evaluate the difference between the aforementioned geometrical factors both experimentally and through simulations. The Taguchi method was implemented to explore the effect of geometric factors on structural response. These results were further extended to the structures to optimize the elastic modulus and compressive strength.

The advent of industry 4.0 and the continuous digitalization of production ask for the enhancement of human skills and competences in the field of information and communication technology (ICT). Therefore, higher education has to keep pace with the global market needs for the necessary ICT skills and the overall understanding of the complexity of industries in 21st century. This paper focuses on the development and integration of Virtual Learning Factory (VLF) tools that can be used in production management and engineering education. The digital tools integrated in VLF toolkit can help students to exploit enabling technologies like simulation and virtual reality in their manufacturing studies and practical projects with industrial companies.

Modern quality management systems, including ISO 9001 standard based, are widely used by companies. Availability of ISO 9001 certificate and quality management system, that runs like well-lubricated machine, gives the company the tool to concentrate on customer needs, to keep the high quality standard of all processes in the company, to collaborate with reliable partners and as a result to offer the high quality products and services. There is a tendency that management systems are becoming more risk thinking based and refer to risk management standard ISO 31000. Risk management standard stands for managing risks with consequences related to safety, economic performance, environmental and other outcomes thus support company continuous improvement.

For machine industry risk assessment is crucial as this is a part of CE marking documentation. According to EU legislation, to sell the machinery within European Economic Area, CE marking of machines showing the machine correspondance to Machinery directive requirements is mandatory. Risk assessment in machine industry is applied for evaluation of the risks associated with corresponding hazards to guarantee the safety of design, production process and machinery produced. Risk assessment is conducted to evaluate machine design, exploitation or manufacturing process risks. For production process risk estimation the risk levels of subprocesses should be considered.

There are no available risk assessment industry standards. Risk matrices developed by companies are used to analyse and estimate risks for correct decision making and risk reduction. Unfortunately faulty risk matrices cause difficulties during risk estimation process and lead to inappropriate safety measures application. Risk matrices use numerical values and consider minimally hazardous event severity and probability of hazardous event levels. Numerical values of risk levels are listed in the risk matrices during risk assessment. Unfortunately calibration information with defined numerical risk tolerance criteria is often missing. Miscalibrated risk matrices lead to critically wrong decisions on risk elimination issues. This paper describes the aspects of risk matrices calibration and highlights the importance of risk tolerance definition applied during risk assessment.

It is essential for every enterprise existence to satisfy customer and consumer. The main idea of the current research is to apply customer satisfaction level Key Performance Indicators (KPIs) for supply chain reliability improvement. The Supply Chain Operations Reference (SCOR) model based KPI metrics enables to increase the quality of product/service by monitoring, visualization and further digitalization of directly involved processes. In the long run, the solution will ultimately help to reduce/eliminate the number of customer reclamations in the supply chain.

The paper includes a customer satisfaction improvement feasibility case study for the approval of findings, where the garment field business processes are connected to KPI-s of product and service models. In addition, this work suggests modelling tools for faster product/service and business process modelling and evaluation (assessment) based on the selected strategic goal for each management level. The authors defend that the current research helps to create new digital solutions to increase reliability by moving toward the customer satisfaction.

Nevertheless, the proposed approach is adaptable to other fields also, whereas the small and medium enterprise (SMEs) focal player or project owner defines the processes that have the biggest impact on the product/service reliability.

Adhesive bonding makes up a significant part of rigid joints of machine elements. The aim of this study was to investigate the contamination effect of moisture and oil on the bond strength of aluminium alloy 2024 T3 bonded by film and liquid adhesives using mechanical and chemical surface preparation methods. Two types of joints were used: homogeneous (Al-Al) and heterogeneous (Al-GFRP) ones. Surface preparation highly increased surface roughness Ra. The surfaces were moistened with deionized water and mineral oil and glued after a constrained time delay (outlife). Tensile shear strength tests of the joints showed higher strength of the chemically prepared surfaces by gluing with film adhesive. Contrarily mechanically prepared surfaces were stronger with liquid adhesive. Film adhesive seemed less sensitive to surface contamination in general.

Conventional vacuum sintering is not suitable for producing manganese containing cermets because of the physical-chemical properties of manganese, high vapor pressure, combined with high sintering temperature of cermets (1400-1600 °C). Sintering in Mn-rich microatmosphere does not only prevent Mn loss, but also enables additional in-situ alloying of the binder phase during sintering. We studied alloying of TiC-based cermet bonded with high chromium steel during sintering in Mn-rich atmosphere. Sintering in manganese vapor was found to increase sinterability of the TiC-FeCr cermet, resulting in the formation of ∼1 mm thick Mn-rich surface layer with homogeneous microstructure while the core region of the material remained unaffected. This core region exhibited highly increased Mn content and competitive mechanical properties – hardness of ∼1200 HV30 and indentation fracture toughness of ∼13 MPa*m^1/2. In addition, an unusual ε-type martensitic phase was observed in the surface layer.

Over the world rapid growth of demand for photovoltaic systems installations brings forward magnificent increase in production numbers in manufacturing facilities of PV systems. Production companies are facing challenges in providing the best quality simultaneously with rising manufacturing quantities. Due to technology behind not all the quality decisions can be done in real time. This study is focused on the development of experimental study and mathematical modelling of the PV modules quality control parameters, which could only be tested during chemical processes and could not be monitored constantly by operators at the production line.

Cracking of green parts in powder metallurgy (PM) is a big concern in PM industry. Detection of cracks in green parts before sintering can prevent recycling of already sintered parts or production of defective ones. As opposed to sintered parts, where the presence of cracks is well revealed by impact spectroscopy, it is challenging for green parts. The reason is an extremely low mechanical quality factor of these parts composed of compacted but non-sintered metal powder particles. Low mechanical integrity of particles causes the absence of pronounced resonances of the parts. The aim of the study was to test a possibility to discerning healthy and cracked green parts using spectral characteristics of signals obtained by laser vibromery. Four similar green PM gear wheels made of steel powder were obtained from a PM manufacturing company, two of them were healthy and two with simulated cracks that appeared in the area of stress concentration between the hub and the disc. The experimental setup included a Polytec PSV-500 scanning laser vibrometer and a Bruel&Kjer vibration stand type 4824. Integrated spectrograms in the frequency range 50 – 3500 Hz were recorded upon a 95-point network on the gear surface at different vibration intensities proportionally graded in the range from 1 to 5. Comparison of the 3D (frequency-intensity-amplitude) vibration spectrograms showed that the defected specimens with cracks differed from the healthy ones in the following features: resonance frequency shift and/or splitting of resonances when the load changes. The study confirmed the principal possibility of cracks detection in green PM parts using laser vibrometry regardless the crack location in the part. The aim of further studies is to determine the sensitivity limit in terms of crack size.

The usage of far or hard ultraviolet radiation in wavelength 200 – 280 nm or shortly UV-C disinfectors are becoming more and more popular due to their universal ability to fight against bacteria and viruses. It is well known that according to DIN 5031-7, both UV-A and UV-B radiation from sunlight have clear influence on the mechanical and visual properties of plastic parts, but the influence of intensive artificial UV-C is not so widely investigated. As the UV-C is in the shorter end of the UV radiation wavelength spectrum and is completely absorbed by the ozone layer and atmosphere, it is not possible to see the influence of it in everyday life. But in the equipment where the artificial UV-C radiation wavelength is used as a disinfectant, and probably in the open space, the influence of UV-C could be remarkable. Recently, there has been increasing interest in the food industry to avoid contamination in the food packing process. The global COVID-19 coronavirus pandemic has amplified this interest and has forced authors to run a set of tests with printed plastic parts. This paper analyses the outcome of those tests including two different printing directions and two different surface paints. The study shows that there is considerable influence of UV-C radiation on mechanical and aesthetic properties of 3D SLS printed PA12 parts. However, the influence can be diminished by use of appropriate paints.

Autonomous vehicles (AVs) are entering from test areas to the streets, which is one of the key components of smart cities and the future of mobility as a service (Maas). In 2020, two AV services were operated in Tallinn. This paper focuses on one of the services, including how it was set up. The route was set up in Ülemiste City, a tech park with 10,000 people daily working in the area. It connected the offices with the airport and a shopping centre. Autonomous shuttle ise Auto was used for the service (streets with heavy traffic, including some complex crossings). Our findings associated with the Ülemiste experiment in the context of legal requirements set upon autonomous vehicles to be street legal are pointed out. Events that took place during the operation (including an accident) are addressed. Summary of the feedback from clients is presented. Further studies should focus on the extended concept of smart cities with a roadmap for the nearest future.

Self-driving vehicles and mobile robots are used more and more in public transportation and industrial companies. Multiple experimental platforms, which can be operated in an urban or industrial environment have been developed recently. The key development for robust and safe control of the robot's operation is relying on the low-level cyber-physical system (CPS). CPS is composed of a collection of tightly integrated computational (cyber) units which are communicating with the physical world. CPS integrates computation and communication aspects with control and monitoring techniques. In this paper, the scientific goals underscore the analysis of the existing state of the art solutions to increase security, safety, and reliability of the multiple experimental platforms.

For the establishment of a successful quality management system in companies, the quality control of e.g. newly produced goods or the return of old and used parts is an essential component. One solution for this is the optical inspection of the surface of objects with the help of image processing algorithms. Using the case study of printer cartridges, this paper evaluates the extent to which different methods of machine learning can contribute to a successful quality control. Established methods of supervised learning have the advantage that they are already proven in many applications and have a very high detection accuracy. However, they require a lot of labelled training data and this high effort also means high integration costs. A new approach is a data-reduced variant from unsupervised learning. Here, the algorithm is trained only with defect free objects, for example as they come to a large extent from the production. If the objects are defective, the method from the field of anomaly detection or even novelty detection detects something that is different from the learned norm. This has the advantage that not all defects have to be known beforehand. And this in turn avoids acquiring a large amount of training data for each of these defects. This paper compares the effort required to acquire training data and compares it with the detection accuracy of the different methods in order to give an assessment of the extent to which the use of unsupervised learning methods is beneficial. Newly produced and used printer cartridges are used for this purpose. Image data is acquired from 18 different printer cartridge models. Afterwards they are fully annotated (labelled). A smart separation into training, validation and test data allows the training of supervised and unsupervised methods as well as a complete evaluation regarding the effort for data acquisition, annotation and detection accuracy of the defects. Finally, an outlook for chances and risks of the respective procedures is given.

This work deals with a numerical simulation of the friction stir welding FSW process of alloy material AA2195-T8. A 3D transient thermal model for simulating the heat transfer phenomena in the welding phase is applied. In this model, the FSW tool is considered as a circular heat source moving in a rectangular plate having a cooling surface and subjected to non-uniform and non-homogeneous boundary conditions. The thermal problem is solved using the finite element method as part of a Lagrangian formulation. The obtained results allow us to determine the maximum value of the temperature in the Nugget zone of the welded joint. During this process, the thermal cycle and the temperature distribution were determined for different values of the welding process parameters. The obtained numerical results are in good agreement with the one available in the literature.

This research aims to investigate the impact of a novel technique in mechanical nanostructuring on the wear resistance of materials. This technique with the name of High Pressure Torsion Extrusion (HPTE) can produce bulk nanostructured materials with enhanced mechanical properties. Results of microstructural analysis and microhardness testing showed significant enhancement in materials after HPTE. Microstructural characterization by using Electron Back-Scattered Diffraction (EBSD) method illustrated the presence of Ultra-Fine Grained (UFG) materials in the specimens Analysis of the wear by implementing reciprocal wear testing revealed that the amount of displaced volume markedly decreased after processing. This change in the wear behavior can be explained by referring to the hardness increase and the reduction of plasticity in materials which confined the plastic shearing and diminished the built-up edge around the wear track.

Kinetic studies were performed utilizing high-speed temperature scanner in the Ni-Al system including those with and without mechanical activation (MA) of different duration in a planetary ball mill, with and without using carbon nanoadditives (NA). The temperature profiles were taken and treated at different heating rates from 100 up to 2600 °C/min considering the influence of activation duration and the role of nanoadditive on the characteristic points of thermograms. Kissinger method allowed to evaluate activation energy (Ea) for non-activated, activated (1, 2, 3, 5 min), nanoadditive (1 wt.%) containing and nanoadditive (1 wt.%) containing mechanoactivated (1, 3, 5 min) mixtures. The beneficial influence of NA on the interaction between Ni and Al in the non-activated and moderately mechanoactivated mixtures was demonstrated. The influence of MA and NA on the microstructure features and phase formation sequence at various heating rates were revealed. For all the mixtures under study, T* characteristic temperatures (the temperature, where the maximum exothermic effect was observed) were found to increase with increasing heating rates. It was unravelled that mechanical treatment leads to significant changes in the reaction kinetics and phase formation laws. Particularly, in an activated mixture, the formation of Ni3Al is followed by NiAl intermetallic, in contrast to non-activated mixture, where the reaction proceeds only with the NiAl formation. The both MA in 1 min and addition of 1 wt.% NA decreased the activation energy of the Ni-Al reaction, exhibiting commensurate impact on the effective activation energy value of the Ni-Al system. However, > 3 min MA in the presence of 1 wt.% NA have prohibitive effect on the reaction in the Ni-Al system.

The electrical resistivity of thin layer (film, coating) about 5 microns' thick has been measured by the classical four-point probes method. The layer includes titanium-copper alloy grains up to 5 microns in size. Unexpectedly we encountered a physical phenomenon that spoils the measurements: the fluctuation of measurement results, i.e. the error of measurement may exceed 1000%.. Under certain conditions such crystals may exert some long-range influence leading to tenfold fluctuations of results of measuring the electrical resistivity, despite of the fact that these crystals are evenly distributed and do not create large-size clusters It was found that the relative scatter of measurement results decreases along with the increase of the distance between the electrodes (probes) due to averaging of currents, however, the error decreasing occurs inversely proportional to the logarithm of the distance between the probes. That is why the scatter remains significant at distances between the applied probes thousands times bigger than crystal grains. It decreases much slower than it occurs in case of one dimensional long strip where the error of measurement is simply inversely proportional to the distance between the probes. It creates huge difficulties for measurement of surface resistance. To overcome these difficulties, the method for the statistical proceeding of the non-uniform results of multiple measurements of electrical resistivity in two-dimensional systems has been proposed, which enable to extract information about average surface resistance even from such confusing set of measurements. By help of such statistic the four probe method can be potentially used in industry, for example, for controlling the quality of metal film coatings, used for heating by electrical current for de-icing of aircrafts or wind turbines.

The Paper type: Research paper

Atmospheric plasma spraying (APS) consists in injecting a powder feedstock material in a plasma jet to melt and accelerate the injected particles and spray them onto a substrate. However, this mechanism of coating formation induces the presence of pores and micro-cracks. In order to eliminate those defects, laser remleting may be used to improve the properties and performances of plasma sprayed coatings. In the present paper, the Ni-Cr-Re coatings fabricated by plasma spraying on stainless steel substrate were remelted by CO₂ laser, and the effects of laser remelting were studied. The structure and chemical composition of plasma sprayed and laser remelted coatings were analyzed using scanning electron microscopy (SEM) and energy disperse spectroscopy (EDS). The results show that the laser remelted coating becomes much denser and, moreover, the chemical composition of the coatings becomes homogeneous.

The use of industrial robots in production is rapidly growing. However, the vast use of industrial robots and implementation of new manufacturing technologies are mostly adopted by large industrial companies. It is due to the nature of the production volume, as robots have a lot of the same kind of work in one specific position in the production process. In smaller companies, where the robots often do not have enough workload in a single specific workplace, the process of robotization has not been so successful. SME-s need a solution where the robot can be moved from one workplace to another in order to utilize the resources like robot arm efficiently. This paper aims to analyse the feasibility for the usage of a robotic arm (a collaborative robot) to serve more than a single production cell intermittently. Production machines are located at particular distance and the movement of the robotic arm between the machines is carried out autonomously with the help of an autonomous mobile robot. Moreover, simulation and 3D visualization were used to conduct and analyse the two different scenarios. Utilization of production equipment assigns as a key performance indicator of the comparison.

Polytetrafluoroethylene (PTFE) exhibits excellent non-stick properties and a very low coefficient of friction under tribological stress, but it is incompatible with almost all other polymers. In the first part of this study we presented the generation of the novel tribological material based on unsaturated oil, radiation-modified PTFE (MP1100) and Polyamide 66 (PA66). To get a better understanding of the chemical properties and chemical composition of the compounds, the PA66-MP1100-oil-cb (chemical bonded) compounds were examined by differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA). In this part, the mechanical properties of the compounds are compared with plain PA66 and PA66-MP1100-cb. The tribological investigation was carried out using the Block-on-Ring tribometer. It was found that the mechanical properties of PA66-MP1100-oil-cb with 20 wt.% MP1100-oil-cb only show slight differences compared to PA66, but the tribological properties of the compounds have been significantly improved through chemical coupling between the three components. Finally, the amount of the compound that was deposited on the surface of the steel disc counterpart was analyzed after the tribological testing.

The goal of this work was to analyse the influence of laser welding process parameters using different plastic transparency. To achieve this task the elemental composition of plastic PPAGF40 with 20 % and 30 % transparency parts were examined using EDS analysis and cross-sections were evaluated by using optical microscope. Burst pressure was performed to evaluate the strenght of welded joints produced with different laser welding process parameters. Studies showed that welded joints with 20 % of transparency possessed burn spots on the surface of samples. Cross-section analysis revealed tendency, that plastics with 30 % transparency led to higher temperatures in welding seam using the same process parameters used for 20 % transparency, which caused pores to form inside joint. Laser power of 390 W, scan-speed 1000/800 mm/s and 3000 N of clamping force used for 20 % transparency plastic parts are not suitable for 30 % transparency plastic parts. Welding process optimization achieved by using 1400/1200 mm/s scan-speed and 2700-3000N clamping force, which showed improved burst pressure values from 7.2 to 7.9 bar. Reduced welding cycle-time achieved from 2.2 to 2.3 s with 30 % transparency of polymer PPAG40 material.