Event Programe

A robot cell equipped with a Motoman robot type GP180 with a payload of 180 kg, performs cleaning and painting of sand cores for castings. The two-finger servo gripper is equipped with two external robotic axes. Change of product type, only the fingers of the gripper are replaced to suit new shape of sand core. The 3D Vision camera is used to identify the position of the cores on the input pallet and to pinpoint the position of the core in the robotic gripper.

Water is one of the most important raw materials in industrial environments. It serves as a key component in products, as a process medium, as a heating or cooling agent, and as a crucial element in sanitary and technological operations. For this reason, the required water treatment processes vary significantly across industries. Each sector follows its own standards, shaped by process needs, regulatory requirements, technical constraints, and expectations regarding product quality. The fundamental principle of process-water preparation can be expressed simply: the quality of water must always match its intended purpose.

Gas engines represent a specific group of power units in which lubrication conditions differ significantly from those in diesel or gasoline engines. This is primarily due to the varying composition of gaseous fuels, the absence of inherent lubricating components in the fuel, and the pronounced chemical effects of the combustion process. High thermal loads, the presence of nitrogen oxides (NOx), sulphur compounds, and halogens, as well as variable operating regimes, lead to accelerated lubricant degradation, particularly in the form of oxidation, nitration, and the formation of acidic by-products.
Under these conditions, the proper selection of lubricants − with adequate alkalinity reserve, controlled sulphated ash content, and optimized additive formulation − plays a crucial role in ensuring reliable operation and extended service life of engine components. In addition, systematic lubricant diagnostics has become an essential element of maintenance, enabling early detection of degradation processes, optimization of oil drain intervals, and prevention of mechanical failures.
This paper discusses the key mechanisms of lubricant degradation, the influence of fuel composition on oil formulation, and modern condition monitoring techniques, with a particular emphasis on the interpretation of oil analysis results under real operating conditions.

In modern industrial environments, characterized by high demands for dimensional accuracy and quality, portable coordinate measuring systems have become indispensable. Among these, laser trackers (hereinafter referred to as LT) play a key role due to their mobility, wide measurement range and high precision, enabling measurements beyond the capabilities of conventional coordinate measuring machines. Their use is now essential not only for inspecting large-scale products and complex assemblies, but also for the precise calibration of machine tools, robotic cells, and the alignment of production lines. With the increasing deployment of LTs in industry, the demand for their calibration is also growing. Due to stringent accuracy requirements, this presents a significant metrological challenge. Currently, no laboratory in Slovenia offers calibration services for LTs, so the procedure remains largely within the domain of the manufacturer. This paper presents the results of an experimental performance evaluation of a LT, conducted at the Faculty of Mechanical Engineering, University of Maribor. The experiment used a comparative measurement method, comparing the LT with a reference standard – a laser interferometer. Measurements were carried out on a 13 m calibration bench primarily used for calibrating tape measures. Tests were performed in four different LT configurations relative to the measurement bench, resulting in various head rotation angles. The evaluation addressed system repeatability, the influence of measurement distance, and the effect of head rotation on measurement error, including compliance with the manufacturer’s maximum permissible error (MPE) specification. The results provide a practical approach to assessing LT performance in a laboratory environment and establish a basis for further development of traceable verification procedures.

LTH Castings d.o.o. has been continuously enhancing its production processes through the implementation of advanced automation solutions. Within the Process Automation department at the Ljubljana plant, we have developed and implemented a modern robotic cell for die casting with a clamping force of 3.500 t.
The robotic cell is designed for die casting machine tending and for further processing of castings through multiple technological operations. The system includes two robots – one mounted on a floor-mounted linear axis for handling castings between stations, and another fixed robot for dot peen marking. Key components include intermediate buffering stations, a gripper lubrication system, a cooling tank, air blow-off and drying chambers, a trimming press, a saw, and an output conveyor. The process begins in the die casting machine, followed by flash removal, cooling, and optional air blow-off and drying. The casting then proceeds through trimming and, if required, sawing operations. Prior to completion, dot peen marking ensures traceability, and the final product is transferred to the output conveyor.
The entire process is fully automated, requiring only minimal manual intervention for unloading the output conveyor and replacing scrap containers, significantly improving efficiency and reliability.

This paper addresses the replacement of polymer materials in hand mixer components from the perspective of technical suitability and process feasibility. The objective is to assess how laboratory testing can effectively support decision-making when introducing cost-efficient alternative materials into series production. Comparative tests were conducted on the reference materials and alternative materials. This included controlled processing (identifying differences in the injection molding process, determining MFI), mechanical testing (tensile and flexural tests), and thermal/thermo-mechanical analyses (DSC, DMA, TMA).
The results show that the materials are comparable in terms of key properties, and the alternative material meets most of the functional requirements of the components under study. The main challenge is adjusting processing parameters during injection molding, as the processing window of the alternative material differs from that of the reference. By defining appropriate parameters and preparing process guidelines, stable series production can be ensured while minimizing the risk of non-conforming components.
The paper demonstrates how, through proper material validation and process optimization, it is possible to efficiently and systematically implement material replacement across a large number of components. This approach simplifies and accelerates the introduction of changes in production while significantly reducing the need for repeated validation of individual components. Consequently, development cycles are shortened, costs are reduced, and product quality is maintained throughout the entire lifecycle.

Technical cleanliness analysis has become one of the key elements of quality assurance in modern industry in recent years. Due to the miniaturization of components, electrification of drives, and increasingly stringent reliability requirements, contamination control is becoming a critical factor for the proper functioning of systems. Particles only a few micrometers in size can cause wear, blockages, or even complete component failure, especially in high-precision hydraulic, electronic, and mechanical systems.
Traditionally, technical cleanliness analysis was often viewed primarily as a customer requirement, particularly in the automotive industry. However, its role has significantly expanded. Today, it represents an important tool for understanding manufacturing processes, optimizing technologies, and reducing costs associated with product failures and warranty claims. The analysis not only enables particle quantification but also identification of their origin, allowing targeted process improvements.

During operation of mechanical structures, stresses and strains appear as a response to the mechanical loads. The distribution of stresses and strains depends on the size and shape of the structures as well as the materials and manufacturing processes used. The locations where the highest concentrations of stresses and strains occur are usually also the locations where fatigue issues may appear after long-term operation of the structures. In order to predict and prevent such events by application of the appropriate design, simulations of structural behaviour during the operation are carried out already in the early stages of product development. In this paper, a closer look has been taken at the stress distribution in a two-column container mixer for homogenisation of powder mixtures. The stress distribution has been compared in the main frame of the container mixer when loaded due to the structure\'s own weight. First, this was taken into account in the simulation via the concentrated force of gravity at the centre of gravity of the structure and represented a simplified consideration of the load application. Second, the load application has been considered as a distributed mass placed in the gravitational field and this represented a realistic load case. It turns out that simplification can yield slightly different results than consideration of the mass distribution, which can affect decisions regarding potential structural changes during the development process.

Our development vision in the direction of AVR - Autonomous Versatile Robotics. Our next generation of robots will understand and plan independently, they will do more things in more places and do it faster, safer and smarter. We will interact with these robots as we interact with each other.

This study investigates the effects of various additives on the properties of mechanically recycled polyamide 66 reinforced with 15% glass fibres (rPA66 GF15), intended for injection-moulded technical components. Compounding was performed at the Faculty of Polymer Technology using a twin-screw extruder. The rPA66 GF15 matrix was modified with ground waste from wind turbine blades, the finest fraction of waste polyester thermoset powder, a lubricant, and a compatibilizer. Several formulations were prepared to systematically evaluate the influence of each additive. Test specimens were prepared by injection moulding. The incorporation of ground wind turbine blade waste significantly enhanced stiffness and tensile strength, albeit at the expense of impact toughness. The addition of waste polyester thermoset powder, even at minimal concentrations, accelerated crystallization kinetics while simultaneously improving stiffness and strength. The compatibilizer played a crucial role in improving interfacial adhesion between the additives and the polyamide matrix. Conversely, the lubricant reduced stiffness and strength but notably improved additive dispersion and dimensional stability of the material. The optimized formulations exhibiting superior stiffness and strength demonstrate strong potential for injection moulding of demanding technical products. These findings validate the feasibility of incorporating recycled thermoplastic composites into high-performance applications, contributing to circular economy principles and sustainable material utilization. The research was conducted at the FTPO and OPS Breznik within the framework of the DeremCo project.

In the modern industrial environment, characterized by the Industry 4.0 concept, the effective management of technical systems is becoming a decisive factor in competitiveness. Traditional maintenance approaches, such as reactive (repair after failure) or preventive (service at fixed intervals), are increasingly failing to meet the demands for high equipment availability and cost optimization. A key shift occurs with the introduction of intelligent maintenance, which relies on real-time data collection and analysis.

The core of this transformation is IoT (Internet of Things) technology. By connecting physical machinery to digital systems via sensors and RFID identification, a continuous insight into the "health status" of the equipment is enabled. However, the data itself has no value if it is not accessible to those making decisions in the field – maintenance technicians and engineers. This is precisely where dedicated mobile applications play a crucial role.

This paper presents the architecture and functional model of a mobile application that serves as a central interface between the worker and the smart factory. The focus is on the integration of the three pillars of digitalization: precise identification via RFID, parameter monitoring (vibrations, temperature, operating hours) through IoT sensors, and the digitalization of work orders. The goal of this approach is the elimination of paper documentation, the reduction of human error, and a drastic shortening of the time required for diagnostics and intervention, which directly impacts the reduction of unplanned downtime and the extension of machinery service life.

Plasma electrolytic polishing (PeP) is an advanced non-contact surface finishing process with significant potential for improving the surface integrity of complex-shaped metallic products. This paper presents the basic principles of the PeP process, including its operating mechanism, key process parameters, and material removal behaviour. Representative samples are used to illustrate the achievable surface quality and to demonstrate the practical implementation of polishing. The applicability of PeP to geometrically demanding components is discussed, with particular attention to its advantages for external surfaces of complex parts. The paper also addresses the main process limitations, especially regarding material compatibility and the restricted effectiveness when polishing internal features such as holes and narrow cavities. The contribution provides an engineering overview of both the capabilities and constraints of PeP.

The project “Digitalization of Collaborative Screwdriving Applications in Agile Production Systems” (Digi-SAAP) demonstrates an agile manufacturing environment for screwdriving operations using collaborative robots (cobots). The objective of the project is to develop a system that enables rapid task changeovers by leveraging Industry 4.0 technologies. Automated screwdriving requires precise positioning of each fastener and the application of the correct torque, which is ensured through technologies for data acquisition, logging, and cloud-based analytics. Within the project, a novel task-learning methodology for screwdriving operations was developed, reducing changeover times from several hours to just a few minutes. At the demonstration site in ELVEZ d.o.o., an innovative CS-30 tool by Spin Robotics was validated, including data integration via Trendlog.io. The project advanced from Technology Readiness Level (TRL) 5 to TRL 8. Its overarching goal is to increase operational efficiency, reduce human physical workload, and enable digitally driven, agile manufacturing within the European industry.

In this paper, the application of mechanically recycled polyethylene terephthalate glycol (PETG) with enhanced properties is presented, suitable for both injection moulding and 3D printing.
At the Faculty of Polymer Technology, a thermoplastic composite was prepared using recycled PETG, into which ground and sieved thermoset composite waste was incorporated. Three distinct formulations were developed and subjected to two different drying techniques prior to processing. In order to achieve the desired properties of the final composite, an appropriate compatibilizer was added to all formulations to ensure effective interfacial interactions between the waste thermoset phase and the recycled PETG matrix. The mechanical and thermal properties of the recycled composite were evaluated. Test specimens were fabricated using both injection moulding and 3D Fused Granulate Fabrication (FGF) printing, the latter being conducted directly from granulate. From the characterization results, it was demonstrated that, in terms of toughness, values obtained by 3D FGF printing exceed those of injection-moulded components, regardless of the waste thermoset content. The developed material is also suitable for large-format 3D printing applications, by which new possibilities are opened for the production of tools—particularly for the processing of thermoset composites—as well as for the injection moulding of technical parts.
This work is presented as a pertinent example of circular economy principles within the framework of the DeremCo project. It is demonstrated that, by leveraging in-house expertise and existing equipment, the production of thermoplastic composites suitable for practical applications can be achieved.

Unplanned production line downtime represents a significant challenge in industry due to cryptic alarm codes, fragmented knowledge, and the lack of immediate expert support for operators. In this paper, we present an AI assistant for troubleshooting in manufacturing, based on a large language model adapted using the LoRA method for industrial diagnostics. The system integrates technical documentation, incident history, and operator feedback, transforming them into clear, context-aware action instructions. The solution enables faster and more consistent error resolution. Directions for future development are also outlined, including multimodal inputs and context-aware reasoning.

Due to their high operating speeds, stamping tools present significant challenges for the implementation of mechatronic feedback systems. This paper presents a multi-punch mechatronic stamping tool that is integrated into an industrial production cycle, featuring the ability to adjust the position of the punches and, consequently, to manufacture various products on the same production line.

We will showcase how material handling can be automated in real production environments using our AGV and AMR solutions, developed by a Czech manufacturer. The core of the presentation will be real use cases from leading automotive companies such as ŠKODA AUTO and Toyota, where we demonstrate how our systems are deployed in daily operations. You can also look forward to selected projects from other industries, including a hospital application, highlighting the flexibility of our solutions across different environments. Our goal is to provide practical inspiration based on real implementations, not theory, so you can see how similar solutions could be applied in your own operations. Join us and get inspired by real projects.

When a critical component fails and a replacement is no longer available, the choice is simple: give up or build a better part. This paper presents exactly such an engineering challenge through a student assignment (*): the reconstruction of a damaged plastic release button for a carry-on luggage handle, using only the equipment available in the laboratory, without relying on external resources or numerical simulations.
The process began with digitization using an ATOS 3D scanner and the creation of a CAD model, but simply replicating the original proved naive. Testing prototypes on a universal testing machine confirmed that faithful copying also transfers every design flaw of the original, leading to repeated failure after a simulated multi-year usage cycle.
Instead of relying on assumptions, the solution came through direct validation. By using a testing machine and the ARAMIS DIC system for optical strain measurement during mechanical tests, we forced the material to reveal exactly where the highest stresses occur. Based on these measurements, targeted design changes were implemented, resulting in a functional and reliable replacement component. This proves that with rigorous measurement and accessible laboratory equipment, 3D printing ceases to be a mere prototyping tool and becomes a serious answer to industrial maintenance challenges.

Digitalization of manufacturing has become a central driver of development in modern industry, extending beyond traditional automation into areas such as management, maintenance, and sustainable resource management. Manufacturing companies are facing increasing process complexity, a shortage of skilled labor, and rising energy costs, all of which require greater transparency and data-driven decision-making. The key building blocks of this transformation include advanced industrial controllers, digitally integrated servo systems, and open IIoT platforms.
This paper addresses the digitalization of manufacturing as a comprehensive process that begins at the level of industrial control systems and drives, and continues with the use of the FANUC FIELD system Basic Package (FsBP) as a central infrastructure for data collection, standardization, and analysis. Particular emphasis is placed on the second half of the digital value chain—machine connectivity, smart maintenance, operational analytics, and integration with MES/ERP systems. Energy efficiency is considered a direct outcome of improved digital transparency, process stability, and optimized operations.

The K-factor, defined as the ratio between the position of the neutral axis and the sheet thickness, is a key parameter in determining the developed length. However, it is not a material constant, as it depends on process conditions. In this study, it was experimentally determined for 3 mm structural steel after 90° bending using a V-die. The geometry of the deformed part was captured using an optical 3D scanner (GOM ATOS), while the position of the neutral axis was determined based on measurement analysis. The results show deviations from commonly assumed values, confirming the influence of factors such as material anisotropy, the radius-to-thickness ratio, tool geometry, friction, and springback.
Since the K-factor cannot be measured directly, it was determined indirectly by comparing the actual developed length with the geometry of the bent part. Based on measured quantities (radius, thickness, flange lengths, and bend angle), a parameter was calculated that best describes the real condition. The proposed approach enables a more accurate definition of input parameters for CAD modeling and improves the agreement of the developed state as well as the repeatability of the manufacturing process.

Choosing a 3D measurement technology and strategy is a crucial step in product quality control, and modern manufacturing processes require increasingly faster and more comprehensive measurements. In this context, modern advanced optical 3D measurement technologies and industrial computed tomography (CT) stand out as the best choice.

With more than two decades of experience in industrial 3D metrology, Topomatika d.o.o provides a solid foundation for reliable selection and application of these technologies, enabling high-quality control and reliable results in various production processes.

This paper provides an overview of practical examples for the proper selection of 3D measurement system technology, with characteristic examples from the production of polymer products, metal casting and the automotive industry, especially in the segment of new generation vehicles (NEV – New Energy Vehicles).

The article presents examples of 3D measurement results on data obtained using the ATOS and T-SCAN hawk 2 optical 3D measurement systems, and the ZEISS METROTOM industrial CT system. Data processing and creation of measurement reports were performed in the ZEISS INSPECT software package, which supports all of the aforementioned measurement technologies.

Reliable transfer of engineering data from development to production requires a continuous digital flow of information — the digital thread — which begins with the 3D CAD model and continues through the preparation of technological data, process planning, and production simulation. The 3D model acts as the single source of data and the single source of truth, from which bills of materials, manufacturing processes, work instructions, and simulation inputs are generated.

In a connected data environment, information flows between domains without manual transcription or duplication, enabling coordinated collaboration between engineering, manufacturing, and production. A key step is the transition from the Engineering Bill of Materials (EBOM) to the Manufacturing Bill of Materials (MBOM), where the product is structured according to operations, assembly groups, and materials, and where make-or-buy decisions are defined. The MBOM then becomes the direct input for the manufacturing process plan.

The digital thread ensures traceability, version control, and alignment between product and process structures, enabling rapid response to changes while directly influencing cost efficiency, production reliability, and time-to-market.

In modern industrial manufacturing, companies are facing increasing pressure for higher productivity, shorter lead times, and superior product quality. At the same time, a shortage of skilled labor and the need for rapid response to market demands are emerging. In this context, artificial intelligence (AI) represents one of the key factors for optimizing CNC machining processes.

The paper presents a case study of predicting milling tool wear using two machine learning methods widely established in industrial applications: random forests and neural networks. The validation results confirmed that both implemented models are capable of accurately predicting cutting tool wear. The use of the presented system enables a reduction in the number of stoppages and lowers production costs.

This paper presents a comprehensive approach to automating robotic 3D scanning of objects with unknown geometry, without the use of pre-existing CAD models. The proposed methodology combines geometry acquisition using a depth camera, point cloud processing, and the generation of candidate viewpoints based on a segmented triangulated surface using a generative artificial intelligence model. An algorithm is employed to select the optimal set of viewpoints and determine their sequence, minimizing the number of required measurements and the length of the robot trajectory. The trajectory execution is adapted to the robot’s kinematic constraints and implemented in the ROS2 environment using MoveIt tools. Experimental validation on a real system has shown that the proposed approach enables high-quality 3D reconstruction comparable to manual scanning, with approximately 30% longer execution time. The described approach ensures greater repeatability, reduced dependence on the operator, and represents a promising solution for industrial [1] and research applications.

In modern manufacturing, a paradigm shift is taking place—from long development cycles and maximum robustness towards rapid iteration, market adaptability, and economically optimized product lifetime. The traditional European approach emphasizes high quality, precise optimization, and long tool lifetime, while Asian models focus on development speed, serial thinking, and fast market adaptation.
The paper first presents different approaches to tool development, including the use of aluminum prototype tooling, polymer-based tools, and selected best-practice examples of European toolmakers, highlighting the transition from maximum robustness to functionally appropriate lifetime depending on product requirements.
In the second part, the role of generative artificial intelligence (GAI) in CAD environments is discussed as a tool for accelerating development. Differences between parametric modeling, topology optimization, and generative design are presented, along with the importance of data-driven approaches for faster exploration of design solutions.
The paper concludes that combining European engineering expertise with new approaches such as GAI enables the integration of high quality and development speed, representing a key opportunity to enhance the competitiveness of European toolmaking.

In manufacturing, companies often face a strategic decision: invest in a new 5-axis machining center or extend the capability of an existing 3-axis vertical CNC machine by adding a 4th and/or 5th axis. This article presents the investment and process rationale behind the 3+1 / 3+2 approach (a rotary axis or a dual-axis rotary table), enabling multi-sided machining in a single setup, reducing the number of setups, and shortening non-cutting time. From a CAPEX perspective, such an upgrade is typically significantly more cost-effective than purchasing a new 5-axis machine—often requiring at least ~30% lower initial investment—while maintaining flexibility, as the additional axis can be deployed only when needed.
Based on typical calculations from an investment guide and one selected real-life example, we quantify the impact on machine utilization and ROI. For applications involving frequent indexing (e.g., 0–90°), fast rotary positioning can noticeably reduce cycle time, while eliminating re-clamping often saves several minutes per part. These effects are translated into an economic outcome, showing that an ROI below 9 months can be realistic, depending on batch sizes, accuracy requirements, and the chosen fixturing strategy.

The paper presents, using the case of Unior d.d., how manufacturing companies should develop a circular economy strategy. The first step is to assess the current state using indicators that capture the consumption of input materials, water usage, and the amount of waste per kilogram of sold products, as well as the shares of recycled and bio-based input materials.
Next, objectives and measures for achieving them are defined. The results show that Unior d.d. has already implemented many circular economy activities in the past and that the planned measures enable the achievement of even more ambitious targets.

This paper addresses the problem of kinematic redundancy of an industrial robot mounted on a linear track in high-precision laboratory manipulation tasks. Due to the additional degree of freedom, the system allows multiple kinematic configurations to reach the same Cartesian position, which may affect motion stability and positioning repeatability. A geometric optimization-based method for determining the robot position along the linear track is presented. The approach is based on analyzing the intersection between the geometric model of the robot’s optimal reach and the axis of the external linear motion, enabling the robot to reach target positions within a matrix structure located near the boundaries of the robot workspace. The proposed method enables deterministic positioning of the robot along the track for individual target points in the matrix structure and reduces the occurrence of kinematically unfavorable configurations. Practical implementation has shown that the approach ensures stable and repeatable robot positioning while providing sufficient accuracy for demanding laboratory operations.

Digital transformation and the modernization of information systems are indispensable today for maintaining competitiveness and efficiency in modern discrete manufacturing. Despite clear business goals, such projects carry serious risks—even a well-designed implementation can, with the wrong approach, jeopardize the continuity of the entire supply chain. This paper examines the high-profile case study of the SAP S/4HANA implementation at Haribo, which clearly illustrates how inadequate planning can paralyze a company\'s operations at a critical moment. We analyze three sets of challenges: Technical challenges: The complexity of data migration and the adaptation of existing business processes to new system standards required extensive, unforeseen manual intervention and caused launch delays. Business consequences: Critical supply chain disruptions immediately after the system launch led to delivery failures to retail chains, product shortages on shelves, and a 25% drop in sales within a few weeks. Strategic errors: Launching just before the peak sales season; inadequate testing of processes in real-world scenarios; and underestimating the importance of change management and executive oversight.
Based on this analysis, practical lessons are highlighted for manufacturing companies planning a transition to comprehensive ERP solutions: the importance of aligning the launch timing with the sales and production cycles, the necessity of comprehensive testing in real-world scenarios, and the crucial role of executive oversight in change management.

CNC service providers are facing increasing market demands, such as a shortage of skilled labor, higher customer expectations, and the need for rapid quotation preparation. The Spanflug MAKE solution enables automated quotation generation by analyzing CAD models and technical drawings, as well as automatically calculating machining times and costs. This allows companies to prepare quotations faster and more reliably, contributing to greater efficiency and competitiveness.

Industrial robotics has evolved to a point where the mechanical performance of the robot is often no longer the primary limiting factor. The key challenge is becoming how to quickly, safely, and reliably prepare the robot for a new task, and how to bridge the gap between virtual program preparation and the actual behavior of the production cell. This paper discusses the concept of hybrid robot programming, which combines online teaching, offline simulation, and real-time adjustments into a single workflow. Using the ENCY Hyper platform as an example, the core building blocks of this approach are presented, along with the importance of integrating the ENCY Robot solution for more demanding processes.

Increasing customer demands for price reductions and shorter delivery times are forcing companies to increasingly optimize processing procedures. The goal of every company is to use cutting tools that will quickly and efficiently produce a high-quality and precise product. By choosing the right manufacturing technology and the right cutting tool, we achieve high-quality processing and a very favorable ratio between processing quality and tool price. One of the processing procedures is also reaming, which is a very economical procedure, especially compared to boring. The reaming process can achieve a multiple reduction in processing time and a significantly lower cost per processed piece. Conventional larger-sized reamers are manufactured with soldered inserts or have screwed inserts and an adjustable diameter. In both cases, time-consuming logistics are required for tool renewal or tool calibration, which can be a challenge for users. The solution to this is the use of Urmina RX reamers, which are designed to reduce costs per hole, which is achieved with high processing parameters and eliminating the need for tool adjustment. This increases productivity and reduces downtime on the machine to a minimum compared to the boring process, and in addition, we achieve the highest standards of precision and reliability in our production. The advantage of the reamers is the unique modular system with interchangeable inserts, which allows you to replace inserts in the μm range in just a few seconds. The reamers have constant diameter accuracy and a long service life, so no additional tool adjustment is required, resulting in very high-quality processing and a very favorable ratio between processing quality and tool price.

In a modern industrial environment, we are increasingly encountering upgrades and functional optimizations of starters and drive systems. Modern machines and the upcoming change in legislation (Machinery Regulation – EU 2023/1230), may require the implementation of safety functions. This can lead to space constraints, making optimization one of the key factors in production modernization.
The presentation will focus on compact solutions for motor control. By using the presented solutions, you need significantly fewer components and cables, less time and space for integration, achieve significant energy savings, and ensure a longer equipment life and safer maintenance.
Advanced solutions for so-called Direct-On-Line (DOL) motor starting will be presented, which combine a power device for starting and protecting the motor and safety components that enable STO up to Ple in a compact device. Such solutions enable controlled switching at a certain point in the voltage wave, which significantly reduces wear on mechanical contacts, causes lower heat losses and a lower level of electromagnetic interference in the grid.
We will present also solutions with distributed units for frequency control. These units represent a combination of a high-performance frequency converter and a highly efficient motor with a special, patented stator, enabling excellent energy utilization despite minimal size and weight. Particular emphasis will also be placed on functional safety, especially the implementation of Safe Torque Off (STO), which enables safe operation and simpler and faster maintenance interventions.

Validation of automotive components often represents a long period of product development. The internally developed method of rapid temperature shocking of products using liquid media significantly speeds up the manipulation and heat transfer to the interior of the product itself. The complexity of the testing reliably identifies design defects in products and, with a much shorter testing time compared to standard temperature tests, allows for a significant acceleration of the development process and product launch on the market.

The maritime industry is facing increasing demands in the context of the green and digital transition, particularly in terms of improved energy efficiency, reduced emissions, and enhanced control of production processes. In this context, solutions that integrate energy data, production information, and predictive models into a unified operational system play a key role. Within the Inno2Mare project, a custom-built digital twin for energy management was developed. The solution was designed for application in the maritime industry and was pilot-implemented at Iskra Kranj, where in-depth knowledge of production processes enabled effective validation of the system in a real industrial environment. The modular digital twin integrates energy measurements, production execution data, and weather-related inputs. Based on the collected data, it enables energy consumption forecasting, supports decision-making processes, and facilitates the gradual automation of energy management. The implementation achieved a 5% reduction in energy consumption and a 22% improvement in energy management efficiency. The developed predictive model operates with a forecasting accuracy between 90% and 95%. The system has been designed to allow rapid and straightforward transfer to other industrial domains.

The Digi-SAAP project demonstrates an agile production setup for screwdriving applications with collaborative robots (cobots). The goal was to develop a system that enables fast task changeover using Industry 4.0 integration. Automated screwdriving requires precise mounting of each screw with the correct torque, ensured through cloud-based data collection, logging, and analysis. The project will develop a new screwdriving task setup method that reduces changeover time from hours to minutes. The innovative CS-30 tool from Spin Robotics was tested at the Elvez d.o.o. production site in Slovenia, with data integration through Trendlog.io. The project started at TRL 5 and end at TRL 8, aiming to improve efficiency, reduce manual effort, and enable digitalized, agile production for European industry.