For automotive manufacturers, one of the biggest technological challenges is producing different variants on the same production line. At the body-in-white shop at the Magna complete vehicle plant in Graz, this is achieved using transportable positioning devices. They serve as part carriers and adapters between different products, while geometrically aligning them throughout the process. Geometrical deviations in these devices can negatively impact product quality throughout the vehicle assembly value chain. This paper presents the development and implementation of components for a patented closed quality loop that mitigates the effects of deviating positioning devices in real time. Challenges and insights gained from the brownfield implementation into serial production are discussed. Four key modules for automating quality control processes are introduced, providing a basis for future research on cyber-physical systems aimed at achieving zero-defect manufacturing: integrated capture of process and product data, automated analytics, automated decision-making and autonomous process intervention.

Moving towards sustainable production, zero-defect manufacturing plays an important role. Achieving this, the identification of material defects during machining is a decisive factor. This paper introduces innovation through a theoretical model for the smallest detectable material defect in machining, solely based on machine data from the existing numerical controller, eliminating the need for external sensors. The verified model correlates the material defect size with spindle torque changes (affected by tool-, material-, machine-, and machining parameters) and demonstrates the identification of 0.2mm defects compared to 0.7mm in the literature as a remarkable contribution to zero-defect manufacturing.

Collaborative design processes in innovative product development are particularly vulnerable to fragmented workflows, data silos, and inefficient communication across diverse stakeholders. These challenges hinder agility, integration of safety requirements, and iterative development. This study investigates how data spaces—sovereign and interoperable environments for secure data exchange—can address these systemic issues and improve co-design workflows in such innovation-driven contexts. We present a case study of a safety-integrated mobile manipulator developed by a consortium team, revealing critical limitations in data continuity, version control, and real-time collaboration. In particular, we reflect on the shortcomings of a V-model-based co-design workflow and demonstrate how it can be extended through DS to overcome these limitations. Drawing from these findings, we propose a DS-oriented workflow that enables structured, contextual, and traceable information sharing. This approach strengthens requirement traceability, safety integration, and cross-partner collaboration, offering practical insights for advancing co-design processes in innovative product development through federated, data-driven engineering practices.

A key technological challenge for automotive manufacturers is producing multiple vehicle variants on a single production line. At the body-in-white shop of Magna’s complete vehicle plant in Graz, this is addressed through transportable positioning devices that serve as part carriers and adapters between different products, while ensuring consistent geometric alignment throughout the process. Geometrical deviations in these devices can adversely impact product quality along the entire vehicle assembly chain. This paper presents the development and implementation of two patented use cases: a cyber-physical inspection system, fully operational in serial production, and a cyber-physical assembly system, tested successfully in the prototype phase. The first actively mitigates the effects of device deviations in real time, while the second enables the on-demand configuration of flexible, advanced positioning devices via precision part matching, effectively preventing systematic deviations. Challenges and insights from both systems are discussed. Four previously introduced building blocks for automating quality control processes are validated and generalized for broad applicability across manufacturing processes and project phases via cross-system comparative analysis: the integrated capture of process and product data, automated data analytics, automated decision-making, and autonomous process intervention. This work proposes a validated, scalable framework integrating the design and implementation of cyber-physical systems to support zero-defect manufacturing.

Industrial robots often perform handling and assembly tasks in industrial applications. This places high demands on dynamics and positioning accuracy. However, when handling low-weight workpieces, a relatively high robot mass usually leads to a limitation of the motion dynamics. The reason is that the manipulator’s gears and drives are often arranged in series, as in the case of SCARA or articulated robots. This results in high moments of inertia for the actuated axes, located at the start of the kinematic chain. The overall stiffness is determined by the weakest element of the structure in that cases. Manipulators with parallel kinematic structures, such as delta robots, can provide a remedy here. However, when using manipulators of this type, problems arise when integrating them into production systems. They have an unfavourable ratio of workspace to installation space. Installation above the process area is mandatory and therefore strongly restricts the arrangement of other components in the production system. Hybrid structures, consisting of open and closed kinematic chains, offer alternative solutions. Based on such a hybrid approach, a concept of a novel kinematic structure for high dynamic applications is presented and analysed in this publication.

Lightweight design is very closely associated with additive manufacturing. Besides the design possibilities offered by this technology, the material used also plays a key role. Especially in the LPBF process, the production of the powder and the processing of the material is a major challenge. This applies in particular to magnesium alloys as a lightweight material. Due to its low density and good strength and rigidity properties, this material is ideal for lightweight engineering applications. The basis of this contribution is a risk assessment (including a detailed FMEA and measures to minimize risks) for the processing and handling of magnesium powder in the LPBF process. As part of the practical tests, several test specimens with existing parameters for AZ91D were printed, and their properties (relative density, microstructure and bonding behaviour) were analysed. By adjusting the alloy composition (improved evaporation characteristics) and optimizing the process (e.g. optimum inert gas flow, platform temperature) and the process parameters, it is possible to process magnesium more economically in the LPBF process.

The trend toward mass customization of products requires a high degree of flexibility in their production. Traditional and well-established production concepts such as full automation are limited for these products due to their high acquisition costs. Hence, there is a need for a cost-effective, flexible automation in production. However, there is currently a lack of methodology for determining the appropriate level of automation in flexible low quantity productions. This paper addresses this gap by presenting a generalized model for estimating the optimal Degree of Automation, which is evaluated through a case study focusing on the assembly of aerospace modules. In the presented case study two different modules have to be assembled within 5 tasks. The derived model proposed an optimal Degree of Automation of 21

Resource savings, sustainability and financial success are very closely linked to the lowest possible rework and scrap rate in production. Innovations in the measurement process, AI-based data analytics and adaptive quality control are not sufficiently represented in existing learning factory designs. The paper presents a scalable new solution to achieve the defined goals. The presented use case allows the detection of unsuspected systematic deviations when combining product quality data with operational process data. The "Advanced Quality Control" approach offers a hands-on learning opportunity in the execution of a manufacturing process and, at the same time, emphasizes the importance of capturing data that at first view seems irrelevant but is later important for root cause analysis. The key didactic elements are manipulated workpiece carriers that cannot be identified without a detailed final inspection (e.g. using a coordinate measurement machine). Manipulated carriers lead to misalignments of the workpiece during exemplarily a drilling process and therefor to a geometrical deviation. Using of smart factory infrastructure, robot-assisted drilling is utilized to achieve the required level of process accuracy and stability. An additional objective of the contribution is to facilitate understanding and implementation of quality principles in general. AI-based data analysis is being addressed as a teaching content.

In the transition to a circular bioeconomy, engineered wood products can help achieve environmental policy targets. Wood has been used as a raw material for various industries for centuries and the automotive industry could utilize wood as a structural component in vehicles. This study investigates the environmental performance of a battery compartment for electric vehicles that relies on engineered wood as a structural component. In a life cycle assessment, the wood hybrid battery compartment was compared to an industry standard over its whole life cycle with two differing end-of-life scenarios. The results indicate that the wood hybrid battery compartment creates substantially less impact over its whole life cycle. The biggest potential for impact savings is identified in the resource extraction- and production phase. In the use phase, the lightweight battery compartment also generates less environmental impact since the use of engineered wood leads to a more lightweight vehicle overall. A material reutilization of engineered wood components in the end-of-life phase further reduces the environmental impact of the wood hybrid battery compartment. The results of this study indicate that the manufacturing of wood engineered structural components for electric vehicles is beneficial from an environmental perspective.

Powder based additive manufacturing systems often require support structures for overhanging geometries and thermal dissipation. On the one hand, the support material should be reduced to a minimum. On the other hand, the stiffness of the structures can be used as a fixture for post-processing. The contribution presents a unique analytic model to determine the stresses occurring in the support structures during post-processing. FEM simulations with different support types are carried out to validate the new calculation model. The results of this analysis subsequently serve as basis for dimensioning the support elements of complex and large parts. By specifying a machining process, it is possible to determine the required dimensions of the support structure (e.g. block, rod, or cross). The aim of this optimization process is to reduce machining time, material consumption and post-processing costs. The results of this contribution and the new software help to implement direct machining into industrial 3D printing processes.

AbstractPowder based additive manufacturing systems often require support structures for overhanging geometries and thermal dissipation. On the one hand, the support material should be reduced to a minimum. On the other hand, the stiffness of the structures can be used as a fixture for post-processing. The contribution presents a unique analytic model to determine the stresses occurring in the support structures during post-processing. FEM simulations with different support types are carried out to validate the new calculation model. The results of this analysis subsequently serve as basis for dimensioning the support elements of complex and large parts. By specifying a machining process, it is possible to determine the required dimensions of the support structure (e.g. block, rod, or cross). The aim of this optimization process is to reduce machining time, material consumption and post-processing costs. The results of this contribution and the new software help to implement direct machining into industrial 3D printing processes.

As the production engineer of the future operates in a global market environment, a common language for the exchange of technical product information is required. This need has been met with the introduction of the ISO-GPS-system for codifying geometric product specifications. While this standard has been applied in the area of quality assurance for a long time, its importance in the early stages of product design along the lines of functional tolerancing has so far not been recognised sufficiently. In order to address this shortcoming, a new laboratory concept has been developed in the “smartfactory@tugraz”, the learning factory of Graz University of Technology. In it the basics of functional tolerancing are taught within the context of manufacturing precision parts for a hydraulic function assembly. A spool-type pressure relief valve (PRV) is proposed as a suitable function assembly as its operating characteristics are primarily determined by the geometric specifications of the moving spool. Moreover, such hydraulic control valves can easily be modelled and the correlation between geometry and function intuitively understood. Students are provided with a series of machined spools with a targeted variance in their macro and micro geometry. These deviations from the nominal geometry of the spool are then determined using methods of manufacturing metrology. In addition, students conduct functional tests of the valve, which result in a characteristic curve for the respective spool. The valve characteristics determined are then compared with the measured geometrical product specifications and interpreted with regard to design and manufacturing aspects.

The functional properties of a mechanical product are usually defined by the geometrical specifications of its inherent subcomponents.Therefore, any deviation from the design's nominal assigned values, can potentially lead to loss of functionality and failure to meet quality criteria.In order to ensure product functionality such deviations have to be limited by the assignment and allocation of tolerances.The conventional product development process described in VDI 2221, however does not sufficiently emphasize the importance of tolerance design principles in the early stages of product development.This shortcoming has been met by integrating Taguchi's robust design methodology alongside the VDI guidelines, thus introducing the tasks of tolerance design and process planning to the product development engineer.In this contribution a use case for the application of such wholistic tolerancing approaches is being proposed.A spool type pressure relief valve thereby serves as a function assembly for studying the relationship of the valve's geometrical properties and its resulting functional performance.Functional testing, geometrical inspection and mathematical modelling of the transfer function, are the methodologies used for allocating appropriate tolerance values to the parts.

In recent years, research in the field of fuel cells is gaining momentum. Leading automotive industries are investing in e-mobility. In fuel cell research, topics such as fuel cell durability, degradation phenomenon, catalyst performance enhancement, etc., are mainly researched upon. However, one fails to recognize the need for innovations in the area of assembly systems for the stacking process. In this paper, a modular approach referencing the gripping of bipolar plates and the membrane electrode assembly layers for the stacking process is postulated. A vacuum end-effector (VEE) gripper is innovated, designed, and manufactured using 3D printing methods. It is then tested in real-time at the maximum acceleration of the Cobot. The cycle time of assembly per unit cell achieved was 1.25s; for comparison, manual stacking per unit cell is averaged to approx. 8s. Therefore, huge potential savings in assembly time was denoted. Additionally, the benefit of using a vacuum end-effector gripper mitigates the particulate matter induced via manual handling. This prevents the early degradation of the fuel cell. The assembly technology and the demonstrator postulated in this paper integrates a complete loop of design, manufacturing, and assembly of the VEE gripping mechanism.

Additive manufacturing has found its way into industrial series production. However, market growth has only been possible through the introduction of new AM-technologies and the continuous improvement of existing processes. This contribution covers the practical implementation of a prototype for research and validation of the unique SLEDM process patented by TU Graz. The demonstrator includes a feature for powder coating for the melting process as well as the concept of power input via an LED-based light source. The prototype enables a now simple and fast melting of different low-melting powder materials, such as tin, zinc, and aluminum, within an inert gas atmosphere. In addition, the experimental setup forms the basis for the development and adaptation of a suitable light source for the next generation SLEDM process. The goal is to test the additive manufacturing concept with the innovative LED light source and analyze the produced metal parts. The evaluation of the recorded measurement data and the analysis of the test results provide important knowledge about the potential of the SLEDM process for further research and industrial manufacturing. In the future, the individual control of the LED-cells in the matrix can be utilized for optimized temperature profiles in the melting zone and for the reduction of the energy demand of the machine. Overall SLEDM helps to fulfil the targets of sustainable production addressing both the material and energy aspect.

The paper deals with a novel design of a combined machine tool in comparison with known contemporary analogues. It is designed for multifunctional machining of workpieces in one or two setups in collet and centre-to-centre design. Typical of this machine tool is the use of a bed with a trapezoidal cross-section with inclined longitudinal guides on both sides for the slides used for rough, fine and finish machining. With this design, the slides are spatially separated and lightly loaded. The material removal during roughing and finishing is separated from each other. The grinding slide and its guides are not subjected to additional thermal deflections caused by the high -temperature crisps produced during turning, and the slide for roughing and finishing is spatially protected against the influence of grinding powder. The bed meets the requirements for a thermos symmetrical design and allows internal cooling. The advantages of this arrangement from the design, technical and economic points of view are presented.

The cutting process of oak (Quercus robur) was investigated by means of a novel testing approach. A unique testing device, enabling nearly linear stand-alone cuts, was used. The specimens climatized to 6 different moisture content levels were machined within cutting velocities ranging from 5 to 80 m.s(-1), at 5 cutting fibre angles from along to across the grain, and at different uncut chip thicknesses of up to 0.5 mm. The precise quartz sensor utilized for observing cutting forces enabled insights into the cutting mechanism involved while wood disintegration. Cutting velocity evolved as a key process parameter strongly influencing cutting force. Evaluation of uncut chip thickness showed a regression that was strongly influenced by particular force components. The friction force generated by "ploughing" the surface was relevant when cutting thin chips. In contrast, the part of force introduced by chip formation affected the process weightily in the case of cutting a thick chip. When cutting parallel to the grain lower forces were observed than cutting perpendicular to grain orientation. Obtained data supported the mathematical force prediction model establishment involving several parameters (e.g. cutting velocity, cutting fibre angle, uncut chip thickness, and moisture content). [GRAPHICS] .

AbstractProduktionen müssen sich immer kürzeren Produktionszyklen, hohen Nachfrageschwankungen und häufigeren Produktwechseln stellen. Dies erfordert, dass Produktionsanlagen agil und modular gestaltet sein müssen, damit der Aufwand für die Rekonfiguration des Systems möglichst gering ist. Im folgenden Beitrag wird das Konzept für eine automatisierte Rekonfiguration einer Produktion mit einem modularen Layout dargestellt. Die prototypische Umsetzung dieses Konzeptes erfolgt in der smartfactory@tugraz.

The handling, positioning and forwarding of components and products are immanent processes at industrial shopfloors. To a high extent they still are still done manually because even semi-automated concepts seem to be once costly and secondly unnecessarily rigid and inflexible. With the intention to keep humans in the working system and also using the benefits of automation in terms of pick-and-place operations one comes up with the established solutions of a robot assisted handling in collaboration with vision-based detection systems. This allows a certain degree of agility without the need of hard structured working environments and can be mastered at reasonable efforts. But where can you independently come into touch with such systems and learn it?The learning factory of Graz University of Technology offers laboratory exercises, where the students and interested people from industry meet an infrastructure where they can learn to program vision-based pick-and-place operations from zero. They learn to teach a collaborative robot to be moved, previously defined objects to be recognized and they are confronted with various challenges for achieving best learning outcomes. The steady supervision of the instructors and the mandatory laboratory reports of the students do not only provide valuable inputs for improvements of the lecture but also give a good overview which tasks and parts of this learning program are most challenging for newcomers in this field of advanced technologies.

The reduction of CO2 by moving from fossil to renewable energy sources is currently high on the agenda of many governments. Simultaneously these governments are also forcing the reduction of energy consumption. The primary focus of these agendas is on mobility, building, and industrial sectors. For the latter, energy efficient shop floors and machining processes assist the reduction of energy consumption. Previous research has focused on energy-efficient machining strategies during machining processes. However, an energy-efficient start-up of these machines or their spindle axis start-up has been neglected until now. This paper focuses on this neglected issue by comparing the energy-efficiency, production time, and cost-efficiency of the CNC (computer numeric control) machine by varying the power input at the spindle axis. This is done by analysing the high frequency data (500Hz) of the machine from machining operations that is retrieved via the edge device. Concepts of data analytics and especially EDA (exploratory data analytics) were used to interactively visualize the inter-dependencies and develop results. It is shown that optimized reduction of spindle power input value leads to both: peak power smoothing from 20kW to 10kW and lowering of overall energy consumption by approximately 1.4%. Moreover, the costs and production time are marginally affected (0.518% and 0.523% respectively) by this optimized reduction of spindle power input value. Thus, this paper highlights a novel method from data acquisition to process improvement towards energy-efficient and sustainable machining.