Andreas Mayr

Friedrich-Alexander-University Erlangen-Nürnberg | FAU · Institute for Factory Automation and Production Systems (FAPS)

Enameled copper wire is a crucial material for the production of modern electrical machines. With the advent of hairpin windings, copper wire with rectangular cross-section is gaining importance. Being delivered on coil carriers, the wire is subject to initial curvatures which must be leveled out before further processing. Since common straightenin...

Electric traction motors must meet high requirements in terms of efficiency in driving operation as well as cost-effectiveness in manufacturing. The so-called hairpin technology yields potential for both aspects. However, a central bottleneck in hairpin stator manufacturing is the contacting process, commonly performed by laser welding, where a lar...

In the meantime, the final full paper has been published: http://dx.doi.org/10.1016/j.procir.2023.06.150

Die deutsche Automobilindustrie steht angesichts der Elektromobilität vor einem radikalen Wandel. Um ihre Technologieführerschaft beizubehalten, stehen die F & E-Abteilungen der etablierten Akteure unter hohem Druck. Im Rahmen dieses Beitrags wird gezeigt, wie sich ein passgenaues Kennzahlengerüst für das Controlling des operativen F & E-Prozesses...

In the course of series production of high-performance automotive traction motors, the so-called hairpin technology is increasingly coming into focus. An essential process step is the bending of the hairpins, which is significantly influenced by variations in the wire material. Therefore, this paper will investigate how machine learning techniques...

Robot-centric automation solutions (RAS) promise greater efficiency and consistent quality in production, relieving workers of physically demanding and dangerous tasks, especially in the times of COVID-19. Nevertheless, due to their relatively high complexity and implementation costs, RAS are only used to a limited extent by small and medium-sized...

Die Verfahren des maschinellen Lernens eröffnen neue Möglichkeiten, Daten nutzbringend auszuwerten und dadurch den Intelligenzgrad von Maschinen und Anlagen zu erhöhen. Dieser Beitrag umreißt, mit welchen Herausforderungen der Einsatz von maschinellem Lernen im Produktionsumfeld einhergeht, und zeigt aktuelle Trends sowie beispielhafte Anwendungsfä...

In subtractive manufacturing, differences in machinability among batches of the same material can be observed. Ignoring these deviations can potentially reduce product quality and increase manufacturing costs. To consider the influence of the material batch in process optimization models, the batch needs to be efficiently identified. Thus, a smart...

The electric motor production of the automotive industry faces numerous challenges due to weak sales and uncertain sales forecasts of the electric vehicle. To meet these challenges, scalable production systems have increasingly been set up. The application of virtual commissioning to scalable production systems holds increased potential since the d...

With the increasing degree of digitalization in manufacturing industry, advanced data analysis techniques such as machine learning (ML) are moving into focus. In several production processes like machining or welding, ML applications already show high potential for process monitoring, optimization, or control. Although screw fastening and press-in...

The high complexity of today’s automation solutions often raises integration costs to an uneconomic level, particularly for small and medium-sized enterprises. Analyzing the total costs of automation solutions, engineering efforts account for the largest share. However, potentials for time and cost savings as well as quality improvements by reusing...

Digitization within the framework of Industry 4.0 is considered the biggest and fastest driver of change in history of manufacturing industry. While the size of a company is becoming less essential, the ability to adapt quickly to changing market conditions and new technologies is more important than ever. This trend particularly applies to the com...

In the upcoming years, the internet of things (IoT) will enrich daily life. The combination of artificial intelligence (AI) and highly interoperable systems will bring contextsensitive multi-domain services to reality. This paper describes a concept for an AI-based smart living platform with open- HAB, a smart home middleware, andWeb of Things (WoT...

Industry 4.0 is associated with numerous technologies, which offer great potential for optimizing linear winding processes as used in electric motor manufacturing. To further increase flexibility and quality in the production of mass products like coils, data-driven techniques such as machine learning (ML) are increasingly moving into focus. To gen...

The increasing data availability in production processes combined with open source software tools in the field of machine learning (ML) lead to a new level of process improvement possibilities. For many companies, the challenge is now to identify potential use cases with considerable business impact by integrating ML techniques in production proces...

The digitalization in manufacturing offers high potential for optimization in terms of quality and efficiency. In particular, machine learning techniques can be used to analyze data generated along the production chain for complex patterns. As the final product quality highly depends on interactions within the production chain, a process control sy...

Machine learning has often proven superior to traditional white-box modeling in industrial application scenarios. Yet the determinism in finding a solution close to the theoretical optimum is low due to human factors in the development process. Automated machine learning (AutoML), on the other hand, allows a complete automation of the machine learn...

We created an approach for a smart living platform called ForeSight which consists of different modules: a service engineering module, a Web of Things (WoT)-based Internet of Things (IoT) module and an artificial intelligence (AI) component. This paper describes how openHAB, a smart home middleware, is extended to fulfill platform requirements rela...

In the ongoing development of electric traction motors with increasing volumetric power density, concepts are being devel-oped for rotational speeds of more than 30,000 rpm. These motors require an especially high balancing quality. Due to the unavoidable material and production fluctuations, a tuning of the mass distribution regarding the rotation...

Automatic optical inspection (AOI) of solder joints is a common testing process in electronics production. Especially in power electronics production for electric drive systems, such inspection systems are employed for quality control of selective soldering processes for through-hole devices. Up to now, commercial systems rely on rule-based program...

With the increasing demand for electric cars, automobile manufacturers and suppliers are ramping up more and more plants for the production of electric traction motors. In the development of new plants, Industry 4.0 aspects are usually already considered, resulting in a large number of integrated sensors and thus a relatively high data availability...

The interest in artificial intelligence (AI) and its use in industrial production is growing steadily. The increasingly known machine learning, however, is only one of several AI technologies emerging from basic research. Another subarea of AI represent the so-called semantic technologies, which play a decisive role especially in knowledge manageme...

For industrial applications and as traction drives for electric cars, permanent magnet synchronous motors are widely used. They are characterised by excellent dynamic operating behaviour with very good controllability and power density. However, their quality characteristics are influenced by deviations due to material and production variances. One...

Linear winding is one of several process alternatives in coil production. Due to its simplicity and robustness, it is used in various applications. At the Institute for Factory Automation and Production Systems at the Friedrich-Alexander- University Erlangen-Nuremberg, simulation tools are used to validate and evaluate various winding process alter...

The increasing demand for highly efficient electric motors for traction applications leads to novel challenges for electric motor manufacturers. With the use of more advanced motor designs and materials, production processes need to be adapted or even reinvented. To reduce iron losses in ferromagnetic components, the stator and rotor core is lamina...

Artificial intelligence entails a wide range of technologies, which provide great potential for tomorrow's electric motor production. Above all, data-driven techniques such as machine learning (ML) are increasingly moving into focus. ML provides systems the ability to automatically learn and improve from data without being explicitly programmed. Ho...

X-rays have a large range of medical applications and play an important role in imaging diagnostics. However, the ionized radiation that the patient is exposed to during its application is harmful. In order to keep the radiation exposure as low as possible and at the same time improve image quality, the development of X-ray tubes is being pushed to...

The main barriers to the wide acceptance of electric vehicles, such as the limited driving range or the high acquisition costs, are to be countered by various technology alternatives for the powertrain of the future. Promising developments include improved battery technologies, fuel cell technologies or a constant power supply of the vehicle while...

The robotic handling of unsorted parts, also known as bin picking, is still a challenge in industrial automation. Many systems require physical testing and training, resulting in a long commissioning phase. In this paper, a concept for the testing and performance evaluation of bin picking systems based on industrial simulation software is introduce...

Recent trends like autonomous driving, natural language processing, service robotics or Industry 4.0 are mainly based on the tremendous progress made in the field of machine learning (ML). The increased data availability coupled with affordable computing power and easy-to-use software tools have laid the foundation for using such algorithms in a wi...

When it comes to the development of knowledge-based configurators, there is a lack of procedures for the collaborative work on knowledge acquisition and modeling. However, the division of work is inevitable, especially in interdisciplinary application domains such as the configuration of automation solutions. Therefore, this paper presents a practi...

Microservice (MS) architectures, especially in combination with micro front ends, are a modern, scalable and sustainable approach to software development. The modular development of individual components and the possibility of a simple, collaborative and iterative development represent a strategic advantage for companies. In addition, the MS approa...

In future, smart home and smart living applications will enrich daily life. These applications are aware of their context, use artificial intelligence (AI) and are therefore able to recognize common use cases reliably and adapt these use cases individually with the current user in mind. This paper describes a concept for such an AI-based platform....

Simulation is a powerful tool for optimizing energy consumption in manufacturing plants. This paper presents a methodology on how to precisely model the logging of temperature curves of workpieces and machinery in a material flow simulation based on a structured measurement value acquisition. Using Newton's cooling law and regression curves, indivi...

Modeling complex interactions and dependencies in production systems proves effortful in traditional event-based simulation tools mainly relying on a whitebox approach. In this context, the integration of machine learning techniques offers new possibilities for establishing a more efficient modeling of the systems behavior by using historic data. T...

In the production chain of electric drives, the electrical and mechanical contacting of the winding ends with a contact element is a time-consuming and cost-intensive process step. The most common processes, e.g. hot crimping, are characterized by high tool wear and enormous energy consumption. An innovative and at the same time energyefficient pro...

Driven by current developments in the electrification of the automotive drive chain, new technologies for the production of windings for electric drives are focused in automotive industry and research institutes. Especially for the manufacturing of drives with high power density for battery electric vehicles (BEV), the application of distributed wi...

Manufacturers of large electric motors, whether for automation or traction purposes, are facing major challenges in high-wage countries. Due to the high proportion of manual activities, a conflict between ensuring profitability and increasing variant variety arises. In order to meet the high demand for large electric motors and to maintain the valu...

Discrete event simulations are one of the most used techniques by manufacturing system designers. In order to extend the traditional material flow with an advanced energy simulation, this paper presents two specially developed extension modules for the widely used software Tecnomatix Plant Simulation. In contrast to other approaches, the FAPS energ...

Due to the growing individualization and ever shorter product life cycles, the engineering of automation solutions is facing increasing challenges. The rethinking of common engineering processes and the inclusion of knowledge-based approaches are considered inevitable. However, existing optimization measures often do not meet the actual problems as...

Virtual Commissioning increases quality and efficiency in production engineering whilst also decreasing required time. Even though it is a foundation for state-of-the-art production systems, it is not in widespread use yet. In this contribution, an overview of current scientific approaches and use cases for Virtual Commissioning is given. Furthermo...

High quality and low costs are main drivers in electronics production. Regardless of the application, the trend towards batch size 1 heavily challenges current production systems. With higher data availability, the application of machine learning (ML) has great potential for the future of electronics production. Therefore, this paper gives an overv...

Industrie 4.0 geht mit einer Vielzahl an Technologien einher, die großes Potenzial für die Elektromotorenproduktion von morgen bieten. Vor allem datengetriebene Ansätze, die sich der Methoden des maschinellen Lernens (ML) bedienen, rücken zunehmend in den Fokus. Im Rahmen dieses Beitrags wird gezeigt, wie sich die daraus ergebenden Potenziale syste...

Der vorliegende Beitrag vergleicht Six-Sigma- und Data-Mining-Methoden im Hinblick auf das Null-Fehler-Management in Produktionsprozessen. Darauf aufbauend wird ein Six-Sigma-4.0-Prozessmodell abgeleitet, das die Stärken beider Ansätze vereint und somit einen Handlungsleitfaden für Verbesserungsprojekte im Rahmen der Industrie 4.0 bereitstellt. Das...

Die Digitalisierung im Engineering verspricht automatisierte Arbeitsabläufe, höhere Geschwindigkeiten und sinkende Kosten bei der Entwicklung von Automatisierungslösungen. Voraussetzung hierfür ist nicht nur die Modularisierung auf Basis einer strukturierten Beschreibungssprache, sondern auch eine einheitliche, aufeinander aufbauende Modellierung,...

Industry 4.0 (I4.0) is accompanied by a variety of technologies which offer great potential for optimizing the manufacturing of electric motors. However, the application of I4.0 technologies in this sector has hardly been examined yet. For determining I4.0 potentials in the electric motor production, a structured approach is required since the vari...

Requirements for electric traction motors in the automotive context differ significantly from those applicable to industrial electric motors. Innovative production technologies and materials offer optimization potential in motor performance, production characteristics, industrialization and financial key performance indicators. However, those techn...

In the production of electric motors, various manufacturing imperfections occur. These production-related deviations influence the product characteristics concerning power output, efficiency, vibration, noise and lifetime. However, measures to minimize manufacturing deviations are involved with several challenges such as additional measurements, ad...

The market volume of electric drives for industrial applications and electric mobility is increasing steadily. Thus, efficient ways for monitoring and optimizing the production of electric drives are gaining importance. Besides winding, joining or impregnation processes, machining operations have a high share in the production chain. However, devel...

The spread of electric mobility in Germany lags far behind government's targets. High vehicle and energy prices, the limited vehicle range and obligatory time-consuming conductive charging processes are the main obstacles to mass adoption. Strategic mobility concepts, such as electric vehicles with high performance batteries (BEV), hydrogen technol...

In a world of growing electrification, the demand for high-quality, well-optimized electric motors continues to rise. The hairpin winding is one such optimization, improving the slot-fill ratio and handling during production. As this winding technology leads to a high amount of contact points, special attention is drawn to contacting processes, wit...

Due to the increasing areas of application, the development and production of electric motors has become one of the most relevant topics in engineering research. In order to benefit from the growing market demand, companies pursue the adaption of new procedures for enabling an efficient development and manufacturing of electric motors. However, the...

Despite numerous purchase incentives, the spread of electric mobility in Germany is lagging behind expectations and political targets. The main reasons are the high acquisition costs, the limited vehicle driving range and the uncomfortable charging process. With regard to the last two challenges, inductive power transfer (IPT) systems promise great...

Despite numerous research activities, guidelines and regulations, the exploitation of energy and resource efficiency potentials at companies in the field of electric drive technology is still lagging behind. Existing catalogues of measures and research results are mostly too generic or too theoretic for companies, especially for small and medium-si...

There are numerous levers and constraints affecting the sustainability of electric motors. While previous work mostly focuses on individual energy and resource efficiency potentials within single phases of the motor’s lifecycle, this paper summarizes sustainability aspects from three different perspectives, namely from the market, product and proce...

Artificial intelligence (AI) is the overall term for technologies used to build intelligent systems, no matter whether utilized in an industrial or private environment. However, hardly any AI-based approaches have been proposed for the increasingly important electric drives production yet. By identifying and presenting exemplary application scenari...

Machine learning (ML) is a key technology in smart manufacturing. In contrast to common physical simulations, ML algorithms offer insight into complex processes without requiring in-depth domain knowledge. Within the electric drives production, innovative contacting processes such as the ultrasonic crimping are difficult to model and control. Thus,...

Applying lean can boost a firm’s performance significantly by focusing on value-adding activities. Additionally, Industry 4.0 is regarded as another promising trend in industry. Combining these developments resulted in terms like "lean 4.0". However, the existing literature lacks a comprehensive and detailed conjunction of both paradigms. This pape...

Die Verbreitung der Elektromobilität in Deutschland liegt weit hinter den Zielen der Regierung und den Erwartungen der Gesellschaft zurück. Hohe Fahrzeug- und Energiepreise, die begrenzte Reichweite der Fahrzeuge und der umständliche Ladevorgang sind die Haupthindernisse. Diese Hindernisse könnten durch verschiedene technologische Alternativen wie...

Kurzfassung Die Verbreitung der Elektromobilität in Deutschland liegt nach wie vor hinter den Zielen und Erwartungen von Politik und Gesellschaft zurück. Bisherige Hemmnisse der Mobilitätswende sind vor allem die relativ hohen Anschaffungskosten von Elektroautos, die politisch sanktionierten Strompreise, die begrenzten Reichweiten sowie der noch we...

Permanent magnet synchronous motors (PMSM) suffer, depending on the topology, from quality deviations of the used magnets. These can result in insufficient running characteristics, such as low power output, low energy efficiency, consequently excessive heat, strong vibrations and noise. Especially topologies, such as halbach array rotors, are stron...

The development and production of electric drives as mechatronic products involve several engineering domains. With increasing complexity of the individual parts, frequently shifting customer requirements and ever shorter development cycles, integrated approaches are continuing to grow in importance. In this context, an interdisciplinary design met...

Machine learning (ML) is a key technology in data driven industries. In general, ML algorithms offer insight in complex processes by analyzing measured data without acquiring in-depth domain knowledge. In contrast to common physical simulations they do not require excessive computational time and are well suited for real time analysis. This study f...