670 Industrielle Fertigung
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Selective Laser Melting (SLM), also commonly referred to as laser powder bed fusion (LPBF), has become a widely adopted technology in metal additive manufacturing for both industrial and research applications. However, many commercial LPBF systems are based on closed hardware and software architectures, which limit transparency, process monitoring, and direct parameter manipulation during ongoing builds. While recent industrial machines increasingly provide standardized interfaces such as OPC UA for monitoring purposes, fine-grained, layer-wise process control remains restricted. The One Click Metal MPrint+ exemplifies this paradigm by relying on proprietary container-based job execution prepared using commercial software tools such as Autodesk Netfabb or Autodesk Fusion 360. This contribution presents an alternative approach that enables user-defined control of the MPrint+ system through a custom-developed G-code handling framework. Instead of executing complete print jobs as opaque containers, the proposed method establishes a direct network connection to the printer using its gRPC interface. Externally generated G-code is extracted, processed, and transmitted layer-wise to the machine, enabling direct interaction with the build process beyond standard job execution. The approach allows controlled variation of process parameters such as exposure strategies, hatch patterns, or recoating behavior during an ongoing build, thereby supporting efficient design-ofexperiment studies without requiring multiple independent print jobs. In addition, individual G-code commands can be executed interactively, enabling didactic use cases in which machine behavior can be directly observed and linked to abstract toolpath descriptions.
Material flow simulation, by means of discrete event simulation (DES), is frequently applied to support decision-making in production planning and control. However, manual modeling can be time-consuming and error-prone. Hence, numerous studies propose the automation of model generation and synchronization to overcome these challenges. However, in this context, validation techniques are rarely addressed. Therefore, we introduce a subjective validation technique for short-term material flow simulation based on a coherent methodology for data acquisition and visualization. The methodology is utilized to evaluate the outcome of an approach for computerized model generation and simulation. By means of an industrial use case, we hypothesize the causes for the deviation between the operation of a manufacturing system and the simulation of its generated virtual companion.
Material flow simulation, by means of discrete event simulation (DES), is utilized in various industries to support production planning and control. This is due to the fact that changes to manufacturing systems and production strategies can be virtually examined before actual implementation. Since the manual development and repeated adjustment of simulation models is time-consuming and error-prone, numerous studies suggest computerized model generation and synchronization. However, validation of such generated or synchronized models is rarely considered. Here, we present an extendible objective validation technique for the repeated short-term simulation of a generated model. To illustrate this, the technique is applied to a high-volume automotive production line and a series of simulation cycles.
Im Kontext der fortschreitenden Digitalisierung und Automatisierung hat die vorausschauende Wartung, auch Predictive Maintenance (PdM) genannt, insbesondere in industriellen Produktionslinien an Bedeutung gewonnen [1]. Wirtschaftliche Faktoren wie steigende Energiekosten, geringe Stillstand- und Instandhaltungszeiten aber auch die Möglichkeit des Monitorings unterstützen diesen Trend [2]. Diese erfordern im Umkehrschluss neben der technischen Expertise auch eine bedarfsorientierte Qualifizierung sowie ein systemübergreifendes Verständnis. Um diesen Bedarf gerecht zu werden, kann das Thema theoretisch sowie praxisnah behandelt werden. Da nicht für jeden Bildungsbetrieb entsprechende Produktionslinien zur Qualifizierung und Erprobung von (neuen) Ansätzen im Bereich des PdM zur Verfügung stehen, benötigt es Lehr- und Trainingsanlagen, die der Ausbildung von Fachkräften dienen. Solche Anlagen ermöglichen es, Produktionsprozesse abstrakt aber trotzdem in einem realitätsnahen Umfeld zu simulieren, wodurch sich Instandhaltungsstrategien wie PdM praxisnah anhand von Kennzahlen erlernen und erproben lassen. Der vorliegende Beitrag erläutert den Aufbau einer Lehr- und Trainingsanlage zur Simulation von PdM Anwendungen für die Qualifizierung von Auszubildende und Ingenieure und die dabei zu beachtenden Herausforderungen.
This publication demonstrates that determining the maximum speed or Ideal Cycle Time (ICT) of machinery or cyber-physical systems is crucial for uncovering the limits of automation in a given system. Possibly increasing Overall Equipment Effectiveness (OEE) and identify opportunities for further digitization, automation, and AI integration. Based on literature review and expert interviews, methods for establishing ICT, mentioned in literature were identified and crosscheck with what practitioners in operation actually use and how they apply them. The identified methods were: Empirical Measurement and Data Analysis, Time Studies, Statistical Process Control (SPC), Benchmarking, Simulation and Modeling, Expert Judgment, and Continuous Improvement Practices we. We contrast these with insights obtained from interviews conducted with experts from companies in the German federal State of Brandenburg, representing diverse industries and sectors. Findings suggest that while companies recognize somewhat their ICT or maximum operational speeds, they often lack a structured method for determining them. They frequently use combinations of established methods inconsistently. We deduce that a formalized approach to defining ICT can better reveal system limitations and potential for expanding them through advanced automation and. We argue that a well-defined ICT is essential for pushing the boundaries of automated systems, contributing to more effective and Humanity–Centered Automation (HCA) solutions.
The increasing integration of large language models (LLMs) into cyber-physical production systems, necessitating solutions that are both efficient and aligned with human values and needs. Designing effective and reusable prompts is crucial for creating cyber-physical systems(CPS) that are effective, flexible, reliable, user-friendly and aligned with Humanity-centered Automation. This paper introduces essential components of reusable prompts: Versioning, Model Selection, Purpose Definition, Variables, Examples, and Output Structuring. By applying the proposed components, developers might enable CPS employing LLMs to operate with more predictable inputs and outputs, enabling better control over results and facilitating the chaining of multiple prompts or collaboration between different LLMs. These components emerged from extensive experimentation with various LLMs and prompt configurations. The resulting framework supports the maintenance of prompt collections similar to codebases and thus enhances traceability, maintainability, and human oversight. Such structured components for prompt design supports humanity-centered automation by ensuring that technological advances serve human values and improve interaction with complex systems.
EU-Verordnungen und ISO-Normen verändern die Nutzung von Industrieroboter und beeinflussen deren Integration in effiziente Produktionssysteme. Die rasante Entwicklung der Digitalisierung und die Notwendigkeit einer umfassenden Vernetzung haben Auswirkungen auf die Sicherheit von Maschinen, die Gestaltung von Arbeitsplätzen und die Anforderungen an die Ausbildung der Beschäftigten. Mit einer Reihe von Gesetzen und Richtlinien schafft die EU einen Ordnungsrahmen für die aktuellen Technologien und versucht, die Rahmenbedingungen für weitere Entwicklungen festzulegen. Gleichzeitig ist die Industrie gefordert, zusätzliche Kompetenzen in bestimmten Bereichen der Digitalisierung aufzubauen. Einige Herausforderungen sind jedoch noch zu bewältigen, z. B. wie der Sicherheitsnachweis für in Maschinen integrierte Künstliche Intelligenz für autonome mobile Roboter erbracht werden kann, wie die Zertifizierung von Software als Sicherheitselement und dessen Integration in die Automatisierungssysteme und wie die Behandlung von Industrierobotern als vollständige und nicht mehr als unvollständige Maschinen erfolgen wird.
Over the course of the last decade 3D printing has become a more established technology in terms of prototype development (rapid prototyping). The current effort is focused on transferring this knowhow into a product driven approach in order to manufacture even small batch sizes more economic. In terms of this work, this idea is adapted for the development of injection molds (rapid manufacturing). Hereby, a hardened polymer is used to create a forming cavity instead of tool-steel. In order to fulfil the mechanical process requirements of micro injection molding such as form stability under temperature and pressure this cavity is nevertheless integrated into a metal housing. A first set of experiments has been carried out using this develop mold to verify the capabilities of the developed prototype as well as molding process. Based on these first results, an optimization is carried out to improve the next iteration of this molding tool.
3 dimensional (3D) printing evolved during the last decade to a consumer friendly and affordable craft. Furthermore, implementations of this techniques in the field of biotechnological research and development within laboratories is a very expansive process. Bio-printers’ prices cover a wide spectrum and most basic models are available for around 5000€. On the other end, high-end printer machines with a vast variety of features are available for several hundreds of thousands of euros. Thus, due to the immense potential in the field of Biotechnology the availability of this technology for research purpose should be enhanced. A developed ecological syringe extruder prototype for processing of biological based gels has been further improved. The original prototype was capable to processing multiple layers of agar with concentrations of 1% and 2.5%. Based on these results the prototype was revised regarding printing process parameter, which include among others applied forces to the substrate, air-ventilation, and heating of the substrate. The process behavior will be simulated with computational fluid dynamics for the processing of biological based substrate. After a concluding validation these results are intended to be implemented into a new design for improved processing of a variety of bioinks.
The operation of manufacturing systems is increasingly accompanied by data-driven continuous improvement processes and product traceability is required. Commonly, radio-frequency identification (RFID) technology is applied to track the flow of a uniquely-identifiable workpiece along various stations or waypoints within a factory. Based on an automotive use case, this paper describes how to analyze the resulting traceability data in order to identify several properties of a manufacturing system. The acquired knowledge can support performance evaluation and facilitate model building for material flow simulation as a foundation for digital twins and cyber-physical production systems.

