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Institute
„Promovieren? Promovieren!" Mit diesem Slogan wirbt das FIR an der RWTH Aachen in seinen Stellenanzeigen für die industrienahe Promotion am Forschungsinstitut. Was junge Hochschulabsolvent:innen der Ingenieur- und Wirtschaftswissenschaften dazu motiviert, diesen Weg zu gehen, welche Erfahrungen sie am FIR machen und welche Perspektiven die Mitarbeit sowie die Promotion am FIR für ihre zukünftige Karriere eröffnet, beantworteten Dr. Jana Frank, ehemals Bereichsleiterin Dienstleistungsmanagement am FIR und heute 'Country Business Head' für Singapur und Malaysia bei der Henkel AG & Co. KGaA sowie Antoine Gaillard, seit Februar 2022 wissenschaftlicher Mitarbeiter des FIR an der RWTH Aachen im Bereich Produktionsmanagement.
SynLApp: Assistenzsystem für die wechselseitige Synchronisation der Produktions- und Interlogistik zur Effizienzsteigerung von KMU
Ziel des Forschungsprojekts 'SynLApp' war die Optimierung der Schnittstelle Laderampe durch die Entwicklung einer Lösung zur Synchronisation von Produktions- und Interlogistik
Aufgrund verschiedener Faktoren gestalten Unternehmen ihre Wertschöpfungsketten nachhaltiger. In diesem Zusammenhang gewinnt die Rückführung von Altprodukten an Bedeutung. Die Reverse-Logistics optimiert die damit verbundenen Prozesse. Damit einher gehen Herausforderungen wie schwankende Mengen an zurückgehenden Produkten und unvorhersehbare Rückläufe. Im Rahmen des Forschungsprojekts DiCES entstehen digitale Modelle, mit denen sich eine Kreislaufwirtschaft kostengünstig umsetzen lässt.
Climate change, one of the most significant threats to humanity, underscores the urgent need to advance the circular economy, particularly in promoting sustainability. Implementing R-strategies such as refurbishment and remanufacturing within the home appliances industry is central to establishing sustainable and environmentally friendly business models. Key processes, such as workpiece disassembly, reassembly, and component status evaluation, are inherently more complex and variable than conventional production workflows. This requires workers with extensive experience handling comparable products and a deep understanding of critical decision-making processes. Due to the skilled worker shortage and the impact of demographic shifts, developing precise and comprehensive work instructions is increasingly vital for maintaining process quality. A worker assistance system is essential to meet this need, providing robust decision support to ensure accurate and sufficient decision-making. This paper proposes a framework for a worker assistance system tailored to the application of R-strategies in washing machine production. Data from an industrial scenario validates the framework and identifies critical information that should be incorporated into the system, enhancing the applicability and feasibility of the framework in real-world contexts. Within the framework, potential data sources and information flows are proposed, and illustrative processes are employed to demonstrate the derivation of work instructions utilizing the framework.
The research outlines a concept to conduct the double materiality assessment through the synergistic use of Generative AI and the AHP method. In the first step, we employ interactive, moderated workshops as our chosen methodology to create a tailored set of sustainability target criteria. This process is enriched by the inclusion of Generative AI. The outcome is a comprehensive set of company-specific sustainability target criteria.
Circular Economy (CE) has a low implementation rate so far, despite its many environmental and economic benefits. The concept of Upgrade Circular Economy (UCE) aims to address the existing challenges by aiming for a more continuous value enhancement of circular products and an industrialization of the associated processes. Digital Product Passports (DPP) are a key component of the concept as they act as a data hub for the circular value network. However, their prevalence in industrial practice is low. The aim of this work is to extend a concept for the integration of DPPs into the existing system landscape of manufacturing companies to advance the implementation rate. The core aspects of the work are the derivation of new use cases and data requirements that arise in an UCE, the formulation of evaluation options and implementation recommendations for the DPP, as well as examples for the concrete implementation of event technology. The aim is to provide manufacturing companies with practical options for the use of DPPs as a basis for the implementation of UCE.
The transformation from linear to circular production is cornerstone for mastering sustainability. The fundamental aspect is that products from the utilization phase are fed back into the production phase, and a corresponding reverse supply chain exists for this purpose. Although various models for supply chain networks for value-retention circular economy strategies already exist in the scientific literature, there is a lack of decision rules for designing a suitable supply chain network. This paper aims to derive characteristics for selecting an appropriate supply chain network for value-retention circular economy strategies and to discuss rules of action based on case study research according to Yin.
The transition from linear to circular value-preserving models poses significant challenges, particularly in the context of Reverse Logistics. Variability in returned products in terms of time and quality and logistical complexities referring to decentralized and central factories hamper implementation. While digitalization offers the potential to optimize these processes, many companies lack a structured, scalable, and interoperable approach for integrating digital tools into Reverse Logistics. Moreover, the concept has largely been neglected and limited to managing returns from quality and warranty claims. Existing Enterprise Architecture Models frequently fall short in addressing challenges such as product condition and variability, independence from proprietary systems, and the integration of multiple Circular Economy (CE) strategies thereby constraining their practical applicability. The present paper aims to address these gaps by proposing a generic, vendor-independent, data-driven architecture model that enables companies to implement efficient, sustainable Reverse Logistics in alignment with CE goals. This model fulfills the pressing need for practical frameworks that support interoperability, reuse of existing IT infrastructure, and comprehensive process transparency. Consequently, organizations will be empowered to implement smart Reverse Logistics and to meet regulatory demands, resource efficiency targets, and consumer expectations for sustainable products. Furthermore, the model should serve to meet national and supranational environmental protection targets.
