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Due to Digital Transformation, also called Industry 4.0 or the Industrial Internet of Things, the barrier for implementing data collecting technology on the shop floor has decreased dramatically in the past years – leading to an increasingly growing amount of data from a multitude of IT systems in production companies worldwide. Despite that, the production controller still relies heavily on intrinsic knowledge and intuition for the management of disruptions in production. Thanks to advances in the fields of production control and artificial intelligence, potentials for the collected data for disruption management arise. However, in order to transform data into usable information and allow drawing conclusions for disruption management in production, the relevant data-objects, disturbances and alternative actions must be known. Thus, the decision-making can be supported, reducing the decision latency and increasing benefit of alternative actions. Therefore, the goal of this paper is to discuss the prerequisites necessary to perform a data based disruption management and the methodology itself, serving as an approach to allow companies to build a data basis, classify disruptions and alternative actions in order to improve decision making in the future. [https://link.springer.com/chapter/10.1007/978-3-030-28464-0_13]
High Resolution Supply Chain Management (HRSCM) aims to stop the trend of continuously increasing planning complexity. Today, companies in high-wage countries mostly strive for further optimization of their processes with sophisticated, capital-intensive planning approaches. The capability to adapt flexibly to dynamically changing conditions is limited by the inflexible and centralized planning logic. Thus, flexibility is reached currently by expensive inventory stocks and overcapacities in order to cope with rescheduling of supply or delivery. HRSCM describes the establishment of a complete information transparency in supply chains with the goal of assuring the availability of goods through decentralized, self-optimizing control loops for Production Planning and Control (PPC). HRSCM pursues the idea of enabling organization structures and processes to adapt to dynamic conditions. The approach includes the strengths of the existing planning models as well as the process of decision making in organizations. A precondition for this decentralized adaptation is the synchronization of the objectives of the several units or process owners. The basis for this new PPC Model are information transparency, stable processes, consistent customer orientation, increased capacity flexibility and the understanding of the production system as a viable, socio-technical system.
Raus aus der Schockstarre!
(2019)
Nie war die Stellung von vermeintlichen Marktführern unsicherer als im Zeitalter der Digitalisierung. Die neuen technischen Möglichkeiten, in innovativen Geschäftsmodellen Wert aus der explodierenden Datenmenge zu schöpfen, wirbeln den Markt durcheinander. Wer mit dem technischen Wandel nicht mitgeht, riskiert, rasch abgehängt zu werden. Die gute Nachricht: Der Weg zur Industrie 4.0 ist ein Weg der kleinen Schritte. Überschaubare Maßnahmen heute sind allemal besser als der ganz große Wurf übermorgen.
Digitalization is changing the industrial landscape in a way we did not anticipate. The manufacturing industries worldwide are working to develop strategies and concepts for what is labelled with different terms such as the Industrial Internet of Things in the USA or Industrie 4.0 in Germany. Many industrialized economies are driven by the production sector and this sector needs specific approaches and instruments to take up other than those approaches we know from start-ups and ventures coming from Silicon Valley and other places. In this paper, we demonstrate an appropriate approach to transform producing companies in a systematic and evolutionary approach.
In particular, the objective of this paper is to provide results from two initiatives which conceptually build upon each other and are of particular relevance for the production industry. First, we present a global survey on the state of implementation and the future perspectives of the concept Industrie 4.0 from 2016. Findings from this study have forced parts of the German industry to heavily invest into a common approach to accelerate change towards Industry 4.0 in order to stay competitive in worldwide economy. This approach is presented in a second part.
Subscription business transforms traditional business models of machinery and plant engineering. Many manufacturing companies struggle to pull out the potential created by Industry 4.0 and make it economically usable. In addition to technological innovations, it is necessary to transform the business model. This leads to a shift from ownership-based and product-centric business models to outcome-based business models, which focus on the customer's value and thus realize a unique value proposition and competitive advantage – the outcome economy. Based on a case study analysis among manufacturing companies, this paper provides further clarification including a definition and constituent characteristics of subscription business models in machinery and plant engineering.
Klar Schiff
(2009)
Im Rahmen dieser Studie untersuchten das Forschungsinstitut für Rationalisierung e. V. an der RWTH Aachen und die Universität St. Gallen
(Lehrstuhl Produktionsmanagement) 24 Veröffentlichungen von 11 Beratungsunternehmen. Dabei wurden über 200 Aussagen zur Bewältigung der Krise bewertungsneutral identifiziert und analysiert.
More and more manufacturing companies are starting to transform the transaction-based business model into a customer value-based subscription business to monetize the potential of digitization in times of saturated markets. However, historically evolved, linear acquisition processes, focusing the transactionoriented product sales, prevent this development substantially. Elemental features of the subscription business such as recurring payments, short-term release cycles, data-driven learning, and a focus on customer success are not considered in this approach. Since existing transactional-driven acquisition approaches are not successfully applicable to the subscription business, a systematic approach to an acquisition cycle of the subscription business in the manufacturing industry is presented, aiming at a long-term participative business. Applying a grounded theory approach, a task-oriented model for themanufacturing industry was developed.
The model consisting of five main tasks and 14 basis tasks serves as best practice to support manufacturing companies in adapting or redesigning acquisition activities for their subscription business models.
High Resolution Supply Chain Management aims to counteract the trend towards more and more centralised and rigid enterprises. Today, most companies strive to increase efficiency of business processes applying highly sophisticated, centralised planning approaches. These centralised approaches limit the companies’ ability to react flexibly and act adaptively due to external and internal turbulences. In today’s buyer’s markets companies usually try to bypass these turbulences keeping high levels of inventory resulting in a low overall efficiency. High Resolution Supply Chain Management tries to solve the problem at its root from a holistic perspective. Based on the Viable System Model developed by Stafford Beer a four-dimensional holistic production management system model, embedding an organisational structure view, an cause and action view, a control loop perspective and a decision making level has been elaborated. The basis of this model is the integration of all four perspectives into an interacting framework.
Machine Learning
(2019)
In recent years supply chain participants are increasingly suffering the effects of disturbances in transportation supply chains. Both, dynamics in consumer demands and global supply chains lead to a growth in unplanned supply chain events. These can cause from rather manageable disturbances through to complete break-downs of transportation chains, resulting in high follow-up and penalty costs.
Consequently, concepts for an efficient supply chain disturbance management are needed, preferably with a real-time identification and reaction to disturbance events. Therefore in the following paper the research results of the German research project Smart Logistic Grids with the focus on designing an integrated model for the real-time disturbance management in transportation supply networks are presented. This includes the introduction of elaborated classification models for disturbances and action patterns as well as an associated costs and performance measurement system. Finally, a procedure model for the disturbance management is presented.
Das Gegenteil von Theorie ist die Praxis. So sagt man landläufig und unterstellt damit oft, dass wissenschaftiche Erkenntnisse nicht immer für den Alltag taugen. Dass Theorie aber nicht gleich Theorie ist und Wissenschaft und Praxis trotz aller Unterschiedlichkeit aufeinander angewiesen sind, darauf weist das
FIR an der RWTH Aachen schon mit der Auflösung seines Akronyms hin: „Forschung. Innovation. Realisierung."
Industrie 4.0 ist in Politik, Medien, Wissenschaft und Wirtschaft derzeit omnipräsent. Intelligenter, individueller, effizienter, schneller, vernetzter – so lauten nur einige Versprechen dieses neuen industriellen Zeitalters. Tatsächlich sind die Potenziale gerade für den deutschen Maschinen- und Anlagenbau gewaltig: Sowohl für Anbieter als auch für Anwender von Technologien rund um das Thema Industrie 4.0. Aber noch existieren viele ungelöste Fragen, Unsicherheiten und Aufgaben. Hier wollen wir mit unserer Readiness-Studie ansetzen und Hilfestellung leisten. Denn ein Selbstläufer wird Industrie 4.0 nicht. Mit der vorliegenden Studie soll die große Vision näher an die betriebliche Realität gebracht werden. Auch zeigen wir die anspruchsvollen Wegmarken auf, die für viele Unternehmen hinsichtlich ihrer Industrie 4.0-Fähigkeit noch zu passieren sind. Die Studie untersucht, an welcher Stelle der Maschinen- und Anlagenbau aktuell bei der Umsetzung steht. Motivation und Hemmnisse der Unternehmen werden ebenso in den Blick genommen wie die Unterschiede, die sich zwischen Mittelstand und großen Unternehmen ergeben. Im Ergebnis ist es erstmals möglich, die „Industrie 4.0-Readiness“ der Maschinenbau-Industrie detailliert und systematisch abzubilden.
Nachhaltige Lieferketten
(2021)
Das Thema der Nachhaltigkeit ist nicht zuletzt aufgrund aktueller Entwicklungen zunehmend in den gesellschaftlichen und unternehmerischen Fokus gelangt. Pandemien, Naturkatastrophen, aber auch regulatorische Auflagen zur Erfüllung von Klimaschutzzielen haben zu einem Umdenken geführt. Im Rahmen des Thementags „Sustainable Supply-Chain-Management“ hat das FIR an der RWTH Aachen zusammen mit Expert:innen aus Wirtschaft und Forschung Thesen erarbeitet, die widerspiegeln, wie das Thema Nachhaltigkeit aktuell in deutschen Unternehmen wahrgenommen und umgesetzt wird und welche besondere Bedeutung dem Supply-Chain-Management dabei zukommt. Nachhfolgend werden diese und deren Implikationen für die Praxis vorgestellt.
Zusammenfassung und Ausblick
(2012)
Aufgrund kürzer werdender Produktzyklen und steigender Produktvielfalt werden produzierende Unternehmen mit einer zunehmenden Anzahl von Produktanläufen konfrontiert. Ziel aktueller Forschungsaktivitäten ist es daher, anlaufintensive Unternehmen zu befähigen, verlässliche Produktionsprogramme in kurzer Zeit zu erstellen. Lerneffekte sollen genutzt werden können ohne Diversifikationseffekte zu vernachlässigen. Zur Erreichung dieser Zielsetzung wird ein Modell für eine kybernetische PPP bei Produktanläufen entwickelt.
Schwerwiegende Gesundheits- und Wirtschaftskrisen wie die Weltfinanzkrise (ab 2007) oder die Covid-19-Pandemie im Jahr 2020 haben aufgezeigt, in welch turbulentem Umfeld sich die globalisierte Welt heutzutage befindet und wie schnell gewohnte Abläufe in Wertschöpfungsketten unterbrochen und angepasst werden müssen. Die alltäglichen Anforderungen in dem sich immer schneller wandelnden digitalen Zeitalter wachsen stetig und sind komplexer denn je.
Unternehmen sind angehalten, immer kurzzyklischer auf sich ändernde
Bedingungen und Störungen zu reagieren und strategische Entscheidüngen
zur Gestaltung von Wertschöpfungsketten zu treffen. Nur mithilfe
einer umfassenden Datengrundlage und -kommunikation kann die strategische Planung der Supply-Chain effektiv erfolgen und somit die benötigte Robustheit und Agilität ermöglicht werden.
The efficient dealing with the dynamic environment of production industries is one of the most challenging tasks of Supply Chain Management in high-wage countries. Relevant and current information are still not used sufficiently, to handle the influence of the dynamic environment on intra- and inter-company order processing adequately. Among other things, the problem is caused by missing or delayed feedback of relevant data. As a consequence of that, planning results differ from the actual situation of production. High Resolution Supply Chain Management describes an approach aiming on high information transparency in supply chains in combination with decentralized, self-optimizing control loops for Production Planning and Control. The final objective is to enable manufacturing companies to produce efficiently and to be able to react to order-variations at any time, requiring process structures to be most flexible.
Analysis of the Harmonizing Potential of Order Processing Attributes in Spread Production Systems
(2010)
The paper discusses an approach how to measure the competitive advantage of harmonized order processing data by making use of knowledge about the interdependencies between related benefit dimensions. Corresponding harmonization projects are all projects that strive for common structures in product attributes, classification systems or product structures. The main objective of the underlying research work is the development of a method for the estimation of the benefit potential of harmonized order processing data.
Increasing the energy efficiency and meanwhile avoiding unplanned maintenance breaks are keys for manufacturing companies to stay competitive in the future. This paper presents an energy saving and maintenance cost reducing approach for manufacturing environments. The approach describes first occurring types of energy wastage within manufacturing and characterizes them in more detail. Including additional external information, the significance of an identified on-going wastage can be determined. Based on the type of wastage and the significance; concrete recommendations for measures to prevent the wastage are delivered. The identified wastage facilitates detecting inefficient operating mode as well as wearing and malfunctioning at machines. By using complex event processing technologies realtime information can forwarded directly to the responsible persons to enable quick reactions to prevent energy wastage and unplanned downtimes. The paper presents an approach to identify detection and propose concepts for manufacturing enterprises. The information processing procedure is used for the implementation of two Use Cases.
Recent developments have demonstrated the challenges and impacts of disruptions in supply chains. Current disruptions especially affected procurement and have indicated a lack of resilience. Resilience aims at being prepared, decreasing the impact, and enabling fast reactions and adaption in case of disruptions. The systematic design of resilience in procurement is significantly influenced by proactive and strategic actions before disruptions occur. Thus, the procurement strategy plays a major role when increasing resilience. The procurement strategy is influenced by various factors. Thus, a data-based approach for its systematic design is required. Based on the vision of the Internet of Production (IoP), this paper presents a data-based approach for designing procurement strategies. The IoP is a framework that enables cross-domain collaboration by providing semantically adequate and contextual data from production, development, and usage in real-time at an appropriate granularity. The paper aims at analyzing the state of the art regarding the design of procurement strategy in uncertain environments and the identification of success-critical purchased articles. Based on this, an approach is developed that is structured along the action research cycle and uses CRISP-DM to further detail the different steps. Through the use of these frameworks, both practical applicability and objective evaluation are ensured. The proposed approach thus allows the systematic evaluation of purchased articles regarding supply risks and lies the foundation for the adaption of the procurement strategy. The resulting approach is the foundation for future practical application of different use cases. As one central use case for the presented approach, the paper introduces the textile industry and its supply chains.
Progress in the development of small electric and hybrid aircraft promises business opportunities for thin-haul air mobility services. In order to develop demand-oriented flight plan scenarios for Germany, this paper presents a model to estimate the marked volume of thin-haul air mobility. To quantify the potential demand, our model includes the steps of trip generation, trip distribution and mode choice. Trip generation and distribution takes place between 412 geographic subdivisions of Germany and is based on calibrated traffic forecast data for the year 2030. For the first time the five relevant modes of transport, namely: car, intercity train, intercity bus, commercial aircraft and thin-haul air mobility services, have been included in one model. The step of choosing the transport mode is implemented via a generalized cost approach, taking into account travel costs and travel time. Additionally, route modeling of all transport modes is enhanced by real market data using large-scale data readouts of web interfaces. As primary result we predict a market share of 6 % or 81 million trips per year for thin-haul air mobility services. The demand concentrates on a small number of airports: 30 % of the trips are estimated to be between only 20 airports. Hubs and main routes are identified to offer the potential for scheduled air services.
Due to shorter product life cycles and the increasing internationalization of competition, companies are confronted with increasing complexity in supply chain management. Event-based systems are used to reduce this complexity and to support employees' decisions. Such event-based systems include tracking & tracing systems on the one hand and supply chain event management on the other. Tracking & tracing systems only have the functions of monitoring and reporting deviations, whereas supply chain event management systems also function as simulation, control, and measurement. The central element connecting these systems is the event. It forms the information basis for mapping and matching the process sequences in the event-based systems. The events received from the supply chain partner form the basis for all downstream steps and must, therefore, contain the correct data. Since the data quality is insufficient in numerous use cases and incorrect data in supply chain event management is not considered in the literature, this paper deals with the description and typification of incorrect event data. Based on a systematic literature review, typical sources of errors in the acquisition and transmission of event data are discussed. The results are then applied to event data so that a typification of incorrect event types is possible. The results help to significantly improve event-based systems for use in practice by preventing incorrect reactions through the detection of incorrect event data.
Ziel des Forschungsvorhabens war die Erhöhung der Effizienz und Effektivität von Suchanfragen in ERP-Systemen. Dabei sollte der Aufwand für den Nutzer reduziert und die Qualität der Ergebnisse verbessert werden. Die Erreichung der Ziele wurde durch die Entwicklung einer selbstlernenden, kontextbasierten Suchmaschine für ERP-Systeme realisiert. Mit der Berücksichtigung des Kontexts einer Suchanfrage, des Benutzerverhaltens und einer Ergebnisbewertung durch den Anwender wurde die Ergebnisqualität von Suchanfragen kontinuierlich gesteigert. Durch die Entwicklung eines Demonstrators wurde der Nutzen des Konzepts nachgewiesen, indem dieser in verschiedenen Szenarien erprobt und anhand einer Wirtschaftlichkeitsbetrachtung bewertet wurde.
In the food industry, a very large potential of data ecosystems is seen, in which data is understood, exchanged and monetized as an economic asset. However, despite the enormous economic potential, companies in the food industry continue to rely on traditional, product-oriented business models. Existing data in the value chain of industrial food production, e.g., in harvesting, logistics, and production processes, is primarily used for internal optimization and is not monetized in the form of data products. Especially the pricing of data products is a key challenge for data-based business models due to their special characteristics compared to conventional, analog offerings and multiple design options. The goal of this work is therefore to solve this issue by developing a framework that allows the identification of pricing models for data products in the industrial food production. For this purpose, following the procedure of typology formation, essential design parameters and the respective characteristics are derived. Furthermore, three types for pricing models of data products are shown. The results will serve not only stakeholders in the food industry but also manufacturing companies in general as input for an orientation of their databased business models.
Industry 4.0 and Smart Maintenance represent a great opportunity to make manufacturing and maintenance more effective, safer, and reliable. However, they also represent massive change and corresponding challenges for industrial companies, as many different options and starting points have to be weighed and the individual right paths for achieving Smart Maintenance need to be identified. In our paper, we describe our approach to evaluating maintenance organizations in a case study for the oil and gas industry, developing a shared vision for the future, and deriving economical and effective measures. We will demonstrate our approach, by showcasing a specific example from the oil and gas industry, where a need for action on HSE-relevant critical flanges in the company's piping systems was identified. We describe the steps, that were taken to identify the need for action, the specifications of the project and the criticality analysis of the piping system. This resulted in the derivation of a digitalization measure for critical flanges, which was first commercially analyzed and then the flanges were equipped with a continuous monitoring solution. Finally, a conclusion is drawn on the performed procedure and the achieved improvements.
Der 37. KVD-Service-Congress widmet sich der Diskussion, wie effektiver und effizienter Service in der Zukunft gestaltet werden muss. Im Mittelpunkt des Service stehen die Kunden, die Mitarbeiter und das Unternehmen. Und über allem schwebt das Schlagwort Digitalisierung. Was macht sie mit dem Service - heute und morgen?
In immer komplexer werdenden Wertschöpfungsketten wird die Geschwindigkeit, mit der Informationen weitergegeben und entsprechende Maßnahmen umgesetzt werden können, zu einem entscheidenden Wettbewerbsvorteil. In der Realität kommt es jedoch auf dem Weg zwischen einem Ereignis und einer passenden Reaktion zu verschiedenen zeitlichen Verzögerungen, sogenannten Latenzen, die die Agilität eines Unternehmens erheblich hemmen. Insbesondere das Supply-Chain-Management mit seiner koordinierenden Funktion wird dadurch vor enorme Herausforderungen gestellt. Schlüsseltechnologien im Zeitalter von Digitalisierung und Industrie 4.0 bieten jedoch enorme Potenziale, die verschiedenen Formen von Latenzen zu reduzieren. Der Beitrag untersucht die unternehmensübergreifenden Effekte dieser Verzögerungen entlang der Supply-Chain und beleuchtet darüber hinaus die Potentiale konkreter digitaler Technologien auf selbige.
Smart Service Engineering
(2019)
In our digitalized economy, many traditional service engineering models lack flexibility, efficiency and adaptability. As today’s market differs significantly from the market of the late 20th century, service engineering models must meet different requirements today than they had to meet in the past. The present paper starts off by providing an overview of the requirements that modern service engineering models need to fulfill in order to succeed in today’s economic environment. Afterwards, three promising models that meet several of these requirements will be introduced.
Companies operate in an increasingly volatile environment where different developments like shorter product lifecycles, the demand for customized products and globalization increase the complexity and interconnectivity in supply chains. Current events like Brexit, the COVID-19 pandemic or the blockade of the Suez canal have caused major disruptions in supply chains. This demonstrates that many companies are insufficiently prepared for disruptions. As disruptions in supply chains are expected to occur even more frequently in the future, the need for sufficient preparation increases. Increasing resilience provides one way of dealing with disruptions. Resilience can be understood as the ability of a system to cope with disruptions and to ensure the competitiveness of a company. In particular, it enables the preparation for unexpected disruptions. The level of resilience is thereby significantly influenced by actions initiated prior to a disruption. Although companies recognize the need to increase their resilience, it is not systematically implemented. One major challenge is the multidimensionality and complexity of the resilience construct. To systematically design resilience an understanding of the components of resilience is required. However, a common understanding of constituent parts of resilience is currently lacking. This paper, therefore, proposes a general framework for structuring resilience by decomposing the multidimensional concept into its individual components. The framework contributes to an understanding of the interrelationships between the individual components and identifies resilience principles as target directions for the design of resilience. It thus sets the basis for a qualitative assessment of resilience and enables the analysis of resilience-building measures in terms of their impact on resilience. Moreover, an approach for applying the framework to different contexts is presented and then used to detail the framework for the context of procurement.
The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.
Es ist davon auszugehen, dass einfache, repetitive Tätigkeiten in absehbarer Zeit in zunehmendem Maße automatisiert werden. Daher wird für Beschäftigte, die maßgeblich mit diesen Tätigkeiten betraut sind, Qualifizierung zu einem zentralen Faktor. Darüber hinaus wird es für einen großen Teil der Höherqualifizierten zu einer deutlichen Verschiebung der Qualifikationsanforderungen sowie zu einer zunehmenden Informatisierung der Arbeit kommen. Der Buchbeitrag von Volker Stich, Gerhard Gudergan und Roman Senderek verdeutlicht, dass angesichts dieser Herausforderungen für die Unternehmen, das arbeitsnahe Lernen eine Möglichkeit darstellt, Menschen und Unternehmen für den aktuellen industriellen Wandel zu befähigen. Hierbei sind nach Ansicht der Autoren jedoch zunächst Arbeits- und Produktionssysteme zu schaffen, die lernförderlich geplant und gestaltet sind. Um dies zu ermöglichen, bedarf es einer Kategorisierung der verfügbaren arbeitsorientierten Lernformen und insbesondere neuer technologiegestützter Lernformen. Darüber hinaus sind die Rahmenbedingungen und Voraussetzungen von Unternehmen zu prüfen und im Hinblick auf die Anwendung der verschiedenen Lernformen zu bewerten. Eine Systematik hierfür und die Erfahrungen bei der Implementierung von arbeitsorientierten Lernformen bei vier Unternehmenspartnern schließen diesen Beitrag ab.
Eine Herausforderung für produzierende Unternehmen in der Entwicklung intelligenter Produkte besteht darin, dass die Zielstellung, die mit einem intelligenten Produkt verfolgt wird, nicht expliziert ist. Zudem ist oftmals nicht spezifiziert, in welchem Anwendungsfall ein intelligentes Produkt agieren soll. Produzierende Unternehmen benötigen Unterstützung, um eine zielorientierte und folglich wirtschaftliche Melioration existierender Produkte zu gewährleisten. Ebendiese Melioration wird im Kontext von intelligenten Produkten als Smartifizierung bezeichnet und stellt damit einen Entwicklungsprozess dar, der ein bestehendes Produkt als Ausgangssituation im Sinne einer Anpassungskonstruktion expliziert. Die originäre Produktfunktion wird folglich nicht verändert, sondern das Produkt um digitale Funktionen und Dienstleistungen erweitert. Der Artikel befasst sich daher erstens mit der Beschreibung generischer Ziele für den Einsatz intelligenter Produkte im Maschinenbau. Eine Zusammenstellung und Erläuterung solcher Ziele unterstützt Unternehmen, eine Präzisierung der Zielfestlegung in der Initiierungsphase eines Smartifizierungsprojekts durchzuführen. Zweitens wird unter Anwendung der Ziel-Mittel-Beziehung ein Anwendungsfall intelligenter Produkte beschrieben. Abschließend werden beide Aspekte in einer Methode zusammengefasst, wie mittels Ziel- und Anwendungsfallbetrachtung Anforderungen abgeleitet und wie diese Elemente in Vorgehensmodelle der Produktentwicklung eingebettet werden können. Exemplarisch wird anhand einer Stanzmaschine aufgezeigt wie die Methode und die sich daraus ableitenden Ergebnisse im Smartifizierungsprozess zur Entwicklung einer intelligenten Stanzmaschine eingesetzt werden.
Industrie 4.0 is said to have major positive effects on productivity in manufacturing companies. However, these effects are not visible yet. One reason for this is the lack of understanding of maintenance services as a crucial value contributing partner in production processes, although scientific literature already highlighted the importance of indirect maintenance costs. In order to retrieve the unused potential of maintenance services, a digital shadow in form of a sufficiently precise digital representation is required, providing a data model for the value of maintenance actions so that asset and maintenance strategies can be optimized later on. Using case study research for process manufacturers, the first research contribution of this paper consists of 21 value contributing elements being identified. The second contribution is a reference processes model, showing seven major process steps as well as the required intra-organization interaction on an information technology system level. Therefore, it provides the base for the missing data model shaping the targeted digital shadow of maintenance services’ value contribution. [https://link.springer.com/chapter/10.1007/978-3-030-57993-7_69]
Mehr als nur ein Hype
(2021)
Blockchain-Lösungen sind bisher vor allem im Finanzbereich bekannt und erfolgreich. Doch ihre unbestreitbaren Vorteile bieten weit darüber hinaus Potenzial und machen sie auch für industrielle Anwendungen interessant. Vor allem Lieferketten mit ihren komplexen Strukturen, vielen Beteiligten sowie verschiedensten Material-, Informations- und Finanzströmen lassen sich mit der Technologie erheblich effizienter gestalten.
European machinery and equipment manufacturers face multiple logistical challenges in their daily business. Interacting in complex non-hierarchical production networks and thus living with the consequences of a lack of transparency, temporal instability, or imbalanced share of market power finally leads to an inadequate OEM’s delivery adherence which in many cases can be traced back to suppliers’ late deliveries.
This paper presents a framework for improving delivery reliability in non-hierarchical production networks by applying market mechanisms. Knowing the financial consequences of a supplier’s belated delivery provides useful information which can be applied in terms of financial incentives. The framework is supported by the results of a study which has been conducted by the authors throughout German, Spanish, and Italian machine tool manufacturers and their suppliers.
"New Service-Work"
(2021)
Durch die Corona-Krise befinden wir uns auf einmal alle in einer völlig neuen Arbeitswelt. Innerhalb kürzester Zeit waren Unternehmen im Service gezwungen, Antworten für – vielleicht auch manchmal schon länger bestehende Fragen – rund um das Thema „New Work“ zu finden. Daher hat sich der KVD in den vergangenen Monaten im Rahmen einer ausgewiesenen Expertenrunde aus Praxis und Forschung mit dem Thema „New Service-Work“ auseinandergesetzt. Vor dem Hintergrund der aktuellen Herausforderungen haben wir die zentralen Handlungsfelder für die Umsetzung dieser neuen Arbeitswelt einmal intensiver beleuchtet. In über 25 digitalen Treffen wurden die Chancen, Risiken oder auch Hemmnisse zu den jeweiligen Handlungsfeldern intensiv diskutiert und aufbereitet. Mit einigen aktuellen, innovativen Lösungsansätzen aus unseren Mitgliedsunternehmen hoffen wir, auch Ihnen erste Hinweise oder Impulse geben zu können, wie auch bald in Ihrem Unternehmen „New Service-Work“ Einzug halten könnte.
Inhaltsangabe Band:
Die vernetzte Digitalisierung hat die produzierende Industrie fundamental verändert. Im Rahmen dessen eröffnen sich produzierenden Unternehmen kontinuierlich neue Chancen, in einem zunehmend dynamischen und durch das Internet geprägten Wettbewerb, wirtschaftliche Erfolge zu erzielen. Durch die veränderten Rahmenbedingungen der vernetzten Digitalisierung müssen produzierende Unternehmen jedoch neue Ansätze für die Organisation der digitalen Transformation verfolgen: Sie müssen die neue Führungsaufgabe Digitalisierungsmanagement gestalten. Dabei muss das Digitalisierungsmanagement eine breite Aufgabenvielfalt abdecken.
Dieses Buch befähigt produzierende Unternehmen die digitale Transformation erfolgreich zu gestalten. Dazu werden Nutzen und Funktionsweisen der wesentlichen Aufgaben des Digitalisierungs- und Informationsmanagements praxisnah dargestellt. Ein spezifisch für produzierende Unternehmen, die eine digitale Transformation anvisieren, entwickeltes Digitalisierungs- und Informationsmanagement-Modell verknüpft schließlich die Inhalte.
Das vorliegende Buch ist als ein Nachschlagewerk für Führungskräfte und Entscheider entwickelt worden, die die Herausforderungen der Realisierung von digitalen Geschäftsmodellen, digitalisierten Produkten und digitalen Geschäftsprozessen angehen wollen. Die Methoden in diesem Buch helfen dabei, die richtigen Managementaufgaben zu verfolgen und diese in der Unternehmensorganisation umzusetzen. Dabei werden auch die Schnittstellen zwischen dem strategischen Digitalisierungsmanagement und dem taktischen bis operativen Informationsmanagement behandelt. Das Buch bietet einen schnellen und einfachen Zugriff auf die wichtigsten Methoden und viele unterstützende Beispiele. Es ist Teil der Reihe „Handbuch Produktion und Management“ und ergänzt dessen Ordnungsrahmen.
(Quelle: https://link.springer.com/book/10.1007/978-3-662-63758-6)
Als Beispiel einer globalen Krisensituation zeigt die COVID-19-Pandemie eindrucksvoll die Schwachstellen heutiger Wertschöpfungsnetzwerke. Vor dem Hintergrund zunehmend komplexer und vernetzter Wertschöpfungsnetzwerke steigt für Unternehmen die Bedeutung einer resilienten Gestaltung derselben. Dabei wird davon ausgegangen, dass ähnliche Krisensituationen in Zukunft häufiger auftreten werden. Ziel dieser Expertise ist es, Unternehmen bei der Identifikation von Potenzialen und Maßnahmen für die resiliente Gestaltung ihrer Wertschöpfungsnetzwerke zu unterstützen.
Erfolgreiche Serviceinnovation im Zeitalter industrieller, datenbasierter Dienstleistungen unterscheidet sich deutlich von bisherigen Ansätzen der klassischen Dienstleistungsentwicklung. Diese Erkenntnis konnte aus einem breit angelegten Benchmarking in der deutschen Industrie gewonnen werden. Die Benchmarking-Studie identifizierte besonders erfolgreiche Unternehmen, deren Methoden und Ansätze zur Gestaltung innovativer Dienstleistungen in Form von Fallstudien im Detail untersucht wurden. Als Kernergebnis ergeben sich sechs Prinzipien, die erfolgreiche Serviceinnovation für datenbasierte Dienstleistungen auszeichnen.
Generation of a Data Model For Quotation Costing Of Make To Order Manufacturers From Case Studies
(2022)
For contract or make to order manufacturers, quotation costing is a complex process that is mainly performed based on experience. Due to the high diversity of the product range of these mostly small or medium-sized companies (SMEs) and the poor data situation at the time of quotation preparation, the quality of the calculation is subject to strong variations and uncertainties. The gap between the initial quotation costing and the actual costs to be spent (pre- and post-calculation) is crucial to the existence of SMEs. Digitalization in general can help companies to get a better understanding of processes and to generate data. For improving these processes, an understanding of the important data for that specific process is crucial. Accurate quotation costing for customized products is time-consuming and resource-intensive, as there is a lack of an overview of data to be used within the process. This paper therefore derives a data model for supporting quotation costing in the company, based on literature-based costing procedures and recorded case studies for quotation and calculation. Based on the results, SMEs will have a first overview of the needed data for quotation costing to optimize their calculation process.
The aim of the related research project eCloud is to enable small and medium sized enterprises (SMEs) to implement flexible energy management without in-depth energy knowledge and with little distraction from day-to-day business, which is prepared for current and future challenges in the field of energy use. The overall result is a validated prototype for a plug and automate capable (i.e. without implementation effort) operational energy management, which can be successively set up in SMEs based on a cloud platform. Through its gradual and modular implementation, energy management meets the individual needs of each company and contributes to energy system transformation and climate protection by reducing energy costs and greenhouse gas emissions by up to 25%. In total, three expansion stages are available with the levels of monitoring, load management and grid usage, which consist of various Software as a Service (SaaS) modules from the cloud that can be retrieved as required. Thus, the user only needs a minimal hardware intervention in his production and saves a complex IT infrastructure. The methodology developed has been successfully applied by two user companies so far. This proves the effectiveness of the method.
Störungen und Änderungen des Produktionssystems führen zu Kosten und Aufwänden, bieten jedoch auch die Chance zur kontinuierlichen Verbesserung.
Um Änderungsanfragen zu erfassen, können etablierte Ansätze genutzt werden. Diese vernachlässigen jedoch die Anforderungen, denen sich ein Produktionssystem im Zeitalter der Digitalisierung ausgesetzt sieht. Der vorliegende Beitrag stellt einen Ansatz zur standardisierten Erfassung von Änderungsanfragen vor, welcher die Ausgangsbasis für die Bewertung von Änderungsanfragen in bestehenden IT-Systemen bietet.
[Study] Blockchain
(2019)
Distributed ledger technologies, of which the best known example is blockchain, were expected to make their big breakthrough in 2018. Instead, the opposite happened. Cryptocurrency price slumps and delays in promising projects became symptoms of a new sense of caution. Organizations tried to use blockchain in unsuitable applications, and underestimated implementation hurdles. Despite this, the need for effective data exchange and data management in today's connected world remains high. Decentralized solutions, intelligent sensors, global supply chains and vast quantities of customer data will further stimulate demand for specialized and powerful data management systems. Blockchain therefore remains one option to enable a secure and interconnected world. The following five-step approach will help you harness blockchain's potential, avoiding common mistakes and overcoming implementation hurdles on your way.
This paper addresses the challenge of a systematic requirement-oriented configuration and selection of cyber physical systems (CPS) for SMEs. As the key technologies of realizing the digitalization and interconnection of production processes, manufacturing companies have realized the potential benefits brought by CPS. However, due to the
complexity and fast development of CPS technology, it is difficult for SMEs, which lack expertise and financial resources, to select the appropriate CPS technologies meeting both functional and financial requirements. To overcome the issue, an online matching platform is developed to let SMEs express their needs and assist them onceptualize
the individual CPS. This paper presents the matching methodology of the matching platform, which can not only match technical characteristics but also evaluate economic potentials. Then, it was demonstrated by a tracking and tracing use case in the end-of-line assembly of a small-sized German electric automobile manufacturer.
This research area focuses on the management systems and principles of a production system. It aims at controlling the complex interplay of heterogeneous processes in a highly dynamic environment, with special focus on individualized products in high-wage countries. The project addresses the comprehensive application of self-optimizing principles on all levels of the value chain. This implies the integration of self-optimizing control loops on cell level, with those addressing the production planning and control as well as supply chain and quality management aspects. A specific focus is on the consideration of human decisions during the production process. To establish socio-technical control loops, it is necessary to understand how human decisions are made in diffuse working processes as well as how cognitive and affective abilities form the human factor within production processes.
The environment in which companies operate is increasingly volatile and complex. This results in an increased exposure to disruptions. Past disruptions have especially affected procurement. Thus, companies need to prepare for disruptions. The preparedness for disruptions in the context of procurement is significantly influenced by the design of the procurement strategy. However, a high number of purchased articles and a variety of influencing factors lead to high complexity in procurement. The systematic design of the procurement strategy should therefore take into account the criticality of the purchased articles. This enables to focus on the purchased articles that have a high impact on the disruption preparedness. Existing approaches regarding the design of the procurement strategy in uncertain environments either lack practical applicability and objective evaluation or focus on the criticality of raw materials rather than of purchased articles. Therefore, a data-based approach for the systematic design of the procurement strategy in the context of the Internet of Production has been proposed. One central aspect of this approach is the identification of success-critical purchased articles. Thus, this paper proposes a framework for characterizing purchased articles regarding supply risks by combining two systematic analyses. First, a systematic literature review is performed to answer the question of what factors can be used to describe the supply risks of purchased articles. The results are analyzed regarding sources and impacts of risks and thus contribute to a structured characterization of supply risks. Second, existing criticality assessment approaches for raw materials are analyzed to identify categories and indicators that describe purchased articles. The results of both reviews provide the basis for linking product characteristics with supply risks and assessing product criticality which will be integrated into an app prototype.