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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.
Smart Services als Enabler von Subscription-Geschäftsmodellen in der produzierenden Industrie
(2022)
[Der Sammelband] Widmet sich den in Wissenschaft und Praxis aktuell intensiv diskutierten Fragestellungen zu Smart Services. Befasst sich mit Geschäftsmodellen, Erlösmodellen und Kooperationsmodellen von Smart Services. Geht auf branchenspezifische Besonderheiten von Smart Services ein. (link.springer.com)
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.
Electricity generated by wind turbines (WT) is a pillar of the transition to renewable energy [1]. In order to economically utilize WTs, operating and maintenance costs, which account for 25% of total electricity generation costs in onshore WTs, are a focus of cost reduction activities [2]. A prescriptive maintenance approach can support in achieving this goal. Prescriptive maintenance is a maintenance approach, where asset condition data is collected and analyzed to recommend specific actions to prevent breakdowns and reduce downtimes. However, the processing and analysis of data is quite complex. Especially unstructured data (such as comments of service technicians in free text fields) is often left unused, as companies, mostly SMEs lack the capacity to carry out these analyses. In this work we propose an approach to utilize the information from service reports, maintenance reports as well as status records from SCADA systems for the development of a prescriptive maintenance approach to onshore WTs. To achieve this, an ontology was utilized in this approach to codify implicit knowledge of service technicians and aid in making unstructured data usable for further analysis. The ontology was used to link historical service and maintenance reports with status codes, thus enabling automated analysis. In interviews with WT topic experts and through further research, damage mechanisms and corresponding maintenance measures were identified and a measure catalogue was developed to support service and maintenance activities. The recognition of the root cause of problems allows for a prescriptive maintenance approach that recommends targeted actions to reduce downtimes and optimize maintenance activities, it also allows to effectively control the outcome of maintenance activities and optimize their execution.
Auf Basis einer systematischen Literaturanalyse wurden insgesamt 11 Kennzahlen identifiziert, welche die Grundlage zur Beschreibung der operativen Leistungsfähigkeit von Unternehmen bilden. Die Kennzahlen wurden in die vier Leistungsdimensionen Effizienz, Qualität, Zeit und Flexibilität eingeteilt.
The do-it-yourself mentality is particularly widespread in the furniture sector. Homemade furniture is very popular. The individualisation of furniture can be observed in internet forums, such as the online platform Pinterest. These creative ideas of potential customers show a need for individualized sustainable pieces of furniture. The current production structures, however, do not allow individual production according to the end customer's specifications. In addition, information logistics faces a major challenge: making the creative ideas of end consumers available to producers in parametric form. Topics such as customer requirements in relation to sustainable production, material specifications, industrial property rights, fair production conditions and traceability are the focus of this data interchange. An open and innovative European furniture ecosystem must be created to connect all stakeholders in the production process. This is made possible by a platform that channels the creativity of consumers and makes it designable and producible through the professional skills of designers. This requires the involvement of manufacturing specialists who can produce personalised products through sustainable intelligent production technologies. An exchange of information must also take place securely and quickly in order to protect the personal rights of the sources of ideas. This is being developed in the EU research project INEDIT - Open Innovation Ecosystem for do-it-together process. By connecting many different stakeholders along the entire value creation process, a change towards efficient collaborative collaboration is achieved. This paper presents a project insight for the development of an international co-creation platform by presenting the problem and linking it to a potential solution.
Reliability-centered maintenance for production assets is a well-established concept for the most effective and efficient disposition of maintenance resources. Unfortunately, the approach takes a lot of effort and relies heavily on the knowledge of individuals. Reliability data in Computerized Maintenance Management System (CMMS) is scarce and almost never used well. An automated risk assessment system would have the potential to contribute to the dissemination and effective use of risk information and analysis. The individuality of production setting, however, prevents current systems from being practically relevant for most industries. The presented approach combines ontologies to store and link knowledge, an information logistics model displaying the various information streams, and the Internet of production to take the different user systems and infrastructure layers into account. The provided model of a reference digital shadow for risk information and a detailed information logistics model will help software companies to improve reliability software, standardize and enable assets owners to establish a customized digital shadow for their production networks. [https://link.springer.com/chapter/10.1007/978-3-030-57993-7_2]
Technology management can significantly influence the strategic decisions of a company and thus cause success or failure. Basic templates for technology management are technology radars as well as the determination of the technology readiness level (TRL) to be able to evaluate the maturity of newly deployed technologies (e.g., newcomer vs. established). The radars, as well as the TRL, are identified in time-consuming, manual research by subject matter experts from external consultancies. This process is often repeated due to the further development and new development of technologies so that the necessary research becomes an ongoing task. The TechRad research project, therefore, aims to automate the identification of the TRL as well as technology radars using web crawling and Natural Language Processing (NLP). To commercialize the pre-competitive prototype, the development of a pre-competitive business model is the goal of this paper. Based on customer analyses, a target group definition is created. Based on user interviews, the precompetitive business model will be detailed in a four-step approach using a business model canvas and a value proposition canvas.
Der vorliegende Beitrag beschreibt eine Vorgehensweise zur kurzfristigen Umstellung von Blended-Learning- oder Präsenzangeboten. Hierbei werden neben möglichst schnell umsetzbaren technischen Lösungen auch notwendige organisatorische Anpassungen thematisiert und anhand des E-Mas-Weiterbildungsprogramms illustriert.
Einführung
(2012)
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 eines Energiekompensators aufzeigt, wie die Methode und die sich daraus ableitenden Ergebnisse im Smartifizierungsprozess zur Entwicklung eines intelligenten Energiekompensators eingesetzt werden.
Supply Chain Management delivers a considerable amount of ideas and methods to design the value stream. Each of these concepts may lead to significant cost reduction and higher service levels. But the same concept does not work for different customers and their diverse needs. Thus, a “one size fits it all” supply chain cannot lead to success. The key to overcome this obstacle is the hybrid supply chain. This paper outlines the application of hybrid system theory to supply chains. After a comprehensive overview of existing methods for the design of supply chains is given, a methodology for a customer-to-customer oriented supply chain design is presented. This approach adopts the hybrid system theory to supply chains which is in a nutshell that hybrid systems use the advantages of its subsystems to reach a superior result to one system alone. Concluding a case study illustrates the application of the methodology.
Die Variantenfließfertigung ermöglicht die Herstellung konfigurierbarer Produkte bei kurzen Durchlaufzeiten und geringen Beständen. Im Vergleich zu anderen Organisationsformen der Produktion gestaltet sich die Produktionsplanung und -steuerung aufgrund der Variantenvielfalt als anspruchsvoll. Im vorliegenden Beitrag wird der erste Schritt einer Methodik vorgestellt, welche für die Konfiguration der Reihenfolgeplanung entwickelt wurde.
Zeugnis der Reife
(2018)
Aktuell sehen sich deutsche Unternehmen damit konfrontiert, dass ihre bisherigen Produktionsabläufe und Arbeitsweisen immer weniger mit der Digitalisierung und den damit veränderten Maßstäben des 21. Jahrhunderts mithalten können. Neue innovative Lösungen werden benötigt, um produktiv voranzugehen und den Wandel für sich zu nutzen.
Influenced by the high dynamic of the markets and the steadily increasing demand for short delivery times the importance of supply chain optimization is growing. In particular, the order process plays a central role in achieving short delivery times and constantly needs to evaluate the trade-off between high inventory and the risk of stock-outs. However, analyzing different order strategies and the influence of various production parameters is difficult to achieve in industrial practice. Therefore, simulations of supply chains are used in order to improve processes in the whole value chain. The objective of this research is to evaluate two different order strategies (t, q, t, S) in a four-stage supply chain. In order to measure the performance of the supply chain the quantity of the backlog will be considered. A Design of Experiments approach is supposed to enhance the significance of the simulation results.
The use of Business Analytics (BA) helps to improve the quality of decisions and reduces reaction latencies, especially in uncertain and volatile market situations. This expectation leads a continuously rising number of companies to make large investments in BA. The successful use of Business Analytics is increasingly becoming a differentiator. At the same time, the use of BA is not trivial, rather, it is subject to high socio-technical requirements. If these are not addressed, high risks arise that stand in the way of successful use. In particular, it is important to consider the risks in relation to the different types of BA in a differentiated way. So far, there is a lack of suitable approaches in the literature to consider these type-specific risks with regard to the socio-technical dimensions: people, technology, and organization. This paper addresses this gap by initially identifying risks in the use of Business Analytics. For this purpose, possible risks are identified using a systematic literature review and verified with a Delphi survey with various partners experienced in dealing with BA. Subsequently, the identified and validated risks are assigned to three different types of Business Analytics (Descriptive, Predictive and Prescriptive Analytics) and assessed in order to systematically address and reduce the risks. The result of this paper is an overview of the interactions between the socio-technically assigned risks, summarized in a risk catalog, and the different types of Business Analytics.
Europa als erster klimaneutraler Kontinent bis 2050 – unter diesem ambitionierten Ziel treibt die Europäische Union eines der größten Transformationsprogramme dieses Jahrhunderts voran. Das Leben und die Gesellschaft wie sie heute existiert, werden in allen Bereichen signifikanten Musterwechseln unterliegen. Von zentraler Bedeutung bei dieser Transformation wird die Mobilität von Personen und Gütern sein. Eine Reduktion von 90 % der Treibhausgasemissionen soll in weniger als drei Dekaden realisiert werden. Insbesondere im Bereich der Urbanen Logistik ist ein nahtloses Zusammenspiel der verschiedensten Akteure, unterstützt durch neuartige digitale und physische Infrastrukturen, notwendig, um eine nachhaltige Zielerreichung bei mindestens konstantem Serviceniveau sicherzustellen. Cross-industrielle Ansätze, die über das Zusammenspiel von komplementären Lösungsbausteinen Co-Creation ermöglichen, werden zum zentralen Wettbewerbsvorteil für alle Akteure. Die Gestaltung von Business Ecosystems rückt deshalb zunehmend in den Fokus und wird aufgrund des enormen Potenzials für die Urbane Logistik in diesem Beitrag beleuchtet.
Development of a platform business model for co-creation ecosystems for sustainable furniture
(2023)
Existing design platforms with multi-dimensional value chains currently have deficits in terms of their business models, resulting in insufficient attention to sustainability goals and individual requirements for products of these platforms. Co-creation approaches, such as the Do-It-Together (DIT) approach for furniture, involve customers and manufacturers as equal partners in the design and production process. This allows customers to have more influence on the sustainability and individualization of products. The existing literature addresses sustainability-oriented design principles for platform business models, but concrete platform business models for multidimensional DIT cocreation of furniture are still missing. Therefore, the objective of this paper is to develop a business model for a DIT co-creation platform for the furniture industry based on a four-step business model innovation framework. This method will then be applied to a specific project scenario to derive a project-specific DIT co-creation business model. This generates knowledge about the collaborative manufacture of sustainable and customized furniture and contributes to the cross-sectoral transfer of platform business models for the development of sustainable products.
While digitization is a strategic advantage in numerous industries such as the automotive industry or mechanical engineering, other industries like the German quarrying industry have not yet established a transformation towards a digitized industry. This leads to inefficient work and inaccurate forecasting capabilities. To address these challenges, digital platforms can incentivize digitization
by supporting the capacity utilization and forecasting capability of these companies. In this paper, the quarrying industry is analyzed by a morphology and different types of companies are identified. Knowing the digital maturity of these companies and by determining the key factors to forecast demands and the capacity utilization, different operating models are derived. Combined with a morphology and the value creation system, different scenarios for the identification of platform services are examined. These scenarios are weighted in a utility analysis to get an operating model blueprint to develop and establish digital platforms in less digitized industries.
Failure management in the production area has been intensely analyzed in the research community. Although several efficient methods have been developed and partially successfully implemented, producing companies still face a lot of challenges. The resulting main question is how manufacturers can be assisted by a sustainable approach enabling them to proactively detect and prevent failures before they occur. A high-resolution production system based on analyzed real-time data enables manufacturers to find an answer to the main question. In this context, Big Data technologies have gained importance since the critical success factor is not only to collect real-time data in the production but also to structure the data. Therefore, we present in this paper the implementation of Big Data technologies in the production area using the example of an actual research project. After the literature review, we describe a Big Data based approach to prevent failures in the production area. This approach mainly includes a real-time capable platform including complex event processing algorithms to define appropriate improvement measures.
Datenbasierte Services rücken durch die Vernetzung zunehmend in den Fokus von Unternehmen. Für produzierende Unternehmen jeder Größe ist es immanent, die eigenen Daten stärker zu nutzen. Durch ein historisches Wachstum des Unternehmens sind IT-Lösungen oftmals über das Unternehmen verteilt und Daten werden mehrfach gehalten. Mithilfe des Konzepts eines digitalen Schattens können die aufgezeigten Herausforderungen gelöst werden. Dessen Umsetzung erfolgt über software-definierte Plattformen. Diese ermöglichen ein Abbild der relevanten Unternehmensdaten und schaffen Transparenz über aktuelle und vergangene Ereignisse. Unter Nutzung von Datenanalyseverfahren und Visualisierungssystemen tragen sie zur Entscheidungsunterstützung im Unternehmen bei. Dieser Beitrag enthält eine Definition dieses Plattformtyps und eine Morphologie zur Einordnung verschiedener Plattformen vor. Anhand des morphologischen Kastens werden die zentralen, notwendigen Merkmale einer software-definierten Plattform herausgearbeitet und beschrieben. Integrationsanforderungen zur Einführung in Unternehmen werden in den vier Dimensionen Technik, Organisation, Prozesse sowie Anforderungen zur Datenintegration dargestellt.
Ergänzt wird diese Betrachtung um Praxiserfahrungen bei der Umsetzung einer software-definierten Plattform. Damit liefert der Artikel einen Beitrag zur Diskussion um software-definierte Plattformen und unterstützt Unternehmen bei der Einführung einer solchen.
Nowadays, cyber physical systems support the improvement of efficiency in intralogistics by controlling and manipulating the production and logistic environment autonomously. Due to the complexity of the individual production processes, designing suitable cyber-physical systems based on their existing production environment is a challenge for companies.
This paper presents a new methodology on how to design cyber-physical systems conceptually to suit an individual production environment. Compared to existing design approaches, this methodology matches immediately the required functions to existing information and communication technology’s components insisting on the neutral assimilation of requirements.
Therefore, the requirement specification asks for needed functions in relating to offered functions of information and communication technology (ICT) components. The paper focusses the use case of implementing a cutting-edge mobile network technology into an existing tracking and tracing process.
ECM im Mittelstand
(2017)
Mit der ganzheitlichen Strategie des Enterprise Content Management (ECM) werden alle Dokumente eines Unternehmens verwaltet und organisiert. Durch den Einsatz geeigneter ECM Werkzeuge erhalten Unternehmen zum Beispiel Unterstützung beim effizienten Erfassen, Ablegen und Wiederauffinden von Dokumenten, bei der Abwicklung dokumentenbasierter Prozesse sowie bei der Einhaltung rechtlicher Vorgaben, etwa zur revisionssicheren Archivierung. Damit können ECM-Lösungen einen maßgeblichen Beitrag zur Digitalisierung der Geschäfts- und Arbeitswelt im Sinne des »Digital Office« leisten.
Das Konzept des umfassenden ECM ist mittlerweile in großen Unternehmen etabliert. Wesentliche Treiber sind hier neben offensichtlichen Rationalisierungseffekten und hohen Anforderungen an die Rechtssicherheit im Umgang mit Dokumenten(Compliance) vor allem auch neue Formen der Zusammenarbeit in Teams sowie die Automatisierung und Integration von Geschäftsprozessen. Auch die voranschreitende Digitalisierung von Geschäftsmodellen benötigt eine komplett digitale Unterstützung, zum Beispiel die automatisierte Ablage und Weiterverarbeitung von Verträgen oder Bankgeschäften, die im Internet geschlossen werden. Um Medienbrüche zu vermeiden und damit ein Geschäftsvorfall schnell nach den Compliance-Gesichtspunkten verarbeitet werden kann, ist eine ECM-Strategie, die der Unternehmensstrategie folgt, angeraten.
Vor diesem Hintergrund bietet die Studie »ECM im Mittelstand 2017« anhand der Aussagen von über 600 mittelständischen Unternehmen eine Bestandsaufnahme der ECM-Praxis im Mittelstand. Im Vordergrund stehen Fragen zum Begriffsverständnis, zur Verbreitung, zu Nutzen und zu Kosten von ECM-Software ebenso wie zu zukünftigen Entwicklungen und Trends rund um ECM im Mittelstand. Aufgrund vergleichbarer Fragestellungen sind in weiten Teilen Aussagen zur Entwicklung seit 2013 möglich, die auf entsprechenden Studienergebnissen aus einer Vorgängerstudie basieren.
The successful use of Business Analytics is increasingly becoming a differentiating competitive factor. The ability to extract data-driven insights and integrate them into decision-making is becoming growingly important. The underlying technologies are evolving exponentially, the value proposition differs from simple descriptive applications to automated decision-making. Existing approaches found in literature and practice to classify those levels only insufficiently mark down the boundaries between the different technology levels. As a consequence, it is often unclear which characteristics of the technology interact with the working environment, which can be described as a socio-technical system. Using a systematic literature review, this paper identifies the characteristics of Business Analytics and delineates three types of Business Analytics based on case studies. Thus, a starting point for the socio-technical system design and optimization for the use of Business Analytics is created.
The manufacturing industry consumes 54% of global energy and attributes for 20% of global CO2 emissions, demonstrating the industry’s role as global driver of climate change. Therefore, reducing its carbon footprint has become a major challenge as its current energy and resource consumption are not sustainable. Industrie 4.0 presents a chance to transform the prevailing paradigms of industrial value creation and advance sustainable developments. By using information and communication technologies for the intelligent networking of machines and processes, it has the potential to reduce energy and material consumption and is considered a key contributor to sustainable manufacturing as proclaimed by the European Commission in the term “twin transition”. As organizations still struggle to utilize the potential of Industrie 4.0 for a sustainable transformation, this paper presents a framework to successfully align their own twin transition. The framework is built upon three key design principles (micro level: leverage eco-efficient operations, meso level: facilitate circularity and macro level: foster value co-creation) derived using case study research by Eisenhardt, and four structural dimensions (resources, information systems, organizational structure and culture) based on the acatech Industrie 4.0 Maturity Index. Eleven interconnected areas of action are defined within the framework and offer a holistic and practical approach on how to leverage an organization’s twin transition. Within the conducted research, the framework was applied to the challenge of information quality and transparency required for high-value secondary plastics in the manufacturing industry. The result is a digital platform design that enables information transactions for secondary plastics and establishes a circular ecosystem. This shows the applicability of the framework and its potential to facilitate a structured approach for designing twin transitions in the manufacturing industry.
Die Zukunftspotenziale der digitalen Technologie könnten den Dienstleistungssektor entscheidend transformieren und damit der schrumpfenden Wettbewerbsfähigkeit der deutschen Wirtschaft neuen Schwung verleihen.
Das Schiff des Wirtschaftsstandorts Deutschland schwankt in rauer werdender See. Es schwankt weniger, weil die traditionellen deutschen Wertschöpfungssäulen (insbesondere die Flaggschiffe Automobil- und Maschinenbau sowie Chemie- und Logistikindustrie) hierzulande an Know how eingebüßt hätten; es sind vielmehr die großen Technologiedurchbrüche der letzten Jahrzehnte, die die deutschen Tugenden, welche mehr als ein Jahrhundert lang für einen Spitzenplatz unter den großen Wirtschaftsmächten gesorgt haben, drastisch an Bedeutung verlieren lassen. Perfektionismus, Verarbeitungsqualität, Zuverlässigkeit und Langlebigkeit von Produkten aller Art sicherten der deutschen Wirtschaft über viele Jahrzehnte hinweg internationales Ansehen. Das führte allerdings zu einer gewissen Selbstzufriedenheit, die die eigene Spitzenposition in der Welt als Selbstläufer ansah. Verliebt in die eigene Perfektion (der Strategieberater und Blogger Sascha Lobo spricht plakativ von einer „Spaltmaßfixierung“ ganzer Wirtschaftszweige) und an permanenter rein inkrementeller Innovation orientiert, hinkt Deutschland auf wichtigen Gebieten der künftigen Wertschöpfungsfelder dem Wettbewerb gefährlich hinterher – insbesondere auf dem für die Zukunft entscheidenden Technologiegebiet der Digitalisierung.
Glück per Abo
(2019)
Was charakterisiert einen Menschen jenseits seines offensichtlichen Verhaltens und seiner äußeren Gestalt? Wohl nichts so sehr wie seine Bedürfnisse und Wünsche. „Am Ende existiert der Mensch nur durch seine Bedürfnisse“, bringt es der Dichter Friedrich Hebbel überspitzt auf den Punkt. Doch wie sehen diese Bedürfnisse aus?
The technical development of the 5G mobile communication technology has been successfully completed. Now, vendor companies struggle with the analysis of industrial application and sales strategies as well as the development of business cases for their customers. Since this challenge is faced by many technology providers with innovative technologies in the “trough of disillusionment”, FIR’s information technology management has developed a methodology to bridge the gap, based on the example of 5G. This paper presents a methodology for identifying applications and defining business cases to select the most profitable ones. We also validate the methodology in the 5Gang research project.
The digitalization of manufacturing processes is expected to lead to a growing interconnection of production sites, as well as machines, tools and work pieces. In the course of this development, new use-cases arise which have challenging requirements from a communication technology point of view. In this paper we propose a communication network architecture for Industry 4.0 applications, which combines new 5G and non-cellular wireless network technologies with existing (wired) fieldbus technologies on the shop floor. This architecture includes the possibility to use private and public mobile networks together with local networking technologies to achieve a flexible setup that addresses many different industrial use cases. It is embedded into the Industrial Internet Reference Architecture and the RAMI4.0 reference architecture. The paper shows how the advancements introduced around the new 5G mobile technology can fulfill a wide range of industry requirements and thus enable new Industry 4.0 applications. Since 5G standardization is still ongoing, the proposed architecture is in a first step mainly focusing on new advanced features in the core network, but will be developed further later.
In diesem Paper wird eine Architektur für Kommunikationsnetze für industrielle Anwendungen vorgestellt, die neue 5G-Technologien mit vorhandener Kommunikationstechnik auf der Feldbusebene kombiniert. Diese Architektur verbindet private und öffentliche Mobilfunknetze mit lokalen Funktechnologien, um einen flexiblen Aufbau zu ermöglichen, der in der Lage ist, viele industrielle Anwendungsfälle zu unterstützen. Es wird gezeigt, wie die Errungenschaften, die mit der neuen 5G-Technologie eingeführt werden, einen großen Bereich der industriellen Anforderungen erfüllen können. Weiterhin werden relevante Anwendungsfälle beschrieben und eine Gesamtsystemarchitektur vorgeschlagen, welche nicht nur die technischen, sondern auch die funktionalen Anforderungen, welche von den spezifischen Anwendungen heutiger und zukünftiger Herstellungsprozesse gestellt werden, erfüllen kann.
Es geht um die Entwicklung eines Software-Tools zur Unterstützung bei der Auswahl von geeigneten 3D-Druckdienstleistern im Kontext der additiven Ersatzteillogistik. Im Fokus steht der Logistikdienstleister als potentieller Nutzer des Softwaretools. Das Softwaretool erfüllt zwei zentrale Funktionen: Überprüfung ob ein Ersatzteil additiv gefertigt werden soll und Auswahl eines konkreten Produzenten durch Matchingalgorithmus.
Prinzipien zur erfolgreichen Umsetzung von KI-Geschäftsmodellinnovationen
In Zeiten des zunehmenden globalen Wettbewerbs und hoch vernetzter Wertschöpfungsketten entwickelt sich Künstliche Intelligenz zu einem immer wichtiger werdenden Wettbewerbsfaktor für Unternehmen am Wirtschaftsstandort Deutschland. Durch den Einsatz von KI-Verfahren können nicht nur interne Geschäftsprozesse kostensenkend optimiert, sondern auch neue, digitale Geschäftsfelder und -modelle erschlossen werden. Es lassen sich zum einen Trends identifizieren, denen der Einsatz von KI in deutschen Unternehmen folgt. Zum anderen zeigt sich, dass sich KI unterschiedlich stark auf verschiedene Dimensionen innovativer Geschäftsmodelle auswirkt. Insgesamt lassen sich so Prinzipien ableiten, die die erfolgreiche Umsetzung von KI-Geschäftsmodellinnovationen beschreiben.
Neue Technologie- und Anwendungstrends kennzeichnen KI-Nutzung
Die tatsächliche KI-Landschaft in den Wertschöpfungsketten von KI-nutzenden Unternehmen ist durch Trends gekennzeichnet. Diese lassen sich in Technologie- und Anwendungstrends unterteilen. Experteninterviews zeigen beispielsweise, dass KI-Anwendungen bevorzugt auf Cloud-Infrastrukturen entwickelt und bereitgestellt werden. Das wiederum rückt die Frage nach der Wahrung der Datensouveränität in den Vordergrund. Anwendung findet KI tendenziell zur Prognose und Überwachung.
Sechs Prinzipien beeinflussen die erfolgreiche Umsetzung von KI-Geschäftsmodellinnovationen
Fallstudien über ein breites Spektrum der deutschen Wirtschaft beleuchten, welche Aspekte eines KI-basierten Geschäftsmodells den größten Effekt auf das Unternehmen haben. Hier lässt sich ein besonders hoher Einfluss von KI auf das Nutzenversprechen neuartiger, digitaler Leistungen der Unternehmen an die Kundinnen und Kunden feststellen. So lassen sich sechs Erfolgsprinzipien zur erfolgreichen Implementierung von KI-Technologien identifizieren, um die wirtschaftliche Nutzung von KI für Unternehmen in Deutschland im globalen Wettbewerb weiter zu steigern. So empfiehlt es sich zum Beispiel – neben der Auswahl des richtigen KI-Anwendungsfalles – ebenfalls darauf zu achten, dass die KI-Anwendung sowohl den Anbietenden wie auch den Anwendenden nützt. Diese und weitere Erfolgsprinzipien werden detailliert in der Studie Künstliche Intelligenz – Geschäftsmodellinnovationen und Entwicklungstrends beschrieben.
Factory automation and production are currently
undergoing massive changes, and 5G is considered being a key
enabler. In this paper, we state uses cases for using 5G in the
factory of the future, which are motivated by actual needs of the
industry partners of the “5Gang” consortium. Based on these use
cases and the ones by 3GPP, a 5G system architecture for the
factory of the future is proposed. It is set in relation to existing
architectural frameworks.
Vor dem Hintergrund zunehmend komplexer und vernetzter Wertschöpfungsnetzwerke und in Zeiten sich ständig verändernder Rahmenbedingungen steigt für Unternehmen die Bedeutung einer resilienten Gestaltung ihrer Wertschöpfungsnetzwerke. Durch die hohe Vernetzung in einem Wertschöpfungsnetzwerk entsteht eine starke Abhängigkeit zwischen den einzelnen Akteuren. Störungen haben somit häufig nicht nur Auswirkungen auf einzelne Unternehmen, sondern betreffen verschiedene Akteure der Wertschöpfungsnetzwerke. Tritt nun eine Störung auf, kann sich diese im gesamten Netzwerk ausbreiten. Erst der konkrete Eintritt solcher Störungen im großen Umfang – wie zuletzt im Zuge der Corona-Pandemie oder der Blockierung des Suez-Kanals – führt Unternehmen regelmäßig dazu, sich mit ihren Wertschöpfungsnetzwerken auseinander zu setzen. Eine Möglichkeit zur Sicherung der Leistungsfähigkeit in einem volatilen Umfeld stellt der Aufbau von Resilienz dar. Insgesamt ist es hierbei das Ziel, Wertschöpfungsnetzwerke so zu gestalten, dass sie im Falle einer Störung möglichst wenig beeinträchtigt sind und schnell in den ursprünglichen oder einen besseren Zustand zurückkehren können.
Systematisation Approach
(2023)
Current megatrends such as globalisation and digitalisation are increasing complexity, making systems for well-founded and short-term decision support indispensable. A necessary condition for reliable decision-making is high data quality. In practice, it is repeatedly shown that data quality is insufficient, especially in master and transaction data. Moreover, upcoming approaches for data-based decisions consistently raise the required level of data quality. Hence, the importance of handling insufficient data quality is currently and will remain elementary. Since the literature does not systematically consider the possibilities in the case of insufficient data quality, this paper presents a general model and systematic approach for handling those cases in real-world scenarios. The model developed here presents the various possibilities of handling insufficient data quality in a process-based approach as a framework for decision support. The individual aspects of the model are examined in more detail along the process chain from data acquisition to final data processing. Subsequently, the systematic approach is applied and contextualised for production planning and supply chain event management, respectively. Due to their general validity, the results enable companies to manage insufficient data quality systematically.
For developing a European industrial cooperation and involvement in the furniture industry, the international research project INEDIT conducted a survey for furniture customers. By finding out the needs and wishes of the customer regarding innovative products and the production process the project will establish a new way for designing and producing furniture. Within INEDIT a platform is built on which customized, technologically innovative and sustainable furniture can be created and produced in a co-creation process. The furniture industry should thus become significantly more flexible, transparent and sustainable. Following the "do-it-together" approach, a business ecosystem will be generated which creates added value not only for customers but also for designers, suppliers and manufacturing companies. In order to involve the customer even more actively in the design process and the production, the platform will provide access to a mix of digital and physical services and is linked to all other stakeholders in the value chain. To match the platform and the process to the needs, wishes and demands of the customer an anonymous survey with 300 participants was developed and conducted. By analyzing the survey, important factors were found for buying and for using furniture considering new technological inventions (e.g. 3D-printing or smart objects), sustainability of the products and the production process. Furthermore, the potential customer-group and their usage of the do-it-together process and additional activities can be tightened.
Objectives and Key Results (OKR) is an approach that focuses on the company's goals through trust-based agreements between leaders and employees. With the OKR framework in its original form, strategic business goals are aligned with the employees' active involvement, which promotes intrinsic motivation, transparency, commitment, and alignment. Inspired by the successes at Google and Intel and shaped by its use in the tech industry, the use of OKR increased across industries. Although companies within all sectors use the OKR framework, numerous implementation efforts fail. The challenges of practitioners are not fully addressed in the development of implementation concepts for OKR. One main reason is that these challenges are not taken into account in scientific publications. The paper aims to investigate to what extent existing OKR frameworks need to be adapted to provide companies with suiting implementation guidance. Firstly, OKR is placed in the context of academically widely discussed Performance Management Systems (PMS).
Secondly, criteria for successful PMS implementation are identified and used as a baseline for analyzing existing OKR implementation concepts. A systematic literature review shows the current state of research, identifying existing OKR implementation concepts from practice and theory. The OKR implementation concepts identified are systematically mapped to the series of identified criteria for PMS implementation. It is shown that the existing OKR frameworks do not address the described criteria necessary for a successful implementation of PMS, thus the adaptation of existing OKR implementation concepts is required.
Feeding the growing world population is a scientific and economic challenge. The target variables to be optimised are the yield that can be produced on a given area and the reduction of the resources used for this purpose. High-wage countries are faced with the problem that the use of personnel is a significant cost driver. Developing countries, on the other hand, usually operate on much smaller field sizes, so that the work in the field is still strongly characterised by manual labour. One solution to meet these challenges is the use of smaller autonomous harvesting robots. These can be networked into a swarm of machines to work even larger fields. The networking of autonomous agricultural machines is a key use case for rural 5G networks. 5G technology can offer many advantages over older mobile communications standards and therefore make use cases more efficient or enable new ones. Various use cases are also conceivable in the field of agriculture, yet it is unclear how 5G networks can and must be specified for this purpose. In this paper, using the example of 5G-connected harvesters powered by swarm robotics, we present the challenges that have arisen and the specification that has been developed.
The quarrying industry, which largely consists of less digitized SMEs, is an integral part of the German economy. More than 95% of the primary raw materials produced are used by the domestic construction industry. Quarrying companies operate demand-oriented with short planning horizons at several locations simultaneously. Due to the low level of digitization and the reluctance to share data, untapped efficiency potential in data-based demand forecasting and capacity planning arises. The situation is aggravated by the fact that SMEs have a heterogeneous mobile machinery so as not to become dependent on individual suppliers, and that transport distances of over 50 kilometers are uneconomical due to high transport costs and low material values. Within the research project PROmining a data-centric platform which improves demand forecast accuracy and multi-site capacity utilization is developed. One of the core functionalities of this platform is an industry-specific demand forecasting model. Against this background, this paper presents a methodology for establishing this forecasting model. To this end, expected demands of secondary industry sectors will be analyzed to improve mid-term volume-forecasting accuracy for the local quarrying industry. The data-centric platform will connect demand forecasting data with relevant key performance indicators of multi-site asset utilization. Following this methodology, operational planning horizons can be extended while significantly improving overall production efficiency. Thus, quarrying businesses are enabled to respond to fluctuating demand volumes effectively and can increase their personnel and machine utilization across multiple quarry sites.
In road haulage, transports are interrupted by truck drivers to comply with driving and rest times. On long-distance routes, these interruptions lead to a considerable increase in transport time. Transport interruption can be avoided by so-called relay traffic: a vehicle (e. g. semi-trailer) is handed over to a rested driver at the end of the driving time. This type of transport requires a certain company size. In Germany, however, transport companies have 11 employees on average. Intra-company relay traffic is therefore not economically viable for most transport companies. To organize an intermodal transport across forwarding companies, long-distance routes need to be split into partial routes to divide them between freight forwarders and carriers. This paper presents a data concept for an algorithm to find the best possible route sections along a previously defined start and endpoint. The developed data concept includes order-specific data, forwarder-specific data, real-time traffic data, geographical data as well as data from freight forwarding software and telematics to be the basis for the route sectioning algorithm. In this paper, different data sources, external services and logistic systems are analyzed and evaluated. It is shown which data is needed and what the best ways are to select and derive this data from the different data sources.
Supply chains form the backbone of modern economies and therefore require reliable information flows. In practice, however, supply chains face severe technical challenges, especially regarding security and privacy. In this work, we consolidate studies from supply chain management, information systems, and computer science from 2010–2021 in an interdisciplinary meta-survey to make this topic holistically accessible to interdisciplinary research. In particular, we identify a significant potential for computer scientists to remedy technical challenges and improve the robustness of information flows. We subsequently present a concise information flow-focused taxonomy for supply chains before discussing future research directions to provide possible entry points.
Long-term production management defines the future production structure and ensures the long-term competitiveness. Companies around the world currently have to deal with the challenge of making decisions in an uncertain and rapidly changing environment. The quality of decision-making suffers from the rapidly changing global market requirements and the uniqueness and infrequency with which decisions are made. Since decisions in long-term production management can rarely be reversed and are associated with high costs, an increase in decision quality is urgently needed. To this end, four different applications are presented in the following, which support the decision process by increasing decision quality and make uncertainty manageable. For each of the applications presented, a separate digital shadow was built with the objective of being able to make better decisions from existing data from production and the environment. In addition, a linking of the applications is being pursued:
The Best Practice Sharing App creates transparency about existing production knowledge through the data-based identification of comparable production processes in the production network and helps to share best practices between sites. With the Supply Chain Cockpit, resilience can be increased through a data-based design of the procurement strategy that enables to manage disruptions. By adapting the procurement strategy for example by choosing suppliers at different locations the impact of disruptions can be reduced. While the Supply Chain Cockpit focuses on the strategy and decisions that affect the external partners (e.g., suppliers), the Data-Driven Site Selection concentrates on determining the sites of the company-internal global production network by creating transparency in the decision process of site selections. Different external data from various sources are analyzed and visualized in an appropriate way to support the decision process. Finally, the issue of sustainability is also crucial for successful long-term production management. Thus, the Sustainable Footprint Design App presents an approach that takes into account key sustainability indicators for network design. [https://link.springer.com/referenceworkentry/10.1007/978-3-030-98062-7_15-1]
Die Vernetzung von Mitarbeiter*innen und Maschinen sowie die zunehmende Automatisierung, auch von Wissensarbeit, wird die Rolle der Beschäftigten im industriellen Wertschöpfungsprozess fundamental verändern. Aus diesem Grund ist arbeitsbezogene Kompetenzentwicklung aus wirtschaftlicher, gesellschaftlicher sowie sozialer Perspektive ein zentraler Schlüsselaspekt für die mittelfristige Sicherung der Wettbewerbsfähigkeit. Personalabteilungen haben bislang jedoch meist nur bedingt Kenntnisse über die bevorstehenden Veränderungen und die sich daraus ergebenden Kompetenzanforderungen an die Mitarbeiter*innen. Ziel des Forschungsvorhabens LidA war es, die sich aufgrund der fortschreitenden Digitalisierung verändernden Kompetenzanforderungen entlang definierter Industrie-4.0-Reifegradmodelle zu spezifizieren. Hierzu wurden Beschäftigte befähigt, indem zum einen ihre Selbstlernkompetenz gefördert wurde und zum anderen individuelle Lernpfade abgeleitet worden sind. Anschließend wurden diese mit passender Didaktik in Lehr- und Lernmodule überführt und auf einer bewährten Open-Source-Plattform für eine breite Nutzergruppe verfügbar gemacht. Diese soll einem breiten Nutzerkreis, speziell KMU, eine bedarfsgerechte Schulung der Mitarbeiter*innen im Zeitalter des digitalen Wandels gewährleisten.
Anwendungsfälle wie intelligente Routenoptimierung und fortschrittliche Simulationsalgorithmen repräsentieren das riesige Einsatzspektrum von Methoden der künstlichen Intelligenz. Steigende Anforderungen an Liefertermintreue, Flexibilität und Transparenz wie bspw. Emissionsverfolgung, erfordern zunehmend den Einsatz von KI. Die Nutzung dieser Schlüsseltechnologie und die Hebung der Potenziale scheitern oft an der Komplexität in Bezug auf die Eingrenzung und Identifikation von wirtschaftlich relevanten Anwendungsfällen. Unternehmen müssen den Business Fit zwischen den wirtschaftlichen Erfolgsaussichten und den dafür benötigten digitalen Bausteinen herstellen. Mit dem Digital-Architecture Management lassen sich die relevanten KI-basierten Anwendungsfälle identifizieren und eine Roadmap aufbauen, um die datenbasierte Entscheidungsfähigkeit in der Logistik zu verbessern.
Forecasting-based skills management, which is oriented to the respective corporate goals, is gaining enormous importance as a central management tool. The aim is to predict future skills requirements and match them with existing interorganizational skills. Companies are required to anticipate changes in markets, industries, and technologies at an early stage as well as to identify changes in job profiles within an occupational profile by tapping into and evaluating various data sources. Based on these findings, they can then make informed decisions regarding skill gaps, for example, to implement targeted further training measures. Forecasting-based skills management offers the opportunity to optimally qualify employees for constantly changing tasks. At the same time, however, the targeted development of such skills requires a high level of time, financial and personnel resources, which small and medium-sized enterprises (SMEs) generally do not have at their disposal. In addition, many SMEs are not yet aware of the importance of this issue. Within the framework of research and industrial projects of the Smart Work department at the FIR (Institute for Industrial Management) at the RWTH Aachen University, an AI-based skills forecasting tool will be developed. The goal of the paper is to conceptualize the future machine learning method, that is able to generate individualized skills forecasts and recommendations for SMEs. This is achieved by linking societal forecasts and sector trends with company-specific conditions and skills. In order to generate a corresponding database, the derivation system is made available to various companies (large companies and SMEs) in order to obtain as many data sets as possible. The data sets obtained via the derivation system are then used as training data sets for the machine learning method, with the help of which an automatic derivation of competencies depending on new trends is to be made possible.
5G offers the manufacturing industry a wireless, fast and secure transmission technology with high range, low latency and the ability to connect a large number of devices. Existing transmission technologies are reaching their limits due to the increasing number of networked devices and high demands on reliability, data volume, security and latency. 5G fulfills these requirements and also combines the potential and use cases of previous transmission technologies so that unwanted isolated solutions can be merged. Use cases of transmission technologies that previously required a multitude of solutions can now be realized with a single technology. However, the general literature often refers to 5G use cases that can also be realized over cables in particular. In this paper, a literature review presents the current state of research on the various 5G application scenarios in production . Furthermore, concrete characteristics of 5G use cases are identified and assigned to the identified application scenarios. The goal is to verify the identified 5G use cases and to work out their 5G relevance in order to be able to concretely differentiate them from already existing Industrie 4.0 applications.
Digitization is constantly affecting the working world and is of enormous interest in many fields of science. But to what extent are innovative technologies actually being applied in regional SMEs and what are the obstacles to their introduction? From a psychological point of view, it is essential to consider the employee's health and the effects of innovative technologies on their everyday work. The aim of using innovative technologies should not be to completely replace human labor or to dequalify employees, but to relieve the workforce and free up working time for more meaningful activities. One concept that should be included in the human-centered design of human-machine interaction in artificial intelligence is the HAI-MMI concept (Huchler, 2020), which offers starting points for high-quality collaboration at various levels. To reduce the gap between science and industry, this paper focuses on the actual demands of SME in the Aachen region in Germany referring to a requirements analysis within the research project AKzentE4.0 (N = 50 SME) and discusses how appropriate innovative technologies of the Industry 4.0 and AI can be implemented and deployed in a human-centred way. Moreover, the establishment of a Human Factors Competence Center for Employment in Industry 4.0 is outlined, which is meant to be used for the dissemination of research results from the project and should narrow the gap between science and industry in the long run.
Innovation is one of the key drivers of growth, development, and profitability, which increases competitive advantages and has recently been moving towards industry 4.0 technologically. This motivates companies to update their business models (BM) towards industry 4.0. Moreover, there is a technique with the primary characteristics for achieving this motivation called "cross-industry innovation". Cross-industry innovation is a new method of innovation that concerns the creative translation and imitation of existing solutions from other industries for responding to the needs of the current market, sectors, areas, or domains. The challenge is to find out how far managers can rely on that to innovate their BM towards Industry 4.0. The aim of this study was to investigate the application of cross-industry innovation for designing industry 4.0 BM and explore the extent to which companies can rely on it as it has not been used for this purpose previously. This study utilized a database analysis to compare cross-industry innovation practices with industry 4.0 BM's characteristics in terms of value proposition, value creation, and value capture levels. In addition, some interviews were conducted with companies that had previously implemented cross-industry innovation to validate and generalize the results. The results indicated that cross-industry innovation practices can better fulfill flexible and dynamic networks, connected information flows, high efficiency, high scalability, and high availability in terms of value creation as well as variabilization of prices and costs in terms of value capture. Therefore, it demonstrated that cross-industry innovation was a more dependable and applicable strategy for designing the BM of Industry 4.0 than current practices.
Crises are becoming more and more frequent. Whether natural disasters, economic crises, political events, or a pandemic - the right action mitigates the impact. The PAIRS project plans to minimize the surprise effect of these and to recommend appropriate actions based on data using artificial intelligence (AI). This paper conceptualizes a cascading model based on scenario technique, which acts as the basic approach in the project. The long-term discipline of scenario technique is integrated into the discipline of crisis management to enable short-term and continuous crises management in an automated manner. For this purpose, a practical crisis definition is given and interpreted as a process. Then, a cascading model is derived in which crises are continuously thought through using the scenario technique and three types of observations are classified: Incidents, disturbances, and crises. The presented model is exemplified within a non-technical application of a use case in the context of humanitarian logistics and the COVID-19 pandemic. Furthermore, first technical insights from the field of AI are given in the form of a semantic description composing a knowledge graph. In summary, a conceptual model is presented to enable situation-based crisis management with automated scenario generation by combining the two disciplines of crisis management with scenario technique.
The use of chatbots has hardly been established in B2B companies to date and involves various challenges. The goal of this paper is to identify the biggest barriers to the successful implementation of chatbots in B2B customer service and to develop measures to overcome them. The barriers are identified by conducting expert interviews within the framework of Eisenhardt's case study research. These are examined through a socio-technical analysis focusing on people, technology, and organization. By means of systematic literature research and in-depth interviews with German chatbot providers and customers of chatbots, measures for overcoming the barriers are identified. Using interviews with experts from German chatbot providers, the responsible stakeholders of each measure according to the RASCI Responsibility Matrix are determined. A total of 46 implementation barriers and 100 measures to overcome these barriers are identified. The study shows that there are major barriers in the areas of people, technology, and organization of a socio-technical system that can cause the implementation of a chatbot to fail. A holistic view is therefore essential. The results provide firms with a guideline on how to overcome potential barriers during chatbot implementation in B2B customer service.
In der neuen Expertise des Forschungsbeirats Industrie 4.0 untersuchen das FIR e. V. an der RWTH Aachen und das Industrie 4.0 Maturity Center den Status-quo und die aktuellen Herausforderungen der deutschen Industrie bei der Nutzung und wirtschaftlichen Verwertung von industriellen Daten. Handlungsoptionen für Unternehmen, Verbände, Politik und Wissenschaft zeigen auf, wie der Nutzungsgrad der Datenbasis erhöht werden kann und wie sich Potenziale bei der Monetarisierung ausschöpfen lassen. Der Fokus liegt dabei auf produzierenden Unternehmen.
Competitive differentiation in the manufacturing sector is no longer based on product and service innovations alone but on the ability to monetize the usage phase of products and services. To this end, manufacturers are increasingly looking at so-called subscription business models as a way of supplementing the traditional sale of products and services. Since supplier success in the subscription business is directly dependent on customer success, the setup and expansion of a so-called Customer Success Management (CSM) is required. While CSM has already been established in the software industry for several years, companies in the manufacturing sector are often still in the conceptual phase of a CSM, parallel to the setup and expansion of their subscription business. Therefore, this paper aims to support the set-up of a CSM by providing a reference data model, based on case study research, that can be used to support the organizational or daily CSM tasks and to serve as a blueprint for conceptualizing CSM-specific IT systems.