Refine
Year of publication
Document Type
- Book (6)
- Part of a Book (10)
- Conference Proceeding (21)
- Contribution to a Periodical (11)
- doctorallecture (1)
- Doctoral Thesis (1)
- Lecture (2)
- Report (3)
- Working Paper (6)
Is part of the Bibliography
- no (61)
Keywords
- Additive manufacturing (1)
- Agile (1)
- Agile Development (1)
- Agrarproduktion (1)
- Arbeitssystem (1)
- Auction Mechanism (1)
- Bahntechnik (1)
- Baugewerbe (1)
- Best Practices Instandhaltung (1)
- Business Model (1)
Institute
- FIR e. V. an der RWTH Aachen (61) (remove)
Remote services are services enabled by information and communication components and therefore do not require the physical presence of a service technician at the service object to provide a task. The impact of remote service on the capital goods industry has been increasingly significant over the recent yeas. Still many companies struggle with developing and implemenling successful business model, for remote service. This leads to a lot of unaccomplished benefits for the customer as well as for the companies themselves. A survey throughout companies in Ihe industrial machine and plant production sector was conducted in order to determine what successful companies do differently from those that cannot efficiently implement remote service business models.
The study presented in this chapter identifies key suceess factors of companies that effectively implemented remote services for their products. In order to identify the successful companies a scale for measuring remote service success was developed. Only by the use of this scale further findings regarding the success factors were possible. Key findings include the fact that successful companies actively market their remotle service to their customers. Generally they try to approach their remote service business from the operating company's perspective.
Traditional manufacturing companies increasingly launch data-driven services (DDS) to enhance their digital service portfolio. Nonetheless, data-driven services fail more often than traditional industrial services or products within the first year on the market. In terms of market launch, their digital characteristics differ from traditional industrial services and thus need specific structures and actions, which companies currently lack. Therefore, a process guideline for a six-month market launch phase of DDS is developed. The guideline relies on analogies from product, service and software launches based on the latest literature from service marketing and successful practices from various industries. Finally, the guideline is evaluated within five industrial case studies. Thus, the guideline provides scientific research insights regarding the market launch process of DDS and adds to the research of service marketing. It provides practical guidance for manufacturing companies by serving as a reference process for the market launch and offering a collection of successful practices within this area. [https://link.springer.com/chapter/10.1007/978-3-030-00713-3_14]
Erfolgsprinzipien der Smart Maintenance – Was wir von den Besten aus der Praxis lernen können
(2019)
Der Industriestandort Deutschland befindet sich im Wandel. Neue, digitale Technologien ermöglichen es, Betriebs-, Zustands- und Ereignisdaten in stetig steigender Menge zu erfassen, aufzubereiten, zu analysieren und für die industrielle Anwendung nutzbar zu machen. Dieser Nutzen zeichnet sich durch die Beschleunigung der unternehmerischen Entscheidungs- und Anpassungsprozesse aus und stellen damit das eigentliche Potenzial von ‚Industrie 4.0‘ dar. An dieser Stelle stehen Unternehmen heute vor der Herausforderung, die Transformation zur Smart Maintenance effektiv und effizient zu gestalten. Zu häufig neigen Unternehmen dazu, „das Rad wiederkehrend neu zu erfinden“, da Praxiseinblicke über die eigenen Standort- und Unternehmensgrenzen hinweg fehlen. Um eben jene benötigten Praxiseinblicke und Erfahrungswerte liefern zu können, wurde am FIR an der RWTH Aachen gemeinsam mit sechs Industriepartnern sowie dem Fraunhofer IML aus Dortmund das „Konsortial-Benchmarking Smart Maintenance“ durchgeführt. Anhand eines eigenen Ordnungsrahmens wurden zentrale Fragestellungen der Smart Maintenance identifiziert und mittels Fragebogenstudie untersucht. Durch die angeknüpfte statistische Auswertung konnte zwischen sogenannten ‚Top-Performern‘ (TP) und ‚Followern‘ (FL) unterschieden werden. In diesem Beitrag werden ausgewählte Ergebnisse der Studie sowie der Interviews den Ebenen des Ordnungsrahmens folgend vorgestellt.
Operation and Maintenance (O&M) is a key value driver for offshore wind farms. Consequently, reducing O&M costs improves their profitability. This paper introduces different typologies of dispositioning maintenance tasks in offshore wind farms, in order to help design the strategies and organization of maintenance. Based on the special requirements of offshore wind farms regarding planning and controlling the O&M activities, a morphological analysis was developed. With this different disposition strategies for offshore wind farms could be generated. The consequences of choosing different characteristics are allegorized in an exemplary fashion. The work presented in the following is the foundation for designing a software-based dispositioning tool for usage in offshore wind farms, which will help to increase the effectiveness of the disposition in offshore wind farms by maximizing the number of accomplished tasks per day and minimizing the time technicians stay on the wind turbine and the ships.
The industrial food production is currently caught between the increas-ing demands of numerous stakeholders, economic profitability and the challenges of digitization. A solution to face these various challenges can be seen in the aggregation of data into higher-value, independent data products that can be of-fered and sold on a buyer's market. Large amounts of heterogeneous data are already available in the value chain of the industrial food production, e.g. throughout the data-driven harvesting of primary products, further processing by interconnected production facilities and the information-intensive product distri-bution to end consumers. However, the data is usually only evaluated and used locally for the optimization of internal processes or, at the most, within compre-hensive partnerships. The purpose of this paper is to identify new revenue oppor-tunities for current and future players in the industrial food production by using data as an independent economic good (data products). For this purpose, scenar-ios for the development and use of data products via Industrial Internet of Things platforms are developed for a food technical reference process, the industrial chocolate production and its value chain. On this basis, examples for different types of data products and their value propositions are derived. The results can not only serve food producers and relevant stakeholders but all industrial produc-ers as an input for the future, yield-increasing orientation of their business models.
Data-driven services play an important role in
innovative business models of successful manufacturing
companies: They hold great potential for the creation of unique
selling points and improve the differentiation of manufacturing
companies in highly competitive markets. However, the large
number of newly invented digital services that fail shortly after
launching implies that companies struggle with the invention and
implementation of data-driven service solutions, which ends in a
waste of resources. The following paper introduces guideline
principles for successful innovation processes for data-driven
services. The principles were identified during in-depth case
studies with manufacturing companies. They contribute to a
necessary paradigm change for manufacturing companies in
terms of data-driven services for machines. The six identified
principles emphasize new aspects regarding the new dimension of
data-driven solutions and improve the life cycle management of
products and services. They demonstrate how the rules of agile
development can lead to successful and more efficient service
innovations in the industrial sector.
The additive manufacturing technique of "Selective Laser Melting" (SLM) provides the basis for a fundamental paradigm shift in industrial spare part manufacturing, affecting both technological and organizational company prac-tices. To harness the full potential of SLM-technology, considering agility and customizability, decentralized additive production networks need to be estab-lished. According to the principles just in time, just in place and just enough, a global online platform, which efficiently distributes construction orders to local manufacturing hubs could empower the market participants to utilize production capacities at optimal costs and minimal efforts. This work evaluates and selects key factors and creates scenarios for the development of platform-based networks for additive, SLM-based, spare part production. For this purpose, the selected key factors (e. g. material expenses, quality and process management and platform-based business models) are projected into the future, forming the three major scenarios "New distribution of roles in the SLM value chain", "SLM-technology for high wage countries" and "Individualization instead of mass production". These scenarios not only allow estimating the potential of an online network for additive spare part production, but also enable market participants to react pur-posively and agilely to unexpected market developments, and to foster the suc-cess of a platform-based additive spare part production.
Method for a qualitative cost benefit evaluation of process standardisation for industrial services
(2018)
Industrial service providers deliver complex technical services (e.g. inspection, maintenance, repair, improvement, installation and turnarounds) for a wide range of technical assets in process industries such as the chemical industry. Due to the versatility of assets and industries, there is also a variety of the corresponding service offerings. The demand for a high service quality and the general cost pressure leads to the need of a more efficient and standardized design of the service processes. However, cost-benefit ratio related decisions regarding the questions where and how service processes should be standardized entail great challenges for small and medium-sized enterprises. This is because there is often a lack of understanding of cost savings through process standardization, which is caused by a lack of understanding of the correlations between process characteristics and process target values. Because of this, the goal of this paper is to develop a method for a quantitative evaluation of the cost-benefit ratio of process standardization measures. Within this method, the relevant service performance processes are selected first. Next, the process data will be recorded with the help of questionnaires. These are then analyzed by looking for correlations between the process characteristics and the process target values. Afterwards standardization measures are derived on the basis of these findings in order to improve deficit characteristics and thus target values. Finally, the method´s practical applicability is tested and validated by applying it to an industrial service in the chemical industry.
KVD-Service-Studie 2018
(2018)
Digitalisierung ist eine der zentralen Herausforderungen der heutigen Zeit. Aber die Digitalisierung rein technisch zu betrachten, ohne Augenmerk auf die Unternehmenskultur zu legen, wird dazu führen, dass Unternehmen die Potenziale der Digitalisierung nicht vollständig realisieren können. Wer weiterhin wettbewerbsfähig sein will, muss den Wert der Digitalisierung erkennen und sie für sein Unternehmen nutzbar machen. Aber welche Auswirkungen ergeben sich daraus für die Serviceorganisation? Um den aktuellen Stand der digitalen Kultur im Service zu erfassen, die Dimensionen zu verstehen und einen Weg für Unternehmen aufzuzeigen, liegt der Schwerpunkt der diesjährigen Service-Studie, die vom KVD zusammen mit dem FIR durchgeführt wurde, auf dem Themenkomplex Digitale Service-Kultur.
Monetizing Industry 4.0: Design Principles for Subscription Business in the Manufacturing Industry
(2019)
Subscription business models have a major role for monetizing products and services for manufacturing companies in the age of Industry 4.0. As the manufacturing industry has difficulties generating revenues through digitalization, the implementation of innovative business models are essential to remain successful. Physical assets are often capital-intensive and require a more complex manufacturing process than subscription business models. Moreover, subscription models can focus on the individual customer benefit and a consistent service transformation, constituting a unique selling proposition and a competitive advantage. Hence, the following paper provides a management model that enables manufacturing companies to successfully realize the transformation towards a subscription business model. The management model presents four major fields of action, each matched with one design principle that must be considered when dealing with subscription models in the manufacturing industry. These principles were determined by an in-depth case study analysis among various manufacturing companies. Opportunities, challenges and recommendations for action were then systematically derived and integrated into the management model.
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?
Kleine und mittlere Unternehmen (KMU) stehen zunehmend vor der Herausforderung, im Wettbewerb immer komplexer und volatiler werdenden Leistungen des After-Sales-Service zu bestehen. Ein Erfolgsfaktor ist die Veränderungsfähigkeit bzw. die stetige Adaption des eigenen Serviceportfolios. Um KMU bei der Identifikation notwendiger Anpassungen ihres Serviceportfolios, bei deren Bündelung, Management und Umsetzung zu unterstützen, wurde das Forschungsprojekt „ReleasePro" gestartet. Im Zuge dieses Vorhabens erfolgt die Entwicklung eines systematischen Service-Release-Managements für KMU.
Smart Service Engineering
(2019)
Industry 4.0 has provided vast opportunities for manufacturing companies whilst simultaneously creating multiple challenges. In this new highly digitized globalized marketplace, manufacturing companies find themselves under pressure to become more service oriented and offer new innovative value offerings such as smart services. These are digital data-driven services that, generally, add value in conjunction with a physical product. However, classical methods of service engineering have not adapted sufficiently to the increasing digital components and requirements of smart services. This paper presents Smart Service Engineering as a novel service-engineering approach for industrial smart services. Smart Service Engineering draws from iterative development models and implements agile and customer-centric methods to decrease the overall development time and achieve an early market success. The paper focuses on the service development steps and presents the interaction and interconnection of different elements of smart services based on a case study research. Finally the paper illustrates the successful application of the Smart Service Engineering approach and its impact on a German medium-sized company in the textile machine industry.
Digitally connected industrial production promises faster and more efficient processes - in development and production, services, marketing & sales and for adapting entire business models. Agility and the ability to make changes in real time are strategic chracteristics of successful companies in Industrie 4.0. To acquire these features, it is necessary to create a continuously expanding data base. However, a company's organisational structure and culture also play an important part in determining whether this data's potential is leveraged effectively.
This acatech STUDY describes a new tool for helping manufacturing enterprises to forge their own individual path towards becoming a learning, agile company. The acatech Industrie 4.0 Maturity Index is a six-stage maturity model that analyses the capabilities in the area of resources, information systems, culture and organisational structure that are required by companies operating in a digitalised industrial environment. The attainment of each development stage promises concrete additional benefits for manufacturing companies. The model's practical application was validated in a medium-sized company.
Die digital vernetzte industrielle Produktion verspricht schnellere und effizientere Prozesse - in Entwicklung und Produktion wie auch in Service, Marketing und Vertrieb oder bei Anpassung ganzer Geschäftsmodelle. Agil zu handeln und in Echtzeit Veränderungen vorzunehmen, wird in der Industrie 4.0 zur strategischen Erfolgseigenschaft eines Unternehmens. Voraussetzung dafür ist der Aufbau einer immer breiteren Datenbasis. Ob deren Potenzial effektiv genutzt wird, hängt jedoch auch wesentlich von der Organisationsstruktur und Kultur eines Unternehmens ab.
Die vorliegende acatech STUDIE stellt ein neues Instrument vor, mit dem produzierende Unternehmen den Weg zum lernenden, agilen Unternehmen individuell gestalten können. Der acatech Industrie 4.0 Maturity Index ist als sechsstufiges Reifegradmodell aufgebaut und analysiert die in der digitalisierten Industrie benötigten unternehmerischen Fähigkeiten in den Gestaltungsfeldern Ressourcen, Informationssysteme, Kultur und Organisationsstruktur. Jede erreichte Entwicklungsstufe verspricht produzierenden Unternehmen einen konkreten Zuwachs an Nutzen. Das Modell wurde in der praktischen Anwendung in einem mittelständischen Betrieb validiert.
Industrial Smart Services - Types of Smart Service Business Models in the Digitalized Agriculture
(2018)
Due to lack of experience of companies with digital business models, agricultural machinery manufacturers and agricultural service companies are facing a positioning problem in their ecosystem. Smart services are getting more important for these companies and they have issues to define a matching business model for their newly developed smart services. The lack of a framework for smart service business models makes it even harder for companies to successfully develop new services.
This paper contributes to a better understanding of business models for smart services and establishes a common morphological framework to define different types of business models for smart services. Six types of business models of industrial smart services were identified during the research based, which was based on a literature review and interviews with leading experts in the field of smart services. The validation of the developed types and its practical application was carried out as part of the German research project Smart-Farming-World and its four developed use cases. This paper gives a detailed description of the application of the framework on the use case nPotato.
Smart Service Engineering
(2018)
Global manufacturing companies currently face an increasingly turbulent economic environment known as the "VUCA-world" (volatility, uncertainty, complexity and ambiguity). After the transformation of many companies from product to solution providers in the last 15-20 years, the focus of many corporate change processes is on digital solutions such as data-driven services. In this context, service development is of particular relevance for industrial services. Companies develop digital strategies and try to maximize the added value for their customers, by offering, for example, smart services. They are based on smart products, which are connected to the internet, interact with their environment and gather environmental data. The collected data sets are combined with other easily accessible information and processed into so-called smart data. Based on this smart data, smart services are designed. They can be defined as individualized combinations of physical and digital services. They generate added value for providers and customers and offer context-related and demand-oriented value via digital platforms. The contribution of this paper to this research field of data-driven services is a service engineering approach for industrial smart services.
Since the 1990s, service engineering has established itself as a systematic process for the development of services. Currently existing service engineering processes are based on engineering science and business model innovation toolsets. However, the increasing digital components in service engineering reveal deficits in the direct application of the classical methods of service engineering to smart services. We suggest that the successful development and implementation of smart services requires a more agile service engineering process. Studies show that companies who develop services successfully (top-performer) act up to six times faster than those with less success (follower). They involve customers in the first running prototype of their digital service to increase customer centricity and focus their development activities on core functionalities of the service to reduce its development time and test it early with customers.
To strengthen the successful development pf data-driven services in future industrial service development projects, this paper contributes to a more agile service engineering approach. Smart service engineering combines elements of linear phase models and implements agile and customer-centric findings to decrease the overall development time by focussing on core functionalities that offer a high value for customers. The paper focuses on the service development steps and presents strategic scenarios for smart service engineering. It presents the interaction and interconnection of different elements of smart services based on a case study research. In addition to this, it illustrates the implications of a customer-centric engineering approach and possible strategic decisions based on the customer feedback. The paper focuses on the successful application of the smart service engineering approach and its impact in a German medium-size company in the textile machine industry.
Smart Services
(2018)
Die Nutzung von Informations- und Kommunikationstechnologien in Wirtschaft und Gesellschaft ist inzwischen zur Selbstverständlichkeit geworden. Deutschen Leitbranchen, wie dem Maschinen- und Anlagenbau, stehen durch die Digitalisierung jedoch noch große Umbrüche vor. Die Erfassung von Daten im laufenden Betrieb der Anlagen bietet die Chance durch die Analyse der Daten wertvolle Informationen zu gewinnen. Diese Informationen lassen sich in datenbasierten Dienstleistungen mehrwertstiftend in der Instandhaltung nutzen. In diesem Beitrag wird das Potenzial von datenbasierten Dienstleistungen in der Instandhaltung erläutert und wie dadurch neue Geschäftsmo-dellen für Unternehmen entstehen können. Der Beitrag schließt ab mit einer Beschrei-bung möglicher Einsatzfelder von datenbasierten Dienstleistungen in der Instandhal-tung am Beispiel des Unternehmens BELFOR DeHaDe GmbH.