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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.