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Die vorliegende DIN SPEC 77007 soll einen Leitfaden zum Aufbau und zur Weiterentwicklung von Dienstleistungsorganisationen entlang der Lean-Management-Prinzipien liefern und einen Überblick über Methoden zur Operationalisierung dieser Prinzipien geben. DIN SPEC 77007 ist insbesondere für industrielle Dienstleistungen, aber auch für andere Dienstleistungs-branchen anwendbar.
Anhang A dieser DIN SPEC enthält eine Sammlung von Methoden, die bei der Anwendung der Prinzipien genutzt werden können.
The evaluation of the maturity level of the participating companies has provided an initial insight into the degree of implementation and the upcoming challenges of Industrie 4.0 in Mexico. The assessment shows that Mexican companies have built the necessary foundation to start their digital transformation. Challenges now lie in establishing an integrated IT landscape that makes it possible to generate a digital shadow of the entire company. In order to leverage the potential of this technological development, it is necessary to work in parallel on an even more flexible organizational structure and an innovation-promoting Culture.
In order to strategically plan the digital transformation of a manufacturing company, a detailed analysis of the company's maturity level must be carried out. The basic dimensions of such an analysis were presented in the present paper. The Industrie 4.0 Maturity Index offers a framework that identifies approximately 50 individual capabilities required for the systematic implementation of Industrie 4.0 and groups them into the four dimensions discussed in this paper. Only an analysis of a company's key processes at this level of detail can form the basis for a sound investment decision and a roadmap that outlines the steps towards its digital transformation for the upcoming years.
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 FIR at the RWTH Aachen University continuously develops the concept and the principles of RoM further. It is already noticeable that the gap between companies that began preparing their maintenance departments for Industrie 4.0 years ago and those that are still struggling with the mere foundations of a professional maintenance organisation is rapidly increasing.
The first driver of the development sparked by Industrie 4.0 is the collection of and work with condition data. It is used to create a digital shadow of a service, e.g. maintenance measures in a specific
context. In the future, critical machine functions will be monitored continuously within production processes.
Based on these observations, the likelihood of machine failures can be predicted, which makes it possible to prioritize data-based maintenance measures. This means that maintenance activities, i.e. production plans, are based on prognoses regarding machine failures. By doing so, the currently existing separation between inspection, maintenance and reactive measures can be overcome, resulting in a holistic approach to maintenance. Maintenance specialists receive support from assistance systems, which give them access to all relevant information (e.g. machine history, spare part availability, proposals for measures, etc.). As a result, they can take on routine tasks in different areas as well and contribute to the increased flexibility of the production process. Although data is becoming an increasingly important driver of successful maintenance strategies,
maintenance employees continue to be central to specific tasks, machines and systems. In the future, it can be expected that they choose to become experts in a certain field and, ideally, actively share their knowledge with others within an open maintenance culture. Systems for interdisciplinary collaboration will be made part of everyday practice.
The maintenance department will be a center and distributor of knowledge in the agile company of the future.Only through the interaction of the outlined success principles, which amount to a paradigm shift within the maintenance department, the potential
benefit of maintenance as defined by RoM can be fully exploited, creating a long-term competitive advantage for those who consistently follow the path towards Industrie 4.0 in maintenance.
Today, machine manufacturers generate a significant share of their revenues with the provision of services. At the same time, they are confronted with the challenge of adopting of Industrie 4.0.
One of the most important Industrie 4.0 concepts is the idea of the digital shadow, which contributes to the comprehensive structuring of different kinds of data from different data sources. It can be defined as the sufficiently precise, digital representation of reality in real-time.
Thus, it also functions as a database of the considered area of a company that can be used for numerous applications. It serves as a central platform for the aggregation and distribution of data. Thereby, it helps to open isolated data silos. A system architecture that enables extraction of data from various sources and the aggregation of that data is an important prerequisite for the digital shadow.
In addition, the merger of data from different sources requires a model of the part of the company to be mapped digitally. In this paper, we focus on maintenance, repair and overhaul (MRO) services of machine manufacturers. The scope comprises the whole order processing of a service including the utilized resources and the obtained results.
MRO services and their single elements are mapped and structured using a case study research in a first step. Those elements provide a basis for designing the digital shadow. A second contribution of this paper is a data model for the digital shadow of MRO services that entails a comprehensive representation of that department.
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.
Gestaltung des Digitalen Schattens für Instandhaltungsdienstleistungen im Maschinen- und Anlagenbau
(2019)
Unternehmen des Maschinen- und Anlagenbaus sind mit der Herausforderung konfrontiert, die digitale Transformation ihres Unternehmens zu gestalten. Eines der zentralen Konzepte der Industrie 4.0 ist der Digitale Schatten. Er fungiert als übergeordnete Datenbank, die alle relevanten Ereignisse im Unternehmen strukturiert aufnimmt. Mit dieser Arbeit wird der Digitale Schatten für den Bereich der Instandhaltungsdienstleistungen definiert und eine Vorgehensweise für dessen Einführung bereitgestellt.
Lean Services ist ein am FIR an der RWTH Aachen entwickeltes Managementkonzept, das die Vermeidung von Verschwendung und die konsequente Ausrichtung der Serviceprozesse an der Erzielung eines möglichst hohen Kundennutzens fokussiert. Konkret bedeutet dies, die Gestaltung schlanker Prozesse bei gleichzeitig komplexer werdenden Markt- und Kundenanforderungen zu berücksichtigen.
Im Mittelpunkt von Industrie 4.0 steht die echtzeitfähige und Intelligente Vernetzung von Menschen, Maschinen und Software, mit dem Ziel, komplexe Systeme transparent zu gestalten und dynamisch zu managen. Industrie 4.0 kann somit als Ergänzung des Lean-Services-Ansatzes dazu beitragen, die zunehmende Komplexität in der Leistungserbringung beherrschbar zu machen. Die Potenziale digitaler Technologien müssen dabei allerdings zunächst durch die Anwendung grundlegender Lean-Prinzipen "nutzbar" gemacht werden. Der Lean-Services-4.0-Zyklus gibt vor, wie Unternehmen diesen Weg gestalten können, indem die fünf Phasen des bewährten Aachener Lean-Services-Zyklus, ergänzt durch die drei übergeordneten Schalen Technologische Enabler, 'Lean Services 4.0'-Methoden und Potenziale von Lean Services 4.0 durchlaufen werden.
Today, however, agility is seen more than ever as a critical success factor for companies. In times of an increasing degree of digital interconnection and minimum viable products, a mentality is entering the industrial service sector that has so far only been exemplified by Internet companies (e.g. Google): New products and especially digital services are developed in highly iterative processes. To this end, customers are involved in early test phases of development and provide feedback on individual functional modules, which – in contrast to the previous approach – are only gradually assembled into a market-ready “100 percent version”. But especially with the development of new digital services, companies must ensure more than ever that both the existing analog service business and the design of new digital services are geared to effectiveness and efficiency in order to meet the growing demands of customers and competitors.
To achieve this, companies must not only be familiar with the products currently on the market, but also master the entire product history, which in some cases goes back more than 30 years and varies greatly from one industry to another.
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.
Data-driven transparency in end-to-end operations in real-time is seen as a key benefit of the fourth industrial revolution. In the context of a factory, it enables fast and precise diagnoses and corrections of deviations and, thus, contributes to the idea of an agile enterprise. Since a factory is a complex socio-technical system, multiple technical, organizational and cultural capabilities need
to be established and aligned. In recent studies, the underlying broad accessibility of data and corresponding analytics tools are called “data democratization”. In this study, we examine the status quo of the relevant capabilities for data democratization in the manufacturing industry.
(1) and outline the way forward.
(2) The insights are based on 259 studies on the digital maturity of factories from multiple industries and regions of the world using the acatech Industrie 4.0 Maturity Index as a framework. For this work, a subset of the data was selected.
(3) As a result, the examined factories show a lack of capabilities across all dimensions of the framework (IT systems, resources, organizational structure, culture).
(4) Thus, we conclude that the outlined implementation approach needs to comprise the technical backbone for a data pipeline as well as capability building and an organizational transformation.