Industrie 4.0

Like Facebook on Steroids? Challenges and Good Practice Examples for a Successful Implementation of Enterprise Social Networks

Like Facebook on Steroids? Challenges and Good Practice Examples for a Successful Implementation of Enterprise Social Networks

Herausforderungen und Anwendungsempfehlungen zur betrieblichen Nutzung von sozialen Netzwerken
Jonathan Niehaus, Alfredo Virgillito
With the industrial internet the digitization of communication processes receives a new impulse. By application of social networks within firms, the collaboration of and knowledge transfer between workers can be supported and rationalized. This paper focuses on Enterprise Social Networks and discusses the challenges and opportunities when implementing these digital communication tools. On basis of a real world case study we illustrate some good practices.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 4 | Pages 21-24
Determining the Maturity Level: the Path to SCM 4.0

Determining the Maturity Level: the Path to SCM 4.0

Guido Siestrup, David Zeeb
Recent advancements in cyber physical systems (CPS) and industry 4.0 concepts are expected to result in a disruptive change of business processes in industry and commerce. In particular, this refers also to supply chain management (SCM) and logistics systems and processes. Methodically, maturity models can be used to determine the maturity level of SCM and logistics organisations. In this paper we present an extension for a maturity model being able to check the industry 4.0 compatibility of SCM systems and processes. Moreover, the aim is to provide a tool supporting the transformation towards SCM 4.0-ready systems and processes. The requirements for the digital transformation process are described and important fields of actions are discussed.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 3 | Pages 59-62
Structural Planning of Future Production Systems

Structural Planning of Future Production Systems

The Required Transformation for Planning and Operating the Smart Factory
Samuel Horler, Egon Müller
The Smart Factory concept describes the extensively networked production of industry 4.0, which affects the entire life cycle of a factory and, in particular, factory planning and factory operation. Both classic and more up-to-date factory planning approaches come to their limits through the new requirements. This paper identifies the requirements that are important for the future structural planning of factories and presents the need for a holistic virtual validation of the factory structure. Furthermore, a methodological approach is addressed for the solution of the challenges.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 3 | Pages 54-58
Occupational Health and Safety in Industry 4.0

Occupational Health and Safety in Industry 4.0

Stefan Süß ORCID Icon, Ines Catharina Wulf, Ulrike Körner
As a result of digitalization, the dynamics and complexity of our work environment are continuously expanding, facing employees with increasing man-machine interaction and constantly changing work activities. This technical progress might introduces us to new or altered psychological strains for employees. Results of half-structured interviews show that digitalization leads directly and indirectly to new psychological strains. In order to prevent potential health consequences, it is crucial to consider new dimensions such as flexibility and monitoring in the work place risk assessment.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 3 | Pages 26-30
Developing the Textile Smart Factory

Developing the Textile Smart Factory

How Digitization Changes Textile Production
Egon Müller, Ralph Riedel ORCID Icon, Michael Bojko, Nadine Göhlert, Sten Döhler, Andreas Merkel
Shaping intelligent production environments is one core element of Industry 4.0, but has progressed differently in the various branches. While concepts are well advanced in automotive, SMEs within textile industry still need assistance. As demands on individualization and responsiveness are increasing, a Smart Factory for textile SMEs must be designed. The futureTEX consortium therefor is working on shaping a textile Smart Factory and implements it prototypically by using demonstrators.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 3 | Pages 73-77
Industry 4.0: Knowledge Transfer and Competence Profiles

Industry 4.0: Knowledge Transfer and Competence Profiles

Knowledge Transfer and Competence Profiles for the Smart Factory
Dominik T. Matt, Michael Riedl, Erwin Rauch
In the context of this article, a methodology for an efficient transfer of knowledge from research into industrial practice regarding cyber-physical production systems is presented. The methodology serves above all to sensitize small and medium-sized (SME) enterprises to the possible potentials of the so-called Industry 4.0. The starting point for this is the need-oriented and individual specification of knowledge required for a practical knowledge transfer and the development of tailor-made competence profiles of future employees in smart SMEs
Industrie 4.0 Management | Volume 33 | 2017 | Edition 3 | Pages 11-15
Industrial Data Space® – Digital Sovereignty for the Automated Data Exchange

Industrial Data Space® - Digital Sovereignty for the Automated Data Exchange

Digitale Souveränität für den automatisierten Datenaustausch
Jan Cirullies, Christian Schwede, Lars Nagel
The Industrial Data Space enables business based on networked data and data sovereignty at the same time. The technological solution and the certification scheme of the Industrial Data Space ensures secure access to data which companies usually do not dare to share today. This gives new opportunities and provides new data-driven business models. The Industrial Data Space® initiative consists of a research project owned by the Fraunhofer-Gesellschaft and the Industrial Date Space Association.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 2 | Pages 25-28
Is Predictive Maintenance the Killer App for IIoT?

Is Predictive Maintenance the Killer App for IIoT?

Christoph Papenfuss
Predictive, or condition-based, maintenance is a shining goal for industrial customers and the Industrie 4.0 initiative. Supplementing, or even replacing, inefficient schedule-based maintenance with software promises to reduce equipment failures and unplanned downtime, improve safety and ultimately help the bottom line in an era of unstable prices and uncertain budgets. Predictive maintenance might be taking longer than expected, but in the next five years you might see it move faster than expected.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 2 | Pages 57-60
Logistics 4.0 – Changing Logistics Processes – Technological Changes in Logistics Systems and their Influence on the Working Environment in the Operative Logistics

Logistics 4.0 - Changing Logistics Processes - Technological Changes in Logistics Systems and their Influence on the Working Environment in the Operative Logistics

Natalia Straub, Sandra Kaczmarek, Tobias Hegmanns, Stephanie Niehues
Currently the implementation of digital technologies in response to important competition requirements is promoted in many places. Consequently, the working environment of employees in operative logistics is going to change significantly. This article provides an overview of the possible uses of future-oriented technologies in different logistics processes as well as the thereby changing subtasks and competence requirements of operative employees in the working world 4.0.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 2 | Pages 47-51
Standardization for Industry 4.0 in SMEs

Standardization for Industry 4.0 in SMEs

Welche Herausforderungen werden von kleinen und mittleren Unternehmen durch Standardisierung hinsichtlich Industrie 4.0 gesehen? Ein Branchenvergleich.
Julian M. Müller, Kai-Ingo Voigt
Industry 4.0 requires many efforts in terms of standardization. So far, small and medium-sized enterprises have scarcely been regarded in this context. This study presents empirical results from 225 SMEs regarding three contexts of standardization, inside the enterprise, interfaces with other enterprises and outside the enterprise. Differentiated for ten industry sectors, distinct characteristics and strategies for standardization regarding each industry sector are derived.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 2 | Pages 29-32
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