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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.

Assistance technologies are an approach to support skilled workers in their work processes that are currently changing under the influence of the 4th industrial revolution. They aim at reducing physical and psychological stress by processing the big amount of decision-relevant data in a way that it serves workers for their decision-making process. Work places need to be designed in a way that they encourage learning and competence development and that involves future users in this design process.

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

Maintenance activities require a high degree of problem solving capacity from the specialists in order to be able to successfully carry out troubleshooting tasks. The expertise of the specialists is based in particular on the successful use of knowledge in problem solving situations [2]. Assistance systems should therefore support the specialist in the learning or reflection process and offer the opportunity to use the experience gained from previous measures for the current problem solution. The present paper describes an approach to the development of assistance systems for learning.

The Smart Factory describes the future way of production where intelligent cyberphysical systems (CPS) form the technical foundation. Regarding this vision, decision-makers out of the industry are purchasing for help in order to implement CPS successfully. A method based on the strategical orientation of companies is presented, with which potential CPS applications can be identified and an associated investment decision can be supported.

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.

Due to the rapid development in information technologies, the amount of information production staff has to deal with rises. Additionally, the requirements for the changeability and flexibility of control systems are growing. This leads to a constantly growing complexity in the handling of information. By avoiding unnecessary information logistics processes, this complexity is reduced and information management becomes easier.

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.

Finally digitalization reaches marketing and sales in Germany. Automation of recurring tasks and activities facilitates both increases in process efficiency as well as a rise in effectivity of decisions made in these functions. German researchers and enterprises are not as deeply engaged in this topic yet as their US and British counterparts. However, this will change rapidly. As a consequence of the changed searching and buying behavior of individuals and organizations, the utilization of marketing automation tools will be inevitable for future market success.