Smart Factory

Industrial devices have virtual and physical components that interact with each other in a plethora of ways. We report on a system that enables operators to pose queries about physical, regulatory and functional relationships between components and visualizes responses as a holographic overlay, thereby enabling in-situ querying and rendering of information for “on-the-spot” decisions. Importantly, our approach is not only applicable to digitally integrated components but applies equally well to “simple” objects such as surfaces and workpieces, and the materials they are made of.

The Increasing digitization forces companies to deal with their opportunities and challenges. The study underlying this article identifies the economic potential of technological trends and provides an inventory of the current situation in Industry 4.0. To this end, a total of 106 industrial companies have made a self-assessment of their current maturity levels of various technologies in their company and their current and future economic significance. This results in valuable insights for companies in the manufacturing industry, so that they can better deal with the range of different approaches and concepts.

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.

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.

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

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.

This article deals with the presentation of a concept that shows new possibilities for a holistic improvement in the company’s internal resource efficiency by using Industry 4.0. Subsequently, the structure of a resource management system will be shown. To attain a holistic improvement of the resource efficiency, the viewing frame will be extended to the whole product lifecycle to show which potentials a coupling along the entire value-added chain provides.

The setup and configuration of industrial robots presumes a high degree of expert knowledge due to manufacturer specific control commands and a wide variety of design types. As a result, companies are running robot systems repetitively over long time periods instead of using their inherent flexibility. Therefore, in the research project AKOMI methods are being developed that allow automated setup and solution neutral programming of robot assisted assembly lines.

By digital transformation the German SME sector is faced with huge challenges. It also turns existing corporate processes upside down. 82 percent of the managers who were interviewed for a recent survey expect that the internal communication will accelerate significantly. Four out of five are convinced that the transfer of knowledge will play a key role. Three quarters are also convinced that it is necessary that IT and other departments close ranks. Business-simulations effectively support the required transformation process. Topic of this article is to show how they can help changing the attitude and perspective to generate sustainable value from Industry 4.0.