Industrie 4.0

The existing approaches of Industry 4.0 promise a fundamental change of production organisation and production technologies. The demanded IT-networking and flexibility of production change the value creation process elementary. Hence, there are new requirements emerging to ensure the process. Especially, for the German industry, the adherence of quality requirements is the key factor in being competitive. According to the state of the art, to reduce system down time, systematic testing of the functionality of production facilities before commissioning is employed. Due to the dynamization of production, testing in the engineering and commissioning phase will not be sufficient in the future. The ability to ensure the production of tomorrow plays an important role in increasing the profitability, and with it, the acceptance for Industry 4.0. This article describes the structural changes of a smart production and its effects on testing.

The traditional data management approach is resulting in multiple silos of duplicate data. Across applications, there are multiple data services generating tremendous amounts of redundant data copies that utilize valuable storage capacity and a tremendous amount of storage and data management resources. Most companies try to leverage the data in order to increase the performance and accessibility of production data. A radically different approach is required in order to solve the data copy explosion problem: Copy-Data-Management, based on the virtualization of data copies.

The importance of data science for production and logistics continues to grow because more data are available due to Industry 4.0-Applications used for process and system optimization. In addition, the improved methods and tools for data analysis enable an easier processing of application-specific issues. This article is the second part relating to data science in production and logistics. While the first article dealt with the definition of terms and the potential of data analysis, the article at hand is dedicated to the application of data science in production and logistics by means of various application examples.

The third industrial revolution culminated in the Computer Integrated Manufacturing but limited computing power and the dystopia of a deserted factory prevented its success. Industry 4.0, however, stands for the integration of people, technology and organization. Based on the networking of products, tools and means of production become all relevant information available. The combination with cloud computing and big data enables the analysis and utilization of such information.

The implementation of industry 4.0 concepts requires a new understanding of data processing and analysis. Data Science integrates approaches of mathematical modelling and performant implementation to analyse data of specific application areas. Within this first article, the basics of Data Science are presented and perspectives for a data-driven production and logistics are discussed. Within a second article in a following edition, the process steps for structured data analysis will be explained and illustrated by means of application examples.

Industry 4.0 gain in importance in recent years. Research and business realize increasingly that targeted activities in this area are necessary to preserve the market power of the industry. This article provides a summary of Industry 4.0 initiatives in ten European countries as well as their comparison based on different criteria.

Current developments of Industry 4.0 offer new possibilities for coordination and coope-ration in production networks. Information technology allows for an ad-hoc documentation and analysis of system states. Hence, manufacturing resources can be offered to other companies in the short term, and coordination, scheduling, and billing can be done quickly. Industry and science now need to find appropriate procedures and practices how to implement and run networks of shared resources.

Mixed global economic signs hardly allow for reliable long-term forecasts. While the traditionally export-oriented production sector in Germany is benefitting from the economic recovery in the U.S., Asian demand has started to dwindle. At the same time the third industrial revolution offers new opportunities and challenges through the development of intelligent production systems and manufacturing processes. In order to obtain an advantageous position in a changing technological and economic environment, companies must preserve efficiency and innovation in production processes. The deployment of modern technology and machinery equipment is therefore crucial. Flexible financing solutions help industrial enterprises make investments and maintain flexibility and competitive advantage.

Companies have to cope with an individualization of products. Consequently, they are confronted with an increasing cost pressure and thus, they require optimal manufacturing processes. A possible approach is to share manufacturing resources with other companies to maximize the utilization of these resources. This paper describes possible perspectives of resource sharing for companies by using an analogy between the Web 2.0-based Share Economy and resource sharing of tomorrow’s production based on Industry 4.0.

Demanding challenges arise through interactions of demographic development and change of modern working life in an industry 4.0., especially for enterprises of the production and logistics sector. While facing rapidly changing technologies and demographic homogenous personnel, they are requested to ensure that the required knowledge and the necessary competences are constantly recallable. A demographic-sensitive, operational competence management (ABEKO) plays a major role.