Can Livestock Farming Benefit from Industry 4.0 Technology? Evidence from Recent Study

The term ”Agriculture 4.0” emerged from the term “Industry 4.0” like amany other “4.0” terms. However, are Industry 4.0 technologies and concepts really applicable to agriculture? Are the benefits that Industry 4.0 brings to industrial use cases transferable to livestock farming? This paper tries to answer this question for the three dominant sectors of livestock farming in Central Europe and Germany: Poultry, pig fattening, and dairy farming. These sectors are analyzed along with the eight most relevant Industry 4.0 benefits. The results show that only part of the Industry 4.0 benefits are relevant for livestock farming in a similar manner as in industrial production. Due to basic differences between industrial and livestock farming use cases, some of the benefits must be adapted. The presence of individual living animals and the strong environmental impact of livestock farming affect the role of digital individualization and demand orientation. The position of livestock farming within the value chain minimizes the need for flexibilization. The introduction and adoption of Industry 4.0 concepts and technologies may contribute significantly to transforming agriculture into something that may be called Agriculture 4.0. Technologies are indispensable for this development step, but vocational education and open-mindedness of farmers towards Industry 4.0 is essential as well

IT-based Architecture for Power Market Oriented Optimization at Multiple Levels in Production Processes

Given the increasingly volatile prices on the power markets, it becomes economically more and more important for companies to develop and realize flexible strategies for energy consumption. A steady adaption of production processes which considers current power prices can take place on several levels of the automation pyramid, where each level has its own characteristics and requirements. In this paper, we present an optimization architecture based on an IT-platform which meets the challenges of complex multilayered production processes. We introduce layer-specific optimization strategies as well as an associated information flow, which facilitates creating holistic and well-coordinated optimizations

Wissensentdeckung als Verbesserungsansatz

Erklärung der Anwendung vom Wissensentdeckungsprozess (KDD – Knowledge Discovery in Databases) im Bereich Produktion

Wissensentdeckung als Verbesserungsansatz

Erklärung der Anwendung vom Wissensentdeckungsprozess (KDD – Knowledge Discovery in Databases) im Bereich Produktion

Farming in the era of Industrie 4.0

Consistent supply chain management across all levels of value creation is a common approach in the industrial sector. The implementation in agricultural processes requires rethinking in the supply chain concept. The reasons are the heuristic characterized processes, the stochastic environmental conditions, the mobility of the production facilities and the low division of work. In this paper we deal with how concepts of innovative supply chain management of Industrie 4.0 could not only deliver a way to overcome said problems but also provide the foundation for the development of new forms of work and business models for Farming 4.0

Substitution and Complementation of Production Management Functions with Data Analytics

Complexity in production systems is steadily growing– one of the drivers is the customer’s desire for personalization of products and services. Existing production management systems rely on deterministic functions. Given the diversity and varying influence of these functions, current methods reach their limits and may not meet future needs. We introduce new opportunities provided by replacing and complementing these functionalities with data analytics. With a focus on production management and data-driven analysis we offer a flexible method that extends existing Industrie 4.0 technologies for several application areas (e.g., logistics, inventory management)

A Service-Oriented Approach for the Cognitive Factory - A Position Paper

Contrary to former fears, factories will not be deserted in the foreseeable future. The challenge will be the development of digital approaches that assist human beings in manufacturing environments by processing the enormous amount of data available. The proposed approach allows the implementation of manufacturing functionalities based on artificial intelligence. The objective is to design a Cognitive Factory that is able to both reactively and proactively assist humans in complex manufacturing environments. To this purpose, a combination of the Digital Shadow concept and a Service-based Intelligence is presented

Informationsmanagement in der Smart Factory: Die Entstehung und Anwendung des Digitalen Schattens

In order to meet the requirements of personalized production regarding efficiency and flexibility, Industrie 4.0 approaches are recommended. The utilization of an information management system is necessary to avoid the creation of isolated solutions. It was reasearched at the Industrie 4.0 Application Center how the Digital Shadow is able to fulfill this role and what the required steps are

BMWi-Förderprojekt "Industrie-4.0-Testbeds - Umsetzung von Demonstratoren in realen Umgebungen und Evaluation mit Fokus auf Standardisierung"

Industrie 4.0 ist für den Industriestandort Deutschland von besonderer Bedeutung. Der Erfolg hängt sehr stark von der konsequenten Umsetzung der Digitalisierung in den Fabriken ab. Die Systeme müssen flexibel und effizient arbeiten, um den Herausforderungen in modernen Fertigungsbetrieben gerecht werden zu können. Simultan muss den kleinen und mittelständischen Unternehmen (KMU) zur Innovation die Sicherheit und Interoperabilität einer Norm geboten werden. Dies bedeutet, dass neben der klassischen Normung auch ein beschleunigter agiler Normungsprozess implementiert werden muss. Agiler Normungsprozess bedeutet, dass parallel zur Innovationsentwicklung Quellcode und Referenzimplementierung entwickelt, Use Cases in Testumgehungen getestet und die daraus entstehenden Erkenntnisse in fortlaufende Normungsprofile verstetigt werden. Dieser Aufgabenstellung nimmt sich das Projekt an und setzt auf diesen agilen Prozess. Aktuell konzentriert sich das BMWi-Förderprojekt lndustrie-4.0-Testbeds auf Teilaspekte der Industrie 4.0: Predictive Maintenance, Plug&Produce und Autonome Landmaschinen