Adaptability

Whilst bIoTope should be understood as a highly flexible and dynamic ecosystem capable of seamlessly integrating arbitrary proprietary IoT platforms, it nevertheless builds upon several core components, which provide essential functionality. Those functionalities referenced in this article, are agnostic to other ecosystem-external systems. Inside of the ecosystem, a micro-service-architecture MSA approach is applied. Using O-MI for technical Interoperability and O-DF for syntactic and semantic interoperability are foundation pillars of the ecosystem.

In the course of digitization, the complexity and instability of business networks are considerably increasing. This has also serious effects on intralogistics. Under VUCA conditions, intralogistic systems develop into open, decentralized and self-organization networks of information-processing units. They adapt to the dynamic changes of their environment, by increasing their inner and outer varieties in a preventive manner. Digital technologies are not in a position to adequately control non-deterministic logistic systems; this task is essentially left to the working man. In order to overcome the challenges, appropriate models and methods of preventive work design are developed in the PREVILOG project. The paper presents cybernetic basics and preventive work design principles.

Companies have to be thoroughly agile. Agility means that companies must be able to consider two things at the same time: On the one hand, companies have to maintain the quality of their own products and services at all times. Continuous innovations could help with this. On the other hand, companies have to be able to adapt themselves to these permanent changes due to these innovations, whereby the adaptation speed must be as high as possible. The question arises as to what extent the cultural identity of nations play a role in terms of their mutability, flexibility and vitality.

Current advances result in increasingly complex production programs. Through combination of additive manufacturing and Industry 4.0, new elements can be formed and - as a whole - enable to economically manufacture the above mentioned programs. The Bionic Smart Factory 4.0 provides a framework, structuring them in terms of relation and interaction. Their development and implementation is being promoted through their evaluation against the determinants of complex production programs.

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.

The technological and demographic change in the automotive industry leads to challenges for competence management. Increasing requirements with regard to professional and methodological competencies, combined with shortened innovation cycles, demand an increasing flexibility in employee trainings. The research project PLUG+LEARN aims at the development of reconfigurable solutions in competence development. Competencies along the automotive value chain are pooled in order to achieve a wide application of the results. This enables an effective cooperation between the actors of the PLUG+LEARN market place.

The most basic task of conveyor systems in intra-logistics is the transport of goods. For more complex tasks, such as rotating, sorting or layer forming, additional mechanical components are often needed. These range from simple pneumatic cylinders to complex industrial robots. This paper presents the novel and highly flexible conveyor system Celluveyor. Due to the modular design and system architecture, any plant layout can be generated and virtually any material handling task can be realized by a simple software update with one single conveyor system.

The volatile world urges companies to react more agile to fast changes. Monitoring is a major building block for corporate agility. A lack of understanding of causal interrelations between a multitude of volatility drivers demands a new monitoring approach. Big data is presented as an adequate tool and its agility support is discussed from a data and analytics point of view. Conclusively, guidelines for developing a monitoring system are discussed.

The network as a complexity driver gains in importance due to a proceeding globalization. The amount and location of sites are a key part of the network. A growing number of sites raises the complexity causing further coordination efforts, interfaces and opacity. Complexity has not been taken into account within location decisions yet. Thus this article analyses the connection between the amount of sites and complexity.

Increasing market volatility and uncertainty require manufacturing companies to adapt their operations model to a substantially changing environment. The orientation towards agility can be seen as a key to success in such a situation. To achieve agility for an organization it is necessary to address four distinct dimensions of agility. A company oriented towards lean production tries to optimize one variable at a time. However, to become agile it is required to address two variables simultaneously. This article outlines current challenges for industrial organizations and points out possible solutions.