Adaptability

The disposition and control of orders in the field of event logistics constitutes a complex and dynamic challenge. Changing venues, temporal restrictions as well as order changes and high customer demands require a flexible planning of the related logistic processes. Methods from the field of autonomous control offer a promising approach to cope with these problems. This contribution deals with the design of a special module for the information acquisition within the related logistic processes, as the provision of actual planning data is an indispensable prerequisite for the application of autonomous control.

Customers, society and politics challenge companies to ensure the sustainability of their value creation. Many stakeholder groups have an eye on the logistics. These groups constantly raise new requirements and regulations affecting companies’ businesses.  This is the reason why it is not sufficient anymore to react on changing requirements. Companies can gain competitive advantages if they anticipate trends in sustainability and react immediately. In this context, this article presents an approach for trend monitoring and a change agent suppor-ting to react effectively and efficiently on trends in sustainability.

The steadily alternating requirements for industrial companies implicate the challenge to enhance production systems. In such a turbulent as well as dynamic environment, companies must be enabled to act and react quickly. Therefore they have to be equipped with appropriate technologically and organizationally realizable as well as economically rentable options. Within this paper, a methodical approach for a systematic and individual configuration of production systems is presented in order to solve the depicted problems.

The term adaptability is examined from different point of views in modern research. At the same time it can be noticed that adaptability is a more and more important key feature for companies, because of the fact that the ability to adapt is connected to the future development and positioning of a company. Consequently the reaction to a changing environment is an important aspect for companies to act successfully on a long-term basis. To ensure this long-term orientation a company has to analyze a large number of information. The Controlling body of a company plays a central role in getting and analyzing these information. It has also the general competence to retain, select and provide the available information of a company. First empirical surveys show how the controlling can be engaged to recognize and assess requirements of adaptability as early as possible.

The competitiveness of manufacturing companies producing in high-wage countries is strongly depending on labour productivity. In the course of Germany’s demographic change, companies with manual production need to compare the heterogeneous impact factors on labour productivity to develop goal-oriented measures for productivity improvements. The integral productivity analysis enables the user to identify the various impacts on labour productivity and to prioritise fields for process optimisation. The approach is based on the state-oriented modelling of worker activities.

The primary user-model of enterprise systems is expert-based. It depends on the assumption, that the user has expert knowledge about technical terminology and system functions. This model also assume that developer and user has the same degree of knowledge. This statement cannot be accepted. In the future it is more or less necessary that not-skilled workers are familiar with enterprise systems. For this purpose, the center of enterprise research developed a concept for an enterprise system assistant system. It allows the usage of complex enterprise systems also for less trained users.

In the future, objects with embedded intelligence will be able to coordinate and steer the production sequence in a self-organizing production environment. Instead of existing central planning and control the new product-controlled manufacturing uses a multi-agent system with the possibilities of auctions and negotiation. The project “Self-organizing Production  SOPRO” implements autonomous micro systems and software agents to provide embedded intelligence on objects in production field.

The fourth industrial revolution promises a further automation of process control by cyber-physical systems. The individual products gain the ability for controlling their production and logistics themselves. By coordinating themselves they can jointly achieve business objectives. This logical decomposition reduces the complexity of cross-company process control significantly. Thus, even exceptions on short notice can be dealt with in real-time. In operation, the required artificial intelligence will usually not be implemented on the active objects. Instead, adequate software platforms for the so-called Industry 4.0 are required. This article investigates the requirements for such platforms and describes how they can be implemented.

Along with increasing complexity and dynamics the importance of cyber-physical systems in production and logistics also increases. Hence, the BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen considers the application of cyber-physical systems in logistics. This paper presents the approach for the development of a cyber-physical logistics system. To start we describe the fundamental terms cyber-physical system and cyber-physical production system. Following these definitions we explain the term cyber-physical logistics system. Afterwards we describe the course of action; in particular necessary steps within the development of a cyber-physical logistics system are explained. In detail we present the procedure consisting of requirements analysis, conception and simulation-based evaluation.

Information technology is one of the key enabling technologies of future manufacturing. In the two basic business processes manufacturing is located at the intersection point. However, for manufacturing and its value adding purpose, information technology has to be considered as a tool. In this paper the author describes an approach to the components of a new information model inside the future factory.