Manufacturing Systems

In electric energy systems based on renewable generation plants supply and demand often do not occur in the same time. Consequently energy flexibilization is gaining importance in industrial environments, whereby decentralized automation offers opportunities. Compressed-air systems on industrial plants supply manufacturing equipment with compressed air, nitrogen and other technical gases, which partly can be obtained from air by deposition processes. Those systems consist of air compressors, gas separators, reservoirs and lines. With suitable dimensioning and by equipping with automation technology those product-service systems can be used for energy flexibilization purpose.

The increasing customization of products, which leads to higher numbers of product variants with smaller lot sizes, requires a high flexibility of manufacturing systems. These systems are subject to dynamic influences and need increasing effort for the generation of the production schedules and for the control of the processes. This paper presents an approach that addresses these challenges. First, scheduling is done by coupling an optimization heuristic with a simulation model to handle complex and stochastic manufacturing systems. Second, the simulation model is continuously adapted by real-time data from the shop floor. If, e.g., a machine goes down or a rush order appears, the simulation model and consequently the scheduling model is updated and the optimization heuristic adjusts an existing schedule or generates a new one. This approach uses real-time data provided by future cyber-physical systems to integrate scheduling and control and to manage the dynamics of highly flexible ...

Musculoskeletal disorders are responsible for about one quarter of all days of incapacity to work in Germany. In order to identify which types of strain lead to an increased risk of the emergence and aggravation of work-related musculoskeletal disorders in operational intra-logistics and to identify in which types of jobs this risk especially occurs, 30 people working in different companies were interviewed. It was discovered that almost all types of manual handling of loads (lifting, carrying, pulling and pushing), and both standing permanently as well as forced sitting are relevant.

Digital factory, simultaneous engineering and system interoperability are based on collaborative interdisciplinary working processes in an enterprise. According to a study of the workgoup industry 4.0 [1] the implementation of industry 4.0 leads to new collaborative and cooperative behaviour between employees. For academic teaching this implies, that in addition to technical, methodological and IT expertise, collaboration skills must be encouraged. The following article explains the use of physical models to teach collaboration skills by means of the example of factory planning. These models are currently realized or are already in use in teaching at the department for organization of production and factory planning of the University of Kassel.

Human labor will concentrate increasingly on problem-containing activities in Cyber-Physical Production Systems (CPPS). For this employees need a good understanding of systems and processes, a high ability to solve problems and good communication skills. An appropriate design of the interaction between humans and CPPS can help to ensure that these skills will be acquired, preserved and trained in the work process itself. An appropriate mental model on navigation within CPPS may encourage human competences. For this the metaphor „digital awareness“ is proposed.

Exact planning and configuration of process chains contributes significantly to manufacturing excellence in micro manufacturing. In this type of manufacturing, production must adhere to very low tolerances. Furthermore, a multitude of manufacturing processes is available in micro manufacturing whereas some processes are better suited than others for given tasks. The methodology “Micro Process Planning and Analysis” (µ-ProPlAn), which is described in this article, provides suitable means for planning and configuration of such process chains with the necessary level of detail. To reduce the manual workload in comparing alternative process chains, this article proposes an extension, which enables an automatic selection of alternative processes based on a geometry oriented annotation of the µ-ProPlAn process models.

New areas of application arise for robots due to collaborative robots and new operation concepts. We describe important characteristics of these robotic systems and, as a possible application area for these systems, we present in this article a robotic assistant system for manual manufacturing tasks, which is controlled with a multi-modal user interface.

To infer human intentions by approaches, which are embedded into technical systems, is the foundation of a future key technology that enables the development of novel assistive devices. These devices provide solutions to current and future challenges that are caused by the demographic change and requirements of  “Industry 4.0”. Embedded Brain Reading enables a mobile recognition of human intention embedded into a technical system to support users fault tolerantly. The model of the approach suggests that man-machine interaction is verifiable for correctness and completeness for its safe usage.

The development of industry 4.0 concepts in production and logistics has progressed rapidly in recent years. The systems being affected by rapid technological changes, such as the introduction of Cyber-Physical Systems (CPS). The realization of CPS requires interdisciplinary considerations of mechanical engineering, electrical engineering, information and business management. The full potential of industry 4.0 can only be deployed, when in addition to technical challenges also business opportunities are involved in the development. The aim of this paper is to show specific requirements for development of CPS systems and to identify approaches for Cyber-Physical Product-Service Systems (CPSS).

Manufacturing companies of xxl-products are increasingly forced to distinguish themselves from their competitors by the production costs [1]. However, many manufacturers do not have the capabilities to identify and evaluate approaches to optimize their production. Reasons for this drawback are limited capacities or financial restrictions. Therefore this paper introduces a new approach to the identification and selection of optimization approaches for manufacturers of xxl-products.