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With neutron diffraction, the local stress and texture of metallic components can be analyzed non-destructively. For both, highly accurate positioning of the sample is essential, requiring the measurement at the same sample location from different directions. Current sample-positioning systems in neutron diffraction instruments combine XYZ tables and Eulerian cradles to enable the accurate six-degree-of-freedom (6DoF) handling of samples. However, these systems are not flexible enough. The choice of the rotation center and their range of motion are limited. Industrial six-axis robots have the necessary flexibility, but they lack the required absolute accuracy. This paper proposes a visual servoing system consisting of an industrial six-axis robot enhanced with a high-precision multi-camera tracking system. Its goal is to achieve an absolute positioning accuracy of better than 50μm. A digital twin integrates various data sources from the instrument and the sample in order to enable a fully automatic measurement procedure. This system is also highly relevant for other kinds of processes that require the accurate and flexible handling of objects and tools, e.g., robotic surgery or industrial printing on 3D surfaces.
The energy turnaround in Germany increases the share of renewable energies. Since the amount of renewable energy supply is immanently subject of variation, the electricity price at the European Energy Exchange EEX is highly volatile. If companies would purchase the electricity directly at the EEX instead of from a wholesale power supplier along with price fixing, companies would benefit from increasing production in times with low electricity costs and reducing production in high-cost times. This paper shows, that influencing respectively shifting the time of electricity consumption –e.g. by adjustment of process parameter, shift period, order of jobs or machine utilization, by pausing of processes or delaying of job starts – can theoretically reduce electricity expenditures. The measures are being explained and discussed, followed by a description of company in-house and external requirements for the energy flexible production.
While autonomous guided vehicle systems are increasingly used in homogeneous and structured environments, their use in complex and variable scenarios is usually limited. Established algorithms for the navigation of systems use static maps with deterministic metrics, which can only achieve optimal results in clearly defined environments. In dynamic and extensive deployment scenarios, which are also dependent on a large number of influencing parameters, autonomous intralogistics systems cannot yet be deployed dynamically. One example here is mixed transport between buildings under changing weather conditions. As a solution for dynamic navigation, we propose a hybrid metric in combination with topological maps and cyclic environmental sensing. Based on a quantification of influencing factors on each intralogistics entity, an optimal and dynamic navigation of every system can be performed at any time. The individual components are implemented in the context of an autonomous tow truck system and evaluated in different application scenarios. The results show significant added value in use cases with sudden weather changes and complex route networks.
The current trend in internal value stream structures shows a clear development towards a combination of the specific advantages of the operation-oriented and the process-oriented production systems. All scientific approaches have in common that flexible intralogistics production networks require an autonomous and intelligent transportation systems that is not designed for a specific task, but can take on different transport roles due to their versatility. However, a comprehensive analysis of current designs and research projects in the field of AGVs and intralogistics transport robots show that there is neither the necessary interoperability of different systems nor a system architecture that addresses a flexible material flow independent of the physical design of the transportation system. AGVs mainly have a central control system, which manages the generation of transport orders and their disposition on the vehicles. In addition, the routes are specified centrally for the vehicles, even if they have free navigation. The individual transport unit is therefore only an executing machine that processes the assigned transport orders without any influence on order dispatching or route planning. Therefore, these AGV approaches do not have the flexibility and autonomy required for an intralogistics production network. The research project addresses the necessary interoperability of logistics systems and the abandonment of proprietary standalone solutions. For this purpose, methods for digitizing the workspace, route planning and path execution using a service-oriented architecture (SOA) were developed. A central component of this architecture is the approach described in the paper to enable decentralized path planning on the vehicles. Therefore, the path planning must be applicable to different target platforms without implementation effort and the vehicle software must be designed independently of the application. This approach allows intralogistics systems to be flexible and adaptable, resulting in a more sustained use of these systems.
The running costs of production sites are a decisive factor in the overheads of automotive production. Because of this, it is important for many operators to decrease those costs in a sustainable way. Therefore, they try to reduce both the energy consumption costs of production systems, as well as their maintenance costs. However, most parts of the running costs are already determined during the very early phases of the product creation process. The approach in this paper shows how the decision for a specific manufacturing technology influences the factory costs. It is necessary to determine the life-cycle costs with regard to the manufacturing technology. Therefore, deep knowledge about the process itself and the support processes is required. This paper shows how cost relevant parameters can be identified and introduces a method to determine the prospective costs for maintenance and energy consumption in advance.
In case of concatenated, complex material flow structures such as those in calcium silicate masonry unit plants, plan deviations pose a major challenge for an efficient order processing in production. In order to overcome the separation between the planning and operational levels in traditional production planning and control systems, this paper presents a validated concept to react immediately to critical events while maintaining efficiency using a modular, rolling-reactive optimization tool. A substantial difference to conventional rescheduling models is the intensive integration of event-discrete simulation, which delivers more realistic results and reduces the threat of an obsolete model due to simple modelling.
Owing to a high inflexibility of the factory layout, manufacturers of masonry units are bound to organizational adjustments seizing optimization measures. Regarding such plants, having a given complexity based on a rigid concatenation of heterogeneous sub-processes with heavy goods to be transported, conventional measures such as Lean Management principles involve great efforts in execution. Therefore, an IT solution for planning and controlling the operational processes is to be developed. This solution will be implemented through simulation-supported optimization to support dealing with a higher complexity and setting up a more resource-efficient manufacturing process.
As a basis, a corresponding factory is mapped sufficiently accurate in every detail in a discrete event analysis (DEA) model. In this paper, a methodology, how to configure an arbitrary calcium silicate masonry unit (CS) plant in a simulation model, is presented for the first time. Relevant data is cataloged and modelling approaches for the controlling methods are pointed out.
Special regard is paid to optimization measures at the crucial point of the transition from bulk material to piece goods, which has not been regarded yet in discrete event simulation modelling. The major aspect is a comparison of a unit-based approach and a variable-controlled approach, regarding the runtime.
A case study follows conclusively, which aided in validating the methodology by simulating various scenarios. As a result, several strategic and operational optimization potentials were identified.
Companies are forced by rising energy costs to seize control of their energy consumption to maintain contestability. There-fore, transparency over the companies’ energy flux along the production process is required. Energy data management software is helpful, but cost-intensive. Hence, especially small and medium sized enterprises (SME) spare this investment. In this paper, the requirements for an energy controlling infrastructure in SME are elaborated, followed by a deduced software-architecture which supports the respective controlling structure. Further, the prototypical realization of the corresponding tool “Green-Cockpit” will be presented. The free of cost, open source and web-based tool is designed to help companies monitor, interpret, analyze, plan and report their energy consumption. The Green Cockpit tool outperforms other energy management software at management disciplines with its ability to not only analyze energy consumption, but plan and control it additionally.
Today's research projects propose a modular manufacturing environment for automotive production sites, which adapt itself autonomously and makes manufacturing decisions without the need of human interaction. Tugger trains are an energy-efficient possibility to handle intralogistics material supply due to the bundling of transport volumes but reaches its limits in the proposed automotive manufacturing environments. The spatial nearness of the production units and the necessity of a high-frequented and small-scaled supply lead to the application of small-scaled autonomous transport entities. The main disadvantage of this technology in turn is a higher intralogistics traffic. Therefore, the concluded concept of this paper connects the advantages of both technologies.