optimization

Production in space, of semiconductors for example, offers many advantages for companies. At the same time, high transport costs mean that careful consideration must be given to the production materials being transported. The use of Kalman filters enables (real-time) control from Earth, making space production a cost-efficient option. Machine learning could make it a viable approach even for highly complex production systems.

The supply of production processes and buildings with thermal energy represents a significant share of the total energy demand of an industrial site. The use of industrial waste heat offers a way to reduce the external purchase of final energy. Due to the lack of transparency and the complexity of such measures, their potential often remains untapped. In the research project ETA im Bestand a user-oriented software solution was prototypically implemented. The software solution enables the development and evaluation of industrial energy concepts. Approaches from the research area of operations research and dynamic simulation are applied.

Optimisation is an essential task in many situations. The class of evolutionary algorithms is a population-based, heuristic technique for optimisation. They allow the optimisation of multi-modal problems even with distorted search spaces. They can propose several solutions instead of just one. An important aspect of evolutionary algorithms is encoding search space candidates. In the optimisation of processes, this is a non-trivial task. This article describes a successfully tested encoding.

Modern logistic processes are still characterized by manual labour. In general, mainly unqualified or low-skilled employees are used to carry out value-added services. Individual workloads, employee skills and technical workplace equipment are linked in a developed system. By simulating the effect of changes in workplace equipment, optimizations can be identified. The self-developed algorithm can also be used in other industries.

The core task of logistics can be described by the so-called “seven R”. IT means that the right product must be available in the right condition at the right time and at the right place. In addition, further key factors of a well-functioning logistics system are the right quantity, the right costs and the right information. Providing right or incorrect information at the wrong time can have a significant repercussion on the entire process. In particular, the human being who is the recipient of the information has the demanding task of correctly select and interpret it. Therefore, the human-machine interface plays a decisive role in the communication success between human employees and the digital systems surrounding the human at work. On that account, new user interfaces that do not burden people and provide information in a way that it can be perceived intuitively are needed in the future. This is where data glasses come into play.

Container terminals are complex logistics systems. In order to achieve highly productive processes and an efficient assignment of the resources, optimization methods and simulation modeling are employed in practice. Based on a case study from the Container-Terminal Altenwerder in Hamburg, this contribution demonstrates how simulation and optimization can be applied to improve the processes related to reefer container handling. We show that optimization methods improve the efficiency of the reefer mechanic operations and how simulation models can support the development and evaluation of such methods in practice.

This paper describes an autonomic machine control system applied to the adaptive control of a modular soldering machine. It covers customer requirements, design principles as well as benefits and advantages by making use of software agent technology. The particular case concerns the creation of a novel modular production machine currently running as a pilot, which will be sold worldwide from mid of the year.

Although the relocation trend has slightly decreased during the last five years, nowadays more companies plan to shift abroad in the near future. In particular small- and medium-sized companies plan the relocation of parts of their value chain. The disadvantage of the German location can only be compensated by a combination of cost optimization and an increase of productivity. A systematic procedure and the application of sophisticated evaluation tools support the company in its process of decision making. Considering the type of business, guidelines for competitive value chain management can be developed.