planning

In order to meet the demands of a more flexible supply of small lot sizes, many companies use in-plant milk-run systems. Despite the increasing distribution of milk-runs, a standard has not been established yet and the planning is often carried out without a suitable methodology. Therefore, a methodology was developed that supports the integrated design of the technology, the process and the controlling of an in-plant milk-run system as well as an integrated evaluation of alternatives.

Complex technologies of all industrial ranges require increasingly a holistic view of the entire technological process chains. In many methods processes are illustrated as already established and approved technological processes. The way up to an executable technological process is not supported. Straight in the technologically oriented R&D the know-how which is necessary for reproducible quality-assuring production is developed. In this paper new methods for the technologically oriented modelling and analysis of process chains are described which allow to effectively generate operational technology knowledge.

There are numerous and relevant application domains like inspection, maintenance, surveillance, and handling of non-uniform goods where the use of robots would be beneficial. This article addresses the reasons that make it difficult for a present-day robot to master these domains. The dual arm system AILA will be presented, which takes further steps in the direction of such a use case.

In the planning phase of cyclically interlinked production lines neural networks are used to learn and forecast the characteristics of these systems. To increase the results of learning and to accelerate the training this paper presents a method, based on genetic algorithms, that reduces the attributes to describe the behaviour of the production lines.