Autor: Daniel Rippel

New production technologies have inherent technical risks, but also established production technologies can not always be transferred to new products or components without problems. Accordingly, these technical risks must be taken into account when planning production systems. This paper presents an approach for the optimized allocation of development resources with regard to the technical risks of production technologies and processes. First, the production scenario is modeled and simulated using GRAMOSA. Then the simulation results are used for the optimized assignment of the development budget by means of mathematical optimization.

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.

In the field of micro manufacturing, a highly precise adjustment of relevant process parameters is of major importance. The continuing miniaturization of work pieces and machines leads to very small tolerances. The occurrence of so called size-effects interferes with a direct application of knowledge and experiences from macro manufacturing. Moreover, the high specialization of manufacturing technologies and processes in micro manufacturing requires a careful review of each process’s suitability with respect to the involved materials and components. This article presents a method that supports process designers with structured procedures and notations, to model and evaluate technological as well as logistic dependencies along the process chain. Thereby, it supports the selection and configuration of suitable processes for a given process chain.

Automation is an interdisciplinary technology which has a significant impact on the industry in Germany. Especially in micro-production as a niche market, there are numerous applications that require highly automated production technologies. The biggest challenge is the control of size effects. Size effects occur in the production of micro components because the ratio of volume to surface forces shifts and adhesion appears. Furthermore, micro forming has batches with high volume, which require high flexible and ideally universal automated handling systems for efficient multi-stage manufacturing processes. This paper deals with the adhesion forces and their reduction by minimizing the contact surface. In addition, requirements and approaches to automated allocation of micro-components are discussed.

The Autonomous Logistic Engineering Methodology (ALEM), which is developed within the Collaborative Research Center 637, provides several tools for creating models of autonomously controlled logistic systems. To evaluate such models, the ALEM framework is extended to include a simulation component. As the ALEM Models cannot run directly within simulation software, they are transformed using principles of the Model Driven Architecture. To enable the transformation several open source tools can be applied. This article evaluates a selection of such tools with the aim of integrating them into ALEM.