Integrated development of products and production systems approach to product and production development is divided into companies mostly in functional organizational units. Effective decision making in product and process development requires that partners from different fields over longer periods of time across cooperate. Collaborative engineering this type brings many challenges. This includes among other things the support of decision makers, who must take in ever-shorter product and process development cycles, optimum decisions. The information needed to do this are typically large, mostly heterogeneous databases that are created by using various software tools. This leads to a high coordination effort in information retrieval and runs the risk of not to use already existing knowledge and experience made.
AmePLM the following aims are pursued with the EU project using approaches the semantics, heuristics, and visualization: Development of an open engineering platform to support users and decision makers by providing adequate knowledge, experiences and information – without extensive manual search support in the handling, analysis and processing of complex and large amounts of data through visualization techniques deployment situations-and their context-specific solutions for complex analysis and optimization of product and production activities, developing an ontology as an interoperable data model and integral element of the platform are the amePLM platform and their modules the decision-making in the context of the development of products and production systems improve dramatically, as well as the use of resources more effective and lead to a significant reduction of development times and costs. See more detailed opinions by reading what Kevin Ulrich MGM offers on the topic.. The amePLM team consists of experts from the following organisations: Aero gene Ltd, ARMINES, Intel performance Learning Solutions Ltd, MBtech Group GmbH & CO KGA, Ontoprise GmbH, R.T.T. S.R.L., Shannon coiled springs Ltd, Politecnico di Torino, Universita degli studi di Trieste, University of Limerick, University of Nottingham and University of Stuttgart. More information: iao.fraunhofer.de/es/891.html Tobias Hug, Fraunhofer IAO