AMEPLM | Advanced Platform for Manufacturing Engineering and Product Lifecycle Management

Product and production engineering in companies are typically fragmented across different functional units, distributed across companies along the value chain, requiring input from experts from a variety of disciplines using different methods and tools. This leads to a high coordination effort to synergise work and information transfer as well as to sub-optimal decisions and unused knowledge and experiences. The resulting waste in engineering processes results in an unnecessary lengthening of time-to-market and time-to-production of new products and to a loss of competitiveness of European companies. amePLM will offer a radically new and extensible approach to collaborative engineering, leveraging state-of-the art research on semantics, heuristics and visualization. The objectives are to: • Engineer an ontology that serves as an interoperable model and integrating element for an open engineering system: the amePLM Platform. • Develop an open engineering platform based on existing tools and libraries, by special consideration of open-source software. • Research and develop tools to assist in product and process development, analysis, virtual testing and optimization based on heuristic methods and simulation that operate on knowledge represented by information which is structured by means of an ontology. • Devise a visualization module to enable cross-disciplinary collaboration and remote consultation approaches. The development of a solution will be accomplished through a user-centric approach by 2 leading edge high tech software providers, guided and validated by industrial cases from 3 SME and 2 international companies. The research needed for the innovative amePLM solutions is performed by 5 leading universities and Fraunhofer. The knowledge-driven amePLM platform will drastically accelerate product and production engineering by integrated workflows, capturing and reuse of knowledge and experiences and by facilitating cross-disciplinary knowledge-sharing and collaboration.