No abstract

Products generate a large amount of information during their lifecy-cles. Small and medium enterprises are often not structured enough to enable the efficient management of such amount of information. Several tools of prod-uct lifecycle management have been developed in the last years to address this issue, but they are rarely exploited by companies, especially SMEs. The aim of our work is to present a semantic platform to integrate data along the whole product lifecycle to allow semantic search and knowledge reuse. The integra-tion of data is realized with a reference PLM ontology, containing the main concepts and relations to describe a PLM. This ontology has a modular struc-ture, so that it can be easily extended to describe concrete product lifecycles. An example of a real application of the semantic platform in an industrial case is reported

The rapid growth of the world population, the finiteness of resources on our planet Earth and the ongoing tendency towards urbanisation result in the need to question our actions and economic activities, also for industrial enterprises. A paradigm shift to decouple growth and resource utilisation is needed. By means of ultra-efficiency, factories are targeted, whose positive impact to their surrounding is optimised instead of only minimising negative influences. In the contribution, the concept of ultra-efficient factories and first tools for their implementation are introduced. Therefore, the term ultra-efficient factory is defined based on the state of the art. On this definition, spheres of activity for ultra-efficient factories under consideration of urban surroundings are determined. For the spheres of activity, criteria to assess the according maturity of companies are identified and aggregated into a comprehensive maturity model. The maturity model enables the determination of potentials for advancements of companies. To support the industrial application of the theoretic work, industrial best practices are determined and a visual tool is developed

Products generate a large amount of information during their lifecycle. Small and medium enterprises often lack an efficient management of such an amount of information. Several tools of product lifecycle management have been developed in the last years to address this issue, but they are rarely exploited by companies, especially SMEs. The aim of our work is to present a semantic platform to integrate data along the whole product lifecycle to allow semantic search and knowledge reuse. The integration of data is realised with a reference PLM ontology, containing the main concepts and relations to describe a PLM. This ontology has a modular structure, so that it can be easily extended to describe concrete product lifecycles. An example of a real application of the semantic platform in an industrial case is reported.

During the design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated according to key performance indicators to achieve the optimal system performance. It is a highly complex process involving multidisciplinary stakeholders, various digital tools and protocols. To address the digital discontinuity challenge during this process, this paper proposes a tradespace framework based on semantic technology and Model-Based Systems Engineering. It aims at functionality integration of requirement management, architecture definition, manufacturing system design, solution verification and visualization. An application ontology is developed to integrate assembly system domain knowledge, industrial requirements and system architecture model information. The proposed framework is implemented in a case study to support the fuselage orbital joint process design, which is part of the aircraft Final Assembly Line. A toolchain is presented to support the implementation, which consists of a set of enabling software corresponding to the functional modules of the framework. Different manufacturing system architectures are first designed by industrial system engineers supported by the application ontology semantic-driven tradespace framework stored in a graph database. They are then analyzed through Discrete Event Simulations and 3D simulations. The simulation results are presented through a web-based portal to show the key performance values of each architecture. This study serves as a part of the proofof-concept of the recently proposed Cognitive Digital Twin concept.