Join our project pitches on Product-Production ecosystems
On Friday 3 March 2023 we will pitch these project ideas regarding Product-Production ecosystems.
You can join each pitch by adding the Outlook item to your agenda and joining the online meeting through Microsoft Teams.
The Auto-Seq-Gen project aims to automate the time-consuming and complex process of planning an assembly sequence of a new product on an existing assembly system through model-based optimization. The project will combine information from both the product and system to evaluate the feasibility, requirements, cost, and time of the assembly sequence, which will guide a sequence generation algorithm towards the optimal sequence. The expected outcome is a reduction in development cost and time to market of new products, leading to improved competitiveness for companies adopting this method.
10h30: Knowledge-Based Model Extraction From Manufacturing Process Documents (ModEX_SBO)
The ModEX_SBO project aims to develop computational tools for efficient knowledge construction and management of manufacturing documents, transforming textual engineering documents into formalized knowledge models to surface real-time actionable insights and enable management of manufacturing process documents. The project utilizes AI techniques to discover the cause and solution in manufacturing documents such as fault diagnosis, service repairs, verification reports, and quality check reports. The goal is to make these documents easy to understand and utilize for all stakeholders involved in the manufacturing process.
11h30: Virtual Product Passport: Unlocking Full Traceability (VIPP_SBO)
The increasing complexity of multi-stakeholder, multi-domain, collaborative, and agile systems engineering requires the management and secure preservation of all data/information/knowledge related to products over their extended life-cycle, which can be accomplished with a Virtual Product Passport based on a virtual, federated Knowledge Graph. The knowledge graph enables tracing, slicing, and inferencing to derive insights and optimize the full system, including the product, production, maintenance, and more. This approach can help prevent loss of valuable information and facilitate efficient retrieval and analysis of knowledge.
