KDDS

The long-term vision of this research is to support knowledge-driven decision making in Swedish industry, which in turn can contribute to leverage their overall productivity and competitiveness.

The overall scientific goal is to define a new knowledge discovery and management framework which is built on the synergistic integration and optimization of Virtual Manufacturing (VM)-based models that take into account product, process and system related aspects in the production development lifecycle.

The project will exemplify and demonstrate the framework on two types of production development and two types of manufacturing processes and lines:

• Automotive components and home furniture
• Machining/metal cutting and robotic assembly/material handling

Specifically, in this Synergy project, a new industrial decision-making approach will be developed which is based on the idea that knowledge can be extracted through systematically exploring and analyzing (e.g. using advanced data mining and analysis techniques) multiple optimal designs/configurations/settings, generated via optimization on the VM-based models. We call this approach “Knowledge Discovery via Optimization” and believe that industrial decision-making challenges can be addressed by answering the following core research question:

How can decision making be supported by knowledge discovery and management using many-objective optimization and advanced data mining on integrated multi-disciplinary models from product, process, and system domains?

To address such a complex research question, three independent and interdependent sub-projects are designed:

• OPTIMIZE: Multi-disciplinary Modeling and Optimization
  Research domain: Modeling & Optimization, Many-objective Optimization, Machining, Robotic Cell Optimization, Concurrent Engineering, etc.
• DISCOVER: Multi-disciplinary Knowledge Discovery and Decision Support
  Research domain: Knowledge Discovery, Data Mining, Innovization, Design Space Exploration, High-dimensional Data Visualization, Decision Support, Metamodeling, Multi-Criteria Decision Support, etc.
• MANAGE:Integrated Data, Models and Knowledge Management Systems
  Research domain: PLM, Knowledge Engineering, Knowledge Management, Ontologies.