EDM 2014 - 1st Workshop on Engineering Data Mining (EDM2014)

The intensive use of computational engineering tools in design, development, procurement, logistics, manufacturing, and service in the recent years has resulted in a tremendous increase of data that is managed in an engineering context in applications as diverse as automotive and biomedical industries. The integration and combined analysis of data from multi-disciplinary computational engineering, computer aided design and enterprise resource management is at the heart of engineering data mining. Furthermore, the large scale integration of complex networks of cyber-physical systems in design, development, logistics, manufacturing and service will create new opportunities for a cloud based data handling and analysis also in the engineering domain. The transition from experiment to simulation and the amalgamation of both in augmented reality systems is already under way. Expensive and safety critical tests for structural stability as well as for intelligent control (autonomous driving) in automotive engineering are replaced by computer simulations. The collected data are of high value and their detailed analysis is required for the next generation system design. Specific challenges in engineering data mining are very large individual data sets like in flow field analysis, merging data from different representations like in multi-disciplinary CAE analysis, consistent data management and data handling like in product lifecycle management, cloud based data management and analysis in a cyber-physical manufacturing environment and data security and integrity in safety critical data handling like in autonomous driving or biomedical engineering to name but a few. Finally, the interaction between the engineer and the data analysis tools, the extraction and the visualization of knowledge and the integration of aesthetic design and engineering tools pose additional challenges, which might not be unique to Engineering Data Mining, however, which emphasize the importance of these research directions.
This workshop aims at bringing data mining researchers and engineers together to communicate recent advances in data mining and related domains like cyber-physical systems, and future demands and challenges of engineering applications and processes.
Topics
Data Analytics:
Multi-criteria decision making
CAD, CAE and ERP system integration
Data management of cyber-physical systems in development and manufacturing
Multi-disciplinary simulation management
Knowledge management & representation
Feature-selection & interaction analysis
Causal modeling & analysis
Constraint-based reasoning
Product data management and analysis
Integration of aesthetic design and computational engineering
Visualization of knowledge in engineering tools
Engineering Applications:
Automotive and aircraft industry
Manufacturing industry and additive manufacturing
Material science and mechatronics
Assistant systems, robotics and autonomous driving
Logistics and Services
Civil engineering
Smart energy systems
Geological engineering
Biomedical engineering