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Industrial Dependability

The strategic research in industrial dependability focuses on a wide variety of application areas from aerospace and nuclear industries to automotive and medical parts. The demand for dependable and high precision systems is driven by the need to achieve technological and sustainable goals.

The technical goals of the research are related to improving the understanding of mechanical and physical characteristics in relation to the physical properties of the components, improving the operational performance and safety of systems and components working in e.g. harsh environments, and the integration of information and communication technologies ICT to implement smart manufacturing systems. Economic concerns include increasing equipment utilization and reducing the design and production costs as well as keeping the products flexible and adaptable. A joint economic and environmental goal is the reduction of re-work to increase sustainability.

Focus areas:

  • Industrial analytics for self-diagnostics and prognostics.
  • Model-based and data-driven solutions for increased manufacturing performance.
  • Propagation of uncertainty (errors).

Our particular interest in the area of precision engineering applied in maintenance and manufacturing is to bridge the gap between research in manufacturing accuracy of manufactured parts and planning and executing maintenance activities. The direct benefits for society are the realization of perspective maintenance activities, which reduces the energy and material requirements of manufacturing of products. In order to manufacture a component with high accuracy (e.g., creating a functional surface) several different areas in the manufacturing have to interact, including maintenance. In addition, a system must be designed to be able to manufacture with high precision production equipment (e.g. machine tools), the manufacturing processes and metrology have to be optimized together from a holistic perspective. In studying the manufacturing process is important to eliminate the variation. This analysis of manufacturing process is connected to the quality of the machined part on one side and the capability of processes and system on the other side. By these sources, variation are identified and eliminated through a well-directed maintenance effort.

Core foundation for implementation of the research visions are strongly related to integration of applied science and related information and communication technologies (ICT) in precision engineering for maintenance and manufacturing. It provides a large variety of tools for modelling of processes and measurement systems, statistical data analysis and evaluation of machinery, processes and measurement uncertainties. Design and development of new measurement technologies for prognostics and health management for smart manufacturing systems will require extensive simulations, optimization procedures as well as inverse methods for interpretation of indirect measurements. Mathematics and statistics will play a crucial role in the implementation and extension of guidelines regarding measurement uncertainty and key comparisons.

The development towards smart factories aims to utilize products and production resources such as machines, robots and tools with inbuilt capabilities to communicate, make self-diagnosis, become self-learning and possess the ability to perform self-adjustments, adaptations and optimizations; in other words, products and processes are intended to become more intelligent and autonomous.

The research team on Industrial dependability is led by professor Andreas Archenti .

Page responsible:Amita Singh
Belongs to: Sustainable Production Development
Last changed: Sep 18, 2020