The advent of sensory technologies (e.g., Internet of Things; IoT) combined with the possibilities of the new communication networks like 5G is creating the necessary infrastructure for the Cyber-Physical Systems (CPS). In CPS, software and physical components are deeply intertwined. Such a convergence of the cyber and physical worlds offers boundless opportunities to all areas of industry – manufacturing, logistic, building, energy, health, etc – by becoming the cornerstone of future Industry 4.0.
The research group Smart Industry Group (SIG) is an interdisciplinary partnership between the Department of Computer Science and Media Technology and the Department of Mechanical Engineering, bringing together expertise in the cyber and physical world, respectively.
SIG is interested in leveraging data-driven techniques for making production and products smart, i.e., context-aware, self-aware, and adaptive. For example, a production system can automatically adjust to the desired production level with optimal logistics and flow at the lowest cost, whereas a product can automatically reconfigure with respect to operation and/or human factors.
The integration of CPS elements in production systems and products allows for offering new appealing functionality to the different stakeholders, i.e., operators and end-users, respectively. At the same time, the integration of CPS elements also increases the complexity of production systems and products, and seriously complicates the assessment and assurance of key quality aspects. Such aspects may be safety, security, performance, sustainability (i.e., near-zero power consumption), maintainability, and usability.
To this end, the Smart Industry Group aims at investigating:
- Data-driven discovery techniques for inferring production/products models from data.
- Data-driven analysis techniques for inferring production/products quality aspects from models and data.
The Smart Industry Group also aims at serving as a catalyst for new collaborations and projects between the Department of Computer Science and Media Technology, the Department of Mechanical Engineering, and industry. We are especially interested in the sharing and transfer of methodologies, methods, and tools where the solutions from one field can be reapplied in another one.
SIG aims at applying the research to different areas, including, but not limited to:
- Production systems – automatically adjust the desired production with optimal logistics and flow at the lowest cost.
- Automatic reconfiguration of machines with respect to operation, loads, wear, service, material flow, logistics, human factors, etc. (E.g., changing stiffness with frequency to avoid resonance, changing the degree of anisotropy to adjust for asymmetric loads, and changing the thermal conductivity to adjust for varying temperature fields.)
- Adaption of maintenance management, condition monitoring, and condition-based maintenance.
- Physical machines, etc., ready for smart CPS.
At Linnaeus University Centre for Data Intensive Sciences and Applications (DISA), we encourage and support seed projects. Seed projects are intended to promote and nurture excellence research, development and innovation within data intensive sciences and applications with cross-discipline collaboration.
Seed projects at CPS
- Andreas Linderholt Associate professor
- +46 470-70 81 58
- +46 70-310 39 20
- Basim Al-Najjar Professor
- +46 470-70 84 22
- +46 70-765 30 51
- Charilaos Skandylas Doctoral student
- Diego Perez Palacin Senior lecturer
- +46 470-70 82 90
- Francesco Flammini Associate Professor
- +46 470-70 88 22
- Francis Palma Senior lecturer
- +46 480-49 71 98
- Fredrik Ahlgren Senior lecturer
- +46 480-49 76 71
- Gunnar Bolmsjö Professor, Head of department
- +46 470-76 72 37
- +46 72-246 70 68
- Jetro Kenneth Pocorni Senior lecturer
- +46 470-76 72 01
- Jorge Luis Zapico guest lecturer
- Lars Håkansson Professor
- +46 470-70 83 50
- +46 73-338 57 12
- Lorenzo Pagliari Senior lecturer
- Martin Kroon Professor
- +46 470-70 84 41
- +46 70-358 98 71
- Mauro Caporuscio Associate professor
- +46 470-70 85 58
- Mehdi Saman Azari Doctoral student
- +46 470-70 83 70
- Mirka Kans Associate Professor
- +46 470-70 84 88
- +46 76-760 36 68
- Mirko D' Angelo
- +46 470-76 72 17
- Narges Khakpour Senior lecturer
- +46 470-70 87 04
- Per Lindström Senior lecturer
- +46 480-49 76 22
- +46 76-142 76 22
- Rammohan Kodakadath Premachandran Doctoral student
- +46 470-70 83 31
- Tobias Schauerte Senior lecturer
- +46 470-70 88 24
- +46 72-239 45 73