5th International Symposium on Sensor Science
S5: Sensors Applications
Dr. Stefano Mariani
Department of Civil and Environmental Engineering, Politecnico di Milano, Italy
Prof. Dr. Maurizio Porfiri
Tandon School of Engineering, New York University, USA
* Multiphysics Modeling Ionic Polymer Metal Composites, with Application in Underwater Sensing
Prof. Dr. Dan Zhang
York University, Toronto, Canada
* Parallel Mechanisms and Its Application for Force/Torque Sensors
There has been increasing in developing enviromentally-benign manufacturing technologies, robots, etc. This is considered a significant step in achieving sustainable development. Sustainability of a manufacturing system becomes critical technology that enables manufacturing companies to reduce production costs and improve their global competitiveness. System sustainability can be achieved by reconfiguration and decentralization, whose system configurations are evolved with the changes of design requirements and dynamic environment.
In this talk, the rational of using parallel robotic machines for green and sustainable manufacturing is discussed and explained. A comparative study is carried out on some successful parallel robotic machines and conventional machine tools. Meanwhile, the latest research activities of parallel manipulators in the Laboratory of Robotics and Automation of York University are introduced, they are: parallel robotic machines, reconfigurable/green robotic manipulators, web-based remote manipulation as well as the applications of parallel manipulators in micro-motion device, MEMS (parallel robot based sensors), wearable power assist hip exoskeleton, and rescue robot.
Prof. Dr. Eleni Chatzi
Institute of Structural Engineering, Zürich
* A Monitoring Approach to Smart Infrastructure Management
Technical infrastructure forms a main pilar of the modern world, hosting our built environment, serving transportation and communication needs, as well as enabling the generation and transfer of energy. Within this context, engineers and owners need to warrant safe and robust operation of these systems for ensuring a smooth societal flow and resilience against short- (extreme events) and long-term threats (deterioration and fatigue processes). In tackling this challenge, engineers are becoming increasingly aware of the benefits stemming from Structural Health Monitoring, i.e., the process of gathering feedback from engineered systems via use of appropriate sensory systems. Developments in low-cost and easily deployed sensors allow for instrumentation of large scale structures, such as bridges, buildings, dams or wind turbines, generating a Big Data stream of diverse information, such as acting loads, strains, cracking and dynamic response.
When adequately interpreted through fusion with appropriate models, this data may then be transformed into effective knowledge on structural performance thereby facilitating the operation and maintenance of infrastructure. This talk will discuss methods and tools for tackling the multiplicity of challenges in this non-trivial task. Among others, we will discuss the monitoring, simulation and protection of systems that are of uncertain nature, either due to modeling imprecision or due to influence of continually varying and little known environments; the challenges of non-linearity and high-dimensionality; the extraction of salient features and robust performance indicators able to warn of damage and deterioration, as well as policy-planning for getting more out of engineered components, systems and networks.
Dr. Dirk Lehmhus
ISIS Sensorial Materials Scientific Centre, University of Bremen, Bremen, Germany
* Linking Additive Manufacturing and Sensor Integration: A direct path towards structural electronics?
Additive manufacturing (AM) of polymers, metals and ceramics is receiving tremendous attention since it has matured from a prototyping to a full-fledged manufacturing technology for geometrically complex objects. Several products have already been realized on a commercial basis, covering application areas as demanding as the aerospace industry. Additive manufacturing offers a design freedom which is unparalleled by subtractive manufacturing or forming processes. This feature would in itself create business opportunities in several scenarios that build on high complexity or customization, allowing for example assemblies of numerous parts to be integrated in a single component, and structurally optimized bionic designs to be realized. All this is true for AM parts made from a single, homogeneous material. This, however, is not the end of the approaches generic capabilities. Instead, more and more technologies are emerging which use the fact that most AM approaches grant direct access to each individual voxel of a component volume to locally modify material properties. Some processes even allow the selective deposition of different materials. Besides hybrid approaches, it is these specific solutions which allow creating a direct link between Additive Manufacturing and Sensor integration, ultimately leading to the vision of structural electronics or 3D-printed electronics in a single manufacturing system, or even a single process.
The presentation explains the different classes of Additive Manufacturing processes available and attempts to classify them with respect to their capability of realizing (a) multi-material parts and (b) parts with integrated interconnects, sensors and/or electronics. Practical approaches at creating structural electronics parts via AM techniques are discussed. Typically, these rely on a more or less tight integration of different manufacturing processes – typically a generic AM process which is combined with one or more direct write or similar processes in a manufacturing chain, a manufacturing cell or even a single manufacturing system. Beyond these, special attention is reserved for AM techniques that allow in-process switching of materials at high resolution: In principle, these have the potential of realizing complex systems not by combination of processes, but via a single deposition and consolidation process. Further to the introduction of processes, application scenarios which benefit specifically from the combination of AM and sensor integration are presented.