Strain Sensing Technology to Enable Next-Generation Industry and Smart Machines for the Factories of the Future: A Review
Yazan Hamed, Garret E. O’Donnell, Natalia V. Lishchenko, Irina V. Munina
Trinity College Dublin National University of Ireland Dublin Institute of Technology Odesа Polytechnic National University
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摘要与影响
In the era of digitalization, there is a huge focus on capturing data from manufacturing processes and systems. Since the promotion of Industry 4.0, the industrial marketplace has been crowded with solution providers who excel in capturing and aggregating data on the cloud and presenting it on dashboards. From machine states to production targets, this type of data has become more readily available from tools, controllers, switches, and factory bus systems. As the industry pushes deeper into the machine for information and aspires to have smart machines that can feel and react to experiences during the manufacturing process, then more sophisticated technology is necessary. Strain sensor technology is a logical measurement principle to address this challenge for many industrial sectors. For researchers and industrialists to progress toward the smart machine agenda, there must be a firm grasp of the “technology-solution fit,” i.e., what strain technology could provide the most appropriate solution. This paper presents a review of the state of the art in strain sensors that are foreseen as frontrunners to enable next-generation smart components and intelligent tools. The review focuses on industrial strain sensing technologies that are at a mature place on the technology readiness levels (TRLs) and present themselves as highly practical solutions for smart components and digitized machines, considering sensitivity, powered or passive, wired or wireless, and robustness. Through this review, researchers and industrialists will have a suite of solutions to move on with their innovative designs of smart machines based on embedded strain sensor technology.
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计算机 / AISensor Technology and Measurement Systems
Advanced Sensor and Energy Harvesting Materials · Digital Transformation in Industry
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