Innovative testbed accelerates machine learning for predictive maintenance in high-volume manufacturing
The Industrial Internet Consortium, the world’s leading organization transforming business and society by accelerating the adoption of the Industrial Internet of Things (IIoT), today announced the Smart Factory Machine Learning for Predictive Maintenance Testbed. The testbed is led by two companies, Plethora IIoT, a company, designing and developing cutting-edge answers for Industry 4.0, and Xilinx, the leading provider of All Programmable technology.
This innovative testbed explores machine-learning techniques and evaluates algorithmic approaches for time-critical predictive maintenance. This knowledge leads to actionable insight enabling companies to move away from traditional preventative maintenance to predictive maintenance, which minimizes unplanned downtime and optimizes system operation. This would ultimately help manufacturers increase availability, improve energy efficiency and extend the lifespan of high-volume CNC manufacturing production systems.
“Testbeds are the major focus and activity of the IIC and its members. We provide the opportunity for both small and large companies to collaborate and help solve problems that will drive the adoption of IoT applications in many industries”, said IIC Executive Director Dr. Richard Mark Soley. “The smart factory of the future will require advanced analytics, like those this testbed aims to provide, to identify system degradation before system failure. This type of machine learning and predictive maintenance could extend beyond the manufacturing floor to have a broader impact to other industrial applications.” Read more
Machine Learning for Smart Industry will be among the main topics of the Intelligent Sensor Networks Conference, which will take place on November 8, 2017, at High Tech Campus Eindhoven, The Netherlands. For more info about the conference, visit https://www.isnconference.com/