Project description
The future of predictive maintenance is today
Machine-to-machine communication will be the main feature of the smart factory of the future. Imagine a shop floor where machines can communicate with other machines and humans. This is known as industrial connectivity. The use of 3D signals for Industry 4.0 is crucial to make machines more connected and to enhance predictive maintenance – a way to predict machine failures and detect unanticipated equipment or process degradation. In this context, the EU-funded project Sound Health is an acoustic data acquisition 24/7 system to monitor machinery for predictive maintenance. The system gathers high-resolution data, detects and predicts when maintenance is required, and provides valuable reporting and insights, becoming more efficient and competitive.
Objective
Predictive Maintenance (PdM) is a maintenance technique, based on the monitoring of equipment conditions combined with different sets of real-time analytics to achieve cost savings by predicting failures, and detecting and responding to unanticipated equipment or process degradation. However, there are a few key factors hindering progress and digitalisation of the Industry 4.0: 1) Current estimations state that worldwide, there are 60M machines in factories, of which 90% are not connected; and 2) Current technologies are not appropriate: they are complex to install, requiring the maintenance team to reach to each machine separately; their inability to monitor a combination of machines that work in sequence; the high costs since several sensors are required for the measurement of the different aspects of the machine; ultimately leading to late detection.
Sound Health is an acoustic data acquisition 24/7 system to monitor machinery for predictive maintenance (PdM). The system gathers high resolution data, detecting and predicting when maintenance is required, providing valuable reporting and insights, and becoming more efficient and competitive.
Sound Health is the only Cloud based SW and HW platform for digitisation, visualisation and PdM of machines based on PLC parameters and additional acoustic sensors. Offering also PdM solution based on the large database it collects.
Fields of science
- natural sciencescomputer and information sciencesdata science
- social scienceseconomics and businessbusiness and managementbusiness models
- natural sciencesphysical sciencesacoustics
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- social scienceseconomics and businessbusiness and managementcommerce
Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
4442513 KEFAR SAVA
Israel
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.