A collaboration with NeuronSW involves utilizing IoT for tracking acoustic emissions from bearings, mechanical seals, and reactor shells.
NeuronSW manages hardware installation, data acquisition, ML algorithm training, and service deployment.
The project aims to enhance reactor agitator monitoring, benefiting from NeuronSW’s expertise in acoustics, software, and hardware development.
In this application, Neuron Soundware addresses industrial production challenges using mobile communication (4G and 5G) to enhance equipment performance. By acquiring and processing acoustic data from operating robots, their AI technology identifies unusual robotic arm movements. This solution ensures robust, cost-effective production by preventing damage and anomalies that could compromise the integrity of the production process, with multiple accompanying benefits.
Deployed to prevent the breakdown of components in specialized grinding machines, the NSW AI and Machine Learning solution monitors the process, preventing damage and maintaining correct viscosity of the material on the plant. Benefits include lower maintenance costs, fewer unplanned stoppages, reduced production expenses, increased productivity, and less material wastage.
Addressing the challenge of maintaining steady air supply in fluctuating manufacturing demand, the NSW solution employs AI-driven monitoring and adjustments.
By analyzing real-time data, it ensures optimal air delivery, offers early warnings, and prioritizes inspections, effectively preventing disruptions and reducing operational costs.
Microphones and structure borne sensors provide the operator with not just the ability to listen to the components off site, it also monitors the wind turbine 24/7 using anomaly detection.
In pursuit of production continuity, a leading wheel rim manufacturer sought a solution to monitor vital air compressors using IIoT devices and AI-driven anomaly detection.
By analyzing sound data, this end-to-end system provides real-time insights, enabling early intervention, asset prioritization, and cost reduction while optimizing workforce efficiency.
In the context of a European automotive manufacturer, the use of a piston helium compressor in transmission gear hardening is vital for production. This study addresses the challenge of maintaining uninterrupted operations in the tempering furnace, as equipment failure could lead to production delays and scrap generation. Previously, entire compressors were replaced due to critical incidents. The proposed solution employs IoT devices and non-intrusive sensors to gather and analyze acoustic data. AI and machine learning algorithms assess compressor sounds, promptly detecting deviations from the norm as anomalies. Benefits encompass early detection of potential failures, real-time asset monitoring, preemptive alerts, streamlined inspection prioritization, and reduced costs tied to failures and scrap.
In the past operators tested the quality of the window regulators via listening. This meant the testing approach was dependent on the human factor and listening by ear. The manufacturer decided to replace this manual and demanding method by automatic system delivered by Neuron Soundware.
Neuron soundware delivered a solution for monitoring wear of the turbine bearings. 24/7 monitoring and nGuard platform offer more flexibility than standard solutions on the market.
In this case study, NSW’s AI and Machine Learning solution tackles wear in CNC machine tools. By employing Deep Learning and regression, the solution offers real-time, in-situ alerts for tool quality deviations, enhancing efficiency, cutting costs, and boosting productivity. Experience amplified profitability through zero scraps, reduced waste, and optimized operations.
