We believe in challenging the status quo in manufacturing. What puts us apart from others is our different way of thinking. By using Artificial Intelligence and Machine Learning in combination with the analysis of sound and other physical parameters, we develop state of the art solutions for monitoring and control of machines and manufacturing processes.
NSW technology can be applied to a extensive range of machines, from power generating equipment, pumps, compressors, mills, and various transport systems to CNC machines, complex HVAC systems, robots, welding, and 3D printing machines, amongst many others. We can monitor and control a single piece of equipment, or an entire fleet of machines, or a complete production line.
Partnering with NSW in R&D offers substantial benefits to OEMs including the reduction of the costs and risks associated with R&D, as well as security and confidentiality, fast track developments, patentable innovations, valuable intellectual properties, and more.
NSW is internationally acclaimed as an unparallel innovator in the field of the Internet of Things (IoT), and applications of Artificial Intelligence (AI) and Machine Learning (ML) to process control and predictive maintenance in manufacturing and processing plants.
We have a reputation for exceptional skills and creativity in the development of AI and ML-based value-added solutions for our customers, solving the most challenging problems in maximizing equipment utilization and process supervision.
Unlike other operating and predictive maintenance solutions, NSW delivers a real-time (24/7) continuous monitoring solution based on IoT hardware, and AI and ML data processing. Ease of installation makes it possible to launch the service within hours.
Our expertise in Edge and Fog computing, and IoT architecture, enables us to develop AI and ML-based solutions allowing near or real-time processing of information and decision making at the Edge.
By applying ultra-precise sound analysis, AI and ML, the results achieved include: maximum control over quality output, productivity, energy use, safety and compliance, and a reduction of unscheduled downtimes and scrap rates, enhanced quality, and lower cost of maintenance throughout the manufacturing operations.
