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Pulsar is developing a fully-automated monitoring system for industrial production management. Most manufacturing plants cannot manage their production processes effectively because they lack reliable data collection systems and the tools to build key production indicators and to apply the best continuous improvement methodologies (Lean, Six-Sigma, TPM, Kaizen, among others). At Pulsar, we use plug-and-play wireless sensors and machine learning algorithms that adapt according to the behavior and operation of industrial machines, to classify downtime losses automatically from the machinery electrical signals, building up production indicators in real time and providing expert insights and recommendations for improvement. This system represents a cost-effective option for small and mid-size industrial plants, significantly impacting their productivity and use of resources, by reducing waste, energy, labor inefficiencies and machinery failures.

Team Members

Matias Castillo (MBA, MS EE), Juan Cristobal Ruiz-Tagle, and PI: Prof. Hau Lee (GSB)