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Industry 4.0: IIOT Machine Condition Monitoring and Analytics

Stanley Black & Decker is a $14 billion company and is a top provider of industrial, security, and tool solutions.

The entire organization is moving towards real-time process monitoring, driving decisions through data and a large emphasis is given on improving the overall equipment effectiveness.

The project is focused on key sites in the northeastern US where machines are very old and have no system in place to gather insights into machine health and drive informed decisions.

The Tauber team is tasked with assessing the current state of machine health monitoring, building business use cases to generate a minimum of $150,000 value for 3 sites with the opportunity to scale globally, developing a data analytics model, and creating a roadmap for future deployments to other sites of Stanley Black & Decker divisions.

View team project summary

Student Team:

Janice (Yin Yin) Lau – Master of Science in Industrial & Operations Engineering
Akshay Seth – Master of Science in Industrial & Operations Engineering

Project Sponsors:

Nathan Dietrich – Advanced Manufacturing Engineering Deployment Manager
Aditya Mairal – Advanced Manufacturing Engineer
Ziyan Xu – Advanced Manufacturing Engineer

Faculty Advisors:

Lennart Baardman – Ross School of Business
Line van Nieuwstadt – College of Engineering