Manufacturing the Future Guidewheel's Lauren Dunford on Transforming Factory Ops with AI-Powered Sensors
Meet Lauren Dunford, CEO & Co-founder of Guidewheel
Lauren Dunford, CEO & Co-founder of Guidewheel, brings a refreshing perspective to manufacturing technology. "The nice thing about Guidewheel from the customers is starting with the simple fast 80/20 and then we can layer on lots of things," she explains, describing how their approach prioritizes immediate value over complex implementations.
Guidewheel addresses a critical challenge in manufacturing: gaining operational visibility without the massive disruption of traditional digitization projects. Many manufacturers struggle with the complexity and cost of connecting diverse equipment across their facilities, often deterred by the "nightmare projects" that involve extensive PLC integration across different makes, models, and ages of machinery. Lauren's company solves this by monitoring the one thing all equipment has in common: electricity consumption.
The company was founded after Lauren's experience of making difficult calls to customers about production delays. This frustration, combined with her Stanford MBA work, led to the development of Guidewheel's innovative sensor technology. The company has evolved from a failed energy management system into a comprehensive factory operations platform, guided entirely by customer feedback and real-world applications.
In This Episode
Guidewheel's Factory Ops platform demonstrates how the right technology approach can simultaneously drive productivity improvements and sustainability goals. By starting with controllable downtime and operational efficiency, manufacturers achieve immediate business value while naturally uncovering opportunities for energy savings and emissions reduction, creating a sustainable flywheel of continuous improvement and environmental benefit.
Topics- How Guidewheel's "Fitbit for factories" approach transforms manufacturing visibility through simple electrical monitoring sensors.
- Leveraging universal power consumption data to monitor equipment performance across different makes, models, and ages of machinery.
- Overcoming traditional barriers to manufacturing digitization by avoiding complex PLC integration and focusing on practical solutions.
- Implementing AI algorithms for automatic cycle time detection, anomaly prediction, and prescriptive maintenance recommendations in manufacturing.
- Balancing mission-driven sustainability goals with commercial success through the upper-right quadrant of profitable environmental solutions.
- Creating sustainable manufacturing practices by starting with productivity improvements that naturally lead to energy efficiency gains.
- Attracting and empowering the next generation of manufacturing workers through intuitive, delightful technology tools and platforms.
- Building successful manufacturing technology companies through customer-driven product development and iterative learning from real factory applications.
- Developing platform ecosystems that enable custom manufacturing applications and developer communities for specialized industrial use cases.
- Transforming manufacturing operations from reactive to predictive through real-time data visibility and AI-powered throughput forecasting.
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