As manufacturers struggle to manage increasingly disconnected production data, Rhino Tool House launches RhiKnows, an AI-powered manufacturing intelligence platform designed to help factories identify operational issues before they disrupt production.
ASSEMBLY Audible recently spoke with Rhino Tool House’s Alex Wirth about the challenges that inspired the platform and why manufacturers are increasingly seeking systems that connect fragmented shop floor information into a more actionable operational view.
Rather than serving as another standalone dashboard, RhiKnows was developed around broader manufacturing issues. Plants already generate large amounts of operational data, but much of that information remains segregated across sensors, torque tools, PLCs, MES platforms, and spreadsheets.
Wirth said many manufacturers already have the data they need to reduce downtime and improve quality, but struggle to turn that information into actionable operational insights in real time.
RhiKnows is designed to ingest factory floor data from existing systems, organize the data based on operational roles, and use AI to identify patterns, predict problems, and recommend corrective actions before problems escalate.
The platform focuses on real-world manufacturing applications such as detecting torque drift, identifying abnormal tool performance, monitoring cycle time, and surfacing early signs of quality or maintenance issues.
According to Rhino Tool House, the system is intended to support operations leaders, maintenance managers, quality teams, and process engineers responsible for uptime, throughput, and production consistency.
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The platform also reflects broader changes occurring across the manufacturing industry as companies move beyond isolated automated systems and begin to connect operational data to a centralized intelligence layer that can support predictive decision-making.
Rather than requiring manufacturers to replace existing infrastructure, RhiKnows is designed to integrate with current factory floor systems and scale incrementally over time.
Wirth said the long-term goal is to help manufacturers move from reactive operations to more predictive and adaptive production environments.
