Beyond the Machine: Delivering Plant-Level Insights without Enterprise Complexity

Manufacturing has always been about the details: the temperature of a die, the speed of a conveyor, the pressure in a hydraulic system. But while machine-level data tells you what's happening, it doesn't always tell you what matters. ei³'s latest feature bridges this gap between machine data and line-level insights that actually drive decisions.

Consider a packaging manufacturer running a typical production line: web printing feeds into lamination, which flows to die cutting, then finishing and packaging. Each machine generates its own performance data, each with its own dashboard, each telling part of the story. The printing press shows 85% OEE, lamination hits 92%, die cutting runs at 78%. But what's the line doing as a whole? Where's the real bottleneck? And more importantly, what should the plant manager focus on first?

This is where traditional monitoring approaches break down. You're either: drowning in machine-specific details, or trying to piece together the big picture from scattered data sources.

The aggregation challenge

The latest addition to ei³'s Insights badges addresses this directly: the Aggregate OEE badge. Unlike simple averaging approaches that treat every machine equally, this feature performs mathematically accurate aggregation using raw production data. A high-speed printing press running at 1000 feet per minute doesn't get the same weight as a slower finishing operation—the calculation reflects actual production impact.

But here's what makes this different from enterprise-level analytics platforms: you don't need to be a PowerBI expert to set it up. The same no-code interface that makes ei³ accessible for individual machine monitoring now scales to line-level and plant-level insights.

ei³'s Insights dashboard showing Aggregate OEE badges for four production lines. Each badge aggregates multiple machines into a single, actionable view of line performance.

Built for manufacturing, not just used in manufacturing

The difference matters more than you might think. Generic business intelligence tools can certainly display manufacturing data, but they require:

• Significant customization
• Ongoing maintenance
• Specialized expertise to deliver meaningful insights

They're built for boardrooms, not shop floors.

ei³'s Insights badges work differently. Need to group your extrusion lines separately from your converting equipment? Create two badges with custom names. Want your line supervisors to see department-level performance while plant managers view facility-wide metrics? Deploy multiple badges with different scopes. The same intuitive interface adapts to different organizational needs without requiring different skill sets.

Scalable simplicity

This flexibility extends across facility sizes and complexity levels. A smaller operation might use aggregate badges to monitor their complete production line - printing, laminating, and finishing all in one view. A larger facility could deploy dozens of badges:

• One for each production line
• Others for equipment type
• Perhaps some organized by shift or customer program

Each badge includes a simple menu icon that reveals exactly which machines contribute to the displayed metrics. No complex drill-down interfaces, no separate reporting modules: just transparent access to the underlying data when you need it.

The right level of intelligence

Modern manufacturing operations need multiple layers of visibility. Process control systems handle automation and real-time adjustments. ERP systems manage scheduling and materials. But there's a crucial gap between machine-level data and business-level insights, and that's where aggregate monitoring delivers the most value.

The goal isn't to replace existing systems, but to bridge them effectively. Plant managers get the line-level visibility they need for daily decisions. Line supervisors see department performance without getting lost in individual machine details. Maintenance teams can identify patterns across similar equipment groups.

This layered approach to manufacturing intelligence lets each user access the right information at the right level of detail, without forcing everyone to become a data analyst.