Summary for Auto Component Manufacturers
How Real-Time Production Analytics & OEE Monitoring Work
Real-time production analytics automatically collects data from every machine on the shop floor (cycle time, downtime, rejections, changeovers, operator inputs) and converts it into live OEE metrics. Losses are broken into Availability, Performance, and Quality, so you can clearly see where to focus improvement. Dashboards update continuously (e.g., every minute), eliminating manual data collection and delays.
Boolean & Beyond’s Approach in Indian Auto Hubs
Boolean & Beyond deploys this system across auto component plants in Pune, Chennai, Bengaluru, Coimbatore, and other hubs. We:
- Connect to existing PLCs, CNCs, and sensors via OPC-UA, Modbus, MTConnect.
- Retrofit older machines with sensors for cycle detection, power monitoring, and part counting.
- Typically cover 20–50 machines in 6–8 weeks, with minimal disruption to ongoing production.
Driving Continuous Improvement with Data
The platform highlights your top production losses: long changeovers on specific CNC cells, micro-stoppages on transfer lines, or quality issues on particular operations. Built-in Pareto analysis ranks opportunities by impact. Shift-wise and operator-wise comparisons expose best practices that can be standardised. Customers typically see 10–20 percentage point OEE improvement within 6 months, increasing output without new capital expenditure.
OEM Compliance & Customer Reporting
For Tier 1 and Tier 2 suppliers, the system generates production and quality reports in formats required by OEMs. It provides:
- Traceability from each part to its machine, operator, and process parameters.
- Automatic SPC charts and capability indices (Cp, Cpk) from live production data.
- Configurations aligned with IATF 16949, APQP, PPAP to support audits and customer reporting.
In short, Boolean & Beyond turns your existing machines into a connected, data-driven production system that boosts OEE, supports OEM compliance, and increases throughput without additional machines.
