Testing & Packing Board KPI Monitor

Project Summary

ICES Solutions developed and implemented a comprehensive KPI (Key Performance Indicator) Dashboard to enable real-time visibility into product testing and final packing operations.

This solution is critical in enabling Signify’s production teams to monitor test yields, failures, and packing performance across different shifts and test stations (ATEs), contributing to data-driven decision-making and operational excellence.

Location

Signify Innovations india limited Kural Village,padara-jambusar road

Sector

Lighting industries.

Project Year

2023

Platform

NI Based Software+ Display System

Challenges

Before implementation, data related to product testing, failures, and packing counts were fragmented, manually compiled, and often delayed.

This lack of central visibility led to slow decision-making, reduced responsiveness to production issues, and limited insight into shift-wise performance trends.

Solutions

ICES designed a dynamic KPI dashboard that collects and visualizes real-time data from Automated Test Equipment (ATE), Burn-In (B.I.) units, Hi-Pot stations, and packing areas.

The dashboard provides comprehensive insights into:

  • Yield of Product Testing by station.
  • Test-wise Pass/Fail Summary.
  • Daily Failures in Packing by Shift.
  • Shift-wise Final Packing Count (Good, Rejected, Total).
  • Monthly Testing & Packing Trends.
  • Weekly Pass/Fail Packing Statistics.

All data is stored in a structured MySQL database, enabling historical analysis, traceability, and continuous improvement tracking.

Hardware

    Software

    • Customized KPI Dashboard in NI LabVIEW
    • MySQL database for back-end storage and historical trend analysis

    Results

    • Real-Time Monitoring of all key testing and packing KPIs.
    • Shift-wise visibility into good vs. rejected product counts.
    • Trend analysis to identify recurring failures or inefficiencies.
    • Higher accountability through performance transparency.
    • Better production planning using historical testing/packing data.
    • Increased productivity and quicker issue resolution.