A technology company was experiencing issues with throughput, utilization, and yield in its printer manufacturing operations. BRIDGEi2i worked with the company over 2 months to develop an interactive Tableau dashboard accessible on mobile devices. The dashboard calculated key performance metrics from historical build data, product bills of materials, shortage reports, and other operational data sources. Using causal analysis methods, the dashboard identified gaps in throughput, utilization, and yield metrics and plotted trends to reveal leading indicators of line and station-level bottlenecks. This allowed line management to proactively monitor manufacturing performance and address issues in real-time for timely resolution.

1. A Case Study in
Line Operations
Analytics
A Fortune 500 Technology Company
Quick Context
Objective
a. A contracted manufacturing scenario for printers; OEM has little control over
manufacturing operations
b. Recently experiencing Throughput, Utilization and Yield related issues
Impact
• BRIDGEi2i specializes in several Line
Operations analytics with an
appreciation for the fact that the fixes
must be very well evaluated before
being operationalized
Key Success Elements
Our Approach
2 Months
2 Years
Client
Project length
Length of relationship with client
• Build plan, historical actual builds,
Product BOMs, shortage reports, daily
throughput, utilization, yield and station-
level data was obtained from the Client
ERP
• Capacity and Line configuration was
obtained from the Line Management
System
• Tableau was used for dashboarding the
metrics
• Key Performance Indicators and
Metrics were created to reflect the core
manufacturing metrics – Throughput,
Utilization and Yield Gaps
• Gaps were ascribed to these KPIs
using Causal Analysis methods
• Finally, the KPIs were plotted as a trend
to identify leading indicators of
challenges
• An Interactive Tableau dashboard that
is mobile-ready
• Dashboard reflects leading indicators to
Line and Station-level challenges –
Bottlenecks
• All metrics are calculated in-dashboard
with least latency – makes the
dashboard fast and responsive
Data Management Algorithmic Play Operationalization
a. To develop a mobile-enabled dashboard to identify root cause to Throughput,
Utilization and Yield metrics
b. Real-time reporting using the Line Operations system
• Ability for Line
Management to
monitor
manufacturing on
their mobile
devices
• Proactively
identify issues for
timely resolution