Single Source of Truth (PathWave Manufacturing Analytics)
With the Industry 4.0 transformation going full steam ahead, analytics have transformed the industry from being process-driven to now data-driven, where data speaks for itself. Conventionally, only failed measurement data are logged for repair and troubleshooting purposes. Now, all measurements regardless of whether they are pass or fail, are recorded for further advanced analytics like anomaly detection and predictive analysis.
These data type includes Meta Data, Measurement Data and Environmental Data. All these big chunks of granular data alone provide great analytics potential, but even greater potential when these data are analyzed collectively with correlation. For example: higher temperature will cause resistance measurement to be slightly higher as well.
In this presentation, we will be using PathWave Manufacturing Analytics (PMA) as an example to discuss this topic on “Single Source of Truth.” With the data agnostic nature of PMA, data are transferred to PMA seamlessly where data analytics are performed at diverse levels and perspective, with several different analytics results. Different users ranging from Original Equipment Manufacturers (OEM) monitoring multiple Contract Manufacturers (CM); Factory managers overseeing factory operation; Engineers handling In-Circuit Test or Functional station to Technicians maintaining system uptime, can tap on data analytics results from this “Single Source of Truth.”
There is no ‘data’ ambiguity between the stakeholders as it all comes from a single source. When low First Pass Yield (FPY) is observed by OEM, the factory manager sees the same information as the rest. Engineers can be triggered to review and drill down to the next level analytics to identify root causes such as false failure, degradation anomaly (situation where probes are worn-out and affecting the measurement) and the degraded probes can be easily replaced by the manufacturing stuffs with the aid from the Probe Heatmap (a graphically view of the probes locations).
“Data does not lie.” With the actual data comes together collectively, uncovering insights and identify actual opportunities to improve manufacturing efficiencies and product quality in a brief time becomes a reality.