How an app approach to data analysis cut initial data formatting time and sped defect resolution.

A key tenet of Lean manufacturing is to reduce variation through process standardization and control. To that end, most companies develop a control plan and monitor various steps of the process. The data collected in those monitoring activities are also useful in facilitating continuous improvement activities. This is particularly true as automated data collection technology has evolved and made it easier to share across multiple platforms.

For example, SigmaTron’s team in its Suzhou facility uses a combination of enhanced inspection equipment, a proprietary manufacturing execution system (MES) and a newly created IT tool to drive continuous improvement efforts.

These efforts build on a Lean manufacturing approach that includes design for manufacturability (DfM) recommendations made to eliminate defect opportunities prior to the new product introduction (NPI) process and use of a production part approval process (PPAP) methodology during the NPI process.

Since the facility’s focus is predominately higher volume production, its SMT lines are optimized to include a higher level of in-process inspection, utilizing 3-D solder paste inspection (SPI) following paste or glue deposition and automated optical inspection (AOI) both pre- and post-reflow. The MES collects yield data at those points and during in-circuit and functional test. The MES also tracks assemblies through each production step in the routing to support traceability requirements.

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