SMTA International Conference Proceedings


Author: Thanigai Kumar S. Vellore et al.
Company: Sanmina-SCI Corporation
Date Published: 9/21/2003   Conference: SMTA International

Abstract: The electronics manufacturing industry has witnessed significant improvements in technology, leading to the design and manufacturing of complex products. From the manufacturer’s perspective, this implies "smaller components, denser boards and thereby tighter tolerances". In such an environment, a well-defined quality information system with real-time, accurate statistical data is essential in driving process improvements.

In this research endeavor, a real time Statistical Quality Control (SQC) system that could be deployed in an electronics manufacturing environment was designed, developed and implemented with the goal of proactively eliminating manufacturing defects and improving quality. Performance metrics like First Pass Yield (FPY), Defects Per Unit (DPU), and Defects Per Million Opportunities (DPMO) are shared with the shop floor personnel in real time.

Statistical Process Control (SPC) charts monitor the process in real time and serve as a proactive tool that can predict ‘out-of-control’ situations. This SPC information is also tied into the process triggers module, which provides feedback to the supervisors and engineers with vital non-conformance information for immediate corrective action. The system also provides a separate alarm module wherein shop floor supervisors and managers can set the criteria for the alarms. Process alerts are generated in the form of e-mails and pages when the process is out-of-control for pre-specified alarm requirements.

The implementation of DPMO metrics in the SQC system provides the ability to distinguish between boards with different levels of complexity. These metrics allow for correlations to be drawn between the process and product complexity. Process alarms can be set based on either system pre-specified DPMO levels or user specified levels. These performance-monitoring tools are integrated with a Closed Loop Process Control (CLPC) module, which can stop a process when an out-of-control trend is observed by the system.

The paper focuses on the SQC tools and techniques implemented in the development of closed loop process control in electronics manufacturing. The key performance indicators that were identified and process models that were developed to help with manufacturing decisions are reviewed. The principal functions of each module in the SQC system are also discussed.

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