Journal of SMT Article


Author: Jayang Patel et al.
Company: State University of New York
Date Published: 7/1/2003   Volume: 16-3

Abstract: In a high-mix, low-volume electronics manufacturing service (EMS) provider's environment, sub-optimal processes coupled with less-than-adequate process control and a lack of training result in a significant loss of end-of-line, first-pass assembly yields. Hence, it is of definite advantage to an EMS provider to take a proactive approach to address the future loss of yield rather than be reactive.

In an assembly environment, a significant amount of time is spent in solving a particular problem instead of identifying the root cause(s), which leads to small and regular day-to-day problems. It's therefore necessary to conduct a systematic study that helps to identify and eliminate these 'process clouds', which results in smooth and streamlined day-to-day operations.

While a great deal of attention is being paid to the automated assembly component of electronics manufacturing, manual operations (prepping) and manual assembly (hand-load) encounter a different set of problems that are often neglected. This is especially true in a high-mix, low-volume EMS provider's environment. Consequently, the manufacturing system often fails to deliver the required output and first-pass yields. This can lead to the loss of productivity and the sub-optimal utilization of resources.

The objective of this research was to identify the potential modes in which the aforementioned processes (prepping and hand-loading) may fail. Then, depending on the failure mode, the root cause of the problem can be identified, and methods or processes that help in preventing the failure, or detecting the failure mechanism before the process actually fails, can be implemented.

Different stages of the failure mode and effect analysis (FMEA) process were systematically completed for the manual operations. Various 'process clouds' were identified and were resolved using different solution methodologies that were developed. This resulted in a significant decrease in the time spent by the operators and supervisors in solving the problems encountered during assembly, thus resulting in better productivity and a better working environment [1].

Key words: failure mode and effect analysis (FMEA), PFMEA, continuous process improvement (CPI), root cause analysis.

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