Since the early 1990s, six sigma has been sweeping the business world, driving greater manufacturing and service quality than has ever been seen before. Statistical quality techniques are one of the decisive factors contributing to the success of the six-sigma implementation. Applying statistical quality techniques is especially important in the manufacture of surfacemounted printed circuit boards (PCB). As any defect in the solder joint can lead to circuit failure, the screening process is regarded as the most critical process in PCB manufacturing. According to the current process capability study of a PCB company, the capability of the screening process is under 1.33-the company requirement. That is to say, the current printing process cannot reach a four-sigma level. Therefore, the objective of this study is to improve the sigma level of the screening process through the define-measure-analyse-improvecontrol (DMAIC) approach. At the early stages, process capability analysis (PCA) and statistical process control (SPC) were used to measure and analyse the current printing performance of the screening machines. During later stages, design of experiment (DOE) was conducted to determine the optimal settings of the critical-toquality factors in the screening process. By using these optimal settings, six-sigma performance can be achieved.Keywords Six sigma improvement AE Define-measureanalyse-improve control (DMAIC) approach AE Design of experiment (DOE) AE Multi-layer printed circuit board (PCB) AE Surface mount technology (SMT) AE Screening process 1 Introduction
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