Abstract
Flexible production is essential for manufacturers in the face of changing demands for the printed circuited board assembly (PCBA) industry. Machine flexibility is an important factor used to enhance the flexibility of a PCBA system. Configuring the surface mount assembly (SMA) lines is one of the most significant operational decisions of PCBA to cope with variable demands and product variants. Aggregating the flexibility of a chip-placer group is conducive to evaluate the SMA line flexibility, so that decision-makers can develop better production strategy. In this research, a flexibility measuring framework was developed using an entropy-based method and the Taguchi quality loss function to assess SMA line configurations with different chip-placer groups. Based on the resulting flexibility measurements, a neural network model is adopted to estimate the flexibilities of possible chip-placer combinations and suggest the most appropriate line configurations for the subject company. Some findings and managerial implications are also provided.
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