Semiconductor fabs can optimize fab performance via transparent advanced analytics, chasing perfection one byte at a time.
来源: | 作者:volcos | 发布时间 :2024-10-10 | 872 次浏览: | Share:
The semiconductor industry is poised for recovery and long-term growth, projected to exceed $1 trillion in revenue by 2030. Despite fluctuations in demand for traditional chips, the market has seen a surge in demand for AI and automotive applications.

When seeking to increase production overall or on a single tool, the tendency is often to increase WIP levels, seeking to increase overall throughput. This relationship holds until a bottleneck occurs or a saturation point is reached, after which additional WIP merely increases the cycle time at best or potentially decreases output as the line becomes clogged with excess WIP at worst.4 In many fabs we have examined, we see the tendency to revert to increasing starts to account for fewer outs, which invariably does not always translate.

With standardized data inputs, saturation curves that compare WIP to throughput help quickly identify the ideal levels of inventory WIP to optimize throughput and ways to reduce output variance in established processes. By examining historical performance data, fab leaders can visualize the throughput saturation point and determine the level of control for the fab process.

The saturation curve has helped some semiconductor fabs navigate quantifying ideal WIP quantities at all levels of their fabs. Exhibit 2 highlights the regimes that become quickly apparent for how a fab (or equipment group or tool) is operating, including the following: