How differentiating between utilization of effective availability and utilization of effective capacity leads to a better understanding of performance metrics

The performance curve, or operating curve, is used to compare trade-offs between tool set utilization and normalized cycle time (x-factor). In most cases, the independent variable for comparison is utilization of effective availability. In this context, a tool is considered utilized when actively processing product (i.e. in production). For certain tool sets however, utilization of effective availability is insufficient description of asset utilization. Batch tools are an example where asset utilization is driven by more than straight production time. Based on utilization of effective availability, a batch tool is deemed utilized whenever a batch is being processed regardless of batch size, i.e. a batch of one lot utilizes the tool as much as a batch of four lots. Another example is tools that can achieve a parallel factor >1. Parallel factor measures the average number of batches being processed at the same time or in parallel. Photolithography clusters fall into this category as it is feasible to start another lot prior to a previous lot fully clearing the cluster. Again, the tool is considered utilized if any part of the cluster is processing product even if other parts are starved. For both tool sets, normalized cycle time (x-factor) is lower than expected when plotted against utilization of effective availability on the performance curve. A more refined measure of utilization which accounts for effective capacity and not just availability should be considered. This paper describes underlying variables that determine utilization of effective capacity and gives case studies to demonstrate effects on performance metrics