Efficient cycle time-throughput curve generation using a fixed sample sizeprocedure

The cycle time-throughput curve is one of the most important analytical too ls used to assess operating policies in manufacturing systems. Unfortunatel y, the generation of this curve is complicated and time consuming when gene ration is based upon extensive simulation analysis. This paper presents a s imulation-based, fixed sample size strategy for generating a cycle time-thr oughput curve with minimal mean square error that mitigates the typical pro blems associated with a simulation-based cycle time-throughput curve. The s trategy comprises two components, the sampling method and sampling weights. A queuing network of five workstations in series is used for validation of the approach. Results indicate that the sampling method using antithetic v ariates is effective in reducing the variance as well as bias of a cycle ti me-throughput curve. Furthermore, this method is robust to the sample size. Given a sufficiently large sample, the combination of common random number s and antithetic variates is preferred. A reduction in the sample size and complexity of the system increases the significance of the sampling weights .