A knowledge-based cost estimating expert system is chosen by a Mexican machine shop. Differences between the traditional experience-based system employed and the automated system are studied. Data is gathered to analyze time effectiveness, accuracy and payback of the software. Data from seventy part models is recorded to study the time experiment, and data from fifty part models is used to study the accuracy and consistency. Data is analyzed by calculating mean, standard deviation, and test of hypothesis. The results indicate that the software is faster than the traditional quoting system; however, the payback point is high. Also, results show the software has a smaller average time-to-manufacture percentage difference between the automated system and the actual time-to-manufacture (TTM) compared to the percentage difference between the traditional’s TTM and actual TTMs, and this difference is statistically significant. The standard deviation for the automated system is also less implying better consistency
