A new X-factor contribution measure for identifying machine level capacity constraints and variability

Semiconductor manufacturing is a very complex process involving product mix, reentry lot flows, batching, and machine breakdowns all of which contribute to system variability. Reducing variability in a manufacturing process lowers lot cycle times. This study examines the issue of identifying machines that constrain the system and have a major impact on they system's cycle time. A new X-factor contribution measurement is developed that considers processing time variability and lot arrival variability among the constraining qualities of the machine groups. The effectiveness of this new measure to identify machine groups that significantly impact mean cycle time is tested in several operating scenarios.

[1]  J. Si,et al.  Availability-adjusted X-factor , 2005 .

[2]  A. Schömig,et al.  On the corrupting influence of variability in semiconductor manufacturing , 1999, WSC'99. 1999 Winter Simulation Conference Proceedings. 'Simulation - A Bridge to the Future' (Cat. No.99CH37038).

[3]  J. Si,et al.  A dynamic system regulation measure for increasing effective capacity: the X-factor theory , 2003, Advanced Semiconductor Manufacturing Conference and Workshop, 2003 IEEEI/SEMI.

[4]  D. P. Martin The advantages of using short cycle time manufacturing (SCM) instead of continuous flow manufacturing (CFM) , 1998, IEEE/SEMI 1998 IEEE/SEMI Advanced Semiconductor Manufacturing Conference and Workshop (Cat. No.98CH36168).

[5]  M. Kishimoto,et al.  Optimized operations by extended X-factor theory including unit hours concept , 2001 .