Availability-adjusted X-factor

Abstract

The notion of extended X-factor contribution has been proposed and evaluated recently as a tool to identify system capacity constraints based on machine group utilization and raw processing time. This provides a great convenience for factory-floor managers examining system capacity issues by using only local- or machine-level information. The purpose of this study is twofold: to study fundamental properties of the extended X-factor contribution measure augmented with availability, and to use this new measure to investigate resource allocation for optimizing mean cycle time. The availability-adjusted X-factor was first introduced in the context of local cycle time and its relation to allocation of personnel in individual machine groups. The availability-adjusted X-factor contribution measure developed and evaluated in the current study differs from the previous measure by its ability to identify capacity-constraining machines in the entire system. The measure presented herein is a more accurate indicator of capacity constraints than the extended X-factor contribution measures. With an objective to minimize cycle time or maximize throughput by properly allocating available resources, the results presented herein clearly demonstrate the effectiveness of this new measure to identify capacity-constraining machines. This study also uses availability as a decision variable for mean cycle time optimization.

Keywords:

• X-factor theory
• Availability
• Capacity constraints
• Cycle time performance

Acknowledgements

D. Delp is supported by an Intel Foundation Graduate Fellowship Award and in part by NSF under grants ECS-9553202 and ECS-0002098. J. Si's work is supported by NSF under grants ECS-9553202 and ECS-0002098. J. Fowler's research is supported by NSF under grant DMI-0140441 and by International SEMATECH and the Semiconductor Research Corp. (SRC) under SRC grant 2001-NJ-1124.