2001 IEEE/SEMI Advanced Semiconductor Manufacturing Conference (IEEE Cat. No.01CH37160)
DOI: 10.1109/asmc.2001.925605
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Quantifying operational time variability: the missing parameter for cycle time reduction

Abstract: Operational time variability is one of the key parameters determining the average cycle time of lots. Many different sources of variability can be identified such as equipment breakdowns, setup, and operator availability. However, an appropriate measure to quantify variability is missing. Measures such as the Overall Equipment Efficiency (OEE) in semiconductor industry are entirely based on mean value analysis and do not include variances.The main contribution of this paper is the development of a new algorith… Show more

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Cited by 16 publications
(14 citation statements)
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“…A common methodology for this type of global metrics is found in lithography layers per stepper per day [26]. Jacobs stated that by reducing bottleneck process stagnation contributes greatly to the reduction of cycle time [28]. Both Dietrich and Maynard further this concept by stating the solution of a bottleneck is not simply tool redundancy, but rather lie in tool and facility understanding [14], [38].…”
Section: Hvsf Global Metricsmentioning
confidence: 98%
“…A common methodology for this type of global metrics is found in lithography layers per stepper per day [26]. Jacobs stated that by reducing bottleneck process stagnation contributes greatly to the reduction of cycle time [28]. Both Dietrich and Maynard further this concept by stating the solution of a bottleneck is not simply tool redundancy, but rather lie in tool and facility understanding [14], [38].…”
Section: Hvsf Global Metricsmentioning
confidence: 98%
“…The definition of EPT as it is used throughout this paper is as follows: the EPT of a lot is the total amount of time a lot exploits capacity from a system, until it is processed as a qualified lot [12], [13].…”
Section: ) No Distinction Is Made Between Different Metrologymentioning
confidence: 99%
“…In [Sattler, 1996] it was also noticed that this definition of effective process time is difficult to measure. Instead of taking the bottom-up view of [Hopp and Spearman, 2000], a top-down approach can also be taken, as shown in [Jacobs et al, 2001, Jacobs et al, 2003, where algorithms have been introduced that enable determination of effective process time realizations from a list of events. That is, instead of measuring each source of disturbances individually and derive an aggregate effective process time distribution, one can also derive this effective process time distribution from manufacturing data directly.…”
Section: Effective Process Timesmentioning
confidence: 99%