Full metadata
Title
Analyzing Controllable Factors Influencing Cycle Time Distribution in Semiconductor Industries
Description
Semiconductor manufacturing is one of the most complex manufacturing systems in today’s times. Since semiconductor industry is extremely consumer driven, market demands within this industry change rapidly. It is therefore very crucial for these industries to be able to predict cycle time very accurately in order to quote accurate delivery dates. Discrete Event Simulation (DES) models are often used to model these complex manufacturing systems in order to generate estimates of the cycle time distribution. However, building models and executing them consumes sufficient time and resources. The objective of this research is to determine the influence of input parameters on the cycle time distribution of a semiconductor or high volume electronics manufacturing system. This will help the decision makers to implement system changes to improve the predictability of their cycle time distribution without having to run simulation models. In order to understand how input parameters impact the cycle time, Design of Experiments (DOE) is performed. The response variables considered are the attributes of cycle time distribution which include the four moments and percentiles. The input to this DOE is the output from the simulation runs. Main effects, two-way and three-way interactions for these input variables are analyzed. The implications of these results to real world scenarios are explained which would help manufactures understand the effects of the interactions between the input factors on the estimates of cycle time distribution. The shape of the cycle time distributions is different for different types of systems. Also, DES requires substantial resources and time to run. In an effort to generalize the results obtained in semiconductor manufacturing analysis, a non- complex system is considered.
Date Created
2017
Contributors
- Salvi, Tanushree Ashutosh (Author)
- Bekki, Jennifer M (Thesis advisor)
- Sodemann, Angela (Thesis advisor)
- Shuaib, Abdelrahman (Committee member)
- Ren, Yi (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
184 pages
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.44441
Level of coding
minimal
Note
Masters Thesis Mechanical Engineering 2017
System Created
- 2017-06-07 07:46:55
System Modified
- 2021-08-26 09:47:01
- 2 years 8 months ago
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