Developing a Parametric Carbon Footprinting Tool: A Case Study of Wafer Fabrication in the Semiconductor Industry

Capacity Planning for Cluster Tools of Wafer Fabrication Plant

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.450.365 ◽

2010 ◽

Vol 450 ◽

pp. 365-368

Author(s):

James C. Chen ◽

Chia Wen Chen ◽

Kou Huang Chen ◽

Chien Hsin Lin

Keyword(s):

Capacity Planning ◽

Production Costs ◽

Wafer Fabrication ◽

Total Production ◽

Output Rate ◽

Cluster Tools ◽

And Performance ◽

Using Data ◽

Capital Intensive

Wafer fabrication is a capital intensive industry. A 12-inch wafer fabrication plant needs a typical investment of US$ 3 billion, and the equipment cost constitutes about two-thirds to three-quarters of the total production costs. Therefore, capacity planning is crucial to the investment and performance of wafer fabrication plants. Several formulae are presented to calculate the required number of machines with sequential, parallel, and batch processing characteristics, respectively. An AutoSched AP simulation model using data from real foundry fabrication plants is used in a case study to evaluate the performance of the proposed formulae. Simulation results indicate that the proposed formulae can quickly and accurately calculate the required number of cluster tools leading to the required monthly output rate.

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A case study of the impact of the economies of scale of the semiconductor industry on healthcare

1st IEE International Conference on: Commercialising Technology and Innovation ◽

10.1049/ic:20050601 ◽

2005 ◽

Author(s):

K. Errey

Keyword(s):

Economies Of Scale ◽

Semiconductor Industry ◽

The Impact

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Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry

Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management ◽

10.5220/0010142902630270 ◽

2020 ◽

Author(s):

Georgios Koutroulis ◽

Tiago Santos ◽

Michael Wiedemann ◽

Christian Faistauer ◽

Roman Kern ◽

...

Keyword(s):

Neural Networks ◽

Active Learning ◽

Convolutional Neural Networks ◽

Semiconductor Industry ◽

Defect Classification

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Risk Management in Research and Development: A Case Study from the Semiconductor Industry

Technology Development - Innovation, Technology, and Knowledge Management ◽

10.1007/978-3-319-05651-7_8 ◽

2014 ◽

pp. 163-172

Author(s):

Ramin Neshati ◽

Tugrul U. Daim

Keyword(s):

Risk Management ◽

Research And Development ◽

Semiconductor Industry

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Implementation of Decision Tree for Maintenance Policy Decision Making - A Case Study in Semiconductor Industry

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.591-593.704 ◽

2012 ◽

Vol 591-593 ◽

pp. 704-707 ◽

Cited By ~ 3

Author(s):

Siew Hong Ding ◽

Teing Tien Goh ◽

Pei Sze Tan ◽

Siew Ching Wee ◽

Shahrul Kamaruddin

Keyword(s):

Decision Making ◽

Decision Tree ◽

Failure Mechanism ◽

Semiconductor Industry ◽

Policy Decision ◽

Decision Making Process ◽

Maintenance Policy ◽

Machine Performance ◽

Policy Decision Making

Suitable maintenance policy implemented in particular machine able to improve the machine performance as well as the product quality. However, selecting a suitable maintenance policy is a vital and hard work because it has to be decided from analysis of various criteria including failure mechanism and resources limitation. Thus, decision tree is suggested in this paper to provide assistance for maintenance crew in conducting a systematic and efficient decision making process in determining the suitable maintenance policy. In the end of the paper, a case study in semiconductor industry is conducted to illustrate the practicability of developed decision tree.

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