Abstract
The semiconductor process is designed to meet the requirements of photolithography, thin film, etching, cleaning of 12″ 10 nm advanced commercial semiconductor manufacturing process, and the process integration system obtains the necessary process parameters and product measurement data. The relevant information is transmitted back to the MES system according to the production capacity and the product number of batch. This study first conducted an intelligent review of the 12″ 10 nm furnace process tools. According to the SEMI specification, the production equipment interface standard for the furnace tube equipment should be discussed. The 12″ 10 nm furnace module was selected for MES big data analysis. Due to the large number of process data, only the LPCVD process temperature distribution during the TEOS process was selected for distributed computation discussion. However, the yield results of this study can be maintained at 92%, while the equipment utilization rate can reach 97%. It is obvious that good results have been achieved.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Lu, C.C., Chang, K.C., Chen, C.Y.: Study of high-tech process furnace using inherently safer design strategies (IV). The advanced thin film manufacturing process design and adjustment. J. Loss. Prevent. Proc. 40, 378–395 (2016)
Chen, C.Y., Chang, K.C., Wang, G.B.: Study of high-tech process furnace using inherently safer design strategies (I) temperature distribution model and process effect. J. Loss. Prevent. Proc. 26, 1198–1211 (2013)
Chen, C.M., Wang, K.H., Wu, T.Y., Pan, J.S., Sun, H.M.: A scalable transitive human-verifiable authentication protocol for mobile devices. IEEE T. Inf. Foren. Sec. 8(8), 1318–1330 (2013)
Desu, S.B.: Decomposition chemistry of tetraethoxysilane. J. Am. Ceram. Soc. 72(9), 1615 (1989)
Chen, C.Y., Chang, K.C., Lu, C.C., Wang, G.B.: Study of high-tech process furnace using inherently safer design strategies (II) deposited film thickness model. J. Loss. Prevent. Proc. 26, 225–235 (2013)
Chen, C.M., Xu, L., Wu, T.Y., Li, C.R.: On the security of a chaotic maps-based three-party authenticated key agreement protocol. J. Netw. Intell. 1(2), 61–66 (2016)
Nguyen, T.T., Horng, M.F., Shieh, C.S., Dao, T.K.: An energy-based cluster head selection algorithm to support long-lifetime in wireless sensor networks. J. Netw. Intell. 1(1), 23–37 (2016)
Boehm, B.: A spiral model for software development and enhancement. Computer 21(10), 774–778 (1994)
Chen, C.H., Chen, T.Y., Wang, D.J., Li, Y.F.: Multipath flatted-hexagon search for block motion estimation. J. Inf. Hiding Multimed. Signal Process. 1(2), 110–131 (2010)
Huang, D.Y., Lin, C.J., Hu, W.C.: Learning-based face detection by adaptive switching of skin color models and AdaBoost under varying illumination. J. Inf. Hiding Multimed. Signal Process. 2(3), 204–216 (2011)
Liu, X., Li, J.B., Hu, C., Pan, J.S.: Deep convolutional neural networks-based age and gender classification with facial images. In: First International Conference on Electronics Instrumentation & Information Systems (EIIS) (2017)
Weng, S.W., Pan, J.S., Li, L.D., Zhou, L.Z.: Reversible data hiding based on an adaptive pixel-embedding strategy and two-layer embedding. Inf. Sci. 369, 144–159 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Chang, KC., Pan, JS., Chu, KC., Horng, DJ., Jing, H. (2019). Study on Information and Integrated of MES Big Data and Semiconductor Process Furnace Automation. In: Pan, JS., Lin, JW., Sui, B., Tseng, SP. (eds) Genetic and Evolutionary Computing. ICGEC 2018. Advances in Intelligent Systems and Computing, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-13-5841-8_70
Download citation
DOI: https://doi.org/10.1007/978-981-13-5841-8_70
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-5840-1
Online ISBN: 978-981-13-5841-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)