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Article

Blockchain-Based Long-Term Capacity Planning for Semiconductor Supply Chain Manufacturers

1
School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
2
Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China
3
School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
4
Zhongguancun Laboratory, Beijing 100194, China
5
School of Engineering Science, University of Chinese Academy of Sciences, Beijing 100190, China
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(6), 4748; https://doi.org/10.3390/su15064748
Submission received: 24 January 2023 / Revised: 20 February 2023 / Accepted: 2 March 2023 / Published: 7 March 2023
(This article belongs to the Special Issue Blockchain for Sustainable Supply Chains)

Abstract

The long-term production capacity planning of semiconductor supply chain manufacturers has a series of characteristics, such as large capital investment, fast technology upgrading, long lead-time of manufacturing equipment, and unstable market environment, which leads to the uncertainty of demand. In addition, blockchain technology is widely used to build consortium chains for information sharing across upstream and downstream enterprises, thus having the potential ability to help finance semiconductor manufacturers. This paper combines two uncertainty-oriented methods (stochastic programming and robust optimization) to examine the conversion of capacity between different product types and construct a two-stage mathematical planning model maximizing the net profit of manufacturers. Through the introduction of blockchain technology and information sharing among enterprises, we improve the effectiveness of our model to realize the optimal allocation of long-term capacity planning. Finally, we reformulate the model into a tractable MINLP, construct numerical examples to verify the solvability, and carry out sensitivity analysis.
Keywords: semiconductor manufacturers; long-term capacity planning; uncertainty; stochastic programming; robust optimization; capacity conversion semiconductor manufacturers; long-term capacity planning; uncertainty; stochastic programming; robust optimization; capacity conversion

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MDPI and ACS Style

Yang, J.; Dong, J.; Gao, S.; Wang, G. Blockchain-Based Long-Term Capacity Planning for Semiconductor Supply Chain Manufacturers. Sustainability 2023, 15, 4748. https://doi.org/10.3390/su15064748

AMA Style

Yang J, Dong J, Gao S, Wang G. Blockchain-Based Long-Term Capacity Planning for Semiconductor Supply Chain Manufacturers. Sustainability. 2023; 15(6):4748. https://doi.org/10.3390/su15064748

Chicago/Turabian Style

Yang, Jian, Jichang Dong, Suixiang Gao, and Guoqing Wang. 2023. "Blockchain-Based Long-Term Capacity Planning for Semiconductor Supply Chain Manufacturers" Sustainability 15, no. 6: 4748. https://doi.org/10.3390/su15064748

APA Style

Yang, J., Dong, J., Gao, S., & Wang, G. (2023). Blockchain-Based Long-Term Capacity Planning for Semiconductor Supply Chain Manufacturers. Sustainability, 15(6), 4748. https://doi.org/10.3390/su15064748

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