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Aisiya Chenkhuntod. Optimizing semiconductor inventory network flow to mitigate the impact of COVID-19 disruptions : a study on substrate inventory management and loss minimization. Master's Degree(Logistics and Supply Chain Systems Engineering). Thammasat University. Thammasat University Library. : Thammasat University, 2024.
Optimizing semiconductor inventory network flow to mitigate the impact of COVID-19 disruptions : a study on substrate inventory management and loss minimization
Name: Aisiya Chenkhuntod
keyword:
Optimization
;
COVID-19
Abstract:
The COVID-19 pandemic has severely disrupted the global supply chain, particularly impacting the semiconductor industry, which is critical to multiple sectors. In 2022, demand for semiconductors surged due to factors such as electric vehicles and remote work, causing widespread chip shortages. This situation was further aggravated by the scarcity of substrate materials, leading to a bullwhip effect and inflated inventory levels. This study addresses the surplus substrate inventory issue by optimizing the semiconductor supply chain network flow. The optimization seeks to minimize various costs, including holding inventory, opportunity, scrap, and material costs, while accounting for constraints like ongoing orders, penalties, substrate shelf life, and demand fluctuations. The research aims to explore how supply chain disruptions contribute to excessive inventory and identify strategies to minimize these losses. The literature review highlights the semiconductor industry's unprecedented challenges during the pandemic, including disruptions in supply, demand, and logistics, which exacerbated the bullwhip effect. The study also examines manufacturing strategies and planning decisions. OpenSolver was used to optimize a model to minimize total costs, beginning with the top 10 substrate items, expanding to 30 and 42 items covering 83% and 91% of total demand, respectively. The results reveal that as demand coverage increases, total costs also rise, with Scenario 1 incurring a total cost of $80,995 and Scenario 3 reaching $145,708. Holding inventory and scrap costs are significant contributors to this increase. Importantly, no penalty costs were incurred, suggesting the model successfully avoids this cost driver. In conclusion, this research provides valuable insights into mitigating the effects of COVID-19-induced supply chain disruptions on the semiconductor industry. The optimization strategies derived from this study can help create a more resilient supply chain by balancing inventory levels and minimizing costs. However, limitations of OpenSolver's computational capacity highlight the need for more advanced optimization tools for larger datasets, and future research could explore the impact of different inventory constraints.
Thammasat University. Thammasat University Library
Address:
BANGKOK
Email:
preserv@tu.ac.th
Role:
advisor
Created:
2024
Modified:
2568-05-15
Issued:
2025-04-21
วิทยานิพนธ์/Thesis
application/pdf
eng
DegreeName: Master of Engineering
Level: Master's Degree
Descipline: Logistics and Supply Chain Systems Engineering
Grantor: Thammasat University
©copyrights Thammasat University
RightsAccess:
ใช้เวลา
0.038549 วินาที
Aisiya Chenkhuntod
| Title | Contributor | Type |
|---|---|---|
| Optimizing semiconductor inventory network flow to mitigate the impact of COVID-19 disruptions : a study on substrate inventory management and loss minimization
มหาวิทยาลัยธรรมศาสตร์ Aisiya Chenkhuntod | Jirachai Buddhakulsomsiri | วิทยานิพนธ์/Thesis |
Jirachai Buddhakulsomsiri