Production-Level Artificial Intelligence Applications in Semiconductor Manufacturing-Reference-Cited by-同舟云学术

Production-Level Artificial Intelligence Applications in Semiconductor Manufacturing

Published:2021-12-12 Issue: Volume: Page:
ISSN:
Container-title:2021 Winter Simulation Conference (WSC)
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Author:

Chien Chen-Fu¹,Ehm Hans²,Fowler John³,Monch Lars⁴,Wu Cheng-Hung⁵

Affiliation:

1. National Tsing Hua University,Department of Industrial Engineering and Engineering Management,Hsinchu,TAIWAN,30013

2. Infineon Supply Chain Innovation Infineon Technologies AG,Neubiberg,GERMANY,85579

3. Arizona State University,Department of Supply Chain Management,Tempe,AZ,USA,85249

4. University of Hagen,Department of Mathematics and Computer Science,Hagen,GERMANY,58097

5. College of Management National Taiwan University,Dist Taipei City,TAIWAN,106

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9715283/9715284/09715399.pdf?arnumber=9715399

Reference36 articles.

1. Order Release Planning with Predictive Lead Times: a Machine Learning Approach;schneckenreither;International Journal of Production Research,2020

2. Bi-criteria Parallel Batch Machine Scheduling to Minimize Total Weighted Tardiness and Electricity Cost;rocholl;Journal of Economics and Business,2020

3. Heuristic approaches for master planning in semiconductor manufacturing

4. Exploit the Value of Production Data to Discover Opportunities for Saving Power Consumption of Production Tools

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Leveraging Machine Learning for Capacity and Cost on a Complex Toolset: A Case Study;IEEE Transactions on Semiconductor Manufacturing;2023-11

2. Production-Level Artificial Intelligence Applications in Semiconductor Supply Chains;IEEE Transactions on Semiconductor Manufacturing;2023-11