A semantic web-based risk assessment framework for collaborative planning to enhance overall supply chain effectiveness for semiconductor industry-Reference-Cited by-同舟云学术

A semantic web-based risk assessment framework for collaborative planning to enhance overall supply chain effectiveness for semiconductor industry

Published:2023-12 Issue: Volume:149 Page:110976
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Kuo Hsuan-An,Chien Chen-Fu^ORCID,Ehm Hans,Ponsignon Thomas

Funder

Infineon Technologies

National Science and Technology Council

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

Software

Reference57 articles.

1. An agent-based infrastructure for assessing the performance of planning approaches for semiconductor supply chains;Herding;Expert Syst. Appl.,2022

2. Subpopulation preference adjective non-dominated sorting genetic algorithm for multi-objective capacity expansion for matured fabs;Kuo;Appl. Soft Comput.,2023

3. Smart semiconductor manufacturing for pricing, demand planning, capacity portfolio and cost for sustainable supply chain management;Chien;Int. J. Logist. Res. Appl.,2022

4. Pitfalls and protocols of data science in manufacturing practice;Lee;J. Intell. Manuf.,2022

5. Logistics and supply chain management reorganisation via talent portfolio management to enhance human capital and resilience;Chen;Int. J. Logist. Res. Appl.,2023

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