學術發表

Journal Papers

1. Kuo, H. A., Hong, T. Y., & Chien, C. F. (2025). A deep reinforcement learning based digital twin framework for resilient production planning under demand uncertainty and an empirical study in semiconductor wafer fabrication. Computers & Industrial Engineering, 111389.(https://doi.org/10.1016/j.cie.2025.111389)

2. Chen, C.A., Chien, C. F., & Kuo, H. A. (2025). Hybrid quantum annealing genetic algorithm with auxiliary resource dispatching for TFT-LCD array photolithography scheduling and an empirical study. Computers & Industrial Engineering.(https://doi.org/10.1016/j.cie.2025.110989)

3. Chen, C.A., Kuo, H. A., & Chien, C. F. (2024). Dual-Resource Constrained Flexible Job Shop Scheduling for SMT Back-end Production and An Empirical Study of Wearable Devices. IEEE Transactions on Automation Science and Engineering. (https://ieeexplore.ieee.org/abstract/document/10806845)

4. Chien, C. F., Kuo, H. A., & Lin, Y. S. (2024). Smart semiconductor manufacturing for pricing, demand planning, capacity portfolio and cost for sustainable supply chain management. International Journal of Logistics Research and Applications, 27(1), 193-216. (https://doi.org/10.1080/13675567.2022.2076818)

5. Chien, C. F., Kuo, P. C., Sun, P. C., & Kuo, H. A. (2024). Green production planning for circular supply chain and resource management: An empirical study for high-tech textile dyeing. Resources, Conservation and Recycling, 204, 107499. (https://doi.org/10.1080/13675567.2022.2076818)

6. Kuo, H. A., Chien, C. F., Ehm, H., & Ponsignon, T. (2023). A semantic web-based risk assessment framework for collaborative planning to enhance overall supply chain effectiveness for semiconductor industry. Applied Soft Computing, 149, 110976. (https://doi.org/10.1016/j.asoc.2023.110976)

7. Kuo, H. A., Peng, C. C., & Chien, C. F. (2023). Subpopulation preference adjective non-dominated sorting genetic algorithm for multi-objective capacity expansion for matured fabs. Applied Soft Computing, 147, 110772. (https://doi.org/10.1016/j.asoc.2023.110772)

8. Kuo, H. A., & Chien, C. F. (2023). Semiconductor capacity expansion based on forecast evolution and mini-max regret strategy for smart production under demand uncertainty. Computers & Industrial Engineering, 177, 109077. (https://doi.org/10.1016/j.cie.2023.109077)

Conference Papers

1. Tsai, N. S., & Kuo, H. A. (2026) A digital transformation framework for root cause analysis to drive smart manufacturing and an empirical study for backend equipment vendor, 2026 13th International Conference on Industrial Engineering and Applications (ICIEA 2026).

2. Tsai, P. Y., Chen, Y. M., Kuo, H. A., & Chien, C. F. (2025) New Product Cycle Time Prediction Considering Production Dynamics and an Empirical Study in Semiconductor Wafer Fabrication, In Proceedings of 25rd Asia Pacific Industrial Engineering & Management System Conference AND The 28th Asia Pacific Division Meeting of The International Foundation for Production Research (APIEMS2025).

3. Chen, Z. X., Kuo, H. A., & Chien, C. F. (2025) Data-Driven Framework for Predictive Maintenance Decision Making in IC Substrates Manufacturing, In Proceedings of the International Conference on Industrial Engineering and Operations Management

4. Chen, Y., M., Fan, T., L., Kuo, H. A., & Chien, C. F. (2024). Advanced cycle time prediction for semiconductor manufacturing industry and an empirical study, In Proceedings of 24rd Asia Pacific Industrial Engineering & Management System Conference AND The 27th Asia Pacific Division Meeting of The International Foundation for Production Research (APIEMS2024).

5. Kuo, H. A., Sun, P. C., Lin, Y. S., & Chien, C. F. (2023). A deep reinforcement learning based digital twin framework for resilient production planning and an empirical study in semiconductor wafer fabrication. In Proceedings of International Conference on Computers and Industrial Engineering, Computers & Industrial Engineering (CIE).

6. Kuo, H. A., Lin, Y. S., Sun, P. C., & Chien, C. F. (2023). A hybrid collaborative demand fulfillment framework for printed circuit board production planning to empower symbolic supply chain in post epidemic era, In Proceedings of International Conference on Computers and Industrial Engineering, Computers & Industrial Engineering (CIE).

7. Yang, H. Y., Kuo, H. A., Tseng, P. H, & Chien, C. F (2023). Multi-Objective Production Planning Using Particle Swarm Algorithm Considering Uncertain Production Time and Case Study, In Proceedings of International Conference on Chinese Institute of Industrial Engineers (CIIE).

8. Tseng, P. H, Kuo, H. A., Yang, H. Y., & Chien, C. F (2023). Modified allocated clearing functions based on machine learning for semiconductor frontend production planning model and an empirical study, In Proceedings of 23rd Asia Pacific Industrial Engineering & Management System Conference AND The 26th Asia Pacific Division Meeting of The International Foundation for Production Research (APIEMS2023)

9. Chang, Y. L, Kuo, H. A., & Chien, C. F (2023). Machine learning based cycle time prediction in printed circuit board laser process, In Proceedings of International Conference on Chinese Institute of Industrial Engineers (CIIE).

10. Chen, C. Y., Kuo, H. A., Ma, K. T. & Chien, C. F., (2020) A Human-experience based intelligent scheduling framework to empower Industry 3.5: Implementation of Simulated Annealing Genetic Algorithm in Multi Auxiliary Resource Planning for Job Shop Scheduling in multinational technology manufacturing. Operations Research Society of Taiwan 2020 conference

11. Kuo, H. A., Ponsignon, T., Ehm, H., & Chien, C. F. (2019, April). Overall Supply Chain Effectiveness (OSCE) for Demand and Capacity Incorporation in Semiconductor Supply Chain Industry. In 2019 IEEE International Conference on Smart Manufacturing, Industrial & Logistics Engineering (SMILE) (pp. 24-28). IEEE.

12. Hsu, C., Kuo, H. A., Chien, J. C., Fu, W., Ma, K. T., & Chien, C. F. (2019, March). A machine learning based intelligent agent for human resource planning in IC design service industry. In Proceedings of the International Conference on Industrial Engineering and Operations Management (pp. 3758-3768). MAR.