隨著科技持續發展與環保概念提升，政府與業者對於循環經濟概念愈發重視，積極研發新產品或技術來降低系統失效頻率。然而，在現實生活中系統時常遭受內部退化與外在隨機衝擊加速系統退化速率，致使系統效能大幅降低，此時系統具備自我恢復能力將可大幅延長系統使用時間。目前自我恢復力概念已被廣泛運用於不同領域，如化學材料、建築或交通運輸等領域。然而，回顧過往可靠度領域的文獻只談及當系統具固定恢復力之置換策略，反而鮮少提及具自我恢復力且恢復力遞減系統之相關置換策略與價值，因此本研究探討在系統具自我恢復力且恢復能力隨衝擊次數遞減情況下尋找最佳置換策略，來貼合現實使用情況。根據分析結果得知，在最低期望總成本的目標下，影響系統最佳置換時間的主要因素為受小修成本、置換成本及自我恢復能力，因此決策者在制定相關策略時，應考量各樣因素並取得平衡，藉以尋求最佳置換策略。

Due to technological advancements and the increasing emphasis on environmental protection, both the government and businesses have become more interested in the Circular Economy (CE). To reduce the number of system failures, new techniques and products are being actively developed. However, systems are prone to both internal deterioration and external random shocks that can cause a rapid decline in production capacity. Therefore, if a system has resilience capability, its lifespan can be extended. Currently, resilient systems are being utilized in various fields, such as the chemical, building, transportation industries, and so on. Past literature has only considered the concept of fixed recovery amounts for systems under random shocks and the value of resilience capability without considering the concept of repairable systems with decreasing resilience capability. Therefore, this thesis explores the optimal replacement policy for repairable systems with decreasing resilience capability under random shocks fit practical usage situations. According to the analysis results, the main factors influencing the optimal replacement policy are the costs of minimal repair, resilience capability, and replacement costs to minimize the expected total cost rate. Therefore, decision-makers should consider balancing minimal repair and replacement costs when formulating relevant strategies to seek the optimal replacement policy.

英文文獻：
[1] Merryn, H. G., F. Charnley, and E. O. Adriana, 2021,“ Self-healing materials: A pathway to immortal products or a risk to circular economy systems?,” Journal of Cleaner Production, pp. 128-193.
[2] Holling, S. C., 1973,“ Resilience and Stability of Ecological Systems,” Annual Review of Ecology and Systematics, Vol. 4, pp. 1-23.
[3] Yıldırım, G., O. K. Keskin, S. B. Keskin, M. Sahmaran, and M. Lachemi, 2015,“ A review of intrinsic self-healing capability of engineered cementitious composites: Recovery of transport and mechanical properties,” Construction and Building Materials, Vol.101, pp. 10-21.
[4] Tan, P., H. Wang, F. Xiao, X. Lu, W. Shang, X. Deng, H. Song, Z. Xu, J. Cao, T. Gan, B. Wang, and X. Zhou, 2022,“ Solution-processable, soft, self-adhesive, and conductive polymer composites for soft electronics,” Nature Communications, DOI:10.1038/s41467-022-28027-y.
[5] Wang, G. J., and Y. L. Zhang, 2013,“ Optimal repair–replacement policies for a system with two types of failures,” European Journal of Operational Research, Vol. 226, No. 3, pp. 500-506.
[6] Caballe, N. C., I. T. Castro, C. J. Pérez, and J. M. Lanza-Gutiérrez, 2015,“ A condition-based maintenance of a dependent degradation-threshold-shock model in a system with multiple degradation processes,” Reliability Engineering & System Safety, Vol. 134, pp. 98-109.
[7] Peng, H., Q. Feng, and D. W. Coit, 2010,“ Reliability and maintenance modeling for systems subject to multiple dependent competing failure processes,” IIE Transactions, Vol. 43, No. 1, pp. 12-22.
[8] Keedy, E., and Q. Feng, 2012,“ A physics-of-failure based reliability and maintenance modeling framework for stent deployment and operation,” Reliability Engineering & System Safety, 103, pp. 94-101.
[9] Song, S., D. W. Coit, and Q. Feng, 2016,“ Reliability analysis of multiple-component series systems subject to hard and soft failures with dependent shock effects,” IEEE Transactions, Vol. 48, No. 8, pp. 720-735.
[10] Wang, Z., H. Z. Huang, Y. Li, and N. C. Xiao, 2011,“ An Approach to Reliability Assessment Under Degradation and Shock Process,” IEEE Transactions on Reliability, Vol. 60, No. 4, pp. 852-863.
[11] Qiu, Q., and L. Cui, 2019,“ Optimal mission abort policy for systems subject to random shocks based on virtual age process,” Reliability Engineering & System Safety, Vol. 189, pp. 11-20.
[12] Wang, H., 2002,“ A survey of maintenance policies of deteriorating systems,” European Journal of Operational Research, Vol. 139, No. 3, pp. 469-489.
[13] Tanwar, M., R. N. Rai, and N. Bolia, 2014,“ Imperfect repair modeling using Kijima type generalized renewal process,” Reliability Engineering & System Safety, Vol. 124, pp. 24-31.
[14] Chang, C. C., 2014,“ Optimum preventive maintenance policies for systems subject to random working times, replacement, and minimal repair,” Computers & Industrial Engineering, Vol. 67, pp. 185-194.
[15] Lim, J. H., J. Qu, and M. J. Zuo, 2016,“ Age replacement policy based on imperfect repair with random probability,” Reliability Engineering & System Safety, Vol. 149, pp. 24-33.
[16] Yang, L., Z. S. Ye, C. G. Lee, S. F. Yang, and R. Peng, 2019,“ A two-phase preventive maintenance policy considering imperfect repair and postponed replacement,” European Journal of Operational Research, Vol. 274, No. 3, pp. 966-977.
[17] Zhang, Y. L., R. C. M. Yam, and M. J. Zuo, 2002,“ Optimal replacement policy for a multistate repairable system,” Journal of the Operational Research Society, Vol. 53, No. 3, pp. 336-341.
[18] Badia, F. G., M. D. Berrade, J. H. Cha, and H. Lee, 2018,“ Optimal replacement policy under a general failure and repair model: Minimal versus worse than old repair,” Reliability Engineering & System Safety, Vol. 180, pp.362-372.
[19] Zhang, X., H. Huang, and Q. Yang, 2013,“ Real-time implementation of a self-recovery EMG pattern recognition interface for artificial arms,” IEEE Xplore, DOI：10.1109/EMBC.2013.6610901.
[20] Terryn; S., G. Mathijssen; J. Brancart; T. Verstraten; G. V. Assche; and B. Vanderborght, 2016,“ Toward Self-Healing Actuators: A Preliminary Concept,” IEEE Transactions on Robotics, Vol. 32, No. 3, pp.736-743.
[21] Liu, H., R. H. Yeh, and B. Cai, 2017,“ Reliability modeling for dependent competing failure processes of damage self-healing systems,” Computers & Industrial Engineering, Vol. 105, pp. 55-62.
[22] Chiang, M. H., T. Y. Hong and R. H. Yeh, 2022,“ Cost Efficiency of Resilience Capability for Webibull life-time Products under Random Shocks,”. [Paper presentation]. Poster session presented at the 10th Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling, Hsinchu, Taiwan.
中文文獻：
[23] 翁御庭，在不同隨機衝擊量下系統之最佳置換時程，國立臺灣科技大學碩士論文，2020。
[24] 黃馨玫，在隨機衝擊下之可自我恢復線性退化系統之最佳置換時機，國立臺灣科技大學碩士論文，2021。
[25] 許子揚，隨機衝擊下具自我恢復力退化系統之最佳置換門檻，國立臺灣科技大學碩士論文，2022。
[26] 江旻軒，具自我恢復力之可維修產品在隨機衝擊下之最佳置換時程，國立臺灣科技大學碩士論文，2022。