查詢結果分析
來源資料
相關文獻
- 機械性系統之預防性維修政策--遺傳演算法之應用
- A Genetic Algorithm for Tuning Reliable Fuzzy System
- 高科技產品最佳置換時間圖解法--以多組件產品為例
- 遺傳演算法於合成電力系統可靠度規劃之應用
- 合成發輸電系統之可靠度規劃
- 應用混合型遺傳演算法於合成發輸電系統容量規劃之探討
- 遺傳演算法於配電系統可靠度設計之應用
- 小型SCADA系統之可靠度與架構探討
- 線性軸幅路網接駁系統最適整合區位、路線與排班模式之研究
- Genetic Algorithm Approach for Designing Fir Hilbert Transformers and Differentiators
第1筆 /總和 1 筆
/ 1 筆
頁籤選單縮合
題名 | 機械性系統之預防性維修政策--遺傳演算法之應用=The Preventive Maintenance Policies for Mechanical System: An Application of Genetic Algorithm |
---|---|
作者 | 劉家熙; 盧家斌; | 書刊名 | 國防管理學報 |
卷期 | 26:1 民94.05 |
頁次 | 頁49-70 |
分類號 | 446.8406 |
關鍵詞 | 遺傳演算法; 預防性置換; 小修理; 備份件; 可靠度; Genetic algorithm; Preventive replacement; Minimal repair; Spare parts; Dynamic mechanical reliability; |
語文 | 中文(Chinese) |
中文摘要 | 舉凡武器系統、飛機、捷運、高速鐵路等大型複雜系統,在其長達數十年的生命周期中,系統能否持續正常運作,預防性維修扮演著舉足輕重的角色。另外,系統的維護作為的良莠與否和備份件預估的準確性,也有相當密切的關係。本研究主要目的是探討多組件串聯機械系統最適預防性維修政策、壽期內備份件的預估,以最低的成本維持系統正常運作。模式建構為機械動態可靠度模型,包括預防性置換及符合非齊性卜瓦松分配的小修理。模式中以平均更換成本、平均捨棄成本為取捨條件,並運用遺傳演算法,求取在不同置換周期、不同系統最低可靠度需求下,最適預防性置換組件排程與組合。研究發現、當系統最低可靠度需求值愈小,則以較長之置換周期執行組件置換的工作較佳,可有效降低單位時間成本,否則以較短的置換周期較佳,另外,實施預防性置換政策,系統於置換周期內之非齊性卜瓦松失效次數非常低,有助於降低系統在置換周期內之小修理成本。 |
英文摘要 | Usually large complicated systems, such as weapon systems, airplanes, Mass Rapid Transit (MRT) system and high speed railway, have a product life cycle of several years or even several decades. Preventive maintenance plays a key role to keep system operate normally during the planned life cycle. Besides, the performance of maintenance operations is also heavily relied on the precision of spare part quantity determining. This research tries to find the optimal preventive maintenance policy for the mechanical system with series configuration between modules, determines the frequency of unexpected breakdowns and the related spare part quantity to maintain the system in a required level of normal operation, at the lowest cost. A dynamic mechnical reliability model is developed including preventive replacement and minimal repairs following a non-homogeneous Poisson process. Based on the trade-off analysis of average costs for performing the preventive replacement to keep system continue to operate or stoping replacement until system phase-out, a genetic algorithm is applied to find the optimal preventive replacement schedule and combination of modules under different system reliability requirements and preventive replacement cycle. A couple of numerical examples have been demonstrated. The results show that the lower system reliability level required, the longer preventive replacement cycle should be applied to find the lowest cost per unit cycle time. In addition to this, we also show that the average number of un-scheduled failures turns out to be very few while the proposed preventive replacement policy is taken. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。