| 摘要: | 維護管理工作所伴隨公共設施使用的時間往往最長，亦與設施使用效能直接相關。尤其是公共工 程基礎建設及城市重要設施，維護管理工作不僅只影響單一設施性能問題，設施的有效性更連帶影響 總體產業生產力、民生品質、區域經濟發展等等。隨著智慧城市之建設發展趨勢，當城市設施結合智 慧治理的程度及功能愈高時，由於設施與公共服務之鏈結程度提高，維護管理工作更趨重要，有系統 的週期性設施維護管理成為政府的施政目標中不可或缺的重點項目。過去許多研究與實務經驗中皆指 出，無論維護管理的策略方針為何？有系統判別設施性能老化、修復(deterioration and rehabilitation)、 維護作業預算運用(budgeting for maintenance cost)、設施服務效能維護評估(maintenance level of service) 的決策支援模式可以輔助建立更完善的維護管理制度，更有效的運用預算與相關資源以達到設施設計 性能及公共服務目標。此外，設施維護管理的預算規劃運用、設施的退化與所需修復作業的評估、作 業時間的延遲與時程規劃等等事項都是環環相扣的系統性議題，因此需要跳脫傳統上以單一專案或合 約的觀點，進而規劃結合系統觀點的整合式維護管理決策模式，更適合用於策略性的城市治理政策規 劃，並且更彈性快速地協助進行較中長期的治理規劃。因應智慧治理的公共建設與設施，維護管理制 度建立時之視野亦更需要同步的從單一設施之維護而提昇到整個智慧城市設施之整合維護管理機 制，而且維護管理反應速度更需要提昇且動態的因應各式資訊情報系統所回報之設施運用情況。 為開發更具整合性之設施維護管理實務應用技術，促進執行成效，本計畫嘗試運用美國麻省理工 學院(MIT)所發展的「系統動態學」(System Dynamics)及電腦模擬技術為主要分析方法論，將風險分 析與成本管理之觀念與技術納入實務應用，整合城市治理決策模式以建構「智慧城市設施整合維護管 理系統動態決策支援模式」，輔助專案實務執行過程中所需要進行的異常預警判斷及管理決策。同時， 本計畫力求學理方法與實務需求之結合，預計以台北市智慧洪災管理體系之自動化抽水站設施維護管 理案例為實證研究對象，透過案例資料分析、專家訪談、風險模擬應用以進行實證研究，強化本計畫 實務應用價值。本計畫除了將發展設施維護管理專案之電腦模擬模型，亦將進階結合「策略動態學」 (Strategy Dynamics)方法論，強調以量化模型為基礎的管理(Model-Based Management)、資源基礎觀點 (Resource-Based View, RBV)與時間序列績效的特點，促進了策略規劃與管理實務的動態情境分析能力 與系統觀。 相較於過去相關研究，本計畫具有幾點特色及貢獻：(1)可協助管理團隊在多項專案執行過程中掌 握結構性專案風險變異，提昇異常預警判斷能力，(2)可協助動態性風險分析與生命週期成本管理以有 效連結設施整合維護管理目標，以及(3)可透過電腦情境模擬分析各種設施或專案異常情況，理性評估 風險對策之可行性以輔助資源調度與策略性管理決策。由於本計畫廣泛運用科學基礎與系統化問題診 斷方法，所發展之決策支援模式除了可輔助提昇整合式維護管理決策能力，亦有助於管理團隊的經驗 學習與知識傳承。
Periodic infrastructure maintenance and rehabilitation programs are essential for efficiently managing large networks of infrastructure assets and sustaining their safety and operability for public services. Deterioration of an infrastructure system can manifest itself in several ways such as on the productivity of industries, on the quality of life of the citizens, and on the regional economy. An effective urban infrastructure maintenance system is increasingly important when promoting smart city governance and facilities, while active functions of built infrastructure system are expected. Previous studies proposed that a major challenge for asset managers is to determine the appropriate actions needed to preserve the performance of their rapidly deteriorating infrastructure, over a long service life. Adequate budgeting and planning of infrastructure rehabilitation programs is of extreme importance in achieving this objective. The management of infrastructure deterioration and rehabilitations has been extensively studied and a number of optimization models have been introduced for different assets. However, there is a need to further develop a collaborative urban infrastructure maintenance system from a holistic perspective instead of individual contracts of maintenance projects. The decisions to handling deterioration and rehabilitation, budgeting for maintenance cost, and the maintenance level of public services are critical points of improvements for better design and management of urban infrastructure maintenance system. Furthermore, to realize effective urban infrastructure maintenance management decisions accordance with the quality level of public service, budget, and operations management, systematic planning with life cycle cost management are critical parts and the applications with simulation-based scenario analysis are very demanding. The main goal of the proposed research is to develop a collaborative urban infrastructure maintenance management decision support system for smart city governance with case studies and applications of computer simulations. In order to better integrate the computer models and real world maintenance management practices, the Smart Flood Management System of Taipei City and the infrastructure as well as relevant facilities will be benchmarked for data collection and case studies. System Dynamics modelling and simulation techniques will be used as complementary methodologies for quantitative analysis and computer-aid scenarios analysis. Strategy Dynamics principles such as resource-based planning, model-based management, and time-phase performance evaluation are also incorporated for improving strategic thinking of maintenance management decisions. It is expected that the proposed model can practically support the dynamic risk analysis and life cycle cost assessment for strategic maintenance management decisions. Compared with previous studies, the research results would have a potential to contribute benefits for infrastructure maintenance management practices including: (1)systematically evaluates structural causes and the schedule/cost variances to maintenance plans, so as to better perform early warning system, (2)dynamically supports risk analysis and life cycle cost management, so as to enhance the performance of infrastructure maintenance, (3)strategically integrates resources from executive management and their management decisions with applicable simulation-based scenarios analyses, so as to support rational expectations on maintenance project performance. In addition, the proposed model, which is a scientific and structured decision support system, can also support management team trainings and learning of engineering and management lessons. |
