Developing a Robust Optimal Maintenance Planning Model Considering the Inspected Information

2020 Fiscal Year Final Research Report

• Project/Area Number: 18K04392
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 22050:Civil engineering plan and transportation engineering-related
• Research Institution: Tohoku University
• Principal Investigator: Okubo Kazuaki 東北大学, 国際文化研究科, 准教授 (50546744)
• Co-Investigator(Kenkyū-buntansha): 全 邦釘 東京大学, 大学院工学系研究科(工学部), 特任准教授 (60605955)
• Project Period (FY): 2018-04-01 – 2021-03-31
• Keywords: ロバスト最適化 / 社会インフラ / 維持管理計画

Outline of Final Research Achievements

Periodic inspections of social infrastructures are mandatory and a large amount of inspection information has been accumulated. We developed a robust optimal maintenance planning model that takes into account the inspected information. We provide a robust optimal solution to the prediction error in the deterioration rate during the planning period and proposed a maintenance planning model to determine the timing of repair so that the cost is minimized. As a result, it was confirmed that the proposed method can provide a robust plan and revealed that increasing the number of inspections can reduce the cost. In addition, an empirical analysis was conducted to grasp deterioration factors of social infrastructures based on actual inspection reports, for example, the inspection intervals from the viewpoint of expected life cycle costs were discussed.

Free Research Field

土木計画学

Academic Significance and Societal Importance of the Research Achievements

本研究で提案した手法は，近年，盛んに研究されているデータ駆動型ロバスト最適化手法の一つとして位置づけられ，その中でも新規な手法を提案している点に学術的意義がある．また，本研究では時間経過とともに蓄積されていく大量の点検情報を活用していくための体系的な一つの方法を提案しており，実務において点検調書の情報を維持管理などの計画策定に活用していく方法を検討する上での一つの参考資料を提供していることが期待される．