Effective application of digital integrated management and maintenance systems is essential for successful operation and maintenance management of bridge projects.This article analyzes the application strategy of such...Effective application of digital integrated management and maintenance systems is essential for successful operation and maintenance management of bridge projects.This article analyzes the application strategy of such systems.It provides an overview of comprehensive digital management and maintenance of bridges,an analysis of the basic components of the integrated management and maintenance system,and its application strategies.This study aims to offer guidance for the application of the system and to improve the quality of modern bridge engineering management and maintenance work.展开更多
With the emergence of Industry 4.0, mainte-nance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for a...With the emergence of Industry 4.0, mainte-nance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for asset utilization, service, and after-sales in realizing Industry 4.0. Moreover, artificial intelligence （AI） is also central for Industry 4.0, and offers data-driven methods. The aim of this article is to develop a new maintenance model called deep digital maintenance （DDM）. With the support of theoretical foundations in cyber-physical systems （CPS） and maintenance, a concept for DDM is proposed. In this paper, the planning module of DDM is investigated in more detail with realistic industrial data from earlier case studies. It is expected that this planning module will enable inte- grated planning （IPL） where maintenance and production planning can be more integrated. The result of the testing shows that both the remaining useful life （RUL） and the expected profit loss indicator （PLI） of ignoring the failure can be calculated for the planning module. The article concludes that further research is needed in testing the accuracy of RUL, classifying PLI for different failure modes, and testing of other DDM modules with industrial case studies.展开更多
文摘Effective application of digital integrated management and maintenance systems is essential for successful operation and maintenance management of bridge projects.This article analyzes the application strategy of such systems.It provides an overview of comprehensive digital management and maintenance of bridges,an analysis of the basic components of the integrated management and maintenance system,and its application strategies.This study aims to offer guidance for the application of the system and to improve the quality of modern bridge engineering management and maintenance work.
文摘With the emergence of Industry 4.0, mainte-nance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for asset utilization, service, and after-sales in realizing Industry 4.0. Moreover, artificial intelligence （AI） is also central for Industry 4.0, and offers data-driven methods. The aim of this article is to develop a new maintenance model called deep digital maintenance （DDM）. With the support of theoretical foundations in cyber-physical systems （CPS） and maintenance, a concept for DDM is proposed. In this paper, the planning module of DDM is investigated in more detail with realistic industrial data from earlier case studies. It is expected that this planning module will enable inte- grated planning （IPL） where maintenance and production planning can be more integrated. The result of the testing shows that both the remaining useful life （RUL） and the expected profit loss indicator （PLI） of ignoring the failure can be calculated for the planning module. The article concludes that further research is needed in testing the accuracy of RUL, classifying PLI for different failure modes, and testing of other DDM modules with industrial case studies.
