Research on Risk Assessment and Classification Method of Raise Boring Rig

Shouye Cheng, Guoye Jing and Zhaoyang Song ()
Additional contact information
Shouye Cheng: China Coal Research Institute, Mine Construction Research Branch
Guoye Jing: China Coal Research Institute, Mine Construction Research Branch
Zhaoyang Song: China Coal Research Institute, Mine Construction Research Branch

A chapter in Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), 2024, pp 47-57 from Springer

Abstract: Abstract In order to promote risk identification and prevention of raise boring rigs, an index system is constructed, and a risk assessment and classification method is proposed. By analysing the risk factors such as geology, equipment, environment and personnel, we constructed a work breakdown structure and a risk breakdown structure for raise boring rigs based on WBS-RBS method respectively, and also established a coupling matrix for risk identification. Expert evaluation and engineering construction experience are adopted to classify and quantify the occurrence probability and risk degrees. Then a comprehensive identification and classification method for raise boring rigs is proposed and the applicability and measures for risk prevention and control under different risk levels are discussed briefly. The method of risk identification and classification of raise boring rig is applied to the risk assessment of inclined shaft construction in a pumped-storage power station, and the rationality and reliability of the assessment method are verified.

Keywords: risk assessment; risk identification; raise boring rigs; engineering construction; classification method (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-256-9_6

Ordering information: This item can be ordered from
http://www.springer.com/9789464632569

DOI: 10.2991/978-94-6463-256-9_6

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().