[논문]공사일지의 텍스트 마이닝을 통한 우천 공기지연 리스크 정량화

박종호; 조민건; 엄세호; 박선규

doi:10.12652/ksce.2023.43.1.0109

공사일지의 텍스트 마이닝을 통한 우천 공기지연 리스크 정량화
Quantification of Schedule Delay Risk of Rain via Text Mining of a Construction Log 원문보기

KSCE Journal of Civil and Environmental Engineering Research = 대한토목학회논문집, v.43 no.1, 2023년, pp.109 - 117

박종호 (성균관대학교 리질리언트에코스마트시티) , 조민건 (성균관대학교 글로벌스마트시티융합공학과) , 엄세호 (성균관대학교 글로벌스마트시티융합공학과) , 박선규 (성균관대학교 건설환경공학부)

초록
AI-Helper

건설공사에서의 공기지연은 공사금액 증가, 발주처 클레임, 무리한 공기단축에 따른 건설공사의 질 하락 등 건설프로젝트에 악영향을 끼치는 주요 리스크 요인이다. 기존 연구에서는 공기지연 리스크의 중요도 및 우선순위를 파악하고 중요도에 따라 공정을 관리하였으나, 공기지연 리스크의 심도는 데이터 수집의 한계 등으로 정량화 연구가 미흡하다. 따라서 본 연구에서는 BERT (Bidirectional Encoder Representations from Transformers) 언어 모델을 활용하여 비정형데이터로 저장된 공사일지의 작업내용을 분석 가능한 WBS (Work Breakdown Structure) 기반의 정형데이터로 변환하고 리스크 분류 및 도출 체계, 공정계획에 사용가능한 리스크 발생확률, 리스크 확률분포(심도)의 정량화 방안을 제시하였다. 제안된 프로세스를 고속도로공사 8개 공구에 적용하여, 39개 세부 공중 중 8개의 세부 공종에서 75건의 우천 공기지연 리스크를 도출하였다. K-S 검정을 통해 4개 공종에서 유의미한 확률분포를 도출하였으며 위험도를 비교하였다. 향후 본 연구에서 제시된 프로세스는 시공단계에서 발생하는 다양한 공기지연 요인의 도출 및 심도 정량화에 적용될 수 있을 것으로 기대된다.

Abstract ▼ AI-Helper

Schedule delays present a major risk factor, as they can adversely affect construction projects, such as through increasing construction costs, claims from a client, and/or a decrease in construction quality due to trims to stages to catch up on lost time. Risk management has been conducted according to the importance and priority of schedule delay risk, but quantification of risk on the depth of schedule delay tends to be inadequate due to limitations in data collection. Therefore, this research used the BERT (Bidirectional Encoder Representations from Transformers) language model to convert the contents of aconstruction log, which comprised unstructured data, into WBS (Work Breakdown Structure)-based structured data, and to form a model of classification and quantification of risk. A process was applied to eight highway construction sites, and 75 cases of rain schedule delay risk were obtained from 8 out of 39 detailed work kinds. Through a K-S test, a significant probability distribution was derived for fourkinds of work, and the risk impact was compared. The process presented in this study can be used to derive various schedule delay risks in construction projects and to quantify their depth.

주제어

표/그림 (11)

그림 Fig. 1. Flow Chart Showing the Research Process
그림 Fig. 2. Transformer Procedures for the BERT Algorithm
그림 Fig. 3. Risk Classifying Algorithm
표 Table 1. Predictive Performance by Hyperparameter of Ko-BERT
표 Table 2. Work Breakdown Structure (WBS) of Earthwork for Fine-Tuning of Ko-BERT
그림 Fig. 4. Number of Risks and Delay Days by Month
표 Table 3. Supervisor Comments for Determining Schedule Delay by Rain
표 Table 4. Data of Schedule Delay Risk by Month
표 Table 5. Data of Schedule Delay Risk by Work Breakdown Structure (WBS) in Earthwork
표 Table 6. Probability Distribution of Schedule Delay Risk
그림 Fig. 5. Cumulative Distribution of Schedule Delay Days for Different Construction Activities

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저자의 다른 논문 :

표제어: PCR

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