回帰モデルを用いた建設機械の稼働率とコスト分析による事故リスク評価
Minwoo Song1, Jaewook Jeong1, Jaehyun Lee2
1Department of Safety Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.
Risk analysis : an official publication of the Society for Risk Analysis
|December 23, 2025
まとめ
本研究では、コストと稼働率のデータを用いて建設機械の事故を予測する回帰モデルを開発しました。このモデルは、掘削機が最も高い死亡リスクをもたらすことを特定し、安全管理に役立ちます。
科学分野:
- 建設管理
- 労働安全衛生
- リスク分析
背景:
- 建設機械は不可欠ですが、重大な事故リスクをもたらします。
- 技術の進歩は機器の需要を高め、新たな安全上の課題をもたらします。
- 事故の可能性の定量的な分析は、効果的な安全管理のために不可欠です。
研究 の 目的:
- 建設機械の定量的な事故予測モデルを開発すること。
- 稼働率、下請け業者タイプ、コストが事故の可能性に及ぼす影響を分析すること。
- 安全管理と投資決定の強化のためのツールを提供すること。
主な方法:
- 建設機械の使用状況のデータ収集と分類。
- 時間あたり稼働コスト(HOC)と全体的な建設コストの計算。
- 回帰分析のためのデータ拡張技術(多変量正規分布およびポアソン分布)の適用。
主要な成果:
- 回帰分析の結果、ほとんどの機器タイプで高いR-squared値(>0.6)が得られました。
- ダンプトラックは歴史的に最も高い死亡頻度を示しました。
- 予測モデルは、掘削機が最も高い予測死亡数を持つことを示しました。
結論:
- 提案されたモデルは、稼働コストと建設コストに基づいてリスクグループを効果的に分類します。
- このモデルは、安全管理における現場適用に実用的なフレームワークを提供します。
- この研究は、建設機械の安全規制と投資戦略の開発を支援します。
関連する概念動画
Hazard Rate
376
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
376
Multiple Regression
3.7K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.7K
Mechanistic Models: Compartment Models in Individual and Population Analysis
225
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
225
Determination of Expected Frequency
2.5K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.5K
Regression Analysis
7.8K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
7.8K
Introduction To Survival Analysis
710
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
710


