Risk Assessment of Additional Works in Railway Construction Investments Using the Bayes Network

Abstract

The implementation of railway infrastructure construction projects including sustainable development goals is a complex process characterized by a significant extension of individual investment stages. The need for additional works has a big impact on construction railway projects, representing a risk which is the result of many different factors. During the execution of works, both the design assumptions and the conditions of the project’s implementation can be changed. An attempt to eliminate potential risks is a key element of construction projects. The article proposes a proprietary management method for the risk of additional works in railway projects. A methodology for creating risk management strategies using a standard algorithm that includes risk identification, risk analysis, and risk assessment is presented. The original elements of the work include risk identification followed by analysis using Bayesian networks. Using the example of a scenario of events, it is shown that a well-programmed network can be used to implement risk mitigation methods. Using the network, it is possible to compare different ways to reduce risk, check the effect of reducing the risk factors, and determine a satisfactory level of effects, e.g., increased financial resources as a result of additional works.

Construction Safety Risk Assessment for Existing Building Renovation Project Based on Entropy-Unascertained Measure Theory

“…In 1975, Nuclear Regulatory Commission (NRC) developed and established the famous probabilistic risk assessment method, which became a milestone in the history of engineering risk analysis. Misra et al proposed a fuzzy fault tree analysis method, which was applied in safety risk assessment [16]; Dunyak et al established a reliable fuzzy model by introducing the expansion theory, which can effectively deal with the fuzziness of the risk of each bottom event in the fault tree [17]; Roberts proposed the integrated quantitative risk management theory and established the decision support theory after risk analysis, arranging and screening [18]; Fung et al created a risk assessment model, which can help identify and predict the risk levels [19]; Leu et al built a safety risk assessment model based on improved Bayesian network (BN) of fault tree (FT) [20]; Gamble et al established the fuzzy and grey correlation analysis model and evaluated duration risk, cost risk, quality risk and safety risk separately [21]; Aminbakhsh et al presented a safety risk assessment framework, which can give priority to the security risk of the project before making a reasonable budget [22]; Tian proposed a grey hierarchy evaluation model, which can assign the importance priority sequence of safety management measures [23]; Zhao et al proposed a a hybrid risk evaluation model based on the cloud model and fuzzy comprehensive evaluation method [24]; Esmaeili et al presented an attribute-based risk identification and analysis method [25,26]; Ning et al established a safety risk assessment model to carry out site layout and safety management [27]; Huang et al proposed an improved AHP-Grey model of construction safety evaluation, this model can better reflect the actual safety situation of construction [28]; Gebrehiwet et al proposed an integrated model of the technique for order preference by similarity to an ideal solution (TOPSIS) and fuzzy comprehensive evaluation (FCE) [29]; Leśniak et al presented a method for creating risk management strategies using a standard algorithm that includes risk identification, risk analysis, and risk assessment [30]; Dong et al proposed the Pb-Zn mine safety risk evaluation model based on the fuzzy-grey correlation analysis method [31].…”

Application of the Bayesian Networks in Construction Engineering

“…One of the methods using BN to research in the field of engineering of construction projects is the proprietary method of managing the risk of additional works in railway projects, presented in [16]. The Netica program was used to build the model [11], however the HUGIN program was used in the present work [10].…”

“…The influence of new technologies is visible in contemporary works, including the implementation of BIM standards in the construction investment process [27], or the use of information from the "Big Data" [6]. The authors of many papers describe the implementation of the results of their research to the construction industry [9,18,19,24], cost of construction works [13,17,21,25], risk in construction [15,16,23]. One example combining the practical aspect and high research potential are the Bayesian Networks.…”

Probabilistic and Fuzzy Approaches for Estimating the Life Cycle Costs of Buildings under Conditions of Exposure to Risk

“…Many researchers [27][28][29][30][31][32][33][34][35][36][37] and ISO standard [11] state that in some publications the terms risk and uncertainty are treated identically or interchangeably, which is a mistake. According to Knight [28] and ISO standard [11], risk is related to the so-called measurable uncertainty.…”