An Integrated Approach for Failure Analysis of Natural Gas Transmission Pipeline

The main aim of this study is to identify the most important natural gas pipeline failure causes and interrelation analysis. In this research, the rough analytic hierarchy process (Rough-AHP) is used to identify the natural gas pipeline failure causes rank order. Then a combination of rough decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) method is applied to generate the level of importance. The comparison of traditional DEMATEL and Rough-DEMATEL are also performed to establish the cause-effect interrelation diagram. Finally, the Bayesian Belief Network (BBN) is combined with Rough DEMATEL and ISM to identify the interrelation analysis among the most crucial failure causes. As a result, the energy supply company and government policymaker can take necessary safety plan and improve the operation. The main outcome of this study is to improve the security management and reduce the potential failure risks.

[1]  Sushil.  Incorporating polarity of relationships in ISM and TISM for theory building in information and organization management , 2018, Int. J. Inf. Manag..

[2]  Virgilio Cruz-Machado,et al.  Using interpretive structural modelling to identify and rank performance measures: An application in the automotive supply chain , 2013 .

[3]  Xin Guo Ming,et al.  A rough TOPSIS Approach for Failure Mode and Effects Analysis in Uncertain Environments , 2014, Qual. Reliab. Eng. Int..

[4]  Slavko Vesković,et al.  A rough multicriteria approach for evaluation of the supplier criteria in automotive industry , 2018 .

[5]  Rong-xing Duan,et al.  A New Fault Diagnosis Method Based on Fault Tree and Bayesian Networks , 2012 .

[6]  Yang Jian,et al.  Calculation of accident probability of gas pipeline based on evolutionary tree and moment multiplication , 2019 .

[7]  S. Vinodh,et al.  Application of interpretive structural modelling for analysing the factors influencing integrated lean sustainable system , 2016, Clean Technologies and Environmental Policy.

[8]  Valerio Cozzani,et al.  Security vulnerability assessment of gas pipelines using Discrete-time Bayesian network , 2017 .

[9]  John N. Warfield,et al.  Developing Interconnection Matrices in Structural Modeling , 1974, IEEE Trans. Syst. Man Cybern..

[10]  Galina Ilieva,et al.  Group Decision Analysis with Interval Type-2 Fuzzy Numbers , 2017, Cybernetics and Information Technologies.

[12]  Jiang Xu,et al.  Analysis on accident-causing factors of urban buried gas pipeline network by combining DEMATEL, ISM and BN methods , 2019, Journal of Loss Prevention in the Process Industries.

[13]  Kang Liu,et al.  Risk Analysis on Leakage Failure of Natural Gas Pipelines by Fuzzy Bayesian Network with a Bow-Tie Model , 2017, Sci. Program..

[14]  Hong Zhang,et al.  Study on Failure of Third-Party Damage for Urban Gas Pipeline Based on Fuzzy Comprehensive Evaluation , 2016, PloS one.

[15]  Chih-Hung Wu,et al.  Fuzzy DEMATEL method for developing supplier selection criteria , 2011, Expert Syst. Appl..

[16]  Li Pheng Khoo,et al.  A rough set enhanced fuzzy approach to quality function deployment , 2008 .

[17]  John N. Warfield,et al.  Implication Structures for System Interconnection Matrices , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[18]  Maciej Witek.  Gas transmission pipeline failure probability estimation and defect repairs activities based on in-line inspection data , 2016 .

[19]  Hsin-Hung Wu,et al.  A case study of using DEMATEL method to identify critical factors in green supply chain management , 2015, Appl. Math. Comput..

[20]  Yongchun Miao,et al.  Selection of key indicators for reputation loss in oil and gas pipeline failure event , 2019, Engineering Failure Analysis.

[21]  Yan Zhang,et al.  Integration of interpretive structural modelling with Bayesian network for biodiesel performance analysis , 2017 .

[22]  Chia-Li Lin,et al.  Utilisation of interpretive structural modelling method in the analysis of interrelationship of vendor performance factors , 2011 .

[23]  Jon Tømmerås Selvik,et al.  Addressing human error when collecting failure cause information in the oil and gas industry: A review of ISO 14224: 2016 , 2020, Reliab. Eng. Syst. Saf..

[24]  Solomon Tesfamariam,et al.  Consequence-based framework for buried infrastructure systems: A Bayesian belief network model , 2018, Reliab. Eng. Syst. Saf..

[25]  Seth D. Guikema,et al.  Bayesian Belief Networks for predicting drinking water distribution system pipe breaks , 2014, Reliab. Eng. Syst. Saf..

[26]  Xia Wang,et al.  Improved AHP–TOPSIS model for the comprehensive risk evaluation of oil and gas pipelines , 2019, Petroleum Science.

[27]  S. G. Deshmukh,et al.  Development of a balanced scorecard , 2006 .

[28]  Dinesh Kumar,et al.  Evaluating factors in implementation of successful green supply chain management using DEMATEL: A case study ☆ , 2015 .

[29]  Jing Gong,et al.  Gas supply reliability assessment of natural gas transmission pipeline systems , 2018, Energy.

[30]  Prakash P. Shenoy,et al.  A causal mapping approach to constructing Bayesian networks , 2004, Decis. Support Syst..

[31]  Kerrie Mengersen,et al.  Utility of Bayesian networks in QMRA-based evaluation of risk reduction options for recycled water. , 2016, The Science of the total environment.

[32]  Gintautas Dundulis,et al.  Integrated failure probability estimation based on structural integrity analysis and failure data: Natural gas pipeline case , 2016, Reliab. Eng. Syst. Saf..

[33]  Jin Qi,et al.  An integrated AHP and VIKOR for design concept evaluation based on rough number , 2015, Adv. Eng. Informatics.

[34]  P. E. Komers,et al.  Canada’s federal database is inadequate for the assessment of environmental consequences of oil and gas pipeline failures , 2017 .

[35]  Li Pheng Khoo,et al.  A prototype genetic algorithm-enhanced rough set-based rule induction system , 2001, Comput. Ind..

[36]  S. Garg,et al.  Interpretive structural modelling of enablers for improving the performance of automobile service centre , 2010 .

[37]  Wenyan Song,et al.  A rough DEMATEL-based approach for evaluating interaction between requirements of product-service system , 2017, Comput. Ind. Eng..

[38]  Ting Wang,et al.  Analysis and Comparison of Long-Distance Pipeline Failures , 2017, Adv. Artif. Neural Syst..

[39]  Türkay Dereli,et al.  A novel approach based on DEMATEL method and patent citation analysis for prioritizing a portfolio of investment projects , 2015, Expert Syst. Appl..

[40]  Wenyan Song,et al.  An integrated rough number-based approach to design concept evaluation under subjective environments , 2013 .