Operational risk analysis for the management of railway infrastructure maintenance
- Authors: Dhlamini, Phumzile
- Date: 2012-06-04
- Subjects: Railroad engineering , Railroads - Management , Risk management , Railroads - Maintenance and repair
- Type: Mini-Dissertation
- Identifier: uj:2307 , http://hdl.handle.net/10210/4766
- Description: M. Ing. , This dissertation proposes a methodology for the analysis of the operational risks that are caused by railway infrastructure component failure. The objective of this methodology is to assist the engineers that manage railway infrastructure maintenance to forecast the following: • the frequency of operational risk events that are caused by railway infrastructure failure; • the cost of rehabilitating railway infrastructure after an operational risk event that was caused by railway infrastructure failure; and • the impact that railway infrastructure maintenance strategies have on the frequency and cost of operational risk events that are caused by railway infrastructure failure. A brief literature study of operational risk analysis is presented. The proposed operational risk analysis methodology involves the identification of the operational risks that are caused by railway infrastructure failure and causal modelling using Bayesian network causal models. The proposed operational risk methodology is applied in a case study concerning a railway company (called African Railways Ltd as a pseudonym for the sake of confidentiality). The train derailments that are caused by infrastructure component failure in a particular region are analysed in the case study. The case study presents historical data and the results of a questionnaire that was used during face-to-face individual interviews with three track maintenance experts. The frequency of train derailments, the cost of rehabilitating railway infrastructure after train derailments and the impact of railway infrastructure maintenance on these two issues are forecasted. The case study concludes with a comparison of the forecasted and actual frequency of train derailments and cost of rehabilitating the railway infrastructure after a train derailment.
- Full Text:
- Authors: Dhlamini, Phumzile
- Date: 2012-06-04
- Subjects: Railroad engineering , Railroads - Management , Risk management , Railroads - Maintenance and repair
- Type: Mini-Dissertation
- Identifier: uj:2307 , http://hdl.handle.net/10210/4766
- Description: M. Ing. , This dissertation proposes a methodology for the analysis of the operational risks that are caused by railway infrastructure component failure. The objective of this methodology is to assist the engineers that manage railway infrastructure maintenance to forecast the following: • the frequency of operational risk events that are caused by railway infrastructure failure; • the cost of rehabilitating railway infrastructure after an operational risk event that was caused by railway infrastructure failure; and • the impact that railway infrastructure maintenance strategies have on the frequency and cost of operational risk events that are caused by railway infrastructure failure. A brief literature study of operational risk analysis is presented. The proposed operational risk analysis methodology involves the identification of the operational risks that are caused by railway infrastructure failure and causal modelling using Bayesian network causal models. The proposed operational risk methodology is applied in a case study concerning a railway company (called African Railways Ltd as a pseudonym for the sake of confidentiality). The train derailments that are caused by infrastructure component failure in a particular region are analysed in the case study. The case study presents historical data and the results of a questionnaire that was used during face-to-face individual interviews with three track maintenance experts. The frequency of train derailments, the cost of rehabilitating railway infrastructure after train derailments and the impact of railway infrastructure maintenance on these two issues are forecasted. The case study concludes with a comparison of the forecasted and actual frequency of train derailments and cost of rehabilitating the railway infrastructure after a train derailment.
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Schedule risk analysis of railway projects using monte-carlo simulation
- Authors: Mabeba, Motlatso
- Date: 2018
- Subjects: Risk management , Railroads - Management , Monte Carlo method
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/286098 , uj:30951
- Description: M.Ing. (Engineering Management) , Abstract: Railways have been used throughout history for the transportation of goods. Even though the inception of rail improved civilization, due to its inefficiencies, road transport is dominating the freight and logistics industry. Company A, which has the largest market share in rail has embarked on projects in an attempt to improve rail efficiencies by moving more volumes of freight timeously. Most of the projects of Company A have failed largely due to the poor planning of the projects in the feasibility stages. Most of the planning schedules are overoptimistic and thus unreliable. The scope of this study is to investigate the way in which planning schedules of Company A are developed by undertaking a schedule risk analysis and using Monte Carlo simulation to validate the schedule. If projects of Company A can be planned better, using schedule risk analysis, projects can become more successful in terms of delivering projects on time and then execute the projects on time.
- Full Text:
- Authors: Mabeba, Motlatso
- Date: 2018
- Subjects: Risk management , Railroads - Management , Monte Carlo method
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/286098 , uj:30951
- Description: M.Ing. (Engineering Management) , Abstract: Railways have been used throughout history for the transportation of goods. Even though the inception of rail improved civilization, due to its inefficiencies, road transport is dominating the freight and logistics industry. Company A, which has the largest market share in rail has embarked on projects in an attempt to improve rail efficiencies by moving more volumes of freight timeously. Most of the projects of Company A have failed largely due to the poor planning of the projects in the feasibility stages. Most of the planning schedules are overoptimistic and thus unreliable. The scope of this study is to investigate the way in which planning schedules of Company A are developed by undertaking a schedule risk analysis and using Monte Carlo simulation to validate the schedule. If projects of Company A can be planned better, using schedule risk analysis, projects can become more successful in terms of delivering projects on time and then execute the projects on time.
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