scholarly journals A Petri Net-based life cycle cost analysis approach

Author(s):  
Paul Kilsby ◽  
Rasa Remenyte-Prescott ◽  
John Andrews

Railway infrastructure providers, such as Network Rail, who owns and manages the British railway infrastructure, can improve the performance and reduce the life cycle cost of their assets through delivering effective asset management. Having the capability to use computer-based models to predict the future performance and life cycle cost of an asset group is a key enabling mechanism for implementing effective asset management. Decision makers can determine the optimum maintenance strategy and the best allocation of capital expenditure based on evidence from modelling results. This paper shows how probabilistic modelling can be used to evaluate asset management projects of the railway overhead line equipment system and undertake a life cycle cost analysis through the use of a stochastically timed high-level Petri Net. A complete modelling framework has been developed, where the components and their maintenance strategies are selected as inputs, and the Petri Net model is used to calculate outputs associated with the performance and life cycle cost of the overhead line equipment system for the corresponding components and strategies considered. This paper presents the practical use of the developed model and describes how the outputs can be used by asset managers to understand the expected system performance and cost over its life cycle. The range of outputs described are the most detailed for such models studying the overhead line equipment and other engineering systems in literature. Whilst the railway overhead line equipment system is used as an example study, the modelling framework is transferable to asset management projects for other engineering systems.

2010 ◽  
Vol 8 (3) ◽  
pp. 162-178 ◽  
Author(s):  
Anurag Shankar Kshirsagar ◽  
Mohamed A. El‐Gafy ◽  
Tariq Sami Abdelhamid

PurposeThe purpose of this paper is to evaluate the accuracy of life cycle cost analysis (LCCA) for institutional (higher education) buildings as a predictor of actual realised facility costs.Design/methodology/approachResearch methodology includes a comprehensive literature review to identify issues, best practices and implementation of LCCA in the construction industry. A case study was conducted to evaluate the accuracy of LCCA in predicting facility costs.FindingsNotwithstanding the benefits of LCCA, its adoption has been relatively slow for institutional buildings. The case study revealed that the average difference between estimated and actual construction cost is 37 per cent, whereas the average difference between the actual and estimated maintenance cost is 48 per cent. There is an average difference of 85 per cent in the actual and estimated administration cost.Research limitations/implicationsWhile limited to a few buildings, the case study underscores that LCCA methods should not be used for cost predictions of facility performance but rather for comparing total costs of alternative building features and systems, as well as building types. Sensitivity analysis also revealed that the selection of a discount rate would have less impact on recurring costs estimates compared to non‐recurring cost estimates. Facilities managers' involvement in LCCA technique developments and implementations will likely improve its performance during programming phases.Practical implicationsThe value of LCCA procedures is limited as a predictor of actual realised facility costs. Educational institutions can use the methods described in this paper to replicate the study and arrive at their own conclusions regarding the LCCA techniques and their potential use in programming stages.Originality/valueThe paper evaluated the accuracy of LCCA for institutional buildings and the potential of LCCA as an asset management tool for institutional buildings and provided suggestions to improve its adoption in facilities management.


2011 ◽  
Vol 4 (5) ◽  
pp. 158-161 ◽  
Author(s):  
A. Morfonios A. Morfonios ◽  
◽  
D. Kaitelidou D. Kaitelidou ◽  
G. Filntisis G. Filntisis ◽  
G. Baltopoulos G. Baltopoulos ◽  
...  

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