Increasing costs, strained financial budgets and customer satisfaction targets all force hard decisions which require painstaking research and deliberation. Whether it is the acquisition of rolling stock, the choice between two separate proposals or even the likelihood of weather-disrupted service, forward thinking has been proven to save money.
The use of computer software designed to model the varying effects and implications of such decisions is rapidly increasing in popularity as a result. The ability to project or predict the likelihood of specific events, such as the number of disrupted services in February or the chance of delays during a certain stage of redevelopment, can allow amendments to be made before costly mistakes occur.
Palisade produces software that, when combined with Microsoft Excel or Project, can aid the user in assessing specific results depending on the model used. Railway-Technology speaks to Palisade managing director Craig Ferri to find out how the software can benefit decision-makers within the railway industry.
Railway Technology: How does the modelling software work?
Craig Ferri: The software itself is essentially an add-in into either Microsoft Excel or Project that allows the user to take a particular model or project and identify probabilities relating to any task of the project within the model.
It works on the basis of a Monte Carlo simulator and runs the simulation thousands of times, compiling a range of data and allowing the user to make an informed decision based on the results. The simulation doesn’t just include static numbers, so this produces a wide range of data that can be used to make an informed decision.
RT: Are there any particular railways that have successfully used the software?
CF: Well, the three main rail entities within the UK are National Rail, Cross Rail and London Underground Projects. They have used the software for a variety of tasks including cost estimation and project schedule risk. This has allowed them to highlight particular pitfalls in an upgrade schedule and amend them to ensure reliability on the service.
Outside of the UK, in France both RFF and SNCF have used the software to analyse risks for projects. In Spain, the Barcelona Metro has utilised the software in order to determine the viability of the opening and closure of particular lines, such as when it would be beneficial to close certain lines for maintenance and when to keep others open.
Alternatively, in Lisbon the software has been used to model cost estimations of improvements and maintenance, as well as aiding the identification of the optimal time to carry out such maintenance work.
RT: What specific mitigating factors are taken into account when predicting viability?
CF: The reason for the success of the software, as well as the fact that it is an add-in for Microsoft programs and can be used for any industry, is its versatility in being able to run any model. It can use analytical tools to highlight factors or crucial tasks that can then be amended.
For instance, if there’s a project that relies on a number of tasks to be completed, and you have a set amount of time to complete the project, the software can model that project thousands of times to identify the key tasks of the project that could cause delays and allow the user to go back and make necessary amendments.
RT: And to what degree of accuracy is the software capable?
CF: It’s difficult to say really, as there’s no ISO standard and in essence the software is only as accurate as Excel is or the particular model that the user has built. This is a key reason as to why we offer the training and consultancy that we do with the software.
RT: How extensive is the training and how long does it take, on average, to become familiar with the software?
CF: It does entirely depend on how familiar or comfortable the user is with Excel, to be honest. We offer training courses that are two to three days, and by that time users should be able to build their own model and easily navigate and understand the software.
To understand some of the more advanced options or modules, it may pay to have an understanding of statistics or mathematics, and the kinds of people that we usually cater for are engineers who are comfortable with mathematics.
RT: Could the software be used to determine contingency plans? For instance, the UK has suffered from poor spells of weather that have seriously infringed on the service offered to customers, could this be used to predict the affect of bad weather and prepare for it?
CF: You could, for instance, build a model in excel and collate data representing the poor weather over a period of ten years, including the number of days that the service was affected. The simulation would then run and compose a percentage likelihood of the chance of disrupted service on specific days relating to the weather.
The result would be something along the lines of "there’s x% chance of disruption on five days in February" and rail companies could compose a contingency plan on that result.