Question

Methods and possible ways of getting data that can be used to Quantify rail network and model its impact.

Answer 1

Methods and possible ways of getting data that can be used to Quantify rail network and model its impact.

Quantification of a system requires a mathematical modelling of the system in terms of the underlying driving factors. When constant reliability values are used, a snapshot of system reliability is given at a specific time, and when time-dependent reliability expressions are used, the system reliability can be observed over a period of time.

Systems can be classified as non-repairable or repairable. A non-repairable system is discarded after its first failure and modelled using the renewal theory. With the renewal theory, the system is replaced after a failure and the condition is restored to the good-as- new condition, and failures are independent and identically distributed (i.i.d.). The renewal theory is not only limited to non-repairable systems, and even if a system can be physically repaired (defined as a repairable system).

         METHODOLOGY FOR QUANTIFICATION

In the literature review, the importance of measuring and managing reliability is discussed, and different methods are discussed to calculate reliability. The methodology followed to calculate the reliability of a system is presented in this section.. It consists of three steps, starting with the creation of the model, and ending with the interpretation of the results. Each step is discussed in more detail below.

Step 1: Identification of systems and creating RBDs

The first step is to analyse the system, simplify the system, and identify the important sub-systems. It is important that the contribution of sub-systems to reliability, their interaction with other sub- systems, and their redundancy be understood. The optimal assignment of components for every sub-system is also important, and the sub-systems must be balanced.

Step 2: Collecting and processing data

Once the sub- systems and components are identified, the best source of failure data must be identified, the data extracted, and analysis techniques used to determine relationships within the data sets (data mining). Techniques such as the Laplace trend test are used to search for trends in data sets, and failure distributions are then fitted to the data accordingly. Various software packages are available that can process data easily, but Microsoft® Excel was preferred for all the data processing.

Step 3: System analysis and results

Once the interactions of sub-systems are known, RBDs are created and failure distributions are determined for the components. The system can then be analysed. Again Microsoft® Excel was used to simulate the performance of the system over a period of time, and the contribution of components and sub-systems to system reliability could be identified.