Literature review of proportional hazards model - Research Paper Example

The prime factor that makes the modeling of preventive maintenance complicated is the quantification of the preventive maintenance’s effect at different intervals. This research is meant to model the preventive maintenance using the proportional hazard model. Objectives of the research The objectives of this research are: To develop a realistic model of preventive maintenance scheduling To introduce a heuristic approach to implement the proportional hazard model for preventive maintenance scheduling To use the full condition history of the equipment for scheduling the successive interval of preventive maintenance Methodology Appropriate explanatory variables will be used to fit two proportional hazard models, one for the equipment’s life after the corrective work, and the other for the equipment’s life after the preventive maintenance.

The next interval of preventive maintenance will be scheduled using the two models within a simulation framework. Two distinct criteria will be used to estimate the schedules of optimal preventive maintenance, one of which will be a fixed horizon while the other will be the maximization of availability in one interval of preventive maintenance. . Work Plan Time Activity End of August 2012 Approval of research proposal 1 September 2012 to 1 November 2012 Literature review 1 November 2012 to 1 January 2013 Data collection 1 January 2013 to 30 January 2013 Data analysis 1 February 2012 to 15 February 2013 Documentation of results 16 February 2013 to 30 March 2013 Thesis writing and editing 15 April 2013 Thesis submission and defense Literature review of proportional hazard model: The Proportional Hazard Model The proportional hazard model is one of the most widely employed statistical models in the field of engineering and biometrics where it is used for the analysis of survival data.

Measurement error is common to happen in the biometric studies. It is hard to measure the variables of interest without making substantial errors. This imparts the need to make use of surrogates. Plugging in the surrogate yields a naive estimate that can be suspected for bias. Cox was the first to propose the proportional hazard model in the year 1972. The proportional hazard model offers an analysis of the multivariate regression. Impacts of various covariates that affect a system’s TTF are estimated by this model.

The proportional hazard model is used in different kinds of applications in the analysis of lifetime data. It is a very flexible and general model. These properties of the Proportional Hazard Model played a big role in its wide and quick adoption in different fields between the 1970s and the 1990s. These fields included but were not limited to economics, health service and biomedical research (Miller 1). “The proportional hazards model is often used in survival analysis (medical testing) studies.

It is not used much with engineering data” (“Proportional hazards model”). The proportional