Warranty Claim Quantity Forecasting via Multiple Linear Regressions

Abstract

A concrete justification unavailability of the roughly estimated warranty claim quantity is leading to also inability to understand defect trend behavior and its effect upcoming warranty claim quantity. This is where an equation model is derived by considering the previous actual warranty data, to represent warranty claim defect quantity impact. Taking into consideration, identified parameters which link with pricing and cost, it also includes the observation and monitoring of warranty trend from the existing actual warranty data, by plotting cumulative defect quantity over Vehicle Line-off Date, as well as plotting cumulative defect quantity over Vehicle Submission Date. Multiple Linear Regression is deployed to define the best Multiple Regression Equation. Predictors, response and predictors’ validations defined by using normality and probability test. The successfully developed equation model, takes into account the existing warranty data and trend, As a result, the equation model managed to provide forecasted warranty claim quantity, based on a complete 36-month warranty period cycle, which has a significant impact on a reliable and convincing figure – a key factor in warranty budgeting and accrual task.