Simulation of Automotive Warranty Data

<p>This thesis will investigate the prediction of the number of claims in a two dimensional automotive warranty claim model for the case of minimal repair.The method involved fitting marginal distributions for age of claim and mileage of claim seperately. Next, various copulas were fitted to establish the correlation between age and mileage, and assessed for fit. The Gumbel copula is chosen as optimal. From this Gumbel copula, a simulation of warranty claims is undertaken. The method produced a good fit for claim age but performed less well for claim mileage, due to the asymmetry of the correlation between mileage and age. Further research directions to improve the accuracy and usefulness of this model are suggested.</p>

Simulation of Automotive Warranty Data

<p>This thesis will investigate the prediction of the number of claims in a two dimensional automotive warranty claim model for the case of minimal repair.The method involved fitting marginal distributions for age of claim and mileage of claim seperately. Next, various copulas were fitted to establish the correlation between age and mileage, and assessed for fit. The Gumbel copula is chosen as optimal. From this Gumbel copula, a simulation of warranty claims is undertaken. The method produced a good fit for claim age but performed less well for claim mileage, due to the asymmetry of the correlation between mileage and age. Further research directions to improve the accuracy and usefulness of this model are suggested.</p>

Field Reliability Estimation of Agricultural Tractors Based on Warranty Data

HighlightsA LightGBM regression model for predicting tractor usage rates was established based on warranty data and considering agricultural tractors’ usage context (region and season) and was then interpreted using SHAP.The field reliability of tractors was estimated based on the usage of failed and unfailed tractors, after unfailed tractors’ usage was imputed using the LightGBM regression model.The proposed methodology was validated by predicting warranty claims using estimated reliability parameters.The proposed methodology was demonstrated using warranty data from a tractor manufacturing company in China.Abstract. Warranty data provide a valuable source of information for assessing the reliability of products in operation (called the field reliability). However, warranty data consist of failure information only. The unavailability of usage data for unfailed products makes it difficult to estimate the reliability of durable products such as agricultural tractors, for which usage is a greater concern than age for reliability analysis. Several studies have proposed methods to address this problem, but they did not include information on the usage context. This study proposes a methodology to estimate the field reliability of agricultural tractors from warranty data considering the tractors’ usage context. First, by taking features representing tractors’ usage context as the input, a usage rate regression model was established using a light gradient boosting machine (LightGBM). The usage of unfailed tractors was then generated. Finally, parametric estimates of the tractors’ reliability were determined based on the usage of failed and unfailed tractors. By interpreting the LightGBM model using SHapley Additive exPlanations (SHAP), it was found that tractors that were used more days in October and April had higher predicted usage rates. To validate the effectiveness of the proposed methodology, the estimated reliability parameters were used to predict the warranty claims of six types of tractors. The results showed that the proposed methodology performed the best in four cases and close to the best in two other cases when compared with two other baseline methods. The proposed methodology was demonstrated using warranty data from an agricultural tractor manufacturing company in China and can be applied to improve understanding of tractor reliability. Keywords: Field reliability, LightGBM, SHAP, Usage context, Warranty data.

Analysis of Defects in Residential Buildings Reported during the Warranty Period

The aim of the article is to present the results of preliminary research of the defects in residential buildings occurring during the warranty period. Due to the small amount of data, the research results cannot be generalized but allow for the formulation of research hypotheses that will be verified in future studies. The data collected included reports of defects in three multifamily residential buildings constructed by the developer in one of the big cities in Poland, which were then examined. For the examination of defects, statistical analysis was used, which revealed that more than half of the reports contained reasonable defects. The results of the preliminary research also indicate that, on the one hand, owners are very active in making warranty claims in the first three months from the date of commissioning, and, on the other hand, with time, the percentage of reasonable defects increases. In terms of the significance of defects, the largest percentage was significant defects. The results showed little activity on the part of property managers in the initial phase of the operation of the buildings, which is the opposite of that of apartment owners. Reports of faults in windows and door joinery, moisture, scratches on walls, and in the area of balconies and terraces are characterized by a relatively low number of cases reported in the first half of the year after the building is commissioned and a gradual increase in the subsequent warranty period. On the other hand, reports related to electrical installation defects are most frequent in the initial period of the warranty, but, with time, their number decreases.

Copula Model Selection for Vehicle Component Failures Based on Warranty Claims

In the automotive industry, it is important to know whether the failure of some car parts may be related to the failure of others. This project studies warranty claims for five engine components obtained from a major car manufacturer with the purpose of modeling the joint distributions of the failure of two parts. The one-dimensional distributions of components are combined to construct a bivariate copula model for the joint distribution that makes it possible to estimate the probabilities of two components failing before a given time. Ultimately, the influence of the failure of one part on the operation of another related part can be described, predicted, and addressed. The performance of several families of one-parameter Archimedean copula models (Clayton, Gumbel–Hougaard, survival copulas) is analyzed, and Bayesian model selection is performed. Both right censoring and conditional approaches are considered with the emphasis on conditioning to the warranty period.

To Improve Internal RFT by Eliminating Wrapper Fouling with Bumper Issue in MF 9500 Models

Right First Time (RFT) is one of the internal business measure to ensure the quality of the product. This project deals with the elimination of wrapper fouling with bumper issue in MF 9500 Models. The wrapper is A class part which is assemble in front of tractors which when getting damage will lead to customer dissatisfaction. The wrapper damage at field results in customer / warranty claims thus increasing the external cost to the company. The wrapper damage issue is due to fouling issue in tractors and that issue is taken up for this study.. Initially PFMEA study conducted for wrapper assembly process. Further based on PFMEA results, a systematic analysis is done through cause and effect diagram to identify the other causes for wrapper damage issue. Since the cause and effect analysis not able to reveal the real root causes. Two models is proposed with modification and performance of the model is studied and compared. It is observed that proposed models are capable of reducing the wrapper damage considerably. It is also noted that modification in the proposed model reduces the operator inspection time and fatigue.

Implementation of Lean in Four-Wheel Drive Front Axle Sub Assy line

This project deals with the Optimizing the process and eliminating the waste in Four Wheel Drive front axle sub assembly line. Four wheel drive sub assembly line consist of 20 different sub-assemblies are available. In which Axle housing sub assy takes more time to complete i.e. around 20.8 min which is more than TAKT time. In this most fatigue operation is Bush pressing which is done by manual hammering. Due to the manual hammering process TAKT time increases and improper bush assy into the axle housing which leads to failure in the front axle function which results in warranty claims thus increasing the external cost to the company. As the existing process is manual, the accuracy of the pressing operation is not to the standards, while pressing the bush, there is no assurance of full placement of the bush in the axle, also the fatigue is more, and there may be chances of lack of skill in the work. The interference tonnage is found to be 3 to 4 tonnes and so the intensifier unit for the appropriate pressure is to be designed initially 100% inspection is done after bush pressing to check correct position of bush assy, internal diameter of the bush using gauges, Further through PFMEA critical process are identified for failure .