JULIO, Carolina Victória de Jesus Campos de Azevedo; http://lattes.cnpq.br/4882440424155650
Resumo:
This paper presents the conduct of a product reliability assessment, using warranty drive data
as a basis for analyzing failures in the field. Reliability is the probability that a product will
operate fault-free for a specific period of time. Considering that brand image and product
credibility are linked to customers' perception of quality, understanding product reliability
becomes crucial to remaining competitive in the market. Many manufacturers, occasionally
limited by resources, launch products without understanding their reliability, resulting in high
repair costs due to warranty returns. In this context, warranty drive data can provide a
valuable and low-cost opportunity to understand the reliability of products on the market and
apply the concept of continuous improvement, as it offers a realistic view of product operation
and failures in the field. The research focuses on assessing the reliability of hydraulic
centrifugal pumps, manufactured by a leisure equipment industry with more than 50 years on
the market. The aim was to statistically verify product reliability, which has never been
assessed before, using field failure data collected by the Customer Service Department (SAC)
through warranty claims, thus demonstrating a free and timely method, especially for
manufacturers who have products in this context. The Statistical Theory of Reliability was
applied, performing a probabilistic modeling of the data up to the first failure, considering a
single failure mode (due to limitations of the data used). Fitting them to the Weibull
distribution model, using Maximum Likelihood estimation and the Anderson-Darling fit
quality test, the aid and demonstration of the use of computational resources with MINITAB®
software (closed source) was carried out. The same analysis was also demonstrated using
RStudio software (open source) in order to present an accessible resource. Due to the
difficulties in adjusting the field failure data derived from the warranty activation (which is of
an uncertain and censored nature), the results of the parametric Weibull model were compared
with the results obtained by the non-parametric Kaplan-Meier model, generated with the same
software. Tools such as Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis
(FTA) were also used to analyze failure causes and effects, complementing the assessment
and highlighting possible opportunities for organizing failure data by failure mode. The
results obtained using the method showed reliability values of approximately 40% halfway
through the warranty period; this result does not seem to accurately represent the reality of the
product being assessed and may have been influenced by the uncertain and censored nature of
the data derived from the warranty claim, and by the inaccuracies observed in the data
supplied by the manufacturer. These results suggest that, in order to take advantage of the
benefits of applying the method, it is important to consider the uncertainty and censorship
characteristics of the field failure data obtained from the warranty activation records and
minimize them in order to obtain more accurate and coherent results. In this context, studies
to improve the method are suggested and encouraged, in view of its solid benefits
(representing failures in a real scenario, without controlled operating variables, at zero cost)
and social impact, which mainly help small and medium-sized
companies/industries/manufacturers to implement a reliability-oriented culture.