Browse Publications Technical Papers 2008-36-0192

How to use Weibull as tool for a decision making on field issues 2008-36-0192

Reliability, maintainability/serviceability and security are three qualities of product excellence desired by customers and users of products, however customer expectation for product reliability are continually increasing for almost all product and despite of most of the companies has worked on the philosophy of continuous improvement to meet or exceed the customer's expectations, its difficult to avoid failures or its difficult to ensure zero defect.
Once it happens, it generate a customer complaint which is registered by companies. The way that companies used to register the complaints is through their warranty system and also a special database. Most of the companies maintain warranty databases for purposes of financial reporting and warranty expense forecasting. In some cases, there are attempts to extract engineering information from such databases. Another application is to use warranty data to detect potentially serious field reliability problems as early as possible. When a serious problem arises, the existence of the problem will eventually be obvious. Early detection of serious problem through the use of Weibull statistical method, allowing early action to mitigate potential reliability problems, could save large amounts of money and product goodwill.
With the rapid growth of emerging markets such as China and India, it's hard to say but suppliers are forced to improve their capacity in terms of production in order to attend the market growth, but it also bring a reduction on the level of quality of the products. Once a severe failure happens its necessary for the automaker to have the ability to analyze such failure and decide on how to attend the customers, which population of vehicles is involved on the failure and what is the magnitude of the field issue. This article describe a systematic method on how to analyze field data applying Weibull statistical method and how to make a decision based on a set of field data.


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