Manufacturers set reliability targets and then design and develop products based on an expected product lifetime (i.e. Useful Life). During the Product Development process, progressive manufacturers conduct extensive reliability testing to minimize the risk that products will fail prematurely. Key factors to consider are the usage environment as well as how customers use the product. Despite these efforts, unexpected failures may occur due to design flaws, manufacturing process changes, excessive variation, or a misunderstanding of the product use environment. Premature failures alienate customers and significantly impair brand and company reputations. It can also increase litigation risks. Field failure data should be tracked and modeled to forecast future failures and identify emerging issues that present financial risks to the organization.
Forecasting of future failures may be used to:
This webinar by industry expert Steven Wachs explains how models developed with life data analysis (e.g. Weibull) may be used to predict how many failures will be expected to occur in the future. The concept of conditional failure probability is key for this purpose. Steven will also review basic life data analysis and will also focus on using the developed model to develop a forecast of future failures, both during the warranty period and beyond.
Many companies struggle to use available field failure data to proactively address risks to their profitability and success. Analyzing field failure data appropriately can help to understand and characterize the reliability of products in the field. The resulting models can then be used to forecast how many units are likely to fail in the future. This is essential for projecting warranty costs and potential failures that may impact customer satisfaction.
During this live webinar Steven will provide specific knowledge required to develop a forecast of future expected failures both within the warranty period and beyond. Although software will be typically used for this task, the underlying concepts and methods are explained in some detail. After attending this webinar, you will be equipped to apply life data analyses to forecast future failures as well as handle common modeling issues such as the presence of non-homogeneous groups in the data.
Who Should Attend
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