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Reliability Engineering Analysis

Reliability engineering is about improving the useful life of a product. In today’s competitive environment with rapid advances in technology, global manufacturing, and complex products… Businesses need to stay focused on finding new ways to: improve quality, time to market and reduce cost…

 

Successful brands are synonymous with high quality and customer satisfaction. Unreliable product have safety and health hazards. Your product quality can be improved by a dedicated reliability program. Competition demands an emphasis on reliability. Reliability programs improve your warranty, service and liability costs. More commercial contracts specify reliability requirements.

 

Product reliability is generally defined as the probability that a product or service adequately performs its intended function for a specified period (usually warranty or design period) under specified conditions.

Join us for this product development case study, you will learn about life data distributions and how to estimate product reliability for two designs at the end of the warranty period. Specifically, you will gain an understanding of ...

- How to prepare life data (censored data)
- Commonly used distributions to model life data
- How to compare the distributions of the two designs.
- How to estimate product reliability at the conclusion of the warranty period.
- How to determine which design has the lowest probability of failure (B1, B10).
- How to determine an appropriate sample size (demonstration test plan).

Who should attend? Anyone interested in analyzing data to assess the performance of a product relative to its warranty period and in reducing the cost of quality.

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Case Study

Situation: A small home appliance company manufactures domestic appliances provides customers with a one-year ‘defect free’ warranty. 

 

Task: As a data driven research and development manager you need to demonstrate the new product design meets reliability requirements.

 

Action: Use reliability engineering analysis to demonstrate the new design meets the product reliability of greater than 90% at one year.

 

Results: Demonstrate using statistical methods the new design is significantly better than the old design and meets product reliability target.

 

Next Steps: Implement the new validated design change and monitor warranty returns over the next twelve months. Use the cost of poor quality savings for further research and development.

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