Loss Function Analysis with R
- Emilio L. CanoAffiliated withDepartment of Statistics and Operations Research, Rey Juan Carlos University
- , Javier M. MoguerzaAffiliated withDepartment of Statistics and Operations Research, Rey Juan Carlos University
- , Andrés RedchukAffiliated withDepartment of Statistics and Operations Research, Rey Juan Carlos University
Most features defining a product are not usually important to the customer. Only a few of them are critical to quality, in particular, those defining what the customer expects. To meet these expectations, the processes involved in the development of the final product should be correct. This is the Six Sigma way: high-quality processes lead automatically to high-quality products. This is related to the concept of cost of quality, which is the cost of having a low-quality product (from the customer’s perspective). Some managers still think that this concept is equivalent to total quality cost, which corresponds to the amount of money expended in implementing quality methodologies and improving processes. To avoid misunderstandings, we will refer to the cost of quality as the cost of poor quality. The cost of poor quality will result in a quantifiable loss for the organization and for society in general. This loss can be modeled by a function. In Six Sigma, this function is based on the variability of the process. In this chapter, we will analyze the quality loss function introduced by Taguchi and explain how to use it to calculate the average loss of a process.
- Loss Function Analysis with R
- Book Title
- Six Sigma with R
- Book Subtitle
- Statistical Engineering for Process Improvement
- pp 63-75
- Print ISBN
- Online ISBN
- Series Title
- Use R!
- Series Volume
- Springer New York
- Copyright Holder
- Springer Science+Business Media New York
- Additional Links
- Industry Sectors
- eBook Packages
To view the rest of this content please follow the download PDF link above.