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Continuous Improvement activities are often based on a list of top concerns, such as highest RPN (Risk Priority Number) on the PFMEA (Process Failure Modes and Effects Analysis), warranty items, or scrap rates. But a company is in business to make a profit for its stockholders. Therefore, money should be considered, rather than just technical engineering tools and RPNs. Current PFMEA methodology (See references 1 and 2) focuses on delivering quality parts to the customer. The financial impact of various potential process problems is not considered directly. A new and extended technique called FMERA (pronounced Fuh-MAIR-uh) can identify and prioritize the process part of potential problems that have the most financial impact on an operation. Alternatives can be evaluated to maximize the financial benefits. FMERA is a method for getting the voice of the stockholder into process decisions.

Least-squares rank regression is often used for curve fitting Weibull or Normal failure data. Most software packages calculate the correlation coefficient, r, or the coefficient of determination, r2. Monte Carlo simulation was used to create and analyze several thousand data sets. By comparing r from a given sample to results obtained from Monte Carlo simulation, the goodness of fit of the sample can be determined.

A bathtub equation can be used to model data that exhibits infant mortality, chance failures, and wear out. This technique allows for the simultaneous solution of equation parameters affecting the product’s life. The bathtub equation treats a portion of the population as a competing risk mixture. This allows total failure of the infant mortality population without causing complete failure of the entire population. Chance and wear out failures are included by using a compound competing risk mixture.