This Week's Article
21 Common Problems And What To Do About Them
Six sigma deployments do not always run smoothly, this is a list of 21 frequently encountered situations compiled by Forrest Breyfogle III, CEO and founder of Smarter Solution
Latest Six Sigma Tutorial
A Zest of Non Parametric Testing -The Chi Square Test
In our
hypotheses testing examples, we used means and variances to determine if there were statistically significant differences between samples. What happens if the data we want to compare cannot be reduced to means and variances? What if the data are nominal or ordinal?
Suppose that a molding machine has historically produced metal bars with varying strength (measured in PSI) and the strengths of the bars are categorized in the following table. The ideal strength is 1998 PSI.

Building a Multiple Regression Model Using Minitab and Excel
In the
Simple Linear Regression model that we built to determine the effect of the variation of the price of gas on the quantities sold, we only used one independent variable, the price per gallon. In the case of our example, the variations of the quantities sold could have been explained by other factors such as new people moving in or out of the city, the building of a new freeway, the building of a new factory...etc. All these independent variables can have a significant impact on the variation of y and need to be taken into account for a more accurate regression model.

Analysis Of Variance (ANOVA) in short plain English!
The purpose of this article is to present the Analysis Of Variance under less confusing auspices, in plain English.
It is obvious that since most computers are equipped with some form of spreadsheet, specially Excel, using the embedded Data Analysis tool would make it painless to obtain the information we are seeking. But since the Statistics software tools do not provide any interpretation of the results, nor do they explain the process that leads to the results, understanding the step by step process of ANOVA becomes paramount.


 

Quality Articles
Design Of Experiments (DOE) - How to optimize your process at the lowest possible cost (in short sleeved English!)
Whether changes are being made to an existing process (product or system), or a new process (system or product) is being designed, it is always desirable to know the effects of the factors used in the process and the effects of the interactions between those factors on the expected outcome. In other words, a process engineer can optimize his processes if he can quantify the impact of each factor involved in those processes and the effects of the interactions between the factors. 
Is Your Production Process Meeting Your Customers' Expectations?
Statistical Process Control (SPC) enables the producer to determine if his production process is stable and if it is in control, in other words if the process is yielding products that are consistent and in a manner that makes it possible for the producer to be able to make predictions on future trends. What the SPC does not tell the producer is whether the products generated by the process meet the customers’ expectations.
To determine if the production process is yielding good quality products in a consistent and predictable manner, it is necessary to combine the products' engineered specifications with the control charts to generate capability indices.
  How can Six Sigma drive better management reports.
In many companies, performance reporting processes encourage managers to react every time a metric falls outside the desired range. But looking for a reason behind every fluctuation in the results wastes resources and can camouflage the organization’s true problems.
 
 
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