Six Sigma DMAIC – Analyze Phase

1. Six Sigma DMAIC – Analyze Phase This is where the statistical study of a problem starts. In this phase statistical reviews are done to the groups of deviation or variation in order for project owners to identify which are the considerable contributors to the output. The focal point of this phase is to identify and analyze the root cause/s of imperfection. This phase consists of several steps which also require several tools. The phase usually starts by organizing the experimentation schedule to identify which of the potential KPIV’s (key performance indicator variables) is the real origin of defects. Sufficient amount of data is also required. This set of data will be analyzed using an appropriate statistical procedure. www.msystraining.com

2. Analyze Phase - Ishikawa Graph.  The most common tool used in this phase is the fishbone diagram also called the Ishikawa graph. This is a graphical demonstration of possible problem causes. The chart will show the association of cause and effect. The advantage of using this tool is that it stimulates the reasoning during brainstorming activity of possible causes. It gives visual presentation of possible causes. The possible causes are grouped, therefore reducing the chances of omitting some possible causes. And since the causes are charted, project owners will see and understand the relationship between possible causes. Constructing a fishbone diagram is not that easy. Since this is done during a brainstorming activity, conflict of ideas and opinions are always expected. The good thing is that the outcome is always reliable and sound.  www.msystraining.com

3. Box Plot or the whiskers plot • Another tool used in analyze phase is the box plot or the whiskers plot. This is fitting to use if the data sets are as few as ten – twelve values. However, this is not suitable if sample size is less than ten. This gives a graphical review of a data set showing the measure of middle location, two measures of spreading, the skewness, and the outliers. Outliers are known as the values that don’t seem to be part of the standard data. The box displays three values: the median (Q2), the lower quartile (Q1), and the upper quartile (Q3). Extending from the box are lines also known as the whiskers which lengthens to the maximum and minimum value. • To create a box plot, several values must be computed. These are: • Quartile One (Q1) – is the average of the lowest twenty-five percent of the data set • Quartile Three (Q3) – is the average of the highest twenty-five percent of the data set • Maximum (Max) – is the biggest value amongst all data set • Mean – is the standard value • Median – is the center value of a data set • Minimum (Min) – is the least value amongst all data set • Inter Quartile Range (IQR) – using the formula Q3-Q1, this is the middle fifty or the mid spread • Outlier Low – using the formula Quartile One – 1.5 * Inter Quartile Range or higher than • Outlier High – using the formula Quartile Three + 1.5 * Inter Quartile Range www.msystraining.com

4. Creating a Box Plot • To create a box plot, several values must be computed. These are: • Quartile One (Q1) – is the average of the lowest twenty-five percent of the data set • Quartile Three (Q3) – is the average of the highest twenty-five percent of the data set • Maximum (Max) – is the biggest value amongst all data set • Mean – is the standard value • Median – is the center value of a data set • Minimum (Min) – is the least value amongst all data set • Inter Quartile Range (IQR) – using the formula Q3-Q1, this is the middle fifty or the mid spread • Outlier Low – using the formula Quartile One – 1.5 * Inter Quartile Range or higher than • Outlier High – using the formula Quartile Three + 1.5 * Inter Quartile Range • Six Sigma has two key methodologies − • DMAIC − It refers to a data-driven quality strategy for improving processes. This methodology is used to improve an existing business process. • DMADV − It refers to a data-driven quality strategy for designing products & processes. This methodology is used to create new product designs or process designs in such a way that it results in a more predictable, mature and defect free performance. • There is one more methodology called DFSS − Design For Six Sigma. DFSS is a data-driven quality strategy for designing or redesigning a product or service from the ground up. Common rule is that, the smaller the box and the shorter the whiskers, the better. This means that values are close to each other. Defect can easily be detected. www.msystraining.com

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